{"meta":{"query_hash":"e5f4d7ee0847","filters":{"topic":"Transportation and Mobility Innovations"},"cohort_total":1357,"direct_labels_cover":1,"predictions_cover":1357,"exported":1357,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/e5f4d7ee0847","api":"https://metacan.xera.ac/api/v1/cohort?topic=Transportation+and+Mobility+Innovations"},"results":[{"id":"W1220314359","doi":"","title":"Chabotage en Amériques","year":2004,"lang":"fr","type":"article","venue":"Érudit (Université de Montréal)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Art","score_opus":0.0037360993793539485,"score_gpt":0.15540864238373842,"score_spread":0.15167254300438446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1220314359","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.122717656,0.0072096842,0.0032867522,0.007276723,0.0017516643,0.00008502987,0.0015821777,0.00031661408,0.8557738],"genre_scores_gemma":[0.3780839,0.004637539,0.0031431168,0.0016511679,0.00036963003,0.00008234121,0.0014229612,0.00018170287,0.6104276],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995534,0.00007482217,0.000011676263,0.00009659467,0.00011602276,0.00014749971],"domain_scores_gemma":[0.9994479,0.00013567711,0.000057168003,0.000042590305,0.00018332987,0.00013332572],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005814127,0.00037728186,0.00014533653,0.0016398934,0.0025265766,0.001774947,0.00049313705,0.0007124029,0.0690159],"category_scores_gemma":[0.0015624639,0.00017085829,0.000201054,0.0028998125,0.00137321,0.001589169,0.0015282342,0.0014249899,0.0062755086],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031979696,0.00013034866,0.02737524,0.00042725095,0.000022708,0.0018015989,0.042064495,0.00040781114,0.0040841713,0.21155071,0.21171169,0.50010407],"study_design_scores_gemma":[0.000008150251,0.00002867808,0.021929884,0.00009709648,0.0000056473395,0.00028541673,0.006570711,0.00017250043,0.00023920323,0.0024810445,0.96816885,0.00001290692],"about_ca_topic_score_codex":0.21019396,"about_ca_topic_score_gemma":0.2407869,"teacher_disagreement_score":0.21019396,"about_ca_system_score_codex":0.0053386353,"about_ca_system_score_gemma":0.0034899802,"threshold_uncertainty_score":0.41794097},"labels":[],"label_agreement":null},{"id":"W127395072","doi":"","title":"Assessing and Reforming Vancouver's Taxi Regulations","year":2014,"lang":"en","type":"article","venue":"Summit (Simon Fraser University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Political science","score_opus":0.010840301279926568,"score_gpt":0.2033849591666629,"score_spread":0.19254465788673633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W127395072","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8752154,0.00093878846,0.0019845732,0.004754886,0.000060901377,0.00045586104,0.00058164395,0.00008702879,0.11592087],"genre_scores_gemma":[0.9769837,0.0008349601,0.0030880182,0.00077495736,0.000013608547,0.00008764442,0.00037705246,0.000019076406,0.017820971],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9952899,0.00077021273,0.00011517058,0.0002897051,0.0023327959,0.0012021549],"domain_scores_gemma":[0.9867818,0.0019298019,0.00085945055,0.0003691605,0.008620606,0.0014392457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041983887,0.00023912353,0.00025132383,0.0018407298,0.006215016,0.0070682787,0.0015528677,0.0012087817,0.002925317],"category_scores_gemma":[0.012524074,0.0003011996,0.00022745765,0.00249454,0.0019160332,0.00082111976,0.0014602453,0.0014674831,0.00036178433],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026192586,0.0006274657,0.5475225,0.0007001853,0.00011799029,0.0017296079,0.026056388,0.021554265,0.008691203,0.05465147,0.040458176,0.2976288],"study_design_scores_gemma":[0.00006477303,0.00042208267,0.6277294,0.00047513703,0.00012240699,0.0002798095,0.07318395,0.011198117,0.004974521,0.003260666,0.2781257,0.00016345721],"about_ca_topic_score_codex":0.9567832,"about_ca_topic_score_gemma":0.98409224,"teacher_disagreement_score":0.06842668,"about_ca_system_score_codex":0.06842668,"about_ca_system_score_gemma":0.106767595,"threshold_uncertainty_score":0.49647266},"labels":[],"label_agreement":null},{"id":"W1479677959","doi":"","title":"Now Where Are Those Keys? A Primer on Car Sharing","year":2008,"lang":"en","type":"article","venue":"The Parking professional","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Car sharing; Renting; Sharing economy; Payment; Business; Service (business); Transport engineering; Pooling; Traffic congestion; Bike sharing; Advertising; Computer security; Engineering; Marketing; Finance; Computer science; World Wide Web","score_opus":0.03485704065329261,"score_gpt":0.2750947059527709,"score_spread":0.2402376652994783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1479677959","genre_codex":"other","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034750118,0.12621504,0.01859147,0.3737662,0.0108968,0.000088799075,0.00012913032,0.00027835227,0.46655917],"genre_scores_gemma":[0.09528448,0.21973498,0.010819402,0.1787672,0.0074466164,0.0002796264,0.00020364742,0.00039964815,0.48706436],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99857855,0.00064645766,0.00004271891,0.00015643655,0.0003143118,0.00026158674],"domain_scores_gemma":[0.99895835,0.0005176697,0.000045314115,0.000066472654,0.00017815284,0.00023395874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017437731,0.00069857785,0.0003461437,0.0008455894,0.0041904855,0.0061349976,0.001511212,0.0063137063,0.025622467],"category_scores_gemma":[0.0023208978,0.00042619952,0.00037677414,0.0009487275,0.00715873,0.017799245,0.005014484,0.008963393,0.009172127],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018094812,0.00007736487,0.00027457566,0.00020618201,0.0000031180691,0.00015797492,0.0072672586,0.00019194347,0.00020391542,0.46538147,0.3761698,0.15004833],"study_design_scores_gemma":[0.0000010080844,0.000011949712,0.000058068457,0.0001982307,5.8427185e-7,0.00013011425,0.0017280618,0.00003558534,0.00004818095,0.016855258,0.9809279,0.000004921426],"about_ca_topic_score_codex":0.004679057,"about_ca_topic_score_gemma":0.0071292855,"teacher_disagreement_score":0.025622467,"about_ca_system_score_codex":0.0026027618,"about_ca_system_score_gemma":0.0031032425,"threshold_uncertainty_score":0.08571565},"labels":[],"label_agreement":null},{"id":"W1481557935","doi":"","title":"North American Carsharing: A Ten Year Retrospective","year":2008,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"University of California, Davis","keywords":"Diversification (marketing strategy); Market share; Business; Consolidation (business); Competition (biology); Finance; Marketing","score_opus":0.011577555333488808,"score_gpt":0.19293849482536407,"score_spread":0.18136093949187526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1481557935","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7752674,0.010898954,0.0025565333,0.0039725723,0.00060155935,0.00061766355,0.13952573,0.00034431045,0.06621527],"genre_scores_gemma":[0.7491049,0.026914293,0.0036509046,0.0041245837,0.000654518,0.0013894435,0.15862077,0.00028429204,0.055256218],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986297,0.00010297154,0.00016001654,0.00019045814,0.00065190933,0.00026503287],"domain_scores_gemma":[0.98744154,0.000980928,0.0024041967,0.00050456496,0.0076852744,0.0009835527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014056072,0.00031059512,0.00019280316,0.0055576176,0.0022457554,0.0018909555,0.0005535434,0.00044387486,0.0043256325],"category_scores_gemma":[0.003430481,0.0003804584,0.0002884678,0.008681496,0.00047692758,0.0013453286,0.0011717883,0.0010957437,0.0020930285],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017385627,0.00028181495,0.78516084,0.0004036759,0.000051499355,0.00085980486,0.0056474316,0.00020989559,0.00079266436,0.0011057233,0.124908194,0.08040463],"study_design_scores_gemma":[0.0000025098834,0.00008209371,0.7802542,0.00029240153,0.000027679123,0.000759372,0.006221084,0.00014549981,0.0006878426,0.00008657241,0.211399,0.00004168695],"about_ca_topic_score_codex":0.22243048,"about_ca_topic_score_gemma":0.37909514,"teacher_disagreement_score":0.22243048,"about_ca_system_score_codex":0.0022071798,"about_ca_system_score_gemma":0.0050832746,"threshold_uncertainty_score":0.44227153},"labels":[],"label_agreement":null},{"id":"W1489203962","doi":"","title":"Addressing Elderly Mobility Issues in Wisconsin","year":2011,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Population; Gerontology; Quarter (Canadian coin); Social isolation; TRIPS architecture; Crash; Business; Medicine; Psychology; Environmental health; Geography; Engineering; Transport engineering","score_opus":0.09566425498895637,"score_gpt":0.292183580531605,"score_spread":0.19651932554264862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1489203962","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94909024,0.0050614784,0.0010159285,0.008878636,0.0002806333,0.00040778145,0.0012435006,0.000058753572,0.033963177],"genre_scores_gemma":[0.9662761,0.015284901,0.0022369472,0.0025460287,0.00021716053,0.00038057688,0.0012085172,0.000013652695,0.011836294],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994753,0.00010306758,0.00006312622,0.000039433635,0.00011513327,0.00020398217],"domain_scores_gemma":[0.9993864,0.000054530974,0.00015062,0.000020961383,0.00020472075,0.00018283619],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011210857,0.00030331704,0.0001694358,0.0014845895,0.0021672186,0.001834088,0.00065042434,0.00049223186,0.0026108455],"category_scores_gemma":[0.002753694,0.00016365996,0.0003516439,0.0018997072,0.0003429825,0.0011545456,0.0028298546,0.0004486388,0.0003380223],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015779845,0.00057522714,0.5064161,0.0009102818,0.000117872194,0.0029419896,0.049554262,0.00067952386,0.0025489877,0.0037119647,0.045522988,0.38686305],"study_design_scores_gemma":[0.00001882746,0.00044784186,0.62402815,0.0015044411,0.00016971772,0.0013750652,0.12798414,0.00071576383,0.0007390124,0.0014155133,0.2415337,0.000067842004],"about_ca_topic_score_codex":0.09121891,"about_ca_topic_score_gemma":0.29383904,"teacher_disagreement_score":0.09121891,"about_ca_system_score_codex":0.002821601,"about_ca_system_score_gemma":0.005351344,"threshold_uncertainty_score":0.18137592},"labels":[],"label_agreement":null},{"id":"W1500753031","doi":"","title":"Consulting The Experts: Towards A More Passenger-Friendly Accessible Transportation System","year":2009,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Engineering; Business","score_opus":0.01067757500952905,"score_gpt":0.21598880324402836,"score_spread":0.20531122823449932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1500753031","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4388369,0.00158661,0.008736077,0.16292375,0.0007797954,0.00033239715,0.00020804074,0.00015433377,0.3864421],"genre_scores_gemma":[0.77484614,0.002635366,0.0047130045,0.011255455,0.00011969069,0.00007290829,0.0001234763,0.000057147183,0.2061768],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.99895227,0.00039293745,0.000026637133,0.00009195232,0.00027490512,0.0002613118],"domain_scores_gemma":[0.9988927,0.00015989057,0.00009054086,0.00003094513,0.00035203493,0.00047397686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016756314,0.00017721376,0.0000807398,0.0003887018,0.0064304816,0.0032296432,0.0005899413,0.0014067736,0.012127799],"category_scores_gemma":[0.0026724965,0.00012479204,0.00012101154,0.00075359945,0.0025005843,0.0025180434,0.0021020733,0.0012251566,0.0013051274],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002758304,0.0001296424,0.014118827,0.0003512393,0.000007579717,0.0020141941,0.54302144,0.00046106614,0.003798076,0.047175657,0.21544014,0.17345461],"study_design_scores_gemma":[0.000011624221,0.00006648351,0.0140388785,0.00020308713,0.000010168651,0.0002982231,0.3225788,0.0002969388,0.0006124792,0.0032230834,0.6586337,0.00002656964],"about_ca_topic_score_codex":0.32666218,"about_ca_topic_score_gemma":0.4829722,"teacher_disagreement_score":0.32666218,"about_ca_system_score_codex":0.007943125,"about_ca_system_score_gemma":0.020241013,"threshold_uncertainty_score":0.6495216},"labels":[],"label_agreement":null},{"id":"W1507875219","doi":"","title":"Analysis of carpool commuting on slovenian motorways","year":2011,"lang":"en","type":"other","venue":"Repozitorij Univerze v Ljubljani (Univerze v Lgubljani)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Carpool; Transport engineering; Incentive; Order (exchange); Public transport; Rush hour; Engineering; Business; Economics; Finance","score_opus":0.012654954309694395,"score_gpt":0.19742716276556302,"score_spread":0.18477220845586861,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1507875219","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99571687,0.000112828406,0.00036385749,0.000021833102,0.0000054441925,0.000016077976,0.0015842069,0.000014953215,0.0021638595],"genre_scores_gemma":[0.9934329,0.00013842851,0.00031426075,0.000006308205,0.000003112269,0.000019998568,0.0036177868,0.000015451573,0.002451758],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99942565,0.00010215798,0.000033534812,0.00012448968,0.00009523388,0.00021904262],"domain_scores_gemma":[0.9994337,0.0001339768,0.000100821875,0.000043895107,0.00021933013,0.00006832347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003755793,0.0003883931,0.000475789,0.0018356416,0.0005526272,0.0011907887,0.00045426568,0.00031514713,0.0042697527],"category_scores_gemma":[0.0011064406,0.000254224,0.00087481475,0.0035622232,0.0002703732,0.00036912644,0.0005047341,0.0002766681,0.0005606362],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010154963,0.00019805496,0.84157556,0.00027811466,0.0003741942,0.0017698245,0.001949833,0.1147151,0.0013659955,0.0023132688,0.004564361,0.029880336],"study_design_scores_gemma":[0.000009922539,0.00007926332,0.9593884,0.00003678193,0.000058879687,0.00012272704,0.004788008,0.030742684,0.00031129242,0.00020593015,0.0042294343,0.00002677262],"about_ca_topic_score_codex":0.21060403,"about_ca_topic_score_gemma":0.20069766,"teacher_disagreement_score":0.21060403,"about_ca_system_score_codex":0.0017258304,"about_ca_system_score_gemma":0.00086648413,"threshold_uncertainty_score":0.4187563},"labels":[],"label_agreement":null},{"id":"W1510845889","doi":"10.1002/hec.3098","title":"Effects of a Driver Cellphone Ban on Overall, Handheld, and Hands-Free Cellphone Use While Driving: New Evidence from Canada","year":2014,"lang":"en","type":"article","venue":"Health Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Mobile device; Hands free; Unintended consequences; Substitution effect; Advertising; Difference in differences; Internet privacy; Business; Computer science; Political science; Telecommunications; Economics; Law","score_opus":0.015151200812116726,"score_gpt":0.1979656624792331,"score_spread":0.18281446166711637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1510845889","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94390965,0.017553747,0.0006860715,0.0043676347,0.00016412458,0.00011808505,0.008637597,0.000029400502,0.024533728],"genre_scores_gemma":[0.98561424,0.0077969194,0.00042082553,0.0011330384,0.00005258303,0.00003156572,0.0019846824,0.0000144093565,0.0029516441],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9942311,0.0008817908,0.00031448956,0.00062792486,0.003019942,0.00092482555],"domain_scores_gemma":[0.9780005,0.0058250753,0.0053245267,0.0010563199,0.007916517,0.0018770427],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034373002,0.0004367418,0.0007144119,0.0016340042,0.0020983657,0.0017374055,0.0012345267,0.000753602,0.0033607953],"category_scores_gemma":[0.012598146,0.00031668952,0.0013337351,0.003058199,0.001988445,0.0005715101,0.0010986353,0.001416858,0.00019579245],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00097305706,0.00026354534,0.95578355,0.0007693457,0.0013218654,0.00019472782,0.001935024,0.0004375555,0.0004101858,0.0010655479,0.0041947905,0.032650854],"study_design_scores_gemma":[0.000055675762,0.00013271626,0.99159414,0.00022863531,0.00076633424,0.000029775632,0.001049411,0.00016512159,0.0002676377,0.00010301608,0.005582298,0.000025103984],"about_ca_topic_score_codex":0.99049133,"about_ca_topic_score_gemma":0.99439347,"teacher_disagreement_score":0.01897147,"about_ca_system_score_codex":0.01897147,"about_ca_system_score_gemma":0.030155199,"threshold_uncertainty_score":0.13764834},"labels":[],"label_agreement":null},{"id":"W1524279467","doi":"10.2139/ssrn.2566401","title":"Public Transit Data Through an Intellectual Property Lens: Lessons About Open Data","year":2015,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Intellectual property; Public transport; Transit (satellite); Open data; Business; Lens (geology); Data science; Law and economics; Computer science; Transport engineering; Political science; Law; Engineering; Sociology; Optics; Physics","score_opus":0.3719693665461619,"score_gpt":0.35581180264634926,"score_spread":0.016157563899812655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1524279467","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022441508,0.012153443,0.11654852,0.5461972,0.0035825537,0.000079226025,0.0009834684,0.0002848512,0.29772925],"genre_scores_gemma":[0.90134287,0.016082376,0.02925995,0.02222158,0.008220637,0.00019027799,0.0004780852,0.00057164213,0.021632498],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9899624,0.005671919,0.00045903344,0.0008940344,0.002425239,0.00058723753],"domain_scores_gemma":[0.8853962,0.08926798,0.0031515474,0.010915637,0.0083103655,0.0029583469],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.01982221,0.0005688114,0.00075005053,0.004683596,0.005023359,0.029006794,0.0029780993,0.007309833,0.013647166],"category_scores_gemma":[0.06436353,0.00047325125,0.0008890408,0.0070460914,0.035383124,0.07731267,0.008964371,0.013131291,0.0013393009],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000061381734,0.000007965242,0.00027246738,0.0000314322,0.0000033646447,0.000034968838,0.001006099,0.00017483889,0.000017571318,0.9888937,0.0042366977,0.0053146933],"study_design_scores_gemma":[0.0000066620973,0.000007688934,0.00023851666,0.00025615303,0.0000054349307,0.00007557454,0.0038608247,0.0007892936,0.000116213814,0.917158,0.07747315,0.0000124274],"about_ca_topic_score_codex":0.010286204,"about_ca_topic_score_gemma":0.007830846,"teacher_disagreement_score":0.9970219,"about_ca_system_score_codex":0.0073300814,"about_ca_system_score_gemma":0.008781064,"threshold_uncertainty_score":0.1048311},"labels":[],"label_agreement":null},{"id":"W1529629941","doi":"","title":"Transport Canada to determine if new in-car devices affect safety","year":2000,"lang":"en","type":"article","venue":"PubMed Central","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Mandate; Affect (linguistics); Jurisdiction; Computer science; Intelligent transportation system; Transport engineering; Computer security; Telecommunications; Engineering; Psychology; Law; Political science","score_opus":0.008650050219929137,"score_gpt":0.18824208738256906,"score_spread":0.17959203716263994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1529629941","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46986553,0.0021076684,0.0016350559,0.024453206,0.00084278476,0.001250547,0.14349422,0.00036244627,0.3559886],"genre_scores_gemma":[0.75829905,0.0025879343,0.0024071527,0.008988948,0.00008926343,0.0006795698,0.035361096,0.00010777487,0.19147919],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977036,0.00015947726,0.00006338028,0.00016461495,0.0011966934,0.00071220385],"domain_scores_gemma":[0.98336107,0.0010120007,0.0007940199,0.0003537276,0.013496427,0.0009827369],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001718608,0.00038477487,0.0003444318,0.0013558044,0.003381581,0.002048938,0.0012358645,0.0008845234,0.026480597],"category_scores_gemma":[0.008335952,0.0002871534,0.0009263464,0.0028347932,0.000553306,0.000756559,0.00080069684,0.0014334277,0.0024245994],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00094535627,0.0008297924,0.66360235,0.00045053396,0.00039550426,0.00032895603,0.0019524612,0.0018921557,0.0013369161,0.009009605,0.2618768,0.057379514],"study_design_scores_gemma":[0.00026456633,0.00040957003,0.86485,0.00028779623,0.0003502326,0.00007375327,0.0059458627,0.0016946491,0.0018283823,0.0007255006,0.12351235,0.00005734654],"about_ca_topic_score_codex":0.9938212,"about_ca_topic_score_gemma":0.9954651,"teacher_disagreement_score":0.03050033,"about_ca_system_score_codex":0.03050033,"about_ca_system_score_gemma":0.08535948,"threshold_uncertainty_score":0.22129643},"labels":[],"label_agreement":null},{"id":"W1533323647","doi":"","title":"Non-motorised public transport : the past, the present, the future","year":2010,"lang":"en","type":"article","venue":"QUT ePrints (Queensland University of Technology)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Public transport; Taxis; Flexibility (engineering); Sustainability; Happening; Latin Americans; Novelty; Business; Transport engineering; Mode of transport; Engineering; Political science; Economics","score_opus":0.004746841415447203,"score_gpt":0.17669539601036222,"score_spread":0.171948554594915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1533323647","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19310771,0.20273612,0.0018517746,0.33934125,0.003122201,0.00003507965,0.0008183436,0.00006600288,0.25892153],"genre_scores_gemma":[0.85575354,0.11429341,0.0006776139,0.0048168874,0.001011757,0.00002405839,0.00029682278,0.000025948802,0.023099879],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99924445,0.0002039092,0.000032845215,0.000110393914,0.00014984663,0.00025848445],"domain_scores_gemma":[0.9991708,0.00014323436,0.00018208078,0.000043421096,0.00020373944,0.00025672265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010021982,0.00028360038,0.0002278214,0.0008876891,0.003022123,0.009713006,0.0006572639,0.0026815953,0.00844274],"category_scores_gemma":[0.0014902197,0.00023972434,0.00030099062,0.003319415,0.00451127,0.014528087,0.002020095,0.0033251669,0.0008584445],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001851375,0.00029914078,0.059981175,0.002247761,0.000037433092,0.0024483046,0.04940429,0.0013101493,0.0011937973,0.44544572,0.08875784,0.34868923],"study_design_scores_gemma":[0.000007984807,0.00014039155,0.07616311,0.0030814402,0.00003147874,0.0015859687,0.16911268,0.00087207113,0.00028776217,0.030503947,0.718132,0.000081060374],"about_ca_topic_score_codex":0.0625716,"about_ca_topic_score_gemma":0.07675471,"teacher_disagreement_score":0.0625716,"about_ca_system_score_codex":0.009284113,"about_ca_system_score_gemma":0.0056698276,"threshold_uncertainty_score":0.12441474},"labels":[],"label_agreement":null},{"id":"W1533353286","doi":"","title":"Knowledge-workers and the sustainable city: the travel consequences of car-related job-perks","year":2011,"lang":"en","type":"article","venue":"Econstor (Econstor)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Transport engineering; Engineering","score_opus":0.01588605497360602,"score_gpt":0.216044095940398,"score_spread":0.200158040966792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1533353286","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986035,0.00015592377,0.00009843025,0.00015728195,0.0000024213828,0.0000053974873,0.00016972322,0.0000012019808,0.0008061788],"genre_scores_gemma":[0.9995316,0.000072846204,0.000023439983,0.0000114339155,0.0000028671661,0.0000023132757,0.00008840666,3.8077806e-7,0.00026669833],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995565,0.00014792234,0.000024735207,0.000057603465,0.00007188913,0.0001413186],"domain_scores_gemma":[0.99764675,0.0008537935,0.000804125,0.00007610453,0.00012456461,0.0004947512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046048255,0.00014024456,0.00019110704,0.0006726941,0.00036221487,0.0011484283,0.00034243037,0.00081095396,0.0043897578],"category_scores_gemma":[0.0021517037,0.00011369247,0.0005677544,0.0009041413,0.0005564423,0.0006141347,0.0007973566,0.0005978146,0.00033207863],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000094756055,0.00021087185,0.9935959,0.000024511128,0.000056974968,0.00013436427,0.00035782135,0.0013102276,0.00013276278,0.00029142306,0.00012479763,0.003665529],"study_design_scores_gemma":[0.000003756599,0.00008848255,0.99443406,0.000017358465,0.000023088745,0.000057045985,0.002801561,0.0019911763,0.00006725275,0.00022731145,0.00028120689,0.000007700753],"about_ca_topic_score_codex":0.031628143,"about_ca_topic_score_gemma":0.04929975,"teacher_disagreement_score":0.031628143,"about_ca_system_score_codex":0.00080059114,"about_ca_system_score_gemma":0.00079860666,"threshold_uncertainty_score":0.062888086},"labels":[],"label_agreement":null},{"id":"W1540221652","doi":"","title":"The Motorization of North America: causes, consequences, and speculations on possible futures","year":2001,"lang":"en","type":"preprint","venue":"eScholarship (California Digital Library)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Truck; Population; Futures contract; Geography; Commercial vehicle; Business; Engineering; Demography; Finance; Automotive engineering; Sociology","score_opus":0.012881095308441181,"score_gpt":0.20994840571347806,"score_spread":0.1970673104050369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1540221652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7046075,0.030016767,0.0012865048,0.18620755,0.00049314694,0.00005485803,0.0018924585,0.000072654286,0.07536855],"genre_scores_gemma":[0.9834326,0.012870618,0.00023094722,0.0009114848,0.0002772977,0.0000151927525,0.00020140002,0.000008084754,0.002052412],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99961996,0.00009606641,0.000013157327,0.00007469291,0.000045643883,0.00015055222],"domain_scores_gemma":[0.99853754,0.00035331235,0.00055279396,0.00006681689,0.00028139763,0.00020811106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008675796,0.00029414412,0.00023456191,0.0019296968,0.0016092736,0.0021368423,0.00071396923,0.001470471,0.008983425],"category_scores_gemma":[0.0029960817,0.0002567674,0.000358519,0.0031478414,0.0034568515,0.0034575036,0.0012919651,0.0013902235,0.0003394691],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020949738,0.00016759055,0.7807025,0.0004745821,0.00009579644,0.0042704693,0.00991382,0.002175752,0.00044116352,0.10252286,0.027506303,0.071519695],"study_design_scores_gemma":[0.000018765579,0.00007253065,0.83673424,0.00073903275,0.00007132463,0.0014796789,0.05560331,0.0026136073,0.00039098595,0.06759698,0.034595307,0.000084273226],"about_ca_topic_score_codex":0.054595914,"about_ca_topic_score_gemma":0.08316199,"teacher_disagreement_score":0.9454041,"about_ca_system_score_codex":0.0029557294,"about_ca_system_score_gemma":0.0019315345,"threshold_uncertainty_score":0.10855627},"labels":[],"label_agreement":null},{"id":"W1549544518","doi":"10.1002/atr.1296","title":"A revised branch‐and‐price algorithm for dial‐a‐ride problems with the consideration of time‐dependent travel cost","year":2014,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Value of time; Travel time; Computer science; Arrival time; Service (business); Task (project management); Window (computing); Operations research; Level of service; Construct (python library); Transport engineering; Simulation; Real-time computing; Engineering; Economics; Computer network","score_opus":0.006874684862293479,"score_gpt":0.21466926471338235,"score_spread":0.20779457985108887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1549544518","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006614107,0.00021477409,0.9880283,0.00027822127,0.00007875233,0.00018197729,0.000081850274,0.00036469763,0.0041573956],"genre_scores_gemma":[0.11892189,0.0002605697,0.87298256,0.00013658367,0.000096645,0.00060714706,0.00028236737,0.00033433095,0.0063779587],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991412,0.00025733103,0.00005519633,0.00014375863,0.00022765675,0.00017491395],"domain_scores_gemma":[0.9971949,0.0018899741,0.00012943211,0.00010949785,0.0005211947,0.00015497231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022358,0.0014489216,0.0021700552,0.0014680262,0.00096276094,0.0018961971,0.0024365077,0.0021961755,0.014757947],"category_scores_gemma":[0.004669028,0.0010352377,0.0011571231,0.0017065834,0.0007739397,0.0021584816,0.001769774,0.0030814398,0.0018748662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008529527,0.00011081051,0.0004631455,0.0001361192,0.000029491739,0.00014080325,0.00006126405,0.90229505,0.0006643921,0.0157775,0.0038380348,0.076398045],"study_design_scores_gemma":[0.00002115197,0.000014410296,0.000027430642,0.0000053880117,0.0000030405592,0.000010936096,0.0000086625405,0.99621564,0.00007217073,0.0030738243,0.00054398004,0.0000033618935],"about_ca_topic_score_codex":0.015296151,"about_ca_topic_score_gemma":0.01284519,"teacher_disagreement_score":0.015296151,"about_ca_system_score_codex":0.0014001043,"about_ca_system_score_gemma":0.00357532,"threshold_uncertainty_score":0.04937029},"labels":[],"label_agreement":null},{"id":"W1551602292","doi":"10.1002/9780470986424.ch9","title":"Equalization of Cluster Lifetimes","year":2008,"lang":"en","type":"other","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Cluster (spacecraft); Equalization (audio); Energy consumption; Computer science; Telecommunications; Computer network; Engineering; Electrical engineering","score_opus":0.009111000767020969,"score_gpt":0.21438952800449249,"score_spread":0.20527852723747153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1551602292","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35811928,0.0010172563,0.55901,0.0012510832,0.00030897895,0.00014678045,0.0005425977,0.00093927846,0.07866468],"genre_scores_gemma":[0.9763856,0.00028246746,0.0071071973,0.00007135409,0.00003071185,0.00006145196,0.000101441496,0.00015669638,0.015803037],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997838,0.000032987697,0.0000050993067,0.000066424494,0.000042692267,0.00006896136],"domain_scores_gemma":[0.99946314,0.00023724219,0.00004773405,0.0001037445,0.00009797166,0.000050220126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043069647,0.0002359749,0.00035300283,0.00025811887,0.00039909742,0.0007314626,0.0007942924,0.00041822577,0.008525757],"category_scores_gemma":[0.003083239,0.00020081911,0.00022898475,0.00041462824,0.00043216776,0.0013897854,0.00075367524,0.00052233133,0.000567946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013031156,0.000050808718,0.0012251758,0.000055527787,0.0000142867975,0.00003942891,0.00010146633,0.85790324,0.0060953377,0.10383288,0.0028440887,0.02770742],"study_design_scores_gemma":[0.000012213944,0.000028261295,0.0013029749,0.000010295732,0.000010316805,0.000027846343,0.00007493144,0.9732799,0.0021551321,0.020004433,0.0030815732,0.00001212516],"about_ca_topic_score_codex":0.0034973158,"about_ca_topic_score_gemma":0.0034490284,"teacher_disagreement_score":0.008525757,"about_ca_system_score_codex":0.0020003943,"about_ca_system_score_gemma":0.0009374999,"threshold_uncertainty_score":0.028521478},"labels":[],"label_agreement":null},{"id":"W1552027418","doi":"10.1016/j.tre.2014.03.003","title":"A dynamic carsharing decision support system","year":2014,"lang":"en","type":"article","venue":"Transportation Research Part E Logistics and Transportation Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canadian Automobile Association","keywords":"Relocation; Revenue; Operations research; Decision support system; Profit (economics); Order (exchange); Computer science; A priori and a posteriori; Revenue management; Business; Engineering; Microeconomics; Economics","score_opus":0.05648696110910045,"score_gpt":0.34785683237326814,"score_spread":0.2913698712641677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1552027418","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09187725,0.00049222895,0.87956053,0.0010980144,0.0005691059,0.0006467458,0.0015716185,0.012090934,0.012093576],"genre_scores_gemma":[0.8535028,0.00031315727,0.13749352,0.00035090419,0.00017424226,0.00047130778,0.0011782312,0.000075830765,0.0064399377],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995239,0.00007058975,0.00003867239,0.00018403982,0.000121619,0.00006117796],"domain_scores_gemma":[0.9992582,0.00034337773,0.00005110003,0.000062312065,0.0002040772,0.00008088982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081731926,0.0007638762,0.001335785,0.000644249,0.0007920963,0.0018161453,0.0015587748,0.000959618,0.0106300805],"category_scores_gemma":[0.0015226027,0.0003236416,0.00044922958,0.0006996748,0.00027788946,0.0013849286,0.001201549,0.0008927708,0.0015398111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017833894,0.0008704792,0.002992009,0.00029161436,0.00022642265,0.00041938876,0.0001266515,0.42824516,0.010718572,0.008706582,0.014438093,0.53118175],"study_design_scores_gemma":[0.0001079544,0.00019297037,0.00048147034,0.000011047152,0.000053017786,0.000045919533,0.00003449446,0.99161714,0.0015786082,0.0027158542,0.003139337,0.000022168333],"about_ca_topic_score_codex":0.005307546,"about_ca_topic_score_gemma":0.0026123717,"teacher_disagreement_score":0.0106300805,"about_ca_system_score_codex":0.0007472414,"about_ca_system_score_gemma":0.0013120177,"threshold_uncertainty_score":0.035561144},"labels":[],"label_agreement":null},{"id":"W1553136483","doi":"10.15607/rss.2011.vii.034","title":"Load Balancing for Mobility-on-Demand Systems","year":2011,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Office of Naval Research; Division of Emerging Frontiers in Research and Innovation; National Research Foundation; Massachusetts Institute of Technology; National Science Foundation","keywords":"Computer science; Load balancing (electrical power)","score_opus":0.02779595937219225,"score_gpt":0.22204385774765828,"score_spread":0.19424789837546602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1553136483","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02263605,0.0005801245,0.9692951,0.00043871065,0.00008865296,0.000099740144,0.000097326585,0.00028372437,0.0064806934],"genre_scores_gemma":[0.9298711,0.0005967197,0.061799742,0.00011559204,0.00024829805,0.00017641978,0.00018153871,0.00013646531,0.0068741455],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99910563,0.0003002519,0.00003617568,0.00014024173,0.00025970538,0.00015793413],"domain_scores_gemma":[0.9987651,0.0006912343,0.00013751248,0.0001060915,0.0002211917,0.00007882532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009892045,0.0010794121,0.0010656462,0.00060244085,0.00091216475,0.0014116855,0.0019055133,0.00083429454,0.004189137],"category_scores_gemma":[0.0025656729,0.00041110968,0.00046488037,0.00085033226,0.000733826,0.0018328426,0.0015918117,0.00084815227,0.00063650473],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007406821,0.000054077685,0.00031839497,0.000118337746,0.000033036573,0.00007261143,0.000101009035,0.93869096,0.0026255203,0.025831286,0.0019498895,0.030130835],"study_design_scores_gemma":[0.0000063769617,0.000016433018,0.000064078544,0.0000040336226,0.0000037691411,0.000016853355,0.000016501035,0.98992443,0.00031939973,0.0085228225,0.001100249,0.0000050306976],"about_ca_topic_score_codex":0.0031780289,"about_ca_topic_score_gemma":0.0026342198,"teacher_disagreement_score":0.004189137,"about_ca_system_score_codex":0.001513648,"about_ca_system_score_gemma":0.0007586509,"threshold_uncertainty_score":0.014014065},"labels":[],"label_agreement":null},{"id":"W1560871288","doi":"","title":"WE NEED PUBLIC TRANSIT...PUBLIC TRANSIT NEEDS HIGHWAYS","year":2003,"lang":"en","type":"article","venue":"Better roads","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Public transport; Transit (satellite); Transport engineering; TRIPS architecture; Mile; Business; Quarter (Canadian coin); Traffic congestion; Rail transit; Work (physics); Transit system; Population; Engineering; Geography; Environmental health","score_opus":0.025165610485747406,"score_gpt":0.20386537256472723,"score_spread":0.1786997620789798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1560871288","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021827204,0.014736989,0.0032332202,0.59235877,0.0066269506,0.00008044997,0.00097467756,0.0009863601,0.35917547],"genre_scores_gemma":[0.28537092,0.029351125,0.005387341,0.123913705,0.0069963015,0.000112257636,0.0013922402,0.00038654474,0.5470897],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99925107,0.000117773765,0.000018652758,0.000077353725,0.00024197709,0.00029317287],"domain_scores_gemma":[0.9982426,0.00014646594,0.0001540956,0.0000826821,0.00066708063,0.0007070034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005333984,0.00038102485,0.00025823087,0.00044487053,0.0026760816,0.0037309618,0.00041318868,0.0029437544,0.07279674],"category_scores_gemma":[0.0017919965,0.00014952256,0.00024303557,0.0009628981,0.0013173511,0.0048238216,0.0019171861,0.0018828937,0.022363191],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003745107,0.000097638425,0.0037565255,0.00034143048,0.000012675691,0.00019361838,0.0010804512,0.00021405047,0.0012676744,0.037067886,0.8130828,0.14284775],"study_design_scores_gemma":[0.0000066075495,0.000034300523,0.0025172248,0.00010637554,0.000009442465,0.0001661831,0.00106586,0.000054018426,0.00017034335,0.0043262783,0.99153495,0.0000084784215],"about_ca_topic_score_codex":0.016342074,"about_ca_topic_score_gemma":0.02383119,"teacher_disagreement_score":0.07279674,"about_ca_system_score_codex":0.0023300592,"about_ca_system_score_gemma":0.005238762,"threshold_uncertainty_score":0.24352932},"labels":[],"label_agreement":null},{"id":"W1567987244","doi":"","title":"Canadian Study for R&D Needs and Priorities in Accessible Transportation","year":2010,"lang":"en","type":"article","venue":"TRANSED 2010: 12th International Conference on Mobility and Transport for Elderly and Disabled PersonsHong Kong Society for RehabilitationS K Yee Medical FoundationTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Work (physics); Order (exchange); Public relations; Business; Marketing; Political science; Engineering; Finance","score_opus":0.05502267781442271,"score_gpt":0.3618890961786844,"score_spread":0.3068664183642617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1567987244","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6948914,0.011132822,0.00072370254,0.07719413,0.00046215212,0.0010800798,0.0125053665,0.000107445136,0.20190293],"genre_scores_gemma":[0.95794755,0.009231821,0.0019290338,0.00467277,0.000052271334,0.00052121724,0.0029569832,0.000044651704,0.022643648],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9913073,0.00079073437,0.00040818853,0.0003242618,0.004791795,0.0023776707],"domain_scores_gemma":[0.9590837,0.0032191088,0.0019215724,0.0005802057,0.026161253,0.009034178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008487554,0.0002535124,0.0004891873,0.0050371364,0.009733866,0.00489701,0.0018773171,0.0010752502,0.0080070915],"category_scores_gemma":[0.018976195,0.00052158255,0.0005804072,0.012947264,0.0012526948,0.0017729349,0.0022645644,0.001981654,0.0005718684],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028371066,0.00064996723,0.34729102,0.004472025,0.0001035748,0.002378883,0.18990114,0.00068521634,0.0014051389,0.04000814,0.23979732,0.17302385],"study_design_scores_gemma":[0.000038959402,0.00014265442,0.46297356,0.0017655701,0.000059110323,0.00036846346,0.24221225,0.0005512815,0.00027763817,0.0007932853,0.2906721,0.00014510944],"about_ca_topic_score_codex":0.99285203,"about_ca_topic_score_gemma":0.99427044,"teacher_disagreement_score":0.89646083,"about_ca_system_score_codex":0.103539154,"about_ca_system_score_gemma":0.29722324,"threshold_uncertainty_score":0.7512326},"labels":[],"label_agreement":null},{"id":"W1573914938","doi":"10.1016/s0927-0507(06)14007-4","title":"Chapter 7 Transportation on Demand","year":2006,"lang":"en","type":"book-chapter","venue":"Handbooks in operations research and management science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Computer Research Institute of Montréal; HEC Montréal","funders":"","keywords":"Popularity; Destinations; Business; Population; Transport engineering; Engineering; Tourism; Geography","score_opus":0.046586097847577106,"score_gpt":0.3068273592142239,"score_spread":0.26024126136664677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1573914938","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00048548775,0.012229548,0.0020984206,0.002797135,0.0022616908,0.000026043992,0.00044853607,0.00008675148,0.9795664],"genre_scores_gemma":[0.0056090974,0.015649097,0.00087878254,0.00069469766,0.00080300035,0.00003501035,0.00060985726,0.000095749536,0.97562474],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998728,0.000014835072,0.0000040465115,0.000021518597,0.00006780016,0.000018893074],"domain_scores_gemma":[0.9999317,0.000012837764,0.0000031527843,0.000009366789,0.000033612127,0.000009414271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001209962,0.000885232,0.00041186617,0.001031515,0.0009146006,0.0021343718,0.0007010795,0.001053894,0.18525818],"category_scores_gemma":[0.00037733724,0.0002865777,0.00047399732,0.0015881836,0.0004944267,0.002057868,0.00097143213,0.0017536224,0.041311778],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009839483,0.00004749959,0.000092181304,0.00018075215,0.0000050775348,0.000037638063,0.0002007824,0.0006977744,0.00031875228,0.24126251,0.6547141,0.10243308],"study_design_scores_gemma":[0.0000010889596,0.000005722131,0.00012690508,0.00010654608,0.000002219781,0.000025855858,0.00006963508,0.00008871316,0.00008016806,0.023701236,0.9757892,0.000002610144],"about_ca_topic_score_codex":0.0059580156,"about_ca_topic_score_gemma":0.011098019,"teacher_disagreement_score":0.18525818,"about_ca_system_score_codex":0.0017819054,"about_ca_system_score_gemma":0.0015104479,"threshold_uncertainty_score":0.6197504},"labels":[],"label_agreement":null},{"id":"W1574575548","doi":"10.1002/atr.1210","title":"Taxi services with search frictions and congestion externalities","year":2012,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Externality; Profit maximization; Microeconomics; Economics; Pareto principle; Profit (economics); Maximization; Welfare; Social Welfare; Operations management","score_opus":0.008651336276036885,"score_gpt":0.23054511358933197,"score_spread":0.22189377731329507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1574575548","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80806124,0.0012373785,0.10154013,0.002866279,0.00008339694,0.00019742471,0.00061159005,0.0001996129,0.085203],"genre_scores_gemma":[0.9950228,0.00021245414,0.0011907965,0.000035251607,0.000014669866,0.000015901134,0.000038407,0.000010700714,0.0034589139],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993747,0.00017801918,0.000019893054,0.00006245475,0.000114416915,0.00025060808],"domain_scores_gemma":[0.9978011,0.0009563221,0.0005715451,0.00014057285,0.00027485582,0.00025558105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009107383,0.0003395537,0.0006821342,0.0006455551,0.00079545286,0.0023646746,0.0009098237,0.0007966954,0.015414548],"category_scores_gemma":[0.004987487,0.00027146892,0.00077113963,0.0011294057,0.0012739683,0.0026499236,0.0013162638,0.0011127945,0.00035039586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017578478,0.00011209378,0.0075573563,0.00014965385,0.00007796765,0.00057935284,0.00016196693,0.59186405,0.0011769419,0.37840292,0.0030409156,0.016701018],"study_design_scores_gemma":[0.00009284734,0.00017467864,0.0075132223,0.0000716594,0.00010294823,0.00045524215,0.0008579956,0.80322963,0.0011305265,0.17839773,0.007905681,0.00006787566],"about_ca_topic_score_codex":0.020255841,"about_ca_topic_score_gemma":0.0134803755,"teacher_disagreement_score":0.020255841,"about_ca_system_score_codex":0.0030093417,"about_ca_system_score_gemma":0.002513947,"threshold_uncertainty_score":0.05156678},"labels":[],"label_agreement":null},{"id":"W1588783283","doi":"","title":"PDAs and medicine","year":2001,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; World Wide Web; Data science; Multimedia; Internet privacy","score_opus":0.006544107199900717,"score_gpt":0.2177472724833521,"score_spread":0.21120316528345137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1588783283","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0041014412,0.56668705,0.0026305106,0.23972845,0.009958402,0.00002970183,0.00015040925,0.00017610974,0.17653798],"genre_scores_gemma":[0.13053341,0.65905935,0.005837569,0.11097765,0.021403482,0.00013657573,0.00019601856,0.00009093394,0.07176505],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99731344,0.0012455157,0.00012942268,0.0003605803,0.0006941462,0.00025675842],"domain_scores_gemma":[0.9960975,0.0019750406,0.00033098567,0.00023272452,0.0006223382,0.0007414392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029514707,0.00048088134,0.0006639352,0.002041416,0.0024039152,0.006910884,0.00072524656,0.004939705,0.021683622],"category_scores_gemma":[0.0065739835,0.00019352735,0.00046777705,0.0014153706,0.009547772,0.0050368872,0.0036638146,0.0043728724,0.0058479942],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022322015,0.00023968406,0.0044903858,0.0015713372,0.000063521096,0.0005211142,0.0027425953,0.0003412613,0.00061664893,0.32993856,0.20580156,0.45345002],"study_design_scores_gemma":[0.000034444023,0.00017795169,0.0028489695,0.0013886576,0.000022418113,0.0012492478,0.0012911386,0.00006985583,0.00014545534,0.07970879,0.91302115,0.00004190372],"about_ca_topic_score_codex":0.0080347685,"about_ca_topic_score_gemma":0.007807725,"teacher_disagreement_score":0.021683622,"about_ca_system_score_codex":0.0034345589,"about_ca_system_score_gemma":0.003474238,"threshold_uncertainty_score":0.07253897},"labels":[],"label_agreement":null},{"id":"W1591765481","doi":"","title":"Carsharing in France: Past, Present, and Future","year":2009,"lang":"en","type":"article","venue":"Loughborough University Institutional Repository (Loughborough University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Car ownership; Business; Car sharing; Transport engineering; Engineering; Public transport","score_opus":0.005025966214354233,"score_gpt":0.16993069952678908,"score_spread":0.16490473331243485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1591765481","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.586598,0.12744884,0.0019190976,0.10448416,0.0010555751,0.000052114912,0.0027500382,0.00039710107,0.17529505],"genre_scores_gemma":[0.9154565,0.032074533,0.0019307388,0.0035359412,0.00032100087,0.000024484434,0.0009658506,0.000048764865,0.045642275],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99860567,0.00030513675,0.000034022272,0.00016809728,0.00024147765,0.0006456043],"domain_scores_gemma":[0.9984908,0.0002238904,0.0002571032,0.00006138179,0.0004920995,0.00047469075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020409585,0.000313248,0.00025873655,0.0013778683,0.0016690595,0.0041969,0.00073978264,0.0018408438,0.011487008],"category_scores_gemma":[0.0016833089,0.00016165628,0.0005102485,0.0026594275,0.0011238273,0.0026142497,0.0008995489,0.0009854565,0.0012664613],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046434585,0.00062627415,0.15032545,0.0009930003,0.00013719207,0.0018827184,0.006638637,0.0024360688,0.00229724,0.103876546,0.059124485,0.67119807],"study_design_scores_gemma":[0.000020866173,0.0004004021,0.35994703,0.00069687795,0.000045127235,0.00091035414,0.014779732,0.00090738205,0.0007272734,0.0027105473,0.618744,0.00011031249],"about_ca_topic_score_codex":0.1949988,"about_ca_topic_score_gemma":0.25929287,"teacher_disagreement_score":0.1949988,"about_ca_system_score_codex":0.010131961,"about_ca_system_score_gemma":0.0067270915,"threshold_uncertainty_score":0.38772756},"labels":[],"label_agreement":null},{"id":"W1592723029","doi":"","title":"Local Transport Systems for the Elderly and Disabled","year":2004,"lang":"en","type":"article","venue":"10th International Conference on Mobility and Transport for Elderly and Disabled PeopleJapan Society of Civil EngineersTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Public transport; Train; Subsidy; Universal design; Business; Disabled people; Usability; Service (business); Transport engineering; Marketing; Engineering; Computer science; Political science; Psychology; Geography","score_opus":0.04674943397954523,"score_gpt":0.3073508376774533,"score_spread":0.2606014036979081,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1592723029","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.302628,0.014105193,0.011088466,0.01126958,0.00046437432,0.00040705045,0.0036968621,0.0017063643,0.65463406],"genre_scores_gemma":[0.7543028,0.013044038,0.007554884,0.0009373685,0.0001668609,0.00021867701,0.0031942506,0.00014850218,0.22043264],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999519,0.00014066763,0.00003994235,0.00004432978,0.00009209246,0.00016400823],"domain_scores_gemma":[0.9990625,0.00006481466,0.00008782412,0.00010573334,0.00034331196,0.00033580876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005814182,0.00026256082,0.00018084713,0.0015622601,0.0029774506,0.0031771616,0.00061572646,0.00052195956,0.028062612],"category_scores_gemma":[0.0014729216,0.00010204906,0.0002254361,0.0031402106,0.0009473988,0.0018887259,0.0038859788,0.00037799397,0.006700016],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025343877,0.00020123018,0.052663967,0.0015246383,0.00005463262,0.0015873783,0.028392475,0.0038928788,0.0021153481,0.13179809,0.20994413,0.5675718],"study_design_scores_gemma":[0.000021620828,0.00014203438,0.04217271,0.00060869014,0.00004509994,0.00061602384,0.032986004,0.0007246334,0.00047976762,0.0047268528,0.9174227,0.000053813084],"about_ca_topic_score_codex":0.13911127,"about_ca_topic_score_gemma":0.17952545,"teacher_disagreement_score":0.13911127,"about_ca_system_score_codex":0.0044147824,"about_ca_system_score_gemma":0.0069308723,"threshold_uncertainty_score":0.2766031},"labels":[],"label_agreement":null},{"id":"W1598065386","doi":"10.17226/21951","title":"Use of Rear-Facing Position for Common Wheelchairs on Transit Buses","year":2003,"lang":"en","type":"book","venue":"Transportation Research Board eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Position (finance); Transport engineering; Computer science; Aeronautics; Engineering; Business; Public transport","score_opus":0.10721927676289476,"score_gpt":0.3278122079022688,"score_spread":0.220592931139374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1598065386","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.61999106,0.031332847,0.01161543,0.008061317,0.0009947566,0.00037081965,0.0022040885,0.0002763749,0.32515332],"genre_scores_gemma":[0.93358856,0.028549448,0.008755042,0.0007490231,0.0000730379,0.00012475804,0.00089866825,0.00008050215,0.027180934],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9964843,0.0013708768,0.00026519792,0.00037196086,0.0011240388,0.00038375828],"domain_scores_gemma":[0.99730384,0.0005581457,0.00063972257,0.00011265292,0.00125204,0.00013364299],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014004963,0.0003463657,0.00028708007,0.0022699926,0.0022640915,0.0035947452,0.0012776405,0.0006087628,0.007404829],"category_scores_gemma":[0.0048249844,0.00018694256,0.00043022394,0.003258984,0.0012491351,0.002408898,0.0012149932,0.00052271085,0.0014917523],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015844384,0.00015880115,0.062099926,0.009288638,0.00009778791,0.0028036581,0.18469808,0.001037882,0.005796796,0.035423335,0.048431106,0.6500056],"study_design_scores_gemma":[0.000010547158,0.00028877106,0.11830146,0.007542112,0.00017177875,0.0016123009,0.30782962,0.00039526244,0.002505166,0.0009971284,0.5602551,0.000090844835],"about_ca_topic_score_codex":0.117465235,"about_ca_topic_score_gemma":0.33020988,"teacher_disagreement_score":0.117465235,"about_ca_system_score_codex":0.0056113503,"about_ca_system_score_gemma":0.0074408078,"threshold_uncertainty_score":0.233563},"labels":[],"label_agreement":null},{"id":"W168511276","doi":"","title":"Optimisation de tournées de service en temps réel","year":2014,"lang":"fr","type":"dissertation","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Philosophy","score_opus":0.00835731377402496,"score_gpt":0.2286139103846428,"score_spread":0.22025659661061783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W168511276","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20269771,0.002882978,0.71399635,0.0022927371,0.0010435616,0.000799485,0.0014302236,0.005059572,0.06979751],"genre_scores_gemma":[0.85118407,0.0005804407,0.10132057,0.00035812228,0.00012482394,0.00047398635,0.0011189173,0.0009729084,0.043866206],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974655,0.00074683584,0.00012214325,0.00053050567,0.00044216795,0.0006928075],"domain_scores_gemma":[0.99362165,0.0031837882,0.0004915576,0.00050392357,0.0009491316,0.0012499496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003773117,0.0017426776,0.0022790194,0.0013820812,0.0016687878,0.004284173,0.0025269925,0.002058098,0.046972785],"category_scores_gemma":[0.012969874,0.0008130377,0.0014062084,0.0011283805,0.00097332447,0.002193072,0.0025016037,0.0023545744,0.005387771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015075955,0.00046335175,0.0038778118,0.00036252028,0.0001500688,0.00022974706,0.0003608675,0.7997589,0.0033917879,0.022704175,0.014782772,0.15241039],"study_design_scores_gemma":[0.00011910711,0.00042177254,0.0012303427,0.00005736948,0.00004447975,0.00005730272,0.00029272042,0.9796944,0.00089823036,0.0099879885,0.0071669947,0.000029318182],"about_ca_topic_score_codex":0.012504416,"about_ca_topic_score_gemma":0.011513531,"teacher_disagreement_score":0.046972785,"about_ca_system_score_codex":0.0024422898,"about_ca_system_score_gemma":0.0034908424,"threshold_uncertainty_score":0.1571396},"labels":[],"label_agreement":null},{"id":"W169566816","doi":"","title":"Metro's BRT 25: Analysis of Bus Rapid Transit Projects in North America [2008]","year":2008,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Bus rapid transit; Transport engineering; Transit (satellite); Plan (archaeology); Atlanta; Agency (philosophy); Public transport; Engineering; Business; Geography; Metropolitan area","score_opus":0.018087031910601584,"score_gpt":0.21409261117542747,"score_spread":0.19600557926482587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W169566816","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9643578,0.0008687007,0.00037286442,0.00029528118,0.000010727456,0.00012189669,0.021466313,0.000046233064,0.012460223],"genre_scores_gemma":[0.94761807,0.0012295389,0.0011939147,0.00008694404,0.00001461405,0.00029950202,0.038737252,0.000027987016,0.010792186],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994618,0.00007150777,0.000028853396,0.000055646353,0.00028757044,0.000094529714],"domain_scores_gemma":[0.9982917,0.00011873379,0.00044919841,0.00003743943,0.00085536775,0.00024748984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043367632,0.00020283315,0.0001991518,0.004070596,0.0007213205,0.000736305,0.0004282566,0.00017193773,0.0024065787],"category_scores_gemma":[0.0014805292,0.00019137491,0.00024477387,0.009416966,0.00016387623,0.00036037492,0.0005789903,0.00025350827,0.00038994776],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006322221,0.00008308857,0.9362834,0.00020358982,0.00007906146,0.00024711195,0.0026206227,0.0007348631,0.00038279363,0.0008008493,0.026745172,0.031756274],"study_design_scores_gemma":[0.0000022020708,0.00001751676,0.986938,0.00002313205,0.000008460961,0.00004809859,0.003115912,0.00032404822,0.000046914807,0.000022455468,0.009449453,0.000003866664],"about_ca_topic_score_codex":0.58383185,"about_ca_topic_score_gemma":0.78315717,"teacher_disagreement_score":0.58383185,"about_ca_system_score_codex":0.0028036318,"about_ca_system_score_gemma":0.003960169,"threshold_uncertainty_score":0.8372381},"labels":[],"label_agreement":null},{"id":"W1740140547","doi":"10.1016/j.tre.2015.06.012","title":"Vehicle relocation and staff rebalancing in one-way carsharing systems","year":2015,"lang":"en","type":"article","venue":"Transportation Research Part E Logistics and Transportation Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":168,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Relocation; Business; Transport engineering; Travelling salesman problem; Computer science; Engineering","score_opus":0.18356497194715393,"score_gpt":0.3541233505864526,"score_spread":0.17055837863929868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1740140547","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5023816,0.30355603,0.090960875,0.0041242037,0.0030778754,0.00034333082,0.00024444083,0.00032762857,0.094983995],"genre_scores_gemma":[0.9420696,0.043384932,0.0054151765,0.00019444084,0.00030272984,0.000047044097,0.00010152643,0.000025242347,0.008459245],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990388,0.00021356506,0.000041234245,0.00016431071,0.00023699678,0.00030509505],"domain_scores_gemma":[0.99890816,0.0005102261,0.00012896316,0.000072018796,0.00030937153,0.00007128539],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013997202,0.00046229278,0.00058133405,0.000620511,0.0006537551,0.0014926518,0.0017553346,0.0006028098,0.005630631],"category_scores_gemma":[0.002302876,0.0002480931,0.00059623306,0.0013847023,0.0008128409,0.0025533377,0.0007594722,0.00082448684,0.00043005645],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043112002,0.0003421014,0.005671056,0.0020935917,0.00019891688,0.00015020219,0.0005153025,0.110425785,0.003518721,0.06603736,0.009151341,0.8014644],"study_design_scores_gemma":[0.00026071945,0.0045300494,0.0683511,0.0028317997,0.0011276895,0.0015576741,0.0104811825,0.3504537,0.026145501,0.11481181,0.41908467,0.000364091],"about_ca_topic_score_codex":0.007625181,"about_ca_topic_score_gemma":0.009492212,"teacher_disagreement_score":0.007625181,"about_ca_system_score_codex":0.002509004,"about_ca_system_score_gemma":0.0016701921,"threshold_uncertainty_score":0.018836379},"labels":[],"label_agreement":null},{"id":"W178821265","doi":"","title":"Uses of Social Media in Public Transportation: Summary of Findings from TCRP Synthesis SB-20","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Social media; Staffing; Agency (philosophy); Public relations; Dissemination; Business; Service (business); Public service; Advertising; Internet privacy; Political science; Computer science; Sociology; Marketing; World Wide Web","score_opus":0.08234193365698336,"score_gpt":0.3419716386726636,"score_spread":0.2596297050156803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W178821265","genre_codex":"empirical","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.773738,0.0246643,0.0038177026,0.009419691,0.0004222337,0.0041551376,0.05832829,0.00023266867,0.12522194],"genre_scores_gemma":[0.92824227,0.033535525,0.004030685,0.002736616,0.00016826512,0.004860722,0.013250991,0.00020024843,0.012974632],"study_design_codex":"qualitative","study_design_gemma":"not_applicable","domain_scores_codex":[0.9932701,0.0027639195,0.00081759377,0.00054418703,0.0019761096,0.00062804914],"domain_scores_gemma":[0.9767086,0.01183231,0.0022334924,0.0006059095,0.008044581,0.00057509134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009009694,0.0004997727,0.00067795615,0.008586387,0.001956071,0.0040297383,0.000816528,0.00083007984,0.006623683],"category_scores_gemma":[0.023536066,0.00058293337,0.00094500167,0.012873463,0.0011259189,0.0042173318,0.0038525497,0.0011950999,0.001233604],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047699726,0.00022910566,0.19232325,0.03307267,0.00034221527,0.0012375413,0.45918784,0.0006585209,0.0019195357,0.0032357725,0.037578024,0.26973858],"study_design_scores_gemma":[0.000018315279,0.00013964386,0.21420792,0.008506064,0.00020005026,0.00024946852,0.68445385,0.00016950573,0.00065405335,0.00032951095,0.091017544,0.000054154865],"about_ca_topic_score_codex":0.09285308,"about_ca_topic_score_gemma":0.14141208,"teacher_disagreement_score":0.09285308,"about_ca_system_score_codex":0.007213772,"about_ca_system_score_gemma":0.00933863,"threshold_uncertainty_score":0.18462521},"labels":[],"label_agreement":null},{"id":"W1800891536","doi":"10.4271/2002-01-1581","title":"Quarter Vehicle Ride Model","year":2002,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Computer science; Geography","score_opus":0.015523114917249099,"score_gpt":0.2255297461758789,"score_spread":0.2100066312586298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1800891536","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1031895,0.0020471064,0.63441545,0.0015370651,0.0006610312,0.0006352565,0.02001581,0.0034196407,0.2340792],"genre_scores_gemma":[0.7656886,0.0012802737,0.030946925,0.00022699845,0.000094201314,0.0007625877,0.011694288,0.00027571895,0.18903038],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977344,0.000036231835,0.000014688631,0.000064292304,0.000074033014,0.00003736699],"domain_scores_gemma":[0.9998165,0.000027499116,0.000022869646,0.000023237812,0.00009776806,0.000012206198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002104554,0.0007118037,0.00089236256,0.0006601193,0.0006175852,0.0011391074,0.0027824435,0.001367792,0.042519435],"category_scores_gemma":[0.00050926715,0.0003564043,0.00073033455,0.00051497377,0.00032373544,0.0011812515,0.000998653,0.00075676886,0.008364658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017871642,0.000060881852,0.0014395529,0.00021188053,0.0000340399,0.0003236476,0.00010467523,0.9377715,0.0022870926,0.02490276,0.011184989,0.021500347],"study_design_scores_gemma":[0.000026206797,0.000048181635,0.00032024604,0.000010376912,0.000012081453,0.000060203387,0.000035449542,0.9841174,0.000309491,0.0030541283,0.011993199,0.000013076502],"about_ca_topic_score_codex":0.016911132,"about_ca_topic_score_gemma":0.0070392755,"teacher_disagreement_score":0.042519435,"about_ca_system_score_codex":0.0006301164,"about_ca_system_score_gemma":0.0006961275,"threshold_uncertainty_score":0.14224166},"labels":[],"label_agreement":null},{"id":"W1800954673","doi":"10.24908/pceea.v0i0.4678","title":"A HOLISTIC, INTERDISCIPLNARY APPROACH TO THE DESIGN OF A SUSTAINABLE PERSONAL MOBIILTY SYSTEM","year":2012,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Sociotechnical system; Scope (computer science); Engineering management; Personal mobility; Sustainable transport; Knowledge management; Ambiguity; Engineering; Sustainable development; Renewable energy; Work (physics); Systems engineering; Computer science; Sustainability; Telecommunications","score_opus":0.012975997367986183,"score_gpt":0.20715948203760712,"score_spread":0.19418348466962093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1800954673","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032408,0.0009025044,0.890194,0.0023833932,0.00016493656,0.000300741,0.00003060923,0.00036576134,0.07325004],"genre_scores_gemma":[0.39284793,0.0011259192,0.58167416,0.00065123383,0.000047829224,0.00059409847,0.00008938062,0.00010421002,0.0228652],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99803084,0.00088262104,0.000075644006,0.00020904953,0.0005915953,0.0002103109],"domain_scores_gemma":[0.9994784,0.000093689596,0.000032639302,0.00007501782,0.0001636602,0.00015658098],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023948972,0.0006938408,0.00034445937,0.00066745444,0.0015973116,0.0037939704,0.0013979572,0.0014393397,0.005169396],"category_scores_gemma":[0.0016446437,0.0004786815,0.0006851063,0.00034426933,0.0026147147,0.002794507,0.005734712,0.001313767,0.0010893143],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000101118945,0.00041590718,0.0055009075,0.0010047477,0.0001755776,0.0013351261,0.015464274,0.14049928,0.03763393,0.5111682,0.008312395,0.27838853],"study_design_scores_gemma":[0.000098496595,0.00089864404,0.0027550743,0.0008080816,0.00017295167,0.0016761364,0.017044745,0.21045959,0.013614968,0.23841102,0.5139324,0.00012789975],"about_ca_topic_score_codex":0.0014536905,"about_ca_topic_score_gemma":0.002202913,"teacher_disagreement_score":0.005169396,"about_ca_system_score_codex":0.0013959749,"about_ca_system_score_gemma":0.0034303227,"threshold_uncertainty_score":0.017293334},"labels":[],"label_agreement":null},{"id":"W18147807","doi":"10.1038/scientificamerican0549-40","title":"Apply by Phone for a Mortgage or Loan","year":2013,"lang":"en","type":"article","venue":"Scientific American","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Mortgage underwriting; Business; Phone; Prepayment of loan; Loan; Amortizing loan; Finance; Computer science; Mortgage insurance; Bridge loan; Insurance policy; Non-performing loan","score_opus":0.010078390045831817,"score_gpt":0.23109326548794704,"score_spread":0.22101487544211523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W18147807","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0062883566,0.00011263407,0.0005040059,0.0035139774,0.0009169814,0.0003693284,0.001424796,0.00072853884,0.98614144],"genre_scores_gemma":[0.0031563295,0.000073793904,0.0001294527,0.0006150642,0.000059582235,0.000047547564,0.0002870459,0.0000719793,0.99555933],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99907035,0.000038408714,0.000030462943,0.000075828444,0.00043512922,0.00034977138],"domain_scores_gemma":[0.9973398,0.00014838706,0.000070716975,0.00015638128,0.0010454985,0.0012391246],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00053058687,0.0008677912,0.00062917185,0.0012001336,0.0059152115,0.0031159457,0.0009314345,0.0019926215,0.7297926],"category_scores_gemma":[0.0031467092,0.00058520434,0.0006242382,0.0006924061,0.00050828827,0.0009801091,0.0025180422,0.0017082391,0.67092156],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038484453,0.00015359878,0.0015850575,0.000029495412,0.0000034803322,0.00018360713,0.00014603174,0.000051073213,0.0012154198,0.00071532564,0.93915284,0.056725644],"study_design_scores_gemma":[0.000032030657,0.000093333336,0.014146331,0.000040164494,0.0000062719832,0.00017691264,0.00075588684,0.00012271301,0.00048306753,0.00031990412,0.9838075,0.000015837482],"about_ca_topic_score_codex":0.04020791,"about_ca_topic_score_gemma":0.18482417,"teacher_disagreement_score":0.2702074,"about_ca_system_score_codex":0.001174113,"about_ca_system_score_gemma":0.0065094484,"threshold_uncertainty_score":0.38541806},"labels":[],"label_agreement":null},{"id":"W1821418860","doi":"","title":"Carplus annual survey of car clubs 2009/10","year":2010,"lang":"en","type":"article","venue":"UCL Discovery (University College London)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Club; Car ownership; Quarter (Canadian coin); TRIPS architecture; Transport engineering; Neighbourhood (mathematics); Public transport; Advertising; Engineering; Business; Sample (material); Geography; Mathematics","score_opus":0.006807507978966427,"score_gpt":0.1849296970677616,"score_spread":0.17812218908879518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1821418860","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18691526,0.0006724664,0.00047032477,0.0008535263,0.00015692682,0.00051333697,0.75565237,0.00042166008,0.054344088],"genre_scores_gemma":[0.31731084,0.002113982,0.0018561248,0.0010281878,0.00018525666,0.0016544177,0.5997994,0.00015991856,0.075891905],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99868244,0.00018082988,0.00014137586,0.00016012345,0.0006579044,0.00017733453],"domain_scores_gemma":[0.99640226,0.00021441015,0.0010098038,0.00016199073,0.001866823,0.00034472012],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006998355,0.00030208044,0.00025672602,0.0029800918,0.00042871656,0.000623686,0.0007230703,0.00033052466,0.01362582],"category_scores_gemma":[0.002113346,0.0002600835,0.0001884897,0.0035537502,0.00012413773,0.00038652946,0.00066364766,0.00032777205,0.011746875],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002744993,0.00017348815,0.39635053,0.00032515166,0.000046109675,0.00014280468,0.0003432636,0.00020810688,0.0007279403,0.00033514423,0.5762001,0.024872845],"study_design_scores_gemma":[0.000011803864,0.00005007443,0.9024822,0.00008114816,0.0000102907325,0.00014473649,0.0003414589,0.00021057668,0.00025038005,0.000016959108,0.09638195,0.000018409148],"about_ca_topic_score_codex":0.11268349,"about_ca_topic_score_gemma":0.14099324,"teacher_disagreement_score":0.11268349,"about_ca_system_score_codex":0.0016582885,"about_ca_system_score_gemma":0.0010476366,"threshold_uncertainty_score":0.22405517},"labels":[],"label_agreement":null},{"id":"W188833415","doi":"","title":"Adaptation du SIG PHYSITEL pour les besoins de mise en place d'HYDROTEL à partir du réseau filamentaire du gouvernement du Québec","year":2009,"lang":"fr","type":"article","venue":"EspaceINRS (National Institute for Scientific Research (Canada))","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Political science","score_opus":0.03487042308092506,"score_gpt":0.2883325447629324,"score_spread":0.2534621216820073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W188833415","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97903764,0.00014090705,0.00886842,0.00028038354,0.00008731689,0.00008834261,0.00051185524,0.00063669373,0.010348481],"genre_scores_gemma":[0.9825805,0.0000585354,0.005209271,0.000035271427,0.000008822171,0.00004296589,0.00024616794,0.000065732325,0.011752749],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99923193,0.000123355,0.000028409959,0.00013790803,0.00030405537,0.00017427641],"domain_scores_gemma":[0.9972066,0.0005117647,0.00016033545,0.00026374764,0.0015144431,0.0003430067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011794936,0.0004767944,0.00036240811,0.0007719624,0.0015104307,0.0018255095,0.0007266783,0.0007052026,0.005922613],"category_scores_gemma":[0.0044396077,0.00021305103,0.0003145924,0.00064935215,0.000646715,0.00049407146,0.0009412999,0.00046106256,0.0011368277],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002720221,0.00070286304,0.31926546,0.0002389143,0.000201612,0.00080145826,0.0044216155,0.20553806,0.05449236,0.0019963037,0.0076111727,0.40201],"study_design_scores_gemma":[0.00013297527,0.0017645955,0.69217265,0.000104293,0.00020664376,0.00018969444,0.009219928,0.22626314,0.028798897,0.00076301553,0.04020235,0.0001817489],"about_ca_topic_score_codex":0.58718556,"about_ca_topic_score_gemma":0.70303077,"teacher_disagreement_score":0.99523616,"about_ca_system_score_codex":0.0047638486,"about_ca_system_score_gemma":0.0052385856,"threshold_uncertainty_score":0.8304912},"labels":[],"label_agreement":null},{"id":"W1900501498","doi":"10.1002/atr.1289","title":"A methodology for choosing between fixed‐route and flex‐route policies for transit services","year":2014,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China; China Scholarship Council; Government of Jiangsu Province; National Natural Science Foundation of China","keywords":"Transit (satellite); Operability; FLEX; Flexibility (engineering); Service (business); Transport engineering; Computer science; Function (biology); Quality (philosophy); Level of service; Service quality; Operations research; Public transport; Engineering; Business; Economics; Telecommunications","score_opus":0.03088930387238569,"score_gpt":0.3046892800197631,"score_spread":0.2737999761473774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1900501498","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0059649427,0.00007640156,0.9918188,0.00008912812,0.000012520131,0.00016371813,0.000032650423,0.0000894384,0.0017524838],"genre_scores_gemma":[0.17160599,0.00016214112,0.8264847,0.00005228599,0.000020803465,0.00032264684,0.0000744018,0.0000469858,0.0012300698],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982134,0.00086932664,0.000094329014,0.00026573412,0.00039023414,0.00016695513],"domain_scores_gemma":[0.9968681,0.0018796202,0.0003029614,0.00012274484,0.0006943147,0.00013230242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0050469367,0.000934828,0.00077144464,0.0024553544,0.0008096309,0.0016403642,0.001622672,0.0012987353,0.0047811177],"category_scores_gemma":[0.0078200465,0.00054804416,0.0011655472,0.0011858881,0.0010577645,0.001125861,0.0011424941,0.001126348,0.00041445674],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008936842,0.00014466856,0.0018384424,0.0002795805,0.00008319652,0.0002689923,0.00022474075,0.7188191,0.0053373966,0.12338939,0.0021062675,0.14741884],"study_design_scores_gemma":[0.000021201837,0.000058837293,0.00016543429,0.00003331524,0.000020668529,0.00005122765,0.00005734741,0.9756614,0.001155092,0.021122433,0.0016354186,0.000017611354],"about_ca_topic_score_codex":0.00419624,"about_ca_topic_score_gemma":0.0036504308,"teacher_disagreement_score":0.0050469367,"about_ca_system_score_codex":0.0022288286,"about_ca_system_score_gemma":0.0033754942,"threshold_uncertainty_score":0.02669108},"labels":[],"label_agreement":null},{"id":"W1932811023","doi":"10.1002/atr.1283","title":"An agent‐based simulation model to assess the impacts of introducing a shared‐taxi system: an application to Lisbon (Portugal)","year":2014,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":146,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Science Foundation","keywords":"Taxis; TRIPS architecture; Revenue; Operations research; Function (biology); Computer science; Set (abstract data type); Transport engineering; Sharing economy; Mode (computer interface); Matching (statistics); Engineering; Business","score_opus":0.02014116571891006,"score_gpt":0.2947942593456919,"score_spread":0.27465309362678186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1932811023","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90542495,0.00027807037,0.057646815,0.00059168215,0.00012128893,0.00023675084,0.0009798037,0.0005890445,0.034131575],"genre_scores_gemma":[0.98807585,0.00009117618,0.008005284,0.00001653473,0.000004920259,0.000098899385,0.00025362105,0.00002524727,0.0034283933],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997143,0.00014802742,0.000012637756,0.000033269996,0.0000353593,0.00005631168],"domain_scores_gemma":[0.99864095,0.0009008259,0.000096112555,0.00006674305,0.00018133128,0.00011409175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007034648,0.0006941516,0.0007010237,0.00047663716,0.00079265924,0.0015281112,0.0009616535,0.0015644237,0.005156897],"category_scores_gemma":[0.0017893149,0.0003956276,0.0007418646,0.0006072469,0.00052708364,0.000611999,0.00070616324,0.00086034136,0.0003047661],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008448076,0.000059110695,0.0010309394,0.000024049179,0.000013229503,0.000100312194,0.000041923395,0.9957041,0.00020734369,0.0015047232,0.00022199546,0.0010078441],"study_design_scores_gemma":[0.000028455479,0.000039290928,0.00031526992,0.000006627348,0.00000768069,0.0000068353097,0.000048117345,0.998762,0.00013605549,0.0002597191,0.00038379087,0.0000061275646],"about_ca_topic_score_codex":0.06846434,"about_ca_topic_score_gemma":0.029484313,"teacher_disagreement_score":0.06846434,"about_ca_system_score_codex":0.002192127,"about_ca_system_score_gemma":0.001681871,"threshold_uncertainty_score":0.13613164},"labels":[],"label_agreement":null},{"id":"W1964139958","doi":"10.1002/atr.5670400103","title":"The importance of information flows temporal attributes for the efficient scheduling of dynamic demand responsive transport services","year":2006,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Scheduling (production processes); Schedule; Dynamic priority scheduling; Pickup; Operations research; Interval (graph theory); Process (computing); Real-time computing; Distributed computing; Mathematical optimization; Engineering; Mathematics; Artificial intelligence","score_opus":0.004689171996559512,"score_gpt":0.22850047853906935,"score_spread":0.22381130654250983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964139958","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7975157,0.00048941374,0.19764191,0.0005148109,0.000045520912,0.00008623067,0.0001351109,0.00030286115,0.0032684417],"genre_scores_gemma":[0.9892762,0.00006259865,0.010451997,0.000011865351,0.000017096245,0.000014032883,0.000042664964,0.000019335004,0.000104277526],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851006,0.00056251336,0.00009146358,0.00012413638,0.00053882523,0.0001730007],"domain_scores_gemma":[0.9763763,0.018615827,0.0019624566,0.0007561425,0.0016393873,0.00064981927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028398377,0.00036430516,0.00032758774,0.0010949976,0.00057223014,0.0015457525,0.00041152586,0.00041667616,0.00076844776],"category_scores_gemma":[0.022125717,0.00027297423,0.0002064024,0.00092053984,0.0005509652,0.0012758408,0.00035184307,0.0005348998,0.00008055984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017697059,0.00026101543,0.015831776,0.00020965881,0.00006593352,0.00016527997,0.0001736716,0.8077028,0.040930633,0.014364992,0.00054853526,0.11797599],"study_design_scores_gemma":[0.000019277335,0.00015800791,0.0044484506,0.000009013203,0.000028754832,0.0000420587,0.000052802803,0.9830651,0.009217399,0.0025347776,0.00041463642,0.0000096141985],"about_ca_topic_score_codex":0.0019361078,"about_ca_topic_score_gemma":0.0014834971,"teacher_disagreement_score":0.0028398377,"about_ca_system_score_codex":0.0008991705,"about_ca_system_score_gemma":0.0013905638,"threshold_uncertainty_score":0.015018642},"labels":[],"label_agreement":null},{"id":"W1968474825","doi":"10.1061/9780784412862.018","title":"A Modern Mobility Solution for Urban Transit with the Latest Generation of the INNOVIA System","year":2013,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bombardier (Canada)","funders":"","keywords":"Turnkey; Transport engineering; Monorail; Transit system; Service (business); Transport system; Public transport; Stock (firearms); Business; Computer science; Transit (satellite); Telecommunications; Engineering; Marketing; Civil engineering","score_opus":0.016389806550289307,"score_gpt":0.18378246566084352,"score_spread":0.16739265911055423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968474825","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.056070693,0.005693437,0.5809935,0.005211404,0.0025132974,0.00070031435,0.0010929375,0.02450928,0.32321522],"genre_scores_gemma":[0.410974,0.0050877067,0.256119,0.0018330117,0.0008958045,0.00061992806,0.0036991695,0.001196454,0.31957486],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99955684,0.000040501138,0.000020340136,0.00006946358,0.00020794595,0.00010489629],"domain_scores_gemma":[0.9998529,0.000006461813,0.000009441877,0.000022080747,0.00008074545,0.000028411192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003094663,0.0005324477,0.00031291877,0.00075074093,0.00088793266,0.0014135446,0.0008965621,0.00089135556,0.018176591],"category_scores_gemma":[0.000433336,0.00018866519,0.0004530654,0.00065084756,0.00032320776,0.0019610184,0.0020328504,0.00086869,0.0072221304],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002809721,0.00020455156,0.0015780695,0.00035390744,0.000047008154,0.00044972406,0.0007756149,0.0057111126,0.040026125,0.094296604,0.17308156,0.6831948],"study_design_scores_gemma":[0.000058962738,0.00028218995,0.0012970603,0.000081573686,0.000053062384,0.0006939254,0.0002919133,0.03570326,0.0085571045,0.0077719856,0.9451496,0.000059383266],"about_ca_topic_score_codex":0.002246717,"about_ca_topic_score_gemma":0.0024304884,"teacher_disagreement_score":0.018176591,"about_ca_system_score_codex":0.0007123761,"about_ca_system_score_gemma":0.0009025283,"threshold_uncertainty_score":0.06080675},"labels":[],"label_agreement":null},{"id":"W1972707779","doi":"10.4271/2013-01-2493","title":"Implementation of Series-Parallel Multiple-Regime Vehicle Architecture Using 2013 Chevrolet Malibu Platform","year":2013,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"University of Victoria","keywords":"Series (stratigraphy); Architecture; Computer science; Art; Visual arts","score_opus":0.014530466797764253,"score_gpt":0.25151823507473453,"score_spread":0.23698776827697027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972707779","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.59615964,0.00013777464,0.2521674,0.00036222357,0.000293305,0.0010763059,0.0009136467,0.02009971,0.12879005],"genre_scores_gemma":[0.8683342,0.00011540124,0.08694277,0.000070961774,0.000015056981,0.00032043402,0.0015750354,0.0005418134,0.042084455],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99975973,0.000033199463,0.000008546003,0.000039067003,0.00010240071,0.000057091085],"domain_scores_gemma":[0.9998344,0.000008813191,0.000008784091,0.000032011372,0.00009013396,0.000025777776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003836365,0.0003738751,0.00014233871,0.0003254113,0.00031985398,0.00053022796,0.00097178493,0.00030283508,0.009154774],"category_scores_gemma":[0.000290626,0.00017743188,0.00033371977,0.00013111529,0.00015663338,0.00050257525,0.00057551,0.00045852375,0.0025512557],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013150307,0.0011209194,0.016090486,0.0004006515,0.00012229242,0.001731849,0.0007101559,0.16181336,0.38842133,0.023301983,0.033045214,0.37192675],"study_design_scores_gemma":[0.0002797147,0.0039592744,0.018764742,0.00008946607,0.00008529157,0.00074294826,0.00044027125,0.45284674,0.29414275,0.0023720488,0.22614631,0.00013051656],"about_ca_topic_score_codex":0.008381805,"about_ca_topic_score_gemma":0.009468784,"teacher_disagreement_score":0.009154774,"about_ca_system_score_codex":0.00068310153,"about_ca_system_score_gemma":0.0010584353,"threshold_uncertainty_score":0.03062576},"labels":[],"label_agreement":null},{"id":"W1975315301","doi":"10.3141/2063-13","title":"Object-Oriented Analysis of Carsharing System","year":2008,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Database transaction; Transport engineering; Operations research; Object (grammar); Computer science; Transaction data; Population; Business; Operations management; Geography; Engineering; Database","score_opus":0.07951712161297649,"score_gpt":0.34725873707339566,"score_spread":0.2677416154604192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975315301","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27332622,0.0014456713,0.6722939,0.0007363398,0.00010396555,0.0005387485,0.0019943728,0.0016039977,0.04795668],"genre_scores_gemma":[0.7714993,0.0010401986,0.20871982,0.00010706669,0.00010495309,0.00028923067,0.003739619,0.00031297636,0.0141869215],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991068,0.00018461383,0.00005703666,0.00014978898,0.00039912463,0.00010262586],"domain_scores_gemma":[0.99805707,0.0007672649,0.0003324037,0.00020492765,0.0005772458,0.0000610079],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010406674,0.00050155417,0.00027536048,0.003294664,0.0006033237,0.0027120265,0.0007279519,0.00039845516,0.0037187145],"category_scores_gemma":[0.0028581317,0.00023379673,0.000896226,0.003221518,0.0006261706,0.001954476,0.0005553455,0.00044146224,0.00052668387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013627918,0.00023946179,0.06597187,0.0006024336,0.00016282834,0.0009437371,0.0038865614,0.111493714,0.0070268027,0.60975623,0.0074411235,0.19233902],"study_design_scores_gemma":[0.000029675959,0.000109348104,0.044117793,0.0001408807,0.00015121963,0.00050480914,0.0025944952,0.67981845,0.0054001696,0.17013642,0.09692595,0.00007083224],"about_ca_topic_score_codex":0.011470024,"about_ca_topic_score_gemma":0.0038411312,"teacher_disagreement_score":0.011470024,"about_ca_system_score_codex":0.0016570196,"about_ca_system_score_gemma":0.0011864157,"threshold_uncertainty_score":0.022806525},"labels":[],"label_agreement":null},{"id":"W1977079414","doi":"10.1109/tits.2013.2293918","title":"Sizing Finite-Population Vehicle Pools","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Sizing; Quality of service; Computer science; Population; Probabilistic logic; Heuristic; Finite set; Set (abstract data type); Quality (philosophy); Real-time computing; Computer network; Operations research; Engineering; Mathematics; Artificial intelligence","score_opus":0.019323953302397195,"score_gpt":0.23256799444670412,"score_spread":0.21324404114430692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977079414","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14300266,0.00022491779,0.85077083,0.0001503655,0.000035549307,0.00025838253,0.00034156852,0.00046147493,0.004754277],"genre_scores_gemma":[0.7867593,0.00018821389,0.21005125,0.00005442808,0.000017714197,0.0003738881,0.00035561193,0.000089995134,0.002109579],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99953234,0.00015311265,0.000031360803,0.00010543449,0.00008246836,0.0000953391],"domain_scores_gemma":[0.9983841,0.0008898681,0.00028565453,0.00018819151,0.00015233645,0.00009979136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010301566,0.0007289262,0.0008688528,0.0006624306,0.00035274331,0.0009985993,0.0016891636,0.00063330284,0.0024670335],"category_scores_gemma":[0.0028675036,0.00042243864,0.0007244391,0.0008376038,0.00064980815,0.0013224568,0.00089237024,0.00048340028,0.00034847253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005572024,0.000032290776,0.0015632076,0.00006658722,0.000040887393,0.00006188018,0.000059846738,0.9630268,0.0044081933,0.0068988134,0.00060564064,0.023180103],"study_design_scores_gemma":[0.000014628704,0.00007400565,0.0004493546,0.000009887908,0.000017506314,0.000056214845,0.00007721563,0.9889848,0.0032413444,0.005484533,0.0015797638,0.000010674425],"about_ca_topic_score_codex":0.0034376187,"about_ca_topic_score_gemma":0.0038301414,"teacher_disagreement_score":0.0034376187,"about_ca_system_score_codex":0.0010136797,"about_ca_system_score_gemma":0.0016372459,"threshold_uncertainty_score":0.008253038},"labels":[],"label_agreement":null},{"id":"W1977798541","doi":"10.3141/2246-08","title":"Design of a Strategic-Tactical Stated-Choice Survey Methodology Using a Constructed Avatar","year":2011,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Respondent; Choice set; Set (abstract data type); Marketing; Travel behavior; Sample (material); Survey data collection; Avatar; Service (business); Business; Computer science; Advertising; Transport engineering; Psychology; Engineering; Human–computer interaction; Economics; Mathematics; Econometrics","score_opus":0.6125084295360983,"score_gpt":0.4535656764804287,"score_spread":0.15894275305566957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977798541","genre_codex":"protocol","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24868964,0.00017889267,0.22421981,0.0011651103,0.0004264018,0.50913525,0.0024928087,0.0005008131,0.013191262],"genre_scores_gemma":[0.093240365,0.00012847394,0.29569983,0.0006436784,0.000059320973,0.6072832,0.00045729856,0.00005230775,0.0024354972],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9477926,0.04370965,0.001864478,0.0026762309,0.0021010025,0.001856051],"domain_scores_gemma":[0.9549568,0.030433265,0.0020792442,0.004415515,0.0064581167,0.0016569949],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04687149,0.0011974946,0.0011714296,0.0024362388,0.0030821462,0.002438676,0.0025643872,0.0021558653,0.016299358],"category_scores_gemma":[0.045937672,0.0013699222,0.0013537363,0.0022812074,0.0024131634,0.0018140285,0.0028510224,0.0028570571,0.0034656595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.015289569,0.0300926,0.03554847,0.009922991,0.0003364196,0.0020099378,0.17426856,0.018676948,0.031521086,0.04345089,0.014732408,0.62415004],"study_design_scores_gemma":[0.027786551,0.110710055,0.06795358,0.0038078937,0.0008262134,0.00071680057,0.21906893,0.08406815,0.046629168,0.06938384,0.3678655,0.0011832343],"about_ca_topic_score_codex":0.0016541856,"about_ca_topic_score_gemma":0.0029745547,"teacher_disagreement_score":0.04687149,"about_ca_system_score_codex":0.0035434698,"about_ca_system_score_gemma":0.0067035235,"threshold_uncertainty_score":0.24788314},"labels":[],"label_agreement":null},{"id":"W1980388872","doi":"10.1504/ijeh.2007.015325","title":"An intelligent agent approach to improving the coordination efficiency in the donor kidney distribution process","year":2007,"lang":"en","type":"article","venue":"International Journal of Electronic Healthcare","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Joseph’s Healthcare Hamilton; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Process (computing); Computer science; Kidney transplantation; Process management; Transplantation; Distribution (mathematics); Distributed computing; Risk analysis (engineering); Medicine; Engineering; Surgery","score_opus":0.014193950426495653,"score_gpt":0.3114558823989448,"score_spread":0.29726193197244916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980388872","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026968038,0.0004630815,0.96523553,0.0006503146,0.000067686735,0.00011144448,0.00002124486,0.00043137645,0.0060512116],"genre_scores_gemma":[0.5535723,0.00060424116,0.44045624,0.00017105199,0.000080020436,0.00018379049,0.000054037857,0.000060243812,0.004818074],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933225,0.00027203676,0.00003959518,0.000118845084,0.00016279728,0.00007448819],"domain_scores_gemma":[0.9990388,0.00041126308,0.00016417475,0.00010521283,0.00019382038,0.00008677671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012773053,0.0005591217,0.00052280957,0.0005231986,0.0007439556,0.0015849272,0.0011219339,0.00091973814,0.0016392455],"category_scores_gemma":[0.0024597254,0.00024236544,0.00038747332,0.00043990143,0.0006704735,0.0015394299,0.0007725426,0.0006989051,0.00034065303],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040319748,0.00044768886,0.002746177,0.00034236535,0.00018859272,0.00037468926,0.00067484734,0.62323934,0.025626263,0.1257125,0.0035705855,0.21667372],"study_design_scores_gemma":[0.00006821823,0.00017842598,0.00044380783,0.00001899756,0.000062240775,0.000077128556,0.00010165505,0.9672043,0.0053268294,0.016432788,0.010060996,0.000024582723],"about_ca_topic_score_codex":0.0021809672,"about_ca_topic_score_gemma":0.0017971521,"teacher_disagreement_score":0.0021809672,"about_ca_system_score_codex":0.0007247905,"about_ca_system_score_gemma":0.0014695674,"threshold_uncertainty_score":0.006755173},"labels":[],"label_agreement":null},{"id":"W1980402561","doi":"10.1007/s10479-007-0170-8","title":"The dial-a-ride problem: models and algorithms","year":2007,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":866,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Theory of computation; Computer science; Pickup; Set (abstract data type); Algorithm; Plan (archaeology); Operations research; Mathematical optimization; Artificial intelligence; Mathematics; Image (mathematics); Programming language","score_opus":0.22324015215530751,"score_gpt":0.43758322828918544,"score_spread":0.21434307613387793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980402561","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.059100367,0.01769662,0.8856581,0.012878335,0.0006506334,0.00041483852,0.0027136588,0.0004780927,0.020409236],"genre_scores_gemma":[0.7053002,0.021251604,0.213837,0.0013661311,0.0017855013,0.0011318321,0.0037382585,0.00045207166,0.05113747],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99664485,0.001662584,0.00012109902,0.000857725,0.0002586315,0.00045515175],"domain_scores_gemma":[0.98216003,0.0144678885,0.0012721716,0.0005783373,0.00062037364,0.0009010945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005504806,0.0026162884,0.0067568426,0.0027520547,0.0022332699,0.008922808,0.008091384,0.009627685,0.013710114],"category_scores_gemma":[0.024198323,0.0029904821,0.002674738,0.006479082,0.0050605503,0.014828723,0.0042945873,0.0072545996,0.001636959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026384785,0.00039986474,0.0014566866,0.00047623823,0.00017630868,0.0001606819,0.00023190993,0.5600021,0.0001199182,0.3773781,0.030523526,0.028810851],"study_design_scores_gemma":[0.00009161309,0.00003721289,0.00020279364,0.00006252262,0.00006162243,0.00006808496,0.00015236664,0.67720526,0.00006227904,0.3182221,0.0037961837,0.000037889855],"about_ca_topic_score_codex":0.019473007,"about_ca_topic_score_gemma":0.014418564,"teacher_disagreement_score":0.019473007,"about_ca_system_score_codex":0.0046476987,"about_ca_system_score_gemma":0.0039689546,"threshold_uncertainty_score":0.04586488},"labels":[],"label_agreement":null},{"id":"W1985799965","doi":"10.1016/s0166-5316(02)00084-6","title":"A vacation model for the non-saturated Readers and Writers system with a threshold policy","year":2002,"lang":"en","type":"article","venue":"Performance Evaluation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science","score_opus":0.04874494363695795,"score_gpt":0.26013850152115864,"score_spread":0.2113935578842007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985799965","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3919078,0.001742569,0.49545124,0.01966323,0.0007189428,0.00070902955,0.0047010863,0.0014776726,0.08362837],"genre_scores_gemma":[0.914506,0.00052283553,0.012119123,0.0005594246,0.0002682392,0.0002586235,0.0005260134,0.00021053874,0.07102915],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9951062,0.0017854392,0.00017896933,0.00073499145,0.0003366187,0.0018576751],"domain_scores_gemma":[0.9832329,0.0098920325,0.0013560338,0.0010307154,0.002048667,0.0024395878],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0074313898,0.0016540076,0.004920549,0.002042689,0.0024740573,0.00619071,0.0076355445,0.0060107564,0.039609373],"category_scores_gemma":[0.019035911,0.0014536177,0.0023768356,0.0023519078,0.004406294,0.007794448,0.003569912,0.0044311685,0.00449039],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009856654,0.00041637936,0.0026086776,0.00024611325,0.00012207676,0.00047979326,0.0008750055,0.4129268,0.001206055,0.54938114,0.017748557,0.013003747],"study_design_scores_gemma":[0.00019125573,0.00015748135,0.00074335624,0.000034665558,0.000066432025,0.00010411601,0.00043969942,0.90019286,0.00020330332,0.09546597,0.0023294853,0.000071318755],"about_ca_topic_score_codex":0.03363429,"about_ca_topic_score_gemma":0.017458811,"teacher_disagreement_score":0.039609373,"about_ca_system_score_codex":0.005862225,"about_ca_system_score_gemma":0.0043529067,"threshold_uncertainty_score":0.13250655},"labels":[],"label_agreement":null},{"id":"W1986490955","doi":"10.3141/2072-15","title":"Performance Metrics and Data Mining for Assessing Schedule Qualities in Paratransit","year":2008,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Blackberry (Canada)","funders":"","keywords":"Paratransit; Schedule; Transport engineering; Scheduling (production processes); Computer science; Travel time; Productivity; Performance measurement; Performance indicator; Quality (philosophy); Operations research; Engineering; Public transport; Operations management; Business; Marketing; Operating system","score_opus":0.2877044015795379,"score_gpt":0.4354150558231247,"score_spread":0.14771065424358676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986490955","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6028022,0.00040667204,0.37905455,0.0004248485,0.00003638329,0.0010211943,0.005805094,0.0063452586,0.00410374],"genre_scores_gemma":[0.7388957,0.00015664214,0.25431195,0.000030480955,0.000020077632,0.0005727502,0.0054404344,0.00011054689,0.00046140363],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99649847,0.0009488692,0.00055304787,0.00061512535,0.0012266078,0.00015774767],"domain_scores_gemma":[0.97098553,0.01375516,0.006780142,0.0022331183,0.005467635,0.00077848096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004226447,0.0011484256,0.0007780823,0.008287271,0.0006048999,0.0015291673,0.0010940623,0.0006045785,0.0007166611],"category_scores_gemma":[0.028073696,0.0003442145,0.0006407834,0.0075268676,0.00045708058,0.0015307408,0.0007116008,0.0008271868,0.0002873832],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006472239,0.0010929286,0.3239443,0.0006930289,0.00027980638,0.0003446114,0.0010623357,0.22840972,0.009653596,0.004638919,0.0044057835,0.42482778],"study_design_scores_gemma":[0.000048326314,0.0006405437,0.09746908,0.00006284885,0.00005843348,0.00018111631,0.00073920685,0.88465923,0.00936125,0.0034209357,0.003297351,0.00006159563],"about_ca_topic_score_codex":0.0120633,"about_ca_topic_score_gemma":0.013815055,"teacher_disagreement_score":0.0120633,"about_ca_system_score_codex":0.0018452528,"about_ca_system_score_gemma":0.0018350466,"threshold_uncertainty_score":0.02398616},"labels":[],"label_agreement":null},{"id":"W1987093621","doi":"10.1002/atr.5670400207","title":"The optimal dispatching of taxis under congestion: A rolling horizon approach","year":2006,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Croucher Foundation","keywords":"Taxis; Computer science; Heuristics; Predictability; Anticipation (artificial intelligence); Traffic congestion; Transport engineering; Operations research; Time horizon; Truck; Rush hour; Public transport; Engineering; Mathematical optimization; Automotive engineering; Mathematics; Artificial intelligence","score_opus":0.006581190497613161,"score_gpt":0.21563016944948973,"score_spread":0.20904897895187657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987093621","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1702499,0.0015756623,0.8108248,0.0009316248,0.00019819799,0.00028032428,0.000591794,0.0006884084,0.01465922],"genre_scores_gemma":[0.9460792,0.00041588114,0.049716875,0.00008951285,0.000049390517,0.00015356671,0.00028582875,0.00007487335,0.003134911],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992499,0.0003586859,0.000025175226,0.00010098047,0.00009927242,0.00016609851],"domain_scores_gemma":[0.99827564,0.0011982465,0.00015776698,0.00003899465,0.0001609078,0.00016839834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021077923,0.0011368775,0.0023812219,0.0009622254,0.00059951097,0.0016382734,0.0012191428,0.0014479189,0.004108249],"category_scores_gemma":[0.003671225,0.0010728509,0.0007913562,0.0010839273,0.0008715392,0.0011617247,0.00070589076,0.0011889362,0.00028602718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031335207,0.000010003106,0.000058715203,0.0000142857125,0.00000929059,0.000018035476,0.0000067880974,0.9973003,0.00007915602,0.00084731635,0.00014629167,0.0014784507],"study_design_scores_gemma":[0.000005607607,0.000013140285,0.00004004426,0.0000021650199,0.0000035887208,0.0000014448381,0.0000055521214,0.9991986,0.00003218107,0.0006411702,0.000053654017,0.0000028163306],"about_ca_topic_score_codex":0.025696117,"about_ca_topic_score_gemma":0.010354422,"teacher_disagreement_score":0.025696117,"about_ca_system_score_codex":0.0018663167,"about_ca_system_score_gemma":0.00184274,"threshold_uncertainty_score":0.0510931},"labels":[],"label_agreement":null},{"id":"W1987443138","doi":"","title":"CARSHARING’S IMPACT ON HOUSEHOLD VEHICLE HOLDINGS: RESULTS FROM A NORTH AMERICAN SHARED-USE VEHICLE SURVEY","year":2010,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"San José State University; Arizona State University; California Department of Transportation; University of California, Davis; U.S. Department of Transportation","keywords":"Metropolitan area; Car ownership; Vehicle miles of travel; Business; Sample (material); Population; Transport engineering; Geography; Agricultural economics; Economics; Public transport; Engineering; Demography","score_opus":0.02321066714429414,"score_gpt":0.22016667598425935,"score_spread":0.1969560088399652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987443138","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982596,0.000029889776,0.00004881017,0.00003710068,0.00000197843,0.00000998937,0.0010024556,0.000002635122,0.00060745614],"genre_scores_gemma":[0.99659204,0.00011233251,0.0001272643,0.000047619676,0.000003953904,0.000029554509,0.00219651,0.0000032099858,0.0008876302],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994578,0.00017809952,0.0000378588,0.000085609376,0.00016457286,0.000076071425],"domain_scores_gemma":[0.9980744,0.0004455479,0.0005131292,0.00015475985,0.00059792004,0.0002141715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007892979,0.00018758194,0.00016158339,0.0007580326,0.00048554697,0.00046373715,0.00034264344,0.00028740952,0.001469618],"category_scores_gemma":[0.0011250307,0.00026242816,0.00040075183,0.0014964517,0.00025655815,0.00053279323,0.00064973725,0.000428255,0.00040418818],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033244545,0.000117272844,0.995262,0.000014153854,0.00004733929,0.00003496971,0.0007350119,0.000109069355,0.0001719386,0.000019776944,0.0005725234,0.0028825977],"study_design_scores_gemma":[8.96853e-7,0.00003451147,0.99808,0.0000033160106,0.000008951479,0.000017568986,0.0013556309,0.0001067434,0.000063023486,0.000005249146,0.00032158088,0.0000025465504],"about_ca_topic_score_codex":0.09975464,"about_ca_topic_score_gemma":0.21527976,"teacher_disagreement_score":0.09975464,"about_ca_system_score_codex":0.00061120425,"about_ca_system_score_gemma":0.00049532723,"threshold_uncertainty_score":0.19834799},"labels":[],"label_agreement":null},{"id":"W1990632989","doi":"10.3141/1986-15","title":"Who Is Attracted to Carsharing?","year":2006,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":119,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Car sharing; Business; Descriptive statistics; Focus group; Car ownership; The Internet; Marketing; Transport engineering; Advertising; Engineering; Computer science; Public transport","score_opus":0.06880484622699579,"score_gpt":0.3595260622723869,"score_spread":0.29072121604539114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990632989","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90411395,0.006059135,0.00044865487,0.048643075,0.0010708593,0.000077838755,0.000367632,0.000036548874,0.039182175],"genre_scores_gemma":[0.97677976,0.0033846425,0.00014848981,0.00785132,0.0005145002,0.0000460894,0.00011785694,0.000013041512,0.0111441845],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988751,0.00030168213,0.000045637717,0.00012206695,0.00021089126,0.0004446874],"domain_scores_gemma":[0.996439,0.0006411488,0.0005114506,0.00007124297,0.0006698701,0.001667383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014840913,0.00013808373,0.0003892267,0.0013629852,0.0030908757,0.0035320763,0.00047009368,0.0018849443,0.014359304],"category_scores_gemma":[0.0053751143,0.00027386995,0.00029538825,0.0011545632,0.0009719168,0.0028460082,0.0009110369,0.0012695881,0.002770913],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022039494,0.000500106,0.6997412,0.0003591601,0.00009584515,0.0030945211,0.052413806,0.000049022758,0.0008618457,0.005472979,0.07332771,0.16386344],"study_design_scores_gemma":[0.00003245303,0.00031052617,0.3751625,0.0006703116,0.0001827292,0.00846687,0.4826569,0.00049261894,0.0006326288,0.0037313977,0.12755333,0.00010759237],"about_ca_topic_score_codex":0.010748287,"about_ca_topic_score_gemma":0.0104605295,"teacher_disagreement_score":0.014359304,"about_ca_system_score_codex":0.0008553194,"about_ca_system_score_gemma":0.0009906244,"threshold_uncertainty_score":0.048036635},"labels":[],"label_agreement":null},{"id":"W1994182583","doi":"10.1061/9780784412602.0197","title":"Evaluating Advanced Pickup and Delivery Systems: A Simulation Study","year":2012,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pickup; Paratransit; Computer science; Simulation modeling; Set (abstract data type); Simulation; Systems engineering; Engineering; Transport engineering; Public transport; Artificial intelligence","score_opus":0.06254696486744744,"score_gpt":0.3414217366933116,"score_spread":0.2788747718258642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994182583","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9662317,0.00019831173,0.021706214,0.000282138,0.00002218108,0.0003454522,0.00048710278,0.000114117516,0.010612797],"genre_scores_gemma":[0.9863869,0.00025932767,0.011571696,0.000032191758,0.000007153188,0.00016338551,0.00028182898,0.000012687451,0.001284743],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988881,0.0006384818,0.000039793766,0.000074644486,0.00021580547,0.00014321473],"domain_scores_gemma":[0.9949234,0.0037616931,0.00025270547,0.00024154222,0.00061980815,0.00020084454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022862933,0.0008366614,0.000896393,0.0009108737,0.0008493626,0.0011019161,0.0013387671,0.0013914336,0.0021681157],"category_scores_gemma":[0.0039718417,0.0004232434,0.0007323212,0.0013479019,0.00072097307,0.0010738964,0.0006770364,0.0011482812,0.00019517384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000116536256,0.0002838752,0.003790085,0.0000399917,0.000020818972,0.00009711226,0.000107705884,0.98948157,0.00057333976,0.0023118453,0.00021826725,0.0029588926],"study_design_scores_gemma":[0.00009895733,0.000489915,0.0015228328,0.00001456981,0.000022797638,0.000025566767,0.00024487855,0.99488586,0.0010937795,0.0005640974,0.0010186798,0.000018040488],"about_ca_topic_score_codex":0.059548423,"about_ca_topic_score_gemma":0.044820838,"teacher_disagreement_score":0.059548423,"about_ca_system_score_codex":0.0033131689,"about_ca_system_score_gemma":0.0020790168,"threshold_uncertainty_score":0.11840367},"labels":[],"label_agreement":null},{"id":"W1994597293","doi":"10.1016/j.eswa.2010.09.029","title":"Centralized fleet management system for cybernetic transportation","year":2010,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"European Commission","keywords":"Computer science; Interactive kiosk; Scheduling (production processes); Routing (electronic design automation); Operations research; Control (management); Pooling; Computer network; Operations management; Engineering; World Wide Web; Artificial intelligence","score_opus":0.006656007188231658,"score_gpt":0.22212722157499093,"score_spread":0.21547121438675926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994597293","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09361546,0.00040155186,0.8591624,0.00039192068,0.0003693194,0.00039662753,0.0008147283,0.02820666,0.016641337],"genre_scores_gemma":[0.9147088,0.00015768915,0.071972266,0.00012742818,0.00011308757,0.00023552371,0.0010681674,0.00018762625,0.011429416],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995034,0.00006675981,0.00003368554,0.00017317927,0.00013856124,0.000084387786],"domain_scores_gemma":[0.99932706,0.00006161796,0.000059309656,0.00019236864,0.00026844407,0.00009128404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007164423,0.0005531845,0.000888145,0.00093816075,0.0011697337,0.0013801653,0.0015802394,0.000570435,0.0088731665],"category_scores_gemma":[0.00080169854,0.00025920867,0.00029962606,0.000854016,0.00034315587,0.0012132186,0.0010956895,0.00055209204,0.0019492778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012065921,0.0007966254,0.006279476,0.00019402578,0.00019852733,0.00048587742,0.00047252155,0.2669591,0.060736686,0.025083365,0.06735797,0.57022923],"study_design_scores_gemma":[0.0001260167,0.00015572699,0.00199872,0.000014502214,0.00007947524,0.00007998704,0.000081606035,0.9703592,0.009119158,0.0046055783,0.013334258,0.000045715457],"about_ca_topic_score_codex":0.011830735,"about_ca_topic_score_gemma":0.010855205,"teacher_disagreement_score":0.011830735,"about_ca_system_score_codex":0.0014540172,"about_ca_system_score_gemma":0.0024605503,"threshold_uncertainty_score":0.02968371},"labels":[],"label_agreement":null},{"id":"W1994742914","doi":"10.1503/cmaj.109-4123","title":"Touch the screen now to see a doctor","year":2012,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Interactive kiosk; sort; Computer science; Patient satisfaction; Multimedia; World Wide Web; Data science; Human–computer interaction; Medicine; Information retrieval; Nursing","score_opus":0.007877888554755562,"score_gpt":0.22134463695929374,"score_spread":0.21346674840453816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994742914","genre_codex":"other","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018140418,0.0041497396,0.015265375,0.0992459,0.01837812,0.00036979662,0.0027426116,0.0075095864,0.83419853],"genre_scores_gemma":[0.12442663,0.004025108,0.015951801,0.089120775,0.0031204552,0.00030930035,0.0015698075,0.00082353945,0.7606526],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996269,0.00009931575,0.000018033452,0.00006132125,0.00009278069,0.000101671634],"domain_scores_gemma":[0.99785453,0.0005309047,0.00010942336,0.00012533623,0.00038186624,0.0009979708],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004476795,0.000527004,0.0003956553,0.00049903436,0.00146197,0.0018541066,0.00060189504,0.0020660453,0.45588595],"category_scores_gemma":[0.0053497604,0.00026158107,0.00055604836,0.0002468939,0.0005976913,0.002180547,0.0022478108,0.0019050301,0.27177233],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011725586,0.00010378916,0.0014052935,0.00010395043,0.000010008122,0.00031602205,0.0003999193,0.000024800693,0.000911483,0.0010571491,0.91644484,0.07910553],"study_design_scores_gemma":[0.00006093404,0.00011358482,0.0036929615,0.00014984935,0.000013455723,0.0015208245,0.0011613694,0.00012365502,0.0006273602,0.0014598432,0.9910363,0.000039853203],"about_ca_topic_score_codex":0.0022016638,"about_ca_topic_score_gemma":0.0035709331,"teacher_disagreement_score":0.45588595,"about_ca_system_score_codex":0.00031376598,"about_ca_system_score_gemma":0.00053213694,"threshold_uncertainty_score":0.7761127},"labels":[],"label_agreement":null},{"id":"W1996028056","doi":"10.1504/ijssci.2009.026541","title":"Sustainable mobility solutions: a pre-implementation questionnaire study for carsharing","year":2009,"lang":"en","type":"article","venue":"International Journal of Services Sciences","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Business; Psychology; Process management; Environmental economics; Computer science; Economics","score_opus":0.02029348420788102,"score_gpt":0.34356890296030523,"score_spread":0.3232754187524242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996028056","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99299353,0.000035103472,0.0014423621,0.00038892686,0.000044606953,0.003422818,0.0003042036,0.000041246738,0.0013271332],"genre_scores_gemma":[0.96778315,0.00027446327,0.010815665,0.00095510005,0.000062669285,0.013194329,0.0008340539,0.000060944818,0.006019609],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.995884,0.0019705924,0.0003009073,0.00021721132,0.0006186698,0.0010085703],"domain_scores_gemma":[0.9888888,0.0045412355,0.0010198731,0.00059872173,0.0032841412,0.0016673227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013578983,0.0008259667,0.00092653354,0.0017869584,0.002276931,0.0014898599,0.00091855414,0.0015901529,0.003754397],"category_scores_gemma":[0.0163395,0.00093017466,0.00096812675,0.0009128664,0.0012771435,0.0013648968,0.0014634437,0.0022923334,0.0011784312],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011662781,0.042545985,0.3685061,0.001893469,0.00012218166,0.0037855604,0.3472422,0.0015750268,0.014845073,0.0011651781,0.0100935735,0.20705947],"study_design_scores_gemma":[0.00048945297,0.04676309,0.5125842,0.0005007705,0.00009323377,0.00082279387,0.38583815,0.0021681907,0.00719475,0.00042423833,0.042803586,0.00031750478],"about_ca_topic_score_codex":0.0038908473,"about_ca_topic_score_gemma":0.005625545,"teacher_disagreement_score":0.013578983,"about_ca_system_score_codex":0.0026857953,"about_ca_system_score_gemma":0.003216316,"threshold_uncertainty_score":0.071813345},"labels":[],"label_agreement":null},{"id":"W1996612116","doi":"10.1002/atr.5670360303","title":"The future for in‐vehicle information systems: The technology and its impacts","year":2002,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Global Positioning System; Beacon; Modal; Computer science; Mobile phone; Entertainment; Phone; Real-time computing; Transport engineering; Telecommunications; Engineering","score_opus":0.005595434457698993,"score_gpt":0.214165161138472,"score_spread":0.208569726680773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996612116","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0066365777,0.70125294,0.005838773,0.18918929,0.003858782,0.000034303288,0.00018100394,0.000105135165,0.09290319],"genre_scores_gemma":[0.16474618,0.78339195,0.007941456,0.017206652,0.007030642,0.00009901206,0.0001807159,0.000043825145,0.019359635],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99821174,0.00082630874,0.000075220305,0.0001439301,0.00051673385,0.00022609787],"domain_scores_gemma":[0.9929194,0.004265661,0.0004454757,0.00019833827,0.0014676976,0.0007033761],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035408072,0.0006496047,0.0006737065,0.0018942415,0.0012606826,0.0075880527,0.0008134093,0.006867787,0.015032839],"category_scores_gemma":[0.0034601039,0.00024826915,0.00050685665,0.00231282,0.0036594272,0.010507657,0.0017524009,0.0033115032,0.0021214564],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010963026,0.00017909872,0.0024271766,0.0023381978,0.00005258507,0.0004619001,0.000837069,0.002345541,0.0014379155,0.55829704,0.10663852,0.32487535],"study_design_scores_gemma":[0.000014106843,0.00013677342,0.0025804965,0.0022929532,0.00002522056,0.00061622367,0.0020189558,0.0017134988,0.000422977,0.1397575,0.8503673,0.0000540717],"about_ca_topic_score_codex":0.0028476014,"about_ca_topic_score_gemma":0.0023338243,"teacher_disagreement_score":0.015032839,"about_ca_system_score_codex":0.002679864,"about_ca_system_score_gemma":0.0038091962,"threshold_uncertainty_score":0.05028981},"labels":[],"label_agreement":null},{"id":"W1996869679","doi":"10.1002/atr.157","title":"Analogy of fixed route shared taxi (taxi khattee) and bus services under various demand density and economical conditions","year":2011,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Public transport; Transport engineering; Service (business); Mode (computer interface); Level of service; Transit (satellite); Computer science; Operations research; Engineering; Business","score_opus":0.01066052713595454,"score_gpt":0.21603125497294112,"score_spread":0.2053707278369866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996869679","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9913366,0.00004746225,0.0018663547,0.00007035395,0.0000056629165,0.000022820075,0.00015640252,0.00001577932,0.006478588],"genre_scores_gemma":[0.99883133,0.000022660453,0.00031906343,0.0000030708034,0.0000010738,0.000007813869,0.00004926808,0.0000020200334,0.0007637302],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996958,0.00010769178,0.000008911047,0.00004376686,0.000056375222,0.00008751064],"domain_scores_gemma":[0.9985909,0.0007743987,0.00015383918,0.00006953995,0.00028915497,0.00012222196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044061826,0.00023396086,0.00021193849,0.000602724,0.0003676959,0.0007721062,0.00048233752,0.00040163877,0.0074560973],"category_scores_gemma":[0.0020955917,0.0001268842,0.0003471803,0.00077118154,0.0003821651,0.0008338196,0.00046221525,0.00030958405,0.00023148439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010671073,0.00037231733,0.09176347,0.0002096439,0.0000979918,0.0016157818,0.00061131344,0.835189,0.011635943,0.03606791,0.0022025553,0.019167008],"study_design_scores_gemma":[0.000024403971,0.00038585966,0.07101083,0.000018462957,0.000058091046,0.00026814674,0.0022486344,0.9172483,0.002584312,0.004650773,0.0014746202,0.000027606735],"about_ca_topic_score_codex":0.017826024,"about_ca_topic_score_gemma":0.015505802,"teacher_disagreement_score":0.017826024,"about_ca_system_score_codex":0.0014967303,"about_ca_system_score_gemma":0.0003942393,"threshold_uncertainty_score":0.035444498},"labels":[],"label_agreement":null},{"id":"W1997763756","doi":"10.1002/atr.5670350308","title":"Impact of ITS measures on public transport: A Case study","year":2001,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Public transport; Taxis; Transport engineering; Transit (satellite); Modal; Computer science; Telecommunications; Engineering","score_opus":0.03097404147361366,"score_gpt":0.3014273676367655,"score_spread":0.2704533261631518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997763756","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9803847,0.00009979129,0.00075120036,0.0006602889,0.000024617346,0.0001142377,0.00018417902,0.000029206485,0.017751649],"genre_scores_gemma":[0.99777263,0.00012568428,0.0002682188,0.000044088214,0.000010712762,0.00004264452,0.00007333632,0.0000044962294,0.001658057],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977139,0.0011400025,0.00008315074,0.00009354365,0.0004326559,0.00053670874],"domain_scores_gemma":[0.9951526,0.0024091764,0.0005447115,0.0004920509,0.0008591854,0.0005422956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019899406,0.00038049923,0.00027195152,0.0012333549,0.0024782077,0.0017894427,0.00091579085,0.0015918737,0.006137772],"category_scores_gemma":[0.0052099857,0.00019237511,0.0007672876,0.0020227088,0.0011072478,0.0011785155,0.0013654832,0.0011544565,0.00040264413],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002688184,0.01650838,0.46308297,0.0014476607,0.00062094704,0.120631255,0.02111844,0.103212655,0.005091435,0.052250676,0.02764224,0.18570521],"study_design_scores_gemma":[0.0014291265,0.012356733,0.41360924,0.00072069664,0.000818617,0.039507326,0.206647,0.13985881,0.018447908,0.01687822,0.14936729,0.00035912494],"about_ca_topic_score_codex":0.04143714,"about_ca_topic_score_gemma":0.03735913,"teacher_disagreement_score":0.04143714,"about_ca_system_score_codex":0.004506375,"about_ca_system_score_gemma":0.0022794183,"threshold_uncertainty_score":0.08239192},"labels":[],"label_agreement":null},{"id":"W2001127805","doi":"10.3166/jesa.47.617-634","title":"Introduction à la notion d’anticipation et de robustesse dans les problèmes de dial-a-ride dynamiques","year":2013,"lang":"fr","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Anticipation (artificial intelligence); Humanities; Computer science; Philosophy","score_opus":0.01542530741072315,"score_gpt":0.2577832131674514,"score_spread":0.24235790575672825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001127805","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010931162,0.019302646,0.9180604,0.01706821,0.0011395584,0.0001056693,0.00058712467,0.00011050668,0.03269474],"genre_scores_gemma":[0.66888404,0.03242903,0.24361281,0.0052243406,0.007892752,0.0009474658,0.00059799076,0.00026330253,0.04014827],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9951083,0.0020016732,0.0003115711,0.0012399714,0.0010325445,0.00030601193],"domain_scores_gemma":[0.98285496,0.013331153,0.001274324,0.0007498577,0.0012782068,0.00051160634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006636487,0.0015698224,0.0016865733,0.001604808,0.0010303555,0.0042266776,0.002830502,0.0046811956,0.008957545],"category_scores_gemma":[0.020287381,0.0008170382,0.0022756162,0.0027178933,0.0070746294,0.008586285,0.003769974,0.008687427,0.0009032036],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053627118,0.000025217983,0.000436422,0.0003328309,0.00006799382,0.00014093444,0.0002671575,0.02262794,0.0006184378,0.959357,0.0036063201,0.012466058],"study_design_scores_gemma":[0.00003470182,0.0001269335,0.0009332418,0.0003698465,0.000072883515,0.00034445422,0.00025181254,0.10684617,0.0005894035,0.8357748,0.05456384,0.000091989765],"about_ca_topic_score_codex":0.0031048774,"about_ca_topic_score_gemma":0.0011303885,"teacher_disagreement_score":0.008957545,"about_ca_system_score_codex":0.0032109213,"about_ca_system_score_gemma":0.0015998542,"threshold_uncertainty_score":0.03509748},"labels":[],"label_agreement":null},{"id":"W2001558460","doi":"10.3926/jiem.326","title":"Integrated methodological frameworks for modelling agent-based advanced supply chain planning systems: A systematic literature review","year":2011,"lang":"en","type":"article","venue":"Journal of Industrial Engineering and Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Université TÉLUQ; Polytechnique Montréal; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec à Montréal; Université Laval","keywords":"Management science; Systematic review; Supply chain; Process (computing); Computer science; Identification (biology); Scale (ratio); Process management; Data science; Risk analysis (engineering); Engineering; Business","score_opus":0.11233295397428637,"score_gpt":0.2858005340624672,"score_spread":0.1734675800881808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001558460","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00150251,0.9796341,0.011357982,0.0021453188,0.00046904458,0.0031158736,0.00046672896,0.000039558672,0.0012688786],"genre_scores_gemma":[0.026034815,0.92191684,0.041577876,0.0014773305,0.00024171233,0.0077687423,0.00060924276,0.00002788923,0.00034547472],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9456875,0.0310034,0.013094918,0.0026354997,0.006847966,0.0007307831],"domain_scores_gemma":[0.8528989,0.11553862,0.012829286,0.0036203319,0.014155792,0.00095707463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.058223326,0.0027717524,0.0068754824,0.03313011,0.0023384364,0.008973009,0.003887219,0.004247456,0.0054666842],"category_scores_gemma":[0.14171538,0.0019285897,0.007623713,0.0252405,0.0028368146,0.008972793,0.004573443,0.0036505486,0.00084977306],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012885392,0.000118650445,0.0014200571,0.79777515,0.0037502723,0.0002973136,0.0023083263,0.0018201486,0.00034624396,0.015210702,0.0039617023,0.17286262],"study_design_scores_gemma":[0.00012856192,0.0002273493,0.0013086636,0.9203027,0.010373071,0.00041340553,0.0033091926,0.0011543912,0.000327304,0.0076640444,0.054681577,0.00010970151],"about_ca_topic_score_codex":0.007800005,"about_ca_topic_score_gemma":0.01915743,"teacher_disagreement_score":0.058223326,"about_ca_system_score_codex":0.009547488,"about_ca_system_score_gemma":0.056069475,"threshold_uncertainty_score":0.307918},"labels":[],"label_agreement":null},{"id":"W2004240842","doi":"10.1109/iros.2012.6385522","title":"Patch map: A benchmark for occupancy grid algorithm evaluation","year":2012,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Occupancy; Occupancy grid mapping; Benchmark (surveying); Grid cell; Computer science; Grid; Discretization; Algorithm; Mobile robot; Artificial intelligence; Robot; Mathematics; Geography; Geometry; Engineering; Cartography","score_opus":0.024780115874225125,"score_gpt":0.2805234926226149,"score_spread":0.25574337674838976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004240842","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3708863,0.012182076,0.36498302,0.0037751142,0.0025723304,0.0017536617,0.049875464,0.120181054,0.07379108],"genre_scores_gemma":[0.4905476,0.002208459,0.4216527,0.0006679802,0.00019499043,0.0010610189,0.06848393,0.0072269593,0.007956307],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961971,0.0011645373,0.0003676406,0.0006449587,0.0012880901,0.00033759692],"domain_scores_gemma":[0.99138147,0.0048529324,0.0002676487,0.0013004962,0.001866006,0.0003314518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003986009,0.0022565876,0.0017028813,0.0021193386,0.0011206453,0.0021625217,0.004731577,0.0019617735,0.009090298],"category_scores_gemma":[0.01811362,0.00077036617,0.001178466,0.0038653256,0.0009257636,0.0030422402,0.0019033272,0.0017033898,0.0030096308],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001596879,0.00089897757,0.0066120247,0.0021947331,0.00063971995,0.0003131815,0.0002952135,0.5627886,0.0026931905,0.010407638,0.1913063,0.2202536],"study_design_scores_gemma":[0.00037447727,0.00039313416,0.0014608196,0.00007144925,0.00006108424,0.00013982935,0.00017547798,0.9672203,0.0037786146,0.006386013,0.019900473,0.0000383082],"about_ca_topic_score_codex":0.021825522,"about_ca_topic_score_gemma":0.02054086,"teacher_disagreement_score":0.021825522,"about_ca_system_score_codex":0.001867023,"about_ca_system_score_gemma":0.0021200012,"threshold_uncertainty_score":0.04339695},"labels":[],"label_agreement":null},{"id":"W2005207744","doi":"10.5383/juspn.04.01.001","title":"Ambient Intelligence on Personal Mobility Assistants for Sustainable Travel Choices","year":2012,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Personal mobility; Ambient intelligence; Psychology; Computer science; Business; Human–computer interaction; Telecommunications","score_opus":0.022044239403083362,"score_gpt":0.25788802991445725,"score_spread":0.23584379051137389,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005207744","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2234506,0.0030285914,0.66629374,0.0018666602,0.0005159721,0.00041309453,0.00023596075,0.005678566,0.098516844],"genre_scores_gemma":[0.81906545,0.0012296436,0.1520397,0.00030669098,0.00012770879,0.0001767921,0.00017962277,0.00010794281,0.026766364],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997392,0.00009251578,0.000015287518,0.000043571064,0.0000833421,0.00002609535],"domain_scores_gemma":[0.9995994,0.00017513223,0.000030212052,0.00004530736,0.000121123725,0.000028848202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033913364,0.0003594569,0.00021417344,0.00022972346,0.0003850378,0.0009996978,0.00056131074,0.00058940594,0.004788461],"category_scores_gemma":[0.0015968431,0.00015269713,0.00027835718,0.00023964231,0.0003857533,0.0012477047,0.00085966574,0.00043944689,0.0010951547],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009487131,0.0005098719,0.004315879,0.0008791316,0.00007057459,0.0009327092,0.0047213472,0.017099572,0.0662112,0.061301377,0.021750087,0.8212595],"study_design_scores_gemma":[0.00028361919,0.0019329367,0.015118988,0.0005337859,0.00046625175,0.002641724,0.0044002077,0.36979315,0.07406405,0.06983428,0.46067196,0.0002590379],"about_ca_topic_score_codex":0.001456158,"about_ca_topic_score_gemma":0.002120649,"teacher_disagreement_score":0.004788461,"about_ca_system_score_codex":0.0002140871,"about_ca_system_score_gemma":0.00025932805,"threshold_uncertainty_score":0.016018987},"labels":[],"label_agreement":null},{"id":"W2010459266","doi":"10.1002/atr.142","title":"Understanding members' carsharing (activity) persistency by using econometric model","year":2010,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Alberta; University of Toronto; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Ordered probit; Probit model; Probit; Econometric model; Econometrics; Passenger transport; Service (business); Mode (computer interface); Computer science; Transport engineering; Business; Marketing; Economics; Engineering","score_opus":0.050938284379524655,"score_gpt":0.2556205378215456,"score_spread":0.20468225344202093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010459266","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9526437,0.00025773112,0.042197607,0.0006705027,0.000026013293,0.000056173816,0.001139121,0.000093282266,0.0029158634],"genre_scores_gemma":[0.9939809,0.00015562678,0.0022209652,0.000028689501,0.00001582218,0.000038020757,0.0005572236,0.000008015928,0.0029947553],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994011,0.00023491669,0.00004230761,0.00014004085,0.000056191162,0.00012537364],"domain_scores_gemma":[0.9942293,0.004027951,0.001035644,0.0002293925,0.0002533469,0.00022426291],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018786087,0.00043923224,0.0006383108,0.0008298948,0.00039862804,0.0020030492,0.001058027,0.0012879597,0.0058493284],"category_scores_gemma":[0.008153811,0.00035225152,0.000799282,0.0011364358,0.00042291064,0.0012298533,0.00094394793,0.0009989404,0.00072895363],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025629546,0.00041718577,0.4396396,0.000105477266,0.0004560737,0.00040479327,0.00095581426,0.5053144,0.00078574265,0.019533904,0.0019906901,0.030140048],"study_design_scores_gemma":[0.000016622365,0.0001188378,0.06238002,0.000023660701,0.00012050829,0.000057773377,0.00085955707,0.9280138,0.00023754861,0.0064859143,0.0016493851,0.00003634233],"about_ca_topic_score_codex":0.033875365,"about_ca_topic_score_gemma":0.022220243,"teacher_disagreement_score":0.033875365,"about_ca_system_score_codex":0.0014316114,"about_ca_system_score_gemma":0.0007671893,"threshold_uncertainty_score":0.06735641},"labels":[],"label_agreement":null},{"id":"W2016506058","doi":"10.1007/s11116-015-9604-3","title":"Carsharing operations policies: a comparison between one-way and two-way systems","year":2015,"lang":"en","type":"article","venue":"Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":69,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Relocation; Operations research; Profit maximization; Profit (economics); Fleet management; Market share; Computer science; Market segmentation; Transport engineering; Service (business); Integer programming; Order (exchange); Business; Telecommunications; Marketing; Engineering; Economics; Microeconomics; Finance","score_opus":0.07033736258233378,"score_gpt":0.2959970510354575,"score_spread":0.2256596884531237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016506058","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96283495,0.0013371916,0.011102546,0.0007113779,0.0001648864,0.000267321,0.00079240784,0.00015751526,0.022631777],"genre_scores_gemma":[0.9964684,0.00042728256,0.0011111855,0.0000714259,0.000018953815,0.000039883387,0.00023116538,0.000020536121,0.0016111196],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99614394,0.0016829207,0.00015850195,0.00037391693,0.0006597349,0.0009808753],"domain_scores_gemma":[0.98776114,0.0074389265,0.0015524412,0.00087761466,0.0015137768,0.0008560861],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004273251,0.0005883182,0.0009620159,0.0015153186,0.00062153646,0.0037212067,0.0012887856,0.0010664419,0.0074958233],"category_scores_gemma":[0.00934359,0.00032879954,0.0012470203,0.0021691034,0.00093443936,0.004129879,0.0010980285,0.001090377,0.00044666586],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011568559,0.00418445,0.096606545,0.0014600179,0.0021338076,0.000279287,0.0009830598,0.58232987,0.006240073,0.13479443,0.009025478,0.1503944],"study_design_scores_gemma":[0.0024299107,0.01625047,0.29373118,0.0004550112,0.0032783484,0.00028174312,0.012611939,0.56634873,0.011271064,0.06293123,0.030015273,0.00039497463],"about_ca_topic_score_codex":0.012043199,"about_ca_topic_score_gemma":0.012972127,"teacher_disagreement_score":0.012043199,"about_ca_system_score_codex":0.0034925598,"about_ca_system_score_gemma":0.0030371635,"threshold_uncertainty_score":0.025340438},"labels":[],"label_agreement":null},{"id":"W2017383000","doi":"10.1007/s10288-002-0009-8","title":"The Dial-a-Ride Problem (DARP): Variants, modeling issues and algorithms","year":2003,"lang":"en","type":"article","venue":"4OR","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":334,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Set (abstract data type); Computer science; Plan (archaeology); Destinations; Operations research; Algorithm; Mathematical optimization; Engineering; Mathematics; Geography; Programming language","score_opus":0.012774431787790521,"score_gpt":0.2283156917083634,"score_spread":0.21554125992057288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017383000","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018679872,0.003876516,0.9613453,0.0042107026,0.00036939388,0.00013384072,0.00085484766,0.00017895033,0.010350545],"genre_scores_gemma":[0.54643947,0.007971244,0.41416177,0.0008860312,0.0014270175,0.0005570328,0.0019941113,0.0003070986,0.026256256],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966492,0.0016791697,0.00015537262,0.00090988824,0.0002997157,0.00030652608],"domain_scores_gemma":[0.9929765,0.0051940214,0.00061769504,0.0004723416,0.00038930148,0.00035012414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0047966396,0.0016511707,0.003860016,0.0012940236,0.0014829604,0.0057351827,0.005864343,0.006763476,0.0076272534],"category_scores_gemma":[0.016603429,0.0016330307,0.00213064,0.0045678676,0.003070304,0.011790108,0.0043856874,0.0041540833,0.00082789967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000893316,0.00013584341,0.00097113976,0.0003679986,0.00009699129,0.00015655429,0.00013513377,0.4745326,0.00015581,0.4711137,0.0149201555,0.03732466],"study_design_scores_gemma":[0.00002682704,0.000033608267,0.00019001598,0.000050310824,0.000028947004,0.00013189578,0.00011332401,0.64218813,0.00010710929,0.35168704,0.005411539,0.00003120672],"about_ca_topic_score_codex":0.009737788,"about_ca_topic_score_gemma":0.006790852,"teacher_disagreement_score":0.009737788,"about_ca_system_score_codex":0.0020879922,"about_ca_system_score_gemma":0.0020587887,"threshold_uncertainty_score":0.025515676},"labels":[],"label_agreement":null},{"id":"W2018829876","doi":"10.3141/1760-12","title":"Simulation Model for Evaluating Intelligent Paratransit Systems","year":2001,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Paratransit; Field (mathematics); Computer science; Reliability (semiconductor); Transport engineering; Variety (cybernetics); TRIPS architecture; Intelligent transportation system; Public transport; Systems engineering; Risk analysis (engineering); Engineering; Simulation; Operations research","score_opus":0.264538604329994,"score_gpt":0.45407070593120213,"score_spread":0.18953210160120815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018829876","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.086421266,0.00030608347,0.8884174,0.00033861198,0.00008987894,0.0005576185,0.00078152504,0.0011606234,0.021927001],"genre_scores_gemma":[0.9151603,0.00059642247,0.073020935,0.000058050635,0.000033079217,0.001238149,0.0007876867,0.000111889225,0.0089935195],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929297,0.00035446018,0.000037488346,0.00007121791,0.00016574332,0.000078069854],"domain_scores_gemma":[0.9985146,0.000911483,0.00010980139,0.00007728101,0.00032655304,0.00006038694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010380202,0.0011461605,0.0009420773,0.00076706434,0.0006638251,0.001307284,0.0014841697,0.0014360565,0.0049470537],"category_scores_gemma":[0.0033753116,0.00039556314,0.0008665419,0.00067021925,0.0006261781,0.0010197967,0.0007711278,0.0010420216,0.00057753356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026320593,0.000011748003,0.0001730144,0.000010032714,0.0000049691494,0.000015610325,0.000011635255,0.99573994,0.00024048153,0.0027860415,0.000085644504,0.0008946151],"study_design_scores_gemma":[0.000007932929,0.00001995872,0.00003696168,0.0000024946555,0.000003761447,0.0000024933995,0.0000046059804,0.9988426,0.0001584741,0.0006157526,0.0003026538,0.0000022954396],"about_ca_topic_score_codex":0.014677593,"about_ca_topic_score_gemma":0.0062368745,"teacher_disagreement_score":0.014677593,"about_ca_system_score_codex":0.0016486775,"about_ca_system_score_gemma":0.0015982311,"threshold_uncertainty_score":0.029184282},"labels":[],"label_agreement":null},{"id":"W2019761781","doi":"10.1016/j.ecolecon.2011.03.014","title":"What will be the environmental effects of new free-floating car-sharing systems? The case of car2go in Ulm","year":2011,"lang":"en","type":"article","venue":"Ecological Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":489,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Quarter (Canadian coin); Business; Point (geometry); Car ownership; Free riding; Environmental economics; Computer science; Transport engineering; Economics; Engineering; Microeconomics; Public transport; Geography","score_opus":0.01999948077635889,"score_gpt":0.1930638476627719,"score_spread":0.17306436688641302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019761781","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83246404,0.00084298104,0.0040520807,0.02234117,0.000086598055,0.000033275777,0.0002092754,0.000024734378,0.13994578],"genre_scores_gemma":[0.9945359,0.0002439262,0.0003107173,0.00027285135,0.000026912441,0.000006464236,0.00001207372,0.0000059908602,0.004585056],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9990513,0.0002831202,0.000011873617,0.00008273866,0.00007959722,0.0004914112],"domain_scores_gemma":[0.99849284,0.00085951295,0.00017413804,0.00007138138,0.00018542945,0.00021669577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014623773,0.000333213,0.0007041586,0.00056610006,0.0022134832,0.0049389694,0.0010754946,0.0042659976,0.0151750175],"category_scores_gemma":[0.0038255174,0.0002957106,0.0007883613,0.000785609,0.0032092365,0.0057788575,0.0019903774,0.0021850169,0.00040800305],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045421522,0.00034432666,0.01729241,0.00021271106,0.00012332886,0.003106579,0.0013673002,0.08520593,0.0023195087,0.8666157,0.0069475085,0.016010424],"study_design_scores_gemma":[0.00024280461,0.00030888803,0.03368534,0.00016520724,0.0002417328,0.0007004447,0.025250012,0.12348353,0.0030586948,0.76565707,0.046989534,0.0002167162],"about_ca_topic_score_codex":0.039278332,"about_ca_topic_score_gemma":0.04748316,"teacher_disagreement_score":0.039278332,"about_ca_system_score_codex":0.0048183217,"about_ca_system_score_gemma":0.001341344,"threshold_uncertainty_score":0.07809943},"labels":[],"label_agreement":null},{"id":"W2024435407","doi":"10.1007/s00453-008-9181-3","title":"Edge Pricing of Multicommodity Networks for Selfish Users with Elastic Demands","year":2008,"lang":"en","type":"article","venue":"Algorithmica","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Fleischer; Theory of computation; Computer science; Routing (electronic design automation); Mathematical economics; Operations research; Mathematical optimization; A priori and a posteriori; Telecommunications network; Function (biology); Mathematics; Computer network; Algorithm","score_opus":0.013119900043998258,"score_gpt":0.20825905682960347,"score_spread":0.1951391567856052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024435407","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36080372,0.0008378677,0.61551,0.0024842476,0.00017875984,0.00018287897,0.0002522831,0.00021467246,0.019535616],"genre_scores_gemma":[0.96451604,0.00044837367,0.026093833,0.00011297139,0.00010398444,0.00007557111,0.00006907943,0.00006404682,0.008516224],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989856,0.0005232218,0.000030099283,0.000112390524,0.000118576456,0.00023008819],"domain_scores_gemma":[0.99568945,0.003121544,0.00026924637,0.00029789645,0.0002864708,0.00033552828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023127934,0.0007995608,0.0014269209,0.0009799228,0.0013253607,0.0026944126,0.0023129135,0.0019745964,0.006838986],"category_scores_gemma":[0.009797824,0.00079138525,0.00086749025,0.0016496534,0.0013719107,0.004405179,0.0017256703,0.0015565257,0.0004153273],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049662404,0.0001713222,0.001605361,0.00015020155,0.00006909261,0.00031516716,0.0003014739,0.5367117,0.0018795753,0.42137268,0.0066669243,0.030259915],"study_design_scores_gemma":[0.000018022705,0.000028118933,0.00017312053,0.000008538562,0.000014534031,0.000054427594,0.00005227969,0.900285,0.00018078298,0.098571666,0.0006037178,0.000009788211],"about_ca_topic_score_codex":0.002369236,"about_ca_topic_score_gemma":0.0027045128,"teacher_disagreement_score":0.006838986,"about_ca_system_score_codex":0.0020815865,"about_ca_system_score_gemma":0.00094480446,"threshold_uncertainty_score":0.022878647},"labels":[],"label_agreement":null},{"id":"W2024511866","doi":"10.1287/msom.1030.0030","title":"Strategically Seeking Service: How Competition Can Generate Poisson Arrivals","year":2004,"lang":"en","type":"article","venue":"Manufacturing & Service Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Poisson distribution; Competition (biology); Business; Service (business); Marketing; Mathematics; Statistics","score_opus":0.013940825758459853,"score_gpt":0.20952674290505682,"score_spread":0.19558591714659698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024511866","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49696553,0.00060648186,0.437552,0.004964257,0.00019502192,0.00018157552,0.0002560807,0.00022251788,0.05905646],"genre_scores_gemma":[0.98770696,0.0001779645,0.00773128,0.00023607379,0.000041919928,0.00005759479,0.000029892837,0.000024839555,0.003993384],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99844354,0.000730179,0.000035854155,0.00013198672,0.00026925263,0.00038929825],"domain_scores_gemma":[0.9935063,0.0045564743,0.00062680413,0.00018789426,0.0004650804,0.0006574655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024572005,0.00058640254,0.0008655203,0.0007775146,0.001195659,0.0019258279,0.0017647159,0.002011613,0.005326854],"category_scores_gemma":[0.011207933,0.0005803085,0.00090105645,0.0007028536,0.0016471745,0.0020553968,0.0016438273,0.0014870599,0.0005040603],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015843837,0.00015375792,0.0038842256,0.00008420002,0.00004642518,0.0010027088,0.0007264755,0.47567528,0.0020174894,0.5055219,0.0033134914,0.0074156425],"study_design_scores_gemma":[0.000040059953,0.00005118896,0.00042424208,0.000011038919,0.000013933716,0.00013272834,0.0002194247,0.9101337,0.00020466837,0.08781194,0.0009304048,0.000026597414],"about_ca_topic_score_codex":0.011621053,"about_ca_topic_score_gemma":0.008668684,"teacher_disagreement_score":0.011621053,"about_ca_system_score_codex":0.0021256327,"about_ca_system_score_gemma":0.0014801958,"threshold_uncertainty_score":0.023106813},"labels":[],"label_agreement":null},{"id":"W2026191820","doi":"10.3141/2118-05","title":"Driving Factors behind Successful Carpool Formation and Use","year":2009,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Baycrest Hospital; General Electric (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Carpool; TRIPS architecture; Transport engineering; Service (business); Work (physics); Public transport; Sustainable transport; Level of service; Business; Engineering; Sustainability; Marketing","score_opus":0.0713930731656349,"score_gpt":0.3487137494807877,"score_spread":0.2773206763151528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026191820","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9980994,0.00013040057,0.00006756975,0.00013149001,0.000004205498,0.000019300343,0.00017734799,0.000005194954,0.0013652127],"genre_scores_gemma":[0.9991074,0.000107633015,0.00007905473,0.00000910202,0.0000035213677,0.000009657243,0.00014840075,0.0000030171227,0.0005319868],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99948955,0.00007555536,0.000057927267,0.00007038506,0.000136346,0.00017028434],"domain_scores_gemma":[0.99642134,0.0008844872,0.0011013106,0.00019994412,0.00054778764,0.0008451256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006725717,0.00015138337,0.00019410634,0.0008051616,0.00068396697,0.0010690398,0.00057778764,0.0008095696,0.006381399],"category_scores_gemma":[0.00526374,0.0002476377,0.0006357524,0.00097068603,0.0005078812,0.0004970121,0.00065783295,0.00092315907,0.00087709917],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005047705,0.000115207964,0.9963558,0.000010976014,0.00001560033,0.0000620277,0.00035193522,0.00008661599,0.000114377384,0.00007006361,0.00018287095,0.002584064],"study_design_scores_gemma":[0.0000015047009,0.0000367943,0.99768746,0.0000124401295,0.000009241404,0.00006274017,0.0014274687,0.0003644568,0.000053618976,0.00006646574,0.00027315822,0.0000046394885],"about_ca_topic_score_codex":0.059017424,"about_ca_topic_score_gemma":0.07621325,"teacher_disagreement_score":0.059017424,"about_ca_system_score_codex":0.0006041385,"about_ca_system_score_gemma":0.00141513,"threshold_uncertainty_score":0.11734778},"labels":[],"label_agreement":null},{"id":"W2030944447","doi":"10.3141/2359-08","title":"Unraveling the Travel Behavior of Carsharing Members from Global Positioning System Traces","year":2013,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"TRIPS architecture; Transport engineering; Renting; Work (physics); Travel behavior; Business; Advertising; Engineering","score_opus":0.05700626925302051,"score_gpt":0.3381920822181992,"score_spread":0.2811858129651787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030944447","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9884017,0.0000778956,0.00816823,0.000052895834,0.0000068961385,0.000040635314,0.0014040176,0.00009980897,0.0017478224],"genre_scores_gemma":[0.98474497,0.00013360151,0.011403196,0.000008900649,0.0000075097723,0.00003057631,0.002542265,0.000026514765,0.0011025621],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99975187,0.00004022041,0.000017498955,0.00005341684,0.000088651,0.000048250866],"domain_scores_gemma":[0.99892825,0.0002585049,0.00018178314,0.00012738694,0.00040676486,0.00009727033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004188264,0.00035799868,0.00028232785,0.002543774,0.00035044996,0.0008896793,0.00038466317,0.0003227816,0.0010320143],"category_scores_gemma":[0.0020369426,0.00015599099,0.00019330326,0.0039599882,0.0002326194,0.00063644384,0.00057420164,0.00035558824,0.0004678743],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017219636,0.00009304121,0.8269452,0.0001914639,0.000110547146,0.00045308916,0.008064031,0.00999819,0.013192113,0.0010940233,0.0016235383,0.13806267],"study_design_scores_gemma":[0.000004540751,0.000121308665,0.9289652,0.00006229904,0.000064087246,0.00029986614,0.015330279,0.043580886,0.003904854,0.0005383145,0.007089308,0.000038971102],"about_ca_topic_score_codex":0.07766403,"about_ca_topic_score_gemma":0.15692644,"teacher_disagreement_score":0.07766403,"about_ca_system_score_codex":0.00046945596,"about_ca_system_score_gemma":0.00070147746,"threshold_uncertainty_score":0.15442395},"labels":[],"label_agreement":null},{"id":"W2032515475","doi":"10.1007/s11116-012-9427-4","title":"The role of ICTs in the transformation and the experience of travel","year":2012,"lang":"en","type":"article","venue":"Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Université Laval","funders":"Social Sciences and Humanities Research Council of Canada; University of Toronto Mississauga; University of Toronto","keywords":"Population; Telecommunications; Information and Communications Technology; Business; Internet access; Mobile broadband; The Internet; Economic growth; Engineering; Computer science; Economics; Sociology; World Wide Web; Wireless; Demography","score_opus":0.00829960026658139,"score_gpt":0.21831052364759537,"score_spread":0.210010923381014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032515475","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33639482,0.005890551,0.006980877,0.04340303,0.00045460972,0.000046040364,0.00020193568,0.000081045844,0.6065471],"genre_scores_gemma":[0.9904303,0.001172122,0.0002587601,0.00044749407,0.00007336621,0.000014170388,0.000023885257,0.000027177332,0.0075527704],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9964306,0.0024584057,0.00007687065,0.0001490502,0.00032523097,0.0005599602],"domain_scores_gemma":[0.99631566,0.0018532552,0.00036538971,0.00024880335,0.00030437458,0.00091256876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020776747,0.00028681415,0.00026929527,0.0013469079,0.004886245,0.01375088,0.0007566484,0.0019928492,0.010863564],"category_scores_gemma":[0.004802347,0.0001860247,0.00031700457,0.0021948707,0.01890573,0.00982081,0.006000233,0.0034151198,0.0007220894],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000106885054,0.000094938136,0.004022042,0.00018381332,0.000025907066,0.0008318284,0.33688092,0.00065529096,0.00051125034,0.62390596,0.0071385424,0.025642592],"study_design_scores_gemma":[0.00002997248,0.00010906018,0.006588599,0.00037548103,0.000023018818,0.0007878534,0.48884732,0.0008407356,0.00039354275,0.14705904,0.35488716,0.000058277696],"about_ca_topic_score_codex":0.009169558,"about_ca_topic_score_gemma":0.0059337886,"teacher_disagreement_score":0.01375088,"about_ca_system_score_codex":0.0032013068,"about_ca_system_score_gemma":0.0031576892,"threshold_uncertainty_score":0.036342263},"labels":[],"label_agreement":null},{"id":"W2034153215","doi":"10.3141/2416-06","title":"Assessing Impact of Carsharing on Household Car Ownership in Montreal, Quebec, Canada","year":2014,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Car ownership; Service (business); Business; Census; Regression analysis; Population; Transport engineering; Demographic economics; Marketing; Geography; Economics; Statistics; Engineering; Demography; Public transport; Mathematics","score_opus":0.0969724801411694,"score_gpt":0.36291093794377066,"score_spread":0.2659384578026013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034153215","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9788888,0.0011009605,0.00056485005,0.0006341429,0.000031950465,0.00013334244,0.008835421,0.000048132224,0.009762336],"genre_scores_gemma":[0.99264365,0.00039178383,0.000378492,0.000059164733,0.000005339293,0.00003512552,0.0017869228,0.000008094548,0.00469158],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994072,0.00008387263,0.00002373202,0.000085602995,0.00021387069,0.00018576412],"domain_scores_gemma":[0.99793136,0.00013744093,0.00022436498,0.000047943493,0.0012337792,0.00042507655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006004737,0.00048071952,0.00034411214,0.0010920911,0.002206156,0.0010217251,0.0015648216,0.00029447975,0.0047999276],"category_scores_gemma":[0.001823369,0.00021632326,0.00052867056,0.0026425587,0.0005468331,0.00036680454,0.0005729631,0.00043988842,0.0003134365],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006863289,0.000088874076,0.9800842,0.00005776422,0.00012341425,0.000115169976,0.00089581846,0.0007537579,0.0002955846,0.00036872533,0.0042620413,0.012886119],"study_design_scores_gemma":[0.0000036368488,0.000024078541,0.99629635,0.000022462105,0.000021797654,0.0000126936075,0.001121378,0.0007541766,0.00009131809,0.000013005624,0.0016284374,0.000010619134],"about_ca_topic_score_codex":0.998833,"about_ca_topic_score_gemma":0.9994979,"teacher_disagreement_score":0.03872139,"about_ca_system_score_codex":0.03872139,"about_ca_system_score_gemma":0.02730233,"threshold_uncertainty_score":0.28094465},"labels":[],"label_agreement":null},{"id":"W2035971144","doi":"10.1080/15472450601122256","title":"Individual Trip Destination Estimation in a Transit Smart Card Automated Fare Collection System","year":2007,"lang":"en","type":"article","venue":"Journal of Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":368,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Smart card; Transit (satellite); Computer science; Data collection; Estimation; Process (computing); Transport engineering; Real-time computing; Public transport; Engineering; Computer security; Systems engineering; Operating system","score_opus":0.01960926572771334,"score_gpt":0.25754663457191135,"score_spread":0.237937368844198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035971144","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88356113,0.000062766645,0.112178124,0.000097841395,0.000021677344,0.000071773764,0.00049446925,0.0020882466,0.0014239247],"genre_scores_gemma":[0.9815041,0.000019496956,0.017351419,0.00001403348,0.0000031925465,0.000015792744,0.00026064212,0.000011947987,0.00081936346],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997998,0.000045158544,0.0000142978515,0.000062117106,0.000055236927,0.000023475806],"domain_scores_gemma":[0.9994591,0.00017100984,0.00005272769,0.00009105976,0.00019613592,0.000030006564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003967268,0.00030960824,0.00053227926,0.000438422,0.0003082208,0.0005622523,0.0004523622,0.0005201039,0.0008714051],"category_scores_gemma":[0.001310816,0.00018297693,0.00018554216,0.00048146676,0.000116747884,0.00043997963,0.00026375585,0.00024428032,0.0003499557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012477112,0.0004987195,0.067644775,0.00013273073,0.00017420657,0.0004934645,0.0004111036,0.7020362,0.018369673,0.0010674627,0.0028061671,0.20511782],"study_design_scores_gemma":[0.000016237458,0.00010718879,0.0063180504,0.0000027878698,0.000018597137,0.00006238872,0.000036847272,0.98945206,0.0034717296,0.000110493595,0.00039104035,0.000012693955],"about_ca_topic_score_codex":0.024807092,"about_ca_topic_score_gemma":0.013928546,"teacher_disagreement_score":0.024807092,"about_ca_system_score_codex":0.0006101022,"about_ca_system_score_gemma":0.00065157213,"threshold_uncertainty_score":0.049325407},"labels":[],"label_agreement":null},{"id":"W2040395924","doi":"10.3141/2196-03","title":"Multiobjective Optimization for Multimodal Evacuation","year":2010,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Computer science; Traffic congestion; Transit (satellite); Public transport; Vehicle routing problem; Transport engineering; Scheduling (production processes); Budget constraint; Flow network; Operations research; Routing (electronic design automation); Engineering; Mathematical optimization; Computer network; Operations management","score_opus":0.06105033205017096,"score_gpt":0.3762983787042979,"score_spread":0.3152480466541269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040395924","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008802071,0.00083057996,0.9801098,0.00030552183,0.00006272163,0.00008607791,0.00007146529,0.00010294143,0.009628765],"genre_scores_gemma":[0.5405114,0.0021612206,0.44347182,0.00026186334,0.00014160675,0.00074414676,0.00028592392,0.0001678294,0.012254202],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941945,0.0003028731,0.000019222676,0.0000713074,0.00012718854,0.00005994717],"domain_scores_gemma":[0.99952674,0.0002854722,0.000063153675,0.000023822484,0.00007251903,0.000028306496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001256314,0.0015732956,0.00085433904,0.0008347108,0.00056569284,0.0010340682,0.00086647086,0.0010779948,0.003213509],"category_scores_gemma":[0.00152824,0.00041755097,0.0011668436,0.0007460848,0.0007710904,0.0007662099,0.0015760034,0.0011675389,0.00032470596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010375097,0.000023415318,0.00015340516,0.000075593205,0.000034287863,0.00004960626,0.000025584257,0.9693745,0.00057668687,0.018068254,0.00049217057,0.011116173],"study_design_scores_gemma":[0.000006975701,0.000026524429,0.00008203405,0.000015630441,0.000008938128,0.000015217846,0.000018413524,0.98799884,0.00017525667,0.009386157,0.0022594302,0.0000065285253],"about_ca_topic_score_codex":0.004596136,"about_ca_topic_score_gemma":0.0046151676,"teacher_disagreement_score":0.004596136,"about_ca_system_score_codex":0.001391898,"about_ca_system_score_gemma":0.0014194538,"threshold_uncertainty_score":0.010750234},"labels":[],"label_agreement":null},{"id":"W2040441602","doi":"10.1109/mits.2010.935741","title":"Next Steps for the Grand Cooperative Driving Challenge [ITS Events]","year":2009,"lang":"en","type":"article","venue":"IEEE Intelligent Transportation Systems Magazine","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Grand Challenges; Engineering; Aeronautics; Operations research; Computer science; Data science; Engineering management; Political science; Library science; Law","score_opus":0.039171816565042886,"score_gpt":0.27016075860103256,"score_spread":0.23098894203598969,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040441602","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01574045,0.0066170334,0.018486373,0.6122871,0.05335981,0.0017509657,0.0049091172,0.00134418,0.2855049],"genre_scores_gemma":[0.16145645,0.006034893,0.05954445,0.16424403,0.008749604,0.0033564884,0.0175234,0.0013120071,0.57777864],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968099,0.0005918388,0.00008604353,0.00021932939,0.0010721335,0.0012208073],"domain_scores_gemma":[0.9921731,0.00037161892,0.00013015872,0.00027786373,0.0016365726,0.005410748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008913161,0.00072729075,0.00038680682,0.00051359215,0.0057151234,0.009324423,0.0028297917,0.01160674,0.040250964],"category_scores_gemma":[0.0076509006,0.00052749424,0.0009085226,0.00048202084,0.0014045715,0.0048555047,0.0069652796,0.00778564,0.019305503],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000064637825,0.00017224909,0.0004681666,0.000100860234,0.000009439059,0.00018987377,0.0006367445,0.00040998516,0.0005965388,0.023346314,0.95383894,0.020166209],"study_design_scores_gemma":[0.000015009617,0.000045342927,0.00056545605,0.00008124668,0.0000029204,0.00003499322,0.0011870993,0.00017050064,0.00014000785,0.0061949403,0.9915461,0.00001643191],"about_ca_topic_score_codex":0.027380649,"about_ca_topic_score_gemma":0.049276687,"teacher_disagreement_score":0.040250964,"about_ca_system_score_codex":0.0027422232,"about_ca_system_score_gemma":0.020611824,"threshold_uncertainty_score":0.13465285},"labels":[],"label_agreement":null},{"id":"W2044985623","doi":"10.1016/j.trc.2010.12.003","title":"Smart card data use in public transit: A literature review","year":2011,"lang":"en","type":"review","venue":"Transportation Research Part C Emerging Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":911,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Smart card; Public transport; Computer science; Context (archaeology); Data collection; Transit (satellite); Report card; Commercialization; Computer security; Transport engineering; Business; Engineering","score_opus":0.38241595346177376,"score_gpt":0.4254506021966179,"score_spread":0.04303464873484414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044985623","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007466432,0.99811494,0.00009617394,0.00028995136,0.000084945605,0.000007442481,0.00006693833,0.000002619427,0.00059023994],"genre_scores_gemma":[0.0029939811,0.9965431,0.00014877971,0.000097466094,0.000057022622,0.0000051934667,0.000040720413,8.0917283e-7,0.00011286572],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992848,0.00015333743,0.00018011927,0.00012283793,0.00021263045,0.00004627858],"domain_scores_gemma":[0.9949181,0.003461005,0.000655253,0.000048382833,0.000836342,0.00008088687],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015815082,0.0006699504,0.001401459,0.0054556434,0.00033237445,0.00176531,0.0008092664,0.0010235811,0.0034235776],"category_scores_gemma":[0.00406354,0.0003845563,0.001004601,0.009715388,0.00058276416,0.0023434223,0.00066366984,0.00075911405,0.0004920672],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009810212,0.00010729151,0.0045051123,0.11333293,0.00042120248,0.00032928452,0.00042004185,0.00040168277,0.000499462,0.001944013,0.017962603,0.8599783],"study_design_scores_gemma":[0.00004535434,0.00034446275,0.030768963,0.16308236,0.0043772506,0.003409055,0.0037650645,0.0006697541,0.0015160642,0.0022561075,0.78962594,0.00013955738],"about_ca_topic_score_codex":0.007566341,"about_ca_topic_score_gemma":0.016278537,"teacher_disagreement_score":0.007566341,"about_ca_system_score_codex":0.001160261,"about_ca_system_score_gemma":0.004421748,"threshold_uncertainty_score":0.01504457},"labels":[],"label_agreement":null},{"id":"W2045656633","doi":"10.1061/41038(343)35","title":"Somewhere in Time — A History of Automated People Movers","year":2009,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Downtown; Work (physics); Transit system; Engineering; Transport engineering; West virginia; Transit (satellite); Business; Public transport; History; Archaeology","score_opus":0.004835300567916989,"score_gpt":0.18889088708591745,"score_spread":0.18405558651800047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045656633","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.067505464,0.13950677,0.0077565187,0.0925069,0.0048193624,0.00007308483,0.00026929405,0.00031274886,0.6872499],"genre_scores_gemma":[0.6339139,0.10944305,0.0045447703,0.019986607,0.0041778483,0.0001187084,0.00021572922,0.00039604068,0.22720332],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972588,0.0010772139,0.00011504151,0.0005401267,0.00064137444,0.00036736406],"domain_scores_gemma":[0.99760616,0.001237659,0.00021832733,0.00018995436,0.00039974324,0.00034811534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021257913,0.00042691213,0.00027293572,0.002056153,0.0058104875,0.005666643,0.00090512604,0.0026258705,0.010365867],"category_scores_gemma":[0.004596699,0.00040250938,0.0002561732,0.002197599,0.009429344,0.008971385,0.0030119095,0.0035021456,0.0024305936],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014604813,0.00010612022,0.0031758542,0.00057089864,0.000020489364,0.0011940912,0.10606297,0.00033340647,0.00050209434,0.508756,0.0992046,0.27992743],"study_design_scores_gemma":[0.000002061193,0.000030930565,0.0006029509,0.00018963574,0.000003135373,0.00023701416,0.004354233,0.000039538656,0.00015120968,0.004710936,0.9896688,0.000009549011],"about_ca_topic_score_codex":0.008205229,"about_ca_topic_score_gemma":0.009090847,"teacher_disagreement_score":0.010365867,"about_ca_system_score_codex":0.0048822192,"about_ca_system_score_gemma":0.0019933148,"threshold_uncertainty_score":0.0354231},"labels":[],"label_agreement":null},{"id":"W2046294346","doi":"10.1680/tran.2010.163.4.203","title":"Empirical evidence for taxi customer-search model","year":2010,"lang":"en","type":"article","venue":"Proceedings of the Institution of Civil Engineers - Transport","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Taxis; Multinomial logistic regression; Affect (linguistics); Choice set; Market segmentation; Business; Logistic regression; Empirical research; Marketing; Demographics; Set (abstract data type); Computer science; Econometrics; Operations research; Transport engineering; Economics; Statistics; Engineering; Psychology; Mathematics","score_opus":0.057862603709460746,"score_gpt":0.294771308154533,"score_spread":0.23690870444507225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046294346","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87502503,0.0017536224,0.06490822,0.006575934,0.00011829335,0.0003912829,0.004063254,0.00039878418,0.04676561],"genre_scores_gemma":[0.99056506,0.0007418362,0.0027495835,0.00025254732,0.000055207736,0.00010450882,0.0012796101,0.000048034897,0.004203522],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99723816,0.0013665828,0.00018226024,0.00042528816,0.000449848,0.00033789608],"domain_scores_gemma":[0.9023453,0.082466125,0.0068496456,0.0024842103,0.0046620583,0.0011926397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0064214915,0.00058558985,0.0013155356,0.0020249304,0.0008067118,0.0031776708,0.002368142,0.0020579041,0.04944882],"category_scores_gemma":[0.054720476,0.00040167148,0.0013231491,0.003415303,0.0014806215,0.0029152718,0.0010673479,0.0019222962,0.0043761185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011032335,0.0011786041,0.48024288,0.0010877989,0.00061442005,0.0019451642,0.0025416547,0.17732498,0.0005525107,0.24199006,0.021662503,0.069756284],"study_design_scores_gemma":[0.0002334879,0.00030889153,0.08073155,0.00036714834,0.00025221176,0.0010698421,0.004393296,0.8000303,0.0003098287,0.09952018,0.0126717705,0.00011148399],"about_ca_topic_score_codex":0.014660817,"about_ca_topic_score_gemma":0.007099584,"teacher_disagreement_score":0.04944882,"about_ca_system_score_codex":0.0019043809,"about_ca_system_score_gemma":0.0018393175,"threshold_uncertainty_score":0.1654228},"labels":[],"label_agreement":null},{"id":"W2052997156","doi":"10.1016/j.ejor.2014.04.013","title":"The static bicycle relocation problem with demand intervals","year":2014,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":150,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"University of Southampton","keywords":"Mathematical optimization; Bounding overwatch; Relocation; Vehicle routing problem; Travelling salesman problem; Context (archaeology); Branch and cut; Computer science; Integer programming; Routing (electronic design automation); Traveling purchaser problem; Facility location problem; Node (physics); Mathematics; 2-opt; Engineering","score_opus":0.04100789879994455,"score_gpt":0.31392349708450284,"score_spread":0.2729155982845583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052997156","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49823722,0.0026218495,0.4432317,0.0041105137,0.00053824804,0.000416897,0.0035774119,0.0005347474,0.04673145],"genre_scores_gemma":[0.94920266,0.0010085833,0.028058868,0.00023148577,0.00022993045,0.00014488689,0.0014565836,0.00018233509,0.019484658],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99852633,0.00057205156,0.00006754851,0.00031718815,0.00015554432,0.000361379],"domain_scores_gemma":[0.99713886,0.0017965314,0.00028423857,0.00017156768,0.00018765427,0.0004211538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014274645,0.0016517248,0.0031352947,0.0010945972,0.0009996325,0.0025760895,0.0042687044,0.0032709467,0.014308071],"category_scores_gemma":[0.006155384,0.0015453987,0.0012848153,0.002596118,0.0013618104,0.0035724351,0.0019280344,0.0019306542,0.00089521083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00090770074,0.00024912212,0.0013499252,0.00048682216,0.00014332276,0.0008738261,0.00014665288,0.91446644,0.0011607821,0.04907617,0.0101435855,0.02099573],"study_design_scores_gemma":[0.00014962339,0.00017892075,0.00072284,0.000056027067,0.00007045225,0.00028823395,0.00034949445,0.9333266,0.0004833049,0.061604075,0.0027231546,0.000047377456],"about_ca_topic_score_codex":0.008203829,"about_ca_topic_score_gemma":0.0040267385,"teacher_disagreement_score":0.014308071,"about_ca_system_score_codex":0.0015411099,"about_ca_system_score_gemma":0.0011039722,"threshold_uncertainty_score":0.04786527},"labels":[],"label_agreement":null},{"id":"W2054032246","doi":"10.5555/1400549.1400711","title":"The Stochastic Fleet Estimation (SaFE) model","year":2008,"lang":"en","type":"article","venue":"Spring Simulation Multiconference","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Task (project management); Computer science; Duration (music); Monte Carlo method; Estimation; Set (abstract data type); Stochastic modelling; Stochastic process; Fleet management; Operations research; Simulation; Engineering; Statistics; Telecommunications; Systems engineering; Mathematics","score_opus":0.03794811478032884,"score_gpt":0.2674939645256965,"score_spread":0.22954584974536768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054032246","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04712498,0.00012662551,0.9483725,0.0002861633,0.000020932252,0.00006497482,0.0008425852,0.00030730956,0.0028538932],"genre_scores_gemma":[0.8400748,0.00038341206,0.14862493,0.00016298042,0.0000598272,0.00045483373,0.0036275948,0.00015689945,0.0064547393],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979602,0.0008033879,0.000087919616,0.00042480192,0.0004592107,0.00026443246],"domain_scores_gemma":[0.9944581,0.0037930026,0.00071700045,0.00041241467,0.00048242422,0.00013713143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027837048,0.000839198,0.0010466385,0.0012110827,0.00049484964,0.0011451468,0.00238455,0.0014324336,0.0036478806],"category_scores_gemma":[0.011919795,0.0007224277,0.0010085737,0.0013328829,0.0010836031,0.002773006,0.0011139225,0.0014013561,0.0005883003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025642217,0.000008022345,0.00063669,0.000008162493,0.000014747108,0.000021251983,0.000013312512,0.98651206,0.00013951588,0.009299147,0.0003344204,0.002987053],"study_design_scores_gemma":[0.000004561051,0.000008994077,0.00019397298,0.000002708032,0.000004019685,0.0000142686185,0.000004218608,0.9925264,0.000089896224,0.0068541286,0.00029144718,0.0000053512217],"about_ca_topic_score_codex":0.014330044,"about_ca_topic_score_gemma":0.007960982,"teacher_disagreement_score":0.014330044,"about_ca_system_score_codex":0.001379379,"about_ca_system_score_gemma":0.0016562128,"threshold_uncertainty_score":0.028493226},"labels":[],"label_agreement":null},{"id":"W2056200673","doi":"10.1142/s0217595907001206","title":"CORRELATIONS IN STOCHASTIC PROGRAMMING: A CASE FROM STOCHASTIC SERVICE NETWORK DESIGN","year":2007,"lang":"en","type":"article","venue":"Asia Pacific Journal of Operational Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Flexibility (engineering); Robustness (evolution); Stochastic programming; Computer science; Network planning and design; Stochastic optimization; Mathematical optimization; Stochastic modelling; Stochastic process; Service (business); Mathematics; Economics","score_opus":0.08042517883552801,"score_gpt":0.34705683999105846,"score_spread":0.26663166115553044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056200673","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11843451,0.00057488383,0.86487037,0.0030089545,0.000056655885,0.00008368583,0.000103881066,0.0000789853,0.01278808],"genre_scores_gemma":[0.92782736,0.0006329359,0.06671366,0.00032189165,0.00015371984,0.00023059583,0.00005689061,0.000053486052,0.0040094997],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9958192,0.0025706694,0.00014623093,0.00037335575,0.00070463156,0.00038583274],"domain_scores_gemma":[0.98931074,0.00746276,0.0014980164,0.00062835275,0.000578352,0.000521776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0053410237,0.0008187504,0.0014036582,0.0006203546,0.0010471586,0.0016691127,0.00088118244,0.0025734517,0.0017217613],"category_scores_gemma":[0.015295571,0.0007885194,0.0018143929,0.0012944494,0.0026355668,0.0021199558,0.002054947,0.0031532447,0.0001725653],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052613614,0.000042262807,0.001032466,0.000048339756,0.000040450206,0.00050584826,0.00022924428,0.45189166,0.00047987752,0.53886807,0.00060338265,0.006205785],"study_design_scores_gemma":[0.000039569466,0.00006850998,0.00030861702,0.000019747815,0.000016537837,0.00012184861,0.000054336102,0.7243651,0.00028467976,0.27321365,0.0014846239,0.000022703145],"about_ca_topic_score_codex":0.004136022,"about_ca_topic_score_gemma":0.0026619367,"teacher_disagreement_score":0.0053410237,"about_ca_system_score_codex":0.0021897836,"about_ca_system_score_gemma":0.0022310799,"threshold_uncertainty_score":0.028246343},"labels":[],"label_agreement":null},{"id":"W2060625299","doi":"10.1002/atr.5670430304","title":"Passengers' perceptions and effects of bus‐holding strategy using automatic vehicle location technology","year":2009,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"University of Leeds","keywords":"Transport engineering; Automatic vehicle location; Bus priority; Public transport; Engineering; Transit (satellite); Perception; Travel time; Automotive engineering; Simulation; Computer science; Telecommunications; Global Positioning System; Psychology","score_opus":0.006319072210148115,"score_gpt":0.2467657766873794,"score_spread":0.2404467044772313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060625299","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995716,0.000013991527,0.00002234077,0.000013077818,0.0000010907212,0.0000021612454,0.000015077547,0.0000012553526,0.00035941647],"genre_scores_gemma":[0.99978024,0.000017656037,0.000023617355,0.0000051882125,9.213523e-7,0.0000015475373,0.000017005055,3.8874208e-7,0.00015342471],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99963236,0.00014867284,0.00002634171,0.000033168653,0.00008344707,0.00007603727],"domain_scores_gemma":[0.9978084,0.0007426794,0.00067436474,0.0000549821,0.0002569456,0.00046274258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048107642,0.00018144578,0.000113578375,0.00027003288,0.0002285509,0.0006473705,0.00011669513,0.00023639644,0.0027364034],"category_scores_gemma":[0.0023199266,0.00013251776,0.00025683228,0.0002170149,0.0002379096,0.00026040358,0.00026435047,0.00038910017,0.00021630489],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005374613,0.0007712759,0.9749094,0.000075183416,0.00010722499,0.00020634518,0.0058905957,0.0006481253,0.0068637575,0.00008858518,0.00021053178,0.00969143],"study_design_scores_gemma":[0.000010676508,0.0008088049,0.990868,0.000011048959,0.000031177493,0.00007199276,0.006727304,0.00057703897,0.00047831435,0.000019949444,0.00038204945,0.000013607428],"about_ca_topic_score_codex":0.012846061,"about_ca_topic_score_gemma":0.0120447995,"teacher_disagreement_score":0.012846061,"about_ca_system_score_codex":0.00022822057,"about_ca_system_score_gemma":0.00017794591,"threshold_uncertainty_score":0.025542557},"labels":[],"label_agreement":null},{"id":"W2061362148","doi":"10.1016/j.aucc.2009.12.015","title":"Semi-recumbent positioning in Australia and New Zealand","year":2010,"lang":"en","type":"article","venue":"Australian Critical Care","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Observational study; Weaning; Pneumonia; Mechanical ventilation; Emergency medicine; Intensive care medicine; Anesthesia; Internal medicine","score_opus":0.028816727443072548,"score_gpt":0.3131139897599171,"score_spread":0.28429726231684455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061362148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99606055,0.00032182116,0.000067157176,0.00038126297,0.000029662333,0.000027793447,0.00007770505,0.000002869232,0.0030311379],"genre_scores_gemma":[0.9971512,0.00024640755,0.00008365553,0.00006711207,0.0000072466314,0.000014979883,0.000046319405,0.0000028001043,0.0023803827],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99904066,0.00016078282,0.000083269726,0.00014030028,0.0002787885,0.0002962149],"domain_scores_gemma":[0.9978923,0.00015824061,0.00047186224,0.000047458874,0.00058556016,0.0008445341],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076703576,0.0002329732,0.00037494607,0.0009779745,0.0019769452,0.0013530654,0.00070170884,0.00051093224,0.0029067183],"category_scores_gemma":[0.0036829296,0.00025210762,0.00034487998,0.0014484167,0.0010716057,0.00086212304,0.0015030281,0.0008266309,0.00035181522],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006583242,0.0003688806,0.83791673,0.00022764642,0.0000591896,0.004115339,0.09022824,0.00034360835,0.0017876022,0.001673927,0.0022797023,0.06034086],"study_design_scores_gemma":[0.0000098935125,0.00032672644,0.96594906,0.00004759464,0.000009146008,0.00044651394,0.029960139,0.00013117374,0.000046345405,0.00006879272,0.002989867,0.000014700215],"about_ca_topic_score_codex":0.56284446,"about_ca_topic_score_gemma":0.79310477,"teacher_disagreement_score":0.56284446,"about_ca_system_score_codex":0.0046650497,"about_ca_system_score_gemma":0.005572572,"threshold_uncertainty_score":0.8794601},"labels":[],"label_agreement":null},{"id":"W2064051298","doi":"10.1016/j.eswa.2011.11.071","title":"Evaluation of carsharing network’s growth strategies through discrete event simulation","year":2012,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Benchmarking; Operations research; Discrete event simulation; Event (particle physics); Popularity; Market penetration; Decision support system; Business; Simulation; Marketing; Artificial intelligence","score_opus":0.037630796849611986,"score_gpt":0.31625735329542415,"score_spread":0.27862655644581213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064051298","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94823045,0.00016763463,0.043688305,0.00028139944,0.00004262359,0.00015855746,0.00034270252,0.00021075943,0.0068775937],"genre_scores_gemma":[0.99564606,0.000036704518,0.0036650565,0.000007947528,0.000001870755,0.000035741017,0.0000956534,0.000007696231,0.00050330244],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994192,0.00024210577,0.00002140064,0.000085377134,0.00009434897,0.0001374921],"domain_scores_gemma":[0.99416524,0.004521553,0.00028853503,0.00018476212,0.0005991284,0.00024086057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023660262,0.0008689571,0.0007903234,0.0012551593,0.00046712565,0.0011918725,0.0011328835,0.0011824161,0.002145],"category_scores_gemma":[0.0061383797,0.0003405347,0.00055827823,0.0007688668,0.0005220158,0.0011020835,0.0005003824,0.00075087836,0.00016199947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006932411,0.000047100508,0.0005453133,0.000010191719,0.0000071842887,0.00001015735,0.000006761055,0.9970229,0.0002132675,0.00048372982,0.00005956436,0.0015244754],"study_design_scores_gemma":[0.000006996836,0.000036137026,0.00014070378,0.0000011841792,0.000004806393,0.0000019480442,0.000012427425,0.9993831,0.00026892088,0.00010960028,0.00003204936,0.0000020692728],"about_ca_topic_score_codex":0.029563747,"about_ca_topic_score_gemma":0.012349022,"teacher_disagreement_score":0.029563747,"about_ca_system_score_codex":0.002575683,"about_ca_system_score_gemma":0.0014898216,"threshold_uncertainty_score":0.058783352},"labels":[],"label_agreement":null},{"id":"W2064526960","doi":"10.1177/0278364912444766","title":"Robotic load balancing for mobility-on-demand systems","year":2012,"lang":"en","type":"article","venue":"The International Journal of Robotics Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":289,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; TRIPS architecture; Pickup; Destinations; Throughput; Set (abstract data type); Variable (mathematics); Simulation; Real-time computing; Wireless; Telecommunications; Artificial intelligence","score_opus":0.08531598830349683,"score_gpt":0.37384951195778127,"score_spread":0.2885335236542844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064526960","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04014904,0.00031193922,0.9524342,0.00033744713,0.00005105694,0.00009159066,0.000057898258,0.00044725527,0.006119604],"genre_scores_gemma":[0.9279699,0.0002459012,0.06687135,0.000069791975,0.00006241833,0.00013323456,0.000081717655,0.000081936705,0.004483912],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995307,0.00014136509,0.000018862796,0.00008250032,0.00014109505,0.00008560549],"domain_scores_gemma":[0.9993642,0.00030958984,0.00010920477,0.00007383543,0.00009602223,0.00004710664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005153718,0.0007927253,0.000606889,0.0003989677,0.0007568006,0.00089205406,0.0013559232,0.0006382725,0.003130998],"category_scores_gemma":[0.0013174898,0.0003725615,0.0003845024,0.00039796316,0.00077506853,0.0011189816,0.0010866082,0.00059739425,0.00042137803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041444582,0.000037004862,0.00021027013,0.000058877667,0.000014154027,0.00004225886,0.00005611635,0.96981466,0.0029779873,0.009625097,0.00065748004,0.01646455],"study_design_scores_gemma":[0.0000075580033,0.000025588935,0.000081154045,0.0000035879104,0.0000032666303,0.000017194581,0.00002080203,0.9934929,0.0007668665,0.0040291883,0.0015458403,0.0000060640905],"about_ca_topic_score_codex":0.0042815553,"about_ca_topic_score_gemma":0.0035795525,"teacher_disagreement_score":0.0042815553,"about_ca_system_score_codex":0.0011976731,"about_ca_system_score_gemma":0.00085076306,"threshold_uncertainty_score":0.010474265},"labels":[],"label_agreement":null},{"id":"W2066166221","doi":"10.1002/atr.158","title":"Simulation‐based analysis of personal rapid transit systems: service and energy performance assessment of the Masdar City PRT case","year":2011,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Occupancy; Transport engineering; Engineering; Service (business); Track (disk drive); Energy consumption; Transit (satellite); Automotive engineering; Event (particle physics); Discrete event simulation; Urban rail transit; Simulation; Public transport; Civil engineering; Electrical engineering","score_opus":0.020526748549867347,"score_gpt":0.24735392403908402,"score_spread":0.22682717548921666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066166221","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9844312,0.00006492021,0.0049083014,0.00021071751,0.000009254327,0.000067742825,0.0005166389,0.00010311456,0.009688079],"genre_scores_gemma":[0.99762756,0.00004282165,0.0010966453,0.000007371756,0.0000020879072,0.000021918142,0.00023605429,0.000012136342,0.0009533768],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99949265,0.00018590389,0.00001943447,0.000051903102,0.00010179428,0.00014834956],"domain_scores_gemma":[0.9981213,0.0011470092,0.00017948865,0.00012859567,0.00031367867,0.000109963294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000858036,0.0006983958,0.0005683353,0.0009534395,0.00056297384,0.0009988714,0.00091720995,0.0008729097,0.003474755],"category_scores_gemma":[0.0025112317,0.00040463134,0.00092964043,0.0009412397,0.00056960323,0.00064048875,0.0007726917,0.0008124227,0.00019774403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006837263,0.000035239143,0.0020369021,0.000013228751,0.000013753915,0.00008587012,0.000025057787,0.9953134,0.00026635505,0.0010751198,0.0001664415,0.00090024463],"study_design_scores_gemma":[0.000013012886,0.000041737767,0.0009326251,0.0000025153406,0.000007459933,0.000011475861,0.000058899215,0.9983272,0.0002715137,0.00018728756,0.0001411685,0.000005128242],"about_ca_topic_score_codex":0.08274742,"about_ca_topic_score_gemma":0.032447424,"teacher_disagreement_score":0.08274742,"about_ca_system_score_codex":0.0024963205,"about_ca_system_score_gemma":0.0011405852,"threshold_uncertainty_score":0.16453159},"labels":[],"label_agreement":null},{"id":"W2066633656","doi":"10.1109/itsc.2007.4357656","title":"Car sharing system: what transaction datasets reveal on users' behaviors","year":2007,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Database transaction; Computer science; Identification (biology); Transaction data; Information sharing; Database; World Wide Web; Data mining","score_opus":0.0167184247737614,"score_gpt":0.2552408405524735,"score_spread":0.23852241577871208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066633656","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96790457,0.0006506478,0.0032948945,0.0009824296,0.000046887624,0.000053023126,0.025031127,0.0002641085,0.0017724348],"genre_scores_gemma":[0.9749722,0.00025380397,0.003455638,0.000080248436,0.00003298802,0.000043776567,0.020724697,0.000023883013,0.00041285547],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982374,0.0005233687,0.00025971662,0.00035978598,0.0004734383,0.00014614913],"domain_scores_gemma":[0.99025506,0.004423443,0.0013961683,0.0020605468,0.001377585,0.00048724667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013727831,0.00032465864,0.00052291696,0.0018912724,0.00040882165,0.0013396217,0.0005197406,0.0009250953,0.001313149],"category_scores_gemma":[0.009847963,0.00016909621,0.00041836116,0.0027332678,0.00022298265,0.0023085536,0.0004360084,0.0005008894,0.000815044],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001189856,0.0005415737,0.86209416,0.0005383586,0.00035624226,0.00025044224,0.0011384183,0.0048589935,0.006598221,0.0011558156,0.01101647,0.11026153],"study_design_scores_gemma":[0.000040557996,0.00044045807,0.8774877,0.00013563433,0.00020601744,0.0012979611,0.0050314027,0.08543273,0.0073474497,0.002741125,0.019725008,0.00011396498],"about_ca_topic_score_codex":0.004173947,"about_ca_topic_score_gemma":0.0045535085,"teacher_disagreement_score":0.004173947,"about_ca_system_score_codex":0.0004073216,"about_ca_system_score_gemma":0.0003458414,"threshold_uncertainty_score":0.008299291},"labels":[],"label_agreement":null},{"id":"W2068920909","doi":"10.1109/glocom.2013.6831044","title":"On the recruitment of smart vehicles for urban sensing","year":2013,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Redundancy (engineering); Computer science; Greedy algorithm; Cover (algebra); Scheme (mathematics); Trajectory; Selection (genetic algorithm); Real-time computing; Artificial intelligence; Engineering; Algorithm","score_opus":0.05146436319762805,"score_gpt":0.2495224692858141,"score_spread":0.19805810608818603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068920909","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12571867,0.0008105512,0.866124,0.0011868075,0.00008403947,0.00033255172,0.00008324618,0.0003407181,0.005319465],"genre_scores_gemma":[0.87865305,0.0005645137,0.115439594,0.00021965159,0.00006536771,0.00028021433,0.00012459958,0.000033443666,0.0046196603],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99750936,0.001460186,0.00006955141,0.00032016754,0.00034725104,0.00029346035],"domain_scores_gemma":[0.9956564,0.0027807895,0.00037681966,0.00038333779,0.00045886266,0.00034380733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003002404,0.0004744959,0.0007001591,0.0005793466,0.001067436,0.0007202475,0.0016650995,0.00085845555,0.0017721655],"category_scores_gemma":[0.0073699336,0.0002457225,0.00038403022,0.00070125394,0.0011055113,0.0017173756,0.0021942612,0.00056728296,0.0005368302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001230016,0.00041332943,0.012768395,0.00044557685,0.00007185027,0.00060978683,0.0010485151,0.3690358,0.03196609,0.13677481,0.0067516924,0.43888417],"study_design_scores_gemma":[0.000052981795,0.00069022126,0.0015672611,0.00003651808,0.000021369031,0.0004221848,0.00053570914,0.942206,0.008028364,0.034827657,0.011570198,0.000041502564],"about_ca_topic_score_codex":0.0018543695,"about_ca_topic_score_gemma":0.0019316917,"teacher_disagreement_score":0.003002404,"about_ca_system_score_codex":0.0007646326,"about_ca_system_score_gemma":0.0013548892,"threshold_uncertainty_score":0.015878439},"labels":[],"label_agreement":null},{"id":"W2069525318","doi":"10.1002/atr.5670340203","title":"Automation of paratransit reservation, routing, and scheduling","year":2000,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Bombardier (Canada)","funders":"","keywords":"Paratransit; Reservation; Scheduling (production processes); Automation; Transport engineering; Engineering; Computer science; Public transport; Operations management; Computer network","score_opus":0.00866147408453625,"score_gpt":0.23800131599137986,"score_spread":0.22933984190684362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069525318","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78608537,0.0003957243,0.1279885,0.00053021876,0.00016121501,0.00054681033,0.0026037798,0.01839422,0.06329409],"genre_scores_gemma":[0.961643,0.00010486007,0.029265396,0.000034665325,0.000030155494,0.00006221173,0.0012961631,0.00011311336,0.0074503226],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994721,0.00011491559,0.000025239153,0.00014458485,0.00017214159,0.00007102595],"domain_scores_gemma":[0.99858224,0.00031908794,0.00015031663,0.00043061838,0.00043222567,0.00008547143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000371289,0.0002808767,0.000175875,0.00046776547,0.0004421896,0.000877116,0.0007400795,0.00018644394,0.0049217865],"category_scores_gemma":[0.0011994827,0.00017161097,0.00015516276,0.0005318801,0.0001853123,0.00046912787,0.00036933285,0.00032385922,0.0011641879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00068985677,0.0007712797,0.0443897,0.00023839447,0.00005619699,0.00042356836,0.0005403994,0.1725867,0.04649887,0.0042472742,0.03405714,0.6955006],"study_design_scores_gemma":[0.0002761311,0.00055587833,0.09604539,0.00006701071,0.000089199,0.00055688596,0.0007760057,0.68646175,0.049672134,0.004796369,0.16057672,0.0001264968],"about_ca_topic_score_codex":0.047506105,"about_ca_topic_score_gemma":0.047122594,"teacher_disagreement_score":0.047506105,"about_ca_system_score_codex":0.00084304466,"about_ca_system_score_gemma":0.0013912308,"threshold_uncertainty_score":0.094459176},"labels":[],"label_agreement":null},{"id":"W2070175767","doi":"10.1287/trsc.1050.0114","title":"Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching","year":2006,"lang":"en","type":"article","venue":"Transportation Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":245,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université Laval","funders":"","keywords":"Exploit; Probabilistic logic; Vehicle routing problem; Computer science; Operations research; Real-time data; Field (mathematics); Travel time; Routing (electronic design automation); Transport engineering; Engineering; Computer security; Artificial intelligence; Computer network","score_opus":0.008531559982207816,"score_gpt":0.2504757629453988,"score_spread":0.241944202963191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070175767","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29106483,0.00027734946,0.70339274,0.0009969819,0.00006969929,0.000047821824,0.00041195788,0.00036854346,0.0033700038],"genre_scores_gemma":[0.98228914,0.00011707755,0.016983667,0.000028304492,0.0000271727,0.00001682429,0.00017373396,0.000023787767,0.00034031842],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936086,0.00023333938,0.000040134117,0.00013047764,0.00013924802,0.000095859876],"domain_scores_gemma":[0.9934481,0.0046946825,0.00071097753,0.0005405062,0.00039298914,0.00021287322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002008486,0.0009236552,0.0009240853,0.0005682351,0.00040504872,0.0015025388,0.0015205352,0.0011883848,0.0015612696],"category_scores_gemma":[0.009942055,0.00071309233,0.00044372282,0.0007428674,0.0007646548,0.0041136686,0.0008115066,0.0014631136,0.00031374473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015733555,0.000039415037,0.0013639868,0.000034652538,0.00002128075,0.00005863511,0.000042714986,0.9832955,0.0010478181,0.002925847,0.00023369404,0.010779193],"study_design_scores_gemma":[0.000011317308,0.00003631787,0.0005637142,0.0000032273836,0.000010423787,0.00002200644,0.000020528048,0.9941788,0.00070961384,0.004244151,0.00018824714,0.0000117137215],"about_ca_topic_score_codex":0.003732371,"about_ca_topic_score_gemma":0.0043782443,"teacher_disagreement_score":0.003732371,"about_ca_system_score_codex":0.00073895615,"about_ca_system_score_gemma":0.0009890825,"threshold_uncertainty_score":0.010622025},"labels":[],"label_agreement":null},{"id":"W2070723056","doi":"10.1007/s11116-011-9384-3","title":"When the internet is not enough: toward an understanding of carpool services for service workers","year":2011,"lang":"en","type":"article","venue":"Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Carpool; Service (business); Journey to work; Transport engineering; The Internet; Urban sprawl; Internet access; Metropolitan area; Work (physics); Business; Engineering; Public transport; Marketing; Computer science; Urban planning; Geography; Civil engineering; World Wide Web","score_opus":0.0977687771568426,"score_gpt":0.25320739280708504,"score_spread":0.15543861565024245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070723056","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2769338,0.006831964,0.021072494,0.2655285,0.00055538706,0.00013151491,0.00024148176,0.00012403344,0.42858076],"genre_scores_gemma":[0.98004764,0.00307347,0.0021286695,0.00735261,0.000173096,0.00007254907,0.000048067068,0.00005391893,0.007049864],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9977089,0.0010334109,0.00008099055,0.0002226551,0.0003185077,0.0006354815],"domain_scores_gemma":[0.99561656,0.0022423032,0.000567664,0.00017507572,0.0006723818,0.0007260799],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027176233,0.00040414365,0.00037693442,0.002613653,0.007641508,0.015717003,0.002428533,0.006610322,0.0063914144],"category_scores_gemma":[0.006979685,0.00038641246,0.0003800227,0.0022660668,0.018597651,0.018517848,0.005076363,0.0064906613,0.0006318059],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054167638,0.00019900505,0.0139822485,0.00024305114,0.000012768715,0.0006642859,0.21622977,0.0007264642,0.00030495418,0.7142987,0.013872332,0.03941228],"study_design_scores_gemma":[0.000017192058,0.00006749167,0.011759264,0.0012603784,0.000030761483,0.0005243832,0.5000373,0.004390203,0.00039167286,0.34417653,0.13727567,0.000069139576],"about_ca_topic_score_codex":0.052194934,"about_ca_topic_score_gemma":0.047251977,"teacher_disagreement_score":0.052194934,"about_ca_system_score_codex":0.009611658,"about_ca_system_score_gemma":0.01152156,"threshold_uncertainty_score":0.10378224},"labels":[],"label_agreement":null},{"id":"W2071536164","doi":"10.1109/lcomm.2012.042512.112350","title":"Which Vehicle To Select?","year":2012,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Computer network","score_opus":0.026284027826074818,"score_gpt":0.2627422847735626,"score_spread":0.2364582569474878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071536164","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22867478,0.015047591,0.51955825,0.056005068,0.006774423,0.0007492198,0.0033936524,0.0022532402,0.16754375],"genre_scores_gemma":[0.91708565,0.0037134723,0.032812703,0.002132366,0.0010262245,0.00013194952,0.0013067389,0.00011719627,0.041673757],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99953175,0.00012254869,0.000022667933,0.00010521416,0.000076924734,0.00014095062],"domain_scores_gemma":[0.9995474,0.00011692669,0.0000522442,0.0000501595,0.0001407641,0.000092577815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004908686,0.00044879172,0.0004854366,0.0005110871,0.0006010832,0.0010719927,0.0006992359,0.0009948437,0.010788287],"category_scores_gemma":[0.001930632,0.00014594465,0.0003180978,0.0005433632,0.00037479223,0.0017389355,0.00051012007,0.00054408825,0.004081629],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011261029,0.00032178915,0.021634428,0.00041123756,0.000109869085,0.0011009591,0.00032984925,0.030516809,0.007792755,0.099484816,0.12692107,0.7102504],"study_design_scores_gemma":[0.00039629114,0.0011034543,0.0088586295,0.00038244604,0.00029466097,0.004703514,0.0054840683,0.29480657,0.021544568,0.20453979,0.45767242,0.00021363751],"about_ca_topic_score_codex":0.0018861541,"about_ca_topic_score_gemma":0.0034993526,"teacher_disagreement_score":0.010788287,"about_ca_system_score_codex":0.00030353718,"about_ca_system_score_gemma":0.0007636914,"threshold_uncertainty_score":0.036090434},"labels":[],"label_agreement":null},{"id":"W2076937847","doi":"10.2495/ut060191","title":"High occupancy vehicle lanes — worldwide lessons for European practitioners","year":2006,"lang":"en","type":"article","venue":"WIT transactions on the built environment","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Procter & Gamble (Canada)","funders":"","keywords":"Transport engineering; Occupancy; Enforcement; Context (archaeology); Business; Computer science; Engineering; Civil engineering; Geography","score_opus":0.014513022800122927,"score_gpt":0.21062422920119106,"score_spread":0.19611120640106813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076937847","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03395242,0.26477388,0.013397765,0.52442175,0.0066150445,0.000060016333,0.0002658034,0.000409031,0.15610434],"genre_scores_gemma":[0.49367002,0.2768872,0.022253899,0.11694538,0.0035425485,0.00009443008,0.00048180405,0.00033292305,0.085791774],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99738735,0.0009729313,0.0002720501,0.0003706856,0.000493178,0.0005038291],"domain_scores_gemma":[0.99359596,0.0014846632,0.00042257327,0.0005077688,0.0023245276,0.00166444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01145232,0.0007428699,0.0005439713,0.001357446,0.0020006618,0.006641893,0.002541689,0.007414635,0.016931819],"category_scores_gemma":[0.0105380425,0.00034076071,0.00047611338,0.0029246036,0.004520717,0.011263301,0.0047963164,0.0038190666,0.003313528],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016556277,0.0002893765,0.004821445,0.000743012,0.00002372286,0.000634657,0.00498114,0.001354226,0.0004971397,0.07858846,0.14387864,0.7640226],"study_design_scores_gemma":[0.000027616981,0.00021726768,0.0041902238,0.0024357787,0.000017079585,0.00069480453,0.025854861,0.00055325276,0.00036065065,0.03526323,0.930323,0.00006224889],"about_ca_topic_score_codex":0.009165525,"about_ca_topic_score_gemma":0.009280697,"teacher_disagreement_score":0.016931819,"about_ca_system_score_codex":0.0031549465,"about_ca_system_score_gemma":0.005247546,"threshold_uncertainty_score":0.060566366},"labels":[],"label_agreement":null},{"id":"W2079919908","doi":"10.3141/1791-09","title":"Planning and Design of Flex-Route Transit Services","year":2002,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"FLEX; Dwell time; Operator (biology); Transit (satellite); Computer science; Operations research; Service (business); Transport engineering; Industrial engineering; Mathematical optimization; Simulation; Engineering; Public transport; Mathematics","score_opus":0.12918330022730093,"score_gpt":0.3544997052228237,"score_spread":0.22531640499552277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079919908","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0967328,0.00089539296,0.8664708,0.00070862094,0.000055397562,0.00045276328,0.00035932966,0.0005372156,0.033787698],"genre_scores_gemma":[0.82697374,0.0010027824,0.16348341,0.00005843075,0.000019959982,0.00028110316,0.00027322563,0.000097541335,0.007809792],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992924,0.00025267206,0.00002299264,0.00010565657,0.00015622878,0.00017008003],"domain_scores_gemma":[0.9996661,0.00010389558,0.00005510737,0.00001800007,0.000076504126,0.00008041409],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064331485,0.0007789243,0.00049429666,0.00078989565,0.0006150045,0.0014558857,0.0009036603,0.00086134707,0.0039846064],"category_scores_gemma":[0.0013168474,0.00063212693,0.0005231246,0.00072741165,0.00081407954,0.0009501555,0.0007731373,0.0005298043,0.00051308546],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036664307,0.000013791428,0.00021316553,0.000036381793,0.0000067780243,0.000118315795,0.000051983716,0.97542953,0.00097144075,0.011719729,0.0004676166,0.01093451],"study_design_scores_gemma":[0.0000082752795,0.000035971796,0.000103735154,0.000009448098,0.000005318779,0.000033231943,0.000099788056,0.99108255,0.0004623707,0.0058501866,0.0023021095,0.00000713369],"about_ca_topic_score_codex":0.009487604,"about_ca_topic_score_gemma":0.012582845,"teacher_disagreement_score":0.009487604,"about_ca_system_score_codex":0.0017057038,"about_ca_system_score_gemma":0.0031848382,"threshold_uncertainty_score":0.01886475},"labels":[],"label_agreement":null},{"id":"W2084014922","doi":"10.1109/jsac.2011.110106","title":"Coalition Formation Games for Distributed Cooperation Among Roadside Units in Vehicular Networks","year":2011,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":160,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Partition (number theory); Computer network; Scheme (mathematics); Vehicular ad hoc network; Stochastic game; Nash equilibrium; Game theory; Wireless ad hoc network; Telecommunications; Wireless; Mathematical optimization","score_opus":0.04781995912228642,"score_gpt":0.2559237373815255,"score_spread":0.2081037782592391,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084014922","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058775637,0.0004237635,0.92669713,0.0006370611,0.00008088771,0.00023251634,0.00015658628,0.00012092011,0.012875568],"genre_scores_gemma":[0.9029196,0.00055080676,0.085990176,0.00018408596,0.000056162113,0.0006903076,0.0002298388,0.00006278591,0.009316203],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983198,0.00096946064,0.000064169435,0.0001959875,0.00022914482,0.00022146618],"domain_scores_gemma":[0.9967963,0.0021958228,0.0003315516,0.00012874919,0.00025201787,0.0002956233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019426552,0.0012450092,0.0014203253,0.0006412073,0.0009385706,0.0014374207,0.002011482,0.0013134523,0.0028819551],"category_scores_gemma":[0.0068183313,0.00047361723,0.00087850646,0.0007383624,0.001739616,0.0019012279,0.0021196383,0.0016851976,0.0003844093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015762862,0.000058525344,0.00047418804,0.00008453538,0.00007015999,0.0002256946,0.00035608513,0.79291815,0.00089261535,0.19407971,0.0017298593,0.008952821],"study_design_scores_gemma":[0.000050836996,0.000039046794,0.00009926649,0.000011904807,0.000010888165,0.0000318787,0.00006212738,0.9247143,0.0001866003,0.073502764,0.0012786504,0.000011640616],"about_ca_topic_score_codex":0.005754504,"about_ca_topic_score_gemma":0.005152855,"teacher_disagreement_score":0.005754504,"about_ca_system_score_codex":0.0026345504,"about_ca_system_score_gemma":0.0018612355,"threshold_uncertainty_score":0.01911515},"labels":[],"label_agreement":null},{"id":"W2085545977","doi":"10.1109/pesgm.2014.6938958","title":"Location-based forecasting of vehicular charging load on the distribution system","year":2014,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Flexibility (engineering); Computer science; Fuzzy logic; Probability distribution; Real-time computing; Simulation; Automotive engineering; Engineering; Artificial intelligence; Statistics; Mathematics","score_opus":0.014703045454627865,"score_gpt":0.18858006959203966,"score_spread":0.1738770241374118,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085545977","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51600933,0.0005381136,0.46625435,0.00042716335,0.00015822696,0.000104044855,0.0047571533,0.002208023,0.009543583],"genre_scores_gemma":[0.9836126,0.00015091113,0.013543155,0.000008267484,0.000026986265,0.000023683388,0.0008524666,0.000026081534,0.0017558843],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998863,0.000029107336,0.0000070331953,0.000033691893,0.000031855947,0.000011996144],"domain_scores_gemma":[0.99966073,0.00018623933,0.000027712802,0.00003468381,0.000073075375,0.000017540413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031726641,0.0003339489,0.000379905,0.00041131862,0.00017597733,0.00040629512,0.00036768927,0.000329121,0.0025057863],"category_scores_gemma":[0.0011068465,0.00014081835,0.00018451149,0.0005169856,0.000091166454,0.00034505807,0.00015390967,0.0003064157,0.00060986937],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005835762,0.000011054623,0.004607396,0.000026590205,0.0000166669,0.00005533836,0.000009469057,0.9598277,0.0010001356,0.00055596535,0.0011215883,0.032709796],"study_design_scores_gemma":[0.0000016875808,0.000008296953,0.0016857794,0.0000030699753,0.0000038097814,0.000006119522,0.000004661231,0.9971117,0.0005084352,0.0003778121,0.00028537566,0.0000032096755],"about_ca_topic_score_codex":0.010980426,"about_ca_topic_score_gemma":0.010014728,"teacher_disagreement_score":0.010980426,"about_ca_system_score_codex":0.00046429154,"about_ca_system_score_gemma":0.00027034714,"threshold_uncertainty_score":0.021833003},"labels":[],"label_agreement":null},{"id":"W2089866128","doi":"10.1080/12265934.2005.9693575","title":"Transportation Policies for the Elderly and Disabled in Japan","year":2005,"lang":"en","type":"article","venue":"International Journal of Urban Sciences","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Public transport; Subsidy; Disabled people; Transport system; Business; Service (business); Universal design; Mode of transport; Inclusion (mineral); Transport engineering; Political science; Engineering; Marketing; Sociology","score_opus":0.019564123797941427,"score_gpt":0.2863288244733586,"score_spread":0.2667647006754172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089866128","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97741497,0.0025800182,0.0001097027,0.003336457,0.000054671305,0.00003360296,0.00023847289,0.000010013528,0.016222196],"genre_scores_gemma":[0.98743445,0.0033994096,0.00025364573,0.0009254513,0.000039127837,0.0000567984,0.00025225023,0.000004267809,0.0076346067],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99956125,0.0000713186,0.00006128776,0.00003274221,0.000042281514,0.00023115645],"domain_scores_gemma":[0.9993523,0.000033873785,0.00013613487,0.000020102252,0.00018609807,0.00027154534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006138746,0.00023163606,0.00016485389,0.0012957471,0.0028925226,0.0019139451,0.0003563963,0.00068111037,0.0020872192],"category_scores_gemma":[0.00084711076,0.00015936836,0.00031556442,0.0015069634,0.0008657756,0.0009728456,0.0017797804,0.00038828107,0.00021355011],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045794438,0.00067762204,0.7543114,0.0012524794,0.00012124024,0.005258286,0.0827646,0.0022473866,0.003978102,0.044329274,0.021100327,0.08350144],"study_design_scores_gemma":[0.000049668673,0.00020293449,0.7761783,0.0004088933,0.000101892896,0.00046052405,0.13692673,0.0006245513,0.0003515836,0.0011459661,0.08348108,0.00006795704],"about_ca_topic_score_codex":0.30036613,"about_ca_topic_score_gemma":0.32795474,"teacher_disagreement_score":0.30036613,"about_ca_system_score_codex":0.005936295,"about_ca_system_score_gemma":0.008117135,"threshold_uncertainty_score":0.5972356},"labels":[],"label_agreement":null},{"id":"W2090864414","doi":"10.1287/trsc.1030.0067","title":"Issues in Real-Time Fleet Management","year":2004,"lang":"en","type":"article","venue":"Transportation Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Fleet management; Transport engineering; Operations research; Computer science; Engineering","score_opus":0.012522031910038967,"score_gpt":0.2703561003757492,"score_spread":0.2578340684657102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090864414","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015706227,0.0069989404,0.0017942097,0.6547412,0.33237025,0.000015898424,0.00005682378,0.0000656756,0.0037999107],"genre_scores_gemma":[0.0039150957,0.007840765,0.0012411484,0.35208446,0.6263494,0.00003403561,0.000038664988,0.000102618214,0.008393822],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9883031,0.0023516286,0.0015141908,0.0018284278,0.0051242816,0.00087848475],"domain_scores_gemma":[0.9682514,0.019414982,0.0022761307,0.0009569429,0.0075049843,0.0015954854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013729762,0.0017402704,0.0014442194,0.00096618757,0.004152176,0.008318312,0.005686064,0.030400028,0.007112116],"category_scores_gemma":[0.037884414,0.0007630988,0.0019684827,0.0013841683,0.0063294405,0.012061555,0.0025780322,0.03563833,0.003561135],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018302253,0.00001302793,0.00009182161,0.00011469374,0.000010229008,0.00023293016,0.00016771763,0.0002122634,0.000069251386,0.012765676,0.9784882,0.00781588],"study_design_scores_gemma":[0.000020469231,0.000039485963,0.0002987551,0.0002202048,0.000018628438,0.00025978824,0.00025719102,0.0005330224,0.00010387522,0.009859605,0.9883537,0.000035233403],"about_ca_topic_score_codex":0.0061740805,"about_ca_topic_score_gemma":0.010039617,"teacher_disagreement_score":0.030400028,"about_ca_system_score_codex":0.0028666405,"about_ca_system_score_gemma":0.003847773,"threshold_uncertainty_score":0.072610795},"labels":[],"label_agreement":null},{"id":"W2091308281","doi":"10.1002/atr.5670350305","title":"Modeling urban taxi services in road networks: Progress, problem and prospect","year":2001,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Transport engineering; Computer science; Urban network; Context (archaeology); Price elasticity of demand; Operations research; Service (business); Traffic congestion; Aggregate (composite); Urban economics; Engineering; Economics; Civil engineering; Geography; Microeconomics; Economy","score_opus":0.005725374160190583,"score_gpt":0.22109292689529814,"score_spread":0.21536755273510755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091308281","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37814775,0.0039744987,0.58065206,0.0048413626,0.00010368471,0.00019411149,0.0005611047,0.00014164911,0.03138385],"genre_scores_gemma":[0.9679481,0.0025734017,0.021758374,0.00006092185,0.000086543405,0.00009617406,0.00015248216,0.00001957748,0.0073043816],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995883,0.00023417483,0.000010864772,0.000059184338,0.000047510573,0.000059984868],"domain_scores_gemma":[0.9987589,0.0008962823,0.00010935439,0.00003610089,0.00013251734,0.000066865614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010903733,0.00046859353,0.0006694691,0.00066915306,0.0006025628,0.0017788894,0.0013120945,0.001903543,0.0026079216],"category_scores_gemma":[0.0033271494,0.00047846237,0.00058655237,0.0016378796,0.0011447225,0.0023490107,0.0009163805,0.0009672458,0.00022000667],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009852815,0.000020205756,0.0008562716,0.000021213611,0.0000057349525,0.000028025557,0.000030519703,0.96635234,0.00003495519,0.029674435,0.00033819253,0.0026283923],"study_design_scores_gemma":[0.0000025630377,0.000006490094,0.00010609094,0.0000070965225,0.0000025363006,0.000007544144,0.000033445554,0.98719275,0.000031634972,0.012055618,0.00055098394,0.000003205194],"about_ca_topic_score_codex":0.026785703,"about_ca_topic_score_gemma":0.015170529,"teacher_disagreement_score":0.026785703,"about_ca_system_score_codex":0.0022882137,"about_ca_system_score_gemma":0.0015827586,"threshold_uncertainty_score":0.05325961},"labels":[],"label_agreement":null},{"id":"W2093630411","doi":"10.1002/atr.5670380303","title":"Scheduling considerations for a branching transit route","year":2004,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Science Foundation","keywords":"Scheduling (production processes); Schedule; Offset (computer science); Operations research; Transport engineering; Computer science; Engineering; Operations management","score_opus":0.01447821796608724,"score_gpt":0.25198851309454817,"score_spread":0.23751029512846095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093630411","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9164833,0.00023510907,0.06722733,0.00021344869,0.000065946864,0.00013718773,0.00013285929,0.00014267662,0.015362254],"genre_scores_gemma":[0.9870149,0.00008105709,0.011526432,0.000018601855,0.0000075155276,0.000015507816,0.00006693268,0.000023441151,0.001245608],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993641,0.00025786852,0.000018246048,0.0000646424,0.00012024811,0.00017500368],"domain_scores_gemma":[0.9981243,0.00092875113,0.00028810208,0.00011982973,0.00025981973,0.00027914412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010508568,0.0005662142,0.00036650954,0.00048852747,0.00070004334,0.00095848314,0.00080234505,0.0005109975,0.006301035],"category_scores_gemma":[0.0027283046,0.00026871177,0.0005204272,0.0006769039,0.000502563,0.0006059515,0.00057404133,0.0006409065,0.000301984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010306175,0.00012377178,0.004146184,0.00013371492,0.000037165086,0.00067452685,0.00028524216,0.93422884,0.01375125,0.02013189,0.00062866637,0.024828114],"study_design_scores_gemma":[0.00022748839,0.0020276613,0.0057473145,0.000062479296,0.00014778874,0.0004041703,0.0010883503,0.9476304,0.008418445,0.028631004,0.005557883,0.000056999157],"about_ca_topic_score_codex":0.00781454,"about_ca_topic_score_gemma":0.011149506,"teacher_disagreement_score":0.00781454,"about_ca_system_score_codex":0.0010909989,"about_ca_system_score_gemma":0.0009954063,"threshold_uncertainty_score":0.021079123},"labels":[],"label_agreement":null},{"id":"W2093856210","doi":"10.1016/j.dam.2011.01.021","title":"An integer <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si28.gif\" display=\"inline\" overflow=\"scroll\"><mml:mi>L</mml:mi></mml:math>-shaped algorithm for the Dial-a-Ride Problem with stochastic customer delays","year":2011,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Algorithm; Mathematics; Integer (computer science); Computer science","score_opus":0.017507335040693933,"score_gpt":0.23230529831175645,"score_spread":0.21479796327106251,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093856210","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077809864,0.000154707,0.97022176,0.0009640328,0.00027815916,0.0001298835,0.00060270814,0.0007092801,0.019158546],"genre_scores_gemma":[0.09362739,0.00024050227,0.8816236,0.00040638074,0.00009463654,0.00029267825,0.0008559722,0.00063211995,0.022226753],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926275,0.00016161683,0.000047191286,0.00020114366,0.00019583688,0.00013147214],"domain_scores_gemma":[0.9983286,0.00092070067,0.00009697905,0.00021084987,0.0003286512,0.00011416218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013942994,0.0010526492,0.0009285181,0.000871391,0.0008993989,0.0023168635,0.0022843806,0.0017507384,0.036312368],"category_scores_gemma":[0.00927816,0.00044059032,0.0008341729,0.0009790424,0.0008658923,0.002929033,0.0023305137,0.0022369332,0.006173247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007559051,0.00031767754,0.0012024654,0.00056936376,0.00006033642,0.00016745516,0.00028551754,0.18721612,0.0076507665,0.40746716,0.07019339,0.32411394],"study_design_scores_gemma":[0.00016625736,0.00018040373,0.00032372953,0.00012646071,0.000029995947,0.00020518222,0.00012680369,0.7207825,0.004653763,0.24095447,0.032395773,0.000054656095],"about_ca_topic_score_codex":0.0014269908,"about_ca_topic_score_gemma":0.0025236907,"teacher_disagreement_score":0.036312368,"about_ca_system_score_codex":0.0016354393,"about_ca_system_score_gemma":0.0021741022,"threshold_uncertainty_score":0.12147701},"labels":[],"label_agreement":null},{"id":"W2094247434","doi":"10.1111/j.1751-486x.2011.01659.x","title":"How Old Is Sixty?","year":2011,"lang":"en","type":"article","venue":"Nursing for Women s Health","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"CancerCare Manitoba","funders":"","keywords":"Residence; Ethnic group; Immigration; Race (biology); Demographic economics; Interpersonal ties; Geography; Demography; Sociology; Psychology; Social psychology; Gender studies; Economics","score_opus":0.049384712843878416,"score_gpt":0.27607536467894517,"score_spread":0.22669065183506676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094247434","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043579075,0.02551002,0.00028549644,0.84073126,0.031085074,0.000016947326,0.00019529324,0.00003206742,0.058564756],"genre_scores_gemma":[0.48745245,0.063999,0.0005114977,0.35387444,0.01966738,0.000080302256,0.00037057276,0.0001294383,0.07391499],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99763775,0.0005768828,0.00014917045,0.00020075067,0.00061232626,0.00082312484],"domain_scores_gemma":[0.99226534,0.0009371388,0.0007672916,0.00013335474,0.0011487311,0.0047482285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036650961,0.00044491442,0.0004895278,0.0015309812,0.006563609,0.0063182972,0.00067202386,0.0032035261,0.011001673],"category_scores_gemma":[0.016393326,0.00027107165,0.00038826946,0.0011897739,0.006397756,0.009597832,0.0043887347,0.008037502,0.0033127738],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016611163,0.00019345866,0.06380697,0.0004087782,0.000046214762,0.0025379886,0.09088289,0.00004218059,0.0006073226,0.061740506,0.5566055,0.22296213],"study_design_scores_gemma":[0.000012130799,0.00009205266,0.022718836,0.0011266042,0.00003067563,0.0014726192,0.17464903,0.00002170433,0.00009870074,0.019106079,0.7806168,0.000054699147],"about_ca_topic_score_codex":0.0122079365,"about_ca_topic_score_gemma":0.021918768,"teacher_disagreement_score":0.0122079365,"about_ca_system_score_codex":0.0028135036,"about_ca_system_score_gemma":0.0062157433,"threshold_uncertainty_score":0.03680426},"labels":[],"label_agreement":null},{"id":"W2101503454","doi":"10.1002/atr.1312","title":"Optimization of bus allocation to depots by minimizing dead kilometers","year":2015,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kilometer; Metropolitan area; Public transport; Revenue; Transport engineering; Schedule; Population; Point (geometry); Computer science; Operations research; Telecommunications; Engineering; Geography; Business; Mathematics","score_opus":0.013962331729199034,"score_gpt":0.24372631470188674,"score_spread":0.2297639829726877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101503454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.62150633,0.001084639,0.33791378,0.00034066237,0.000119870005,0.0005115026,0.0011255414,0.0005047743,0.03689294],"genre_scores_gemma":[0.9616861,0.00027060756,0.031200865,0.000036237805,0.0000088760535,0.00011286358,0.00037780218,0.00005711194,0.006249594],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996425,0.00011629377,0.00001391377,0.000055007888,0.000046283047,0.000125968],"domain_scores_gemma":[0.9995944,0.0001294077,0.00009187824,0.00001973573,0.00008184604,0.00008280172],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042935743,0.0008835437,0.0008269319,0.0008730994,0.00035475785,0.0010095114,0.00079027214,0.0004254729,0.004796471],"category_scores_gemma":[0.00084877166,0.00053442025,0.00049599697,0.0008711419,0.00028912144,0.00054446387,0.00040859933,0.00049084943,0.00044308873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017311385,0.000057161084,0.0013214651,0.0001110517,0.000030886447,0.000052689396,0.000030765037,0.9824845,0.002013361,0.0018253741,0.00092548516,0.010974096],"study_design_scores_gemma":[0.000021564723,0.00020830455,0.0022898945,0.000020863446,0.000027791772,0.000031535026,0.00013543329,0.9926484,0.0016123985,0.001500496,0.0014924157,0.000010868177],"about_ca_topic_score_codex":0.010997907,"about_ca_topic_score_gemma":0.013814632,"teacher_disagreement_score":0.010997907,"about_ca_system_score_codex":0.001196469,"about_ca_system_score_gemma":0.0012966427,"threshold_uncertainty_score":0.021867812},"labels":[],"label_agreement":null},{"id":"W2103428304","doi":"10.1002/atr.5670390107","title":"Modeling the bilateral micro-searching behavior for urban taxi services using the absorbing markov chain approach","year":2005,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Croucher Foundation","keywords":"Taxis; Markov chain; Queueing theory; Computer science; Set (abstract data type); Logit; Mathematical optimization; Operations research; Markov model; Markov process; Point (geometry); Chain (unit); Transport engineering; Mathematics; Engineering; Computer network; Machine learning; Statistics","score_opus":0.018370153590569697,"score_gpt":0.2644432899934008,"score_spread":0.24607313640283107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103428304","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18607002,0.00028272142,0.80009437,0.0010066107,0.000052147996,0.000104761675,0.00043318505,0.00023682103,0.011719293],"genre_scores_gemma":[0.958062,0.0005282895,0.031302955,0.0000772488,0.000042063817,0.00018429157,0.00019995545,0.000049511516,0.009553748],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99950147,0.00017267198,0.000019727817,0.000087635766,0.000073274394,0.00014519764],"domain_scores_gemma":[0.99823534,0.0011301237,0.00031811887,0.000059462447,0.00014341025,0.000113606104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009664062,0.0005304544,0.000736056,0.0008535941,0.0007305434,0.0014964802,0.0016688553,0.0012950776,0.005654431],"category_scores_gemma":[0.0030874396,0.00063025724,0.0009502464,0.0010876852,0.0009228877,0.0022755393,0.0009073379,0.0010865736,0.0004614853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000184613,0.00004227615,0.0015183223,0.000020527417,0.00002219215,0.00011242676,0.00007413302,0.92578405,0.00037705182,0.06964032,0.00036033115,0.0020299065],"study_design_scores_gemma":[0.0000036386496,0.000005372521,0.00013515813,0.00000227894,0.0000056961303,0.000011335101,0.000015287806,0.99424523,0.00004340144,0.0053862934,0.00014237434,0.000003840787],"about_ca_topic_score_codex":0.028846549,"about_ca_topic_score_gemma":0.022655554,"teacher_disagreement_score":0.028846549,"about_ca_system_score_codex":0.00216539,"about_ca_system_score_gemma":0.0023497238,"threshold_uncertainty_score":0.05735731},"labels":[],"label_agreement":null},{"id":"W2103766950","doi":"10.1109/wi-iat.2009.193","title":"Meeting Scheduling Assembles Children in the Rectangular Forest","year":2009,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Scheduling (production processes); Engineering; Operations management","score_opus":0.00844889149613972,"score_gpt":0.22466915405720894,"score_spread":0.21622026256106922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103766950","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037554298,0.00009698865,0.94369686,0.00061640714,0.000049933,0.0001221671,0.00017806751,0.00030202986,0.017383255],"genre_scores_gemma":[0.4710047,0.00030833515,0.51692134,0.00014824873,0.000035260106,0.00019996578,0.00042944305,0.000269506,0.0106831305],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981019,0.000839501,0.0001030164,0.00039434127,0.00025997794,0.00030125547],"domain_scores_gemma":[0.9975152,0.0010699095,0.00033660448,0.00055171346,0.00025115148,0.0002754343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025712778,0.00037328035,0.0005882327,0.00040067564,0.0016880945,0.0019586,0.0016111057,0.00089885056,0.010148401],"category_scores_gemma":[0.005566627,0.00047373193,0.0008546814,0.0010623913,0.0020617808,0.0041773533,0.0023861025,0.0016135151,0.0012249984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019759443,0.00006106072,0.0021956977,0.00010068708,0.000020305344,0.00029294824,0.0009877629,0.11536716,0.0029890237,0.8353577,0.0037912219,0.038638867],"study_design_scores_gemma":[0.0000773252,0.0001827787,0.0012554885,0.00006783683,0.000038200273,0.000531608,0.002244706,0.51150197,0.005646054,0.3967119,0.081658825,0.00008324322],"about_ca_topic_score_codex":0.014145078,"about_ca_topic_score_gemma":0.01810796,"teacher_disagreement_score":0.014145078,"about_ca_system_score_codex":0.0013138321,"about_ca_system_score_gemma":0.0032691767,"threshold_uncertainty_score":0.033949792},"labels":[],"label_agreement":null},{"id":"W2104306808","doi":"10.3141/1971-17","title":"Implementation of Nationwide Public Transport Smart Card in the Netherlands: Cost-Benefit Analysis","year":2006,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministry of Transportation of Ontario","funders":"","keywords":"Public transport; Business; Smart card; Ministry of Transport; Work (physics); Government (linguistics); Competition (biology); Robustness (evolution); Cost–benefit analysis; Environmental economics; Marketing; Transport engineering; Economics; Computer science; Engineering; Computer security","score_opus":0.06832369641953971,"score_gpt":0.3731416242981651,"score_spread":0.3048179278786254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104306808","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9672866,0.0006022755,0.009803915,0.0006814237,0.000045845274,0.001857042,0.0021128273,0.00004764082,0.017562328],"genre_scores_gemma":[0.98974925,0.00045880856,0.00487081,0.000079055804,0.00000787456,0.000727288,0.0007798834,0.000012239667,0.0033146974],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9944759,0.0035555921,0.00018737206,0.00030605463,0.0005684281,0.0009065315],"domain_scores_gemma":[0.9895075,0.008207205,0.00073616207,0.00031858817,0.00096089666,0.00026962956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008982631,0.0008164603,0.0010857648,0.0009302992,0.00040472794,0.0020669538,0.0014357434,0.0016132018,0.005553813],"category_scores_gemma":[0.01879761,0.0007359683,0.0015523954,0.0018595894,0.00051411305,0.0022078278,0.0010527194,0.00096016127,0.000263606],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031356602,0.0017127628,0.014541013,0.0008087063,0.0007104552,0.00061953114,0.00018669694,0.92274547,0.000998737,0.009633304,0.0017109301,0.04319674],"study_design_scores_gemma":[0.0016084015,0.0067865285,0.041177828,0.00018676967,0.0016468295,0.00020006107,0.0016492854,0.92907786,0.0025750762,0.007014271,0.007935576,0.00014150848],"about_ca_topic_score_codex":0.0729873,"about_ca_topic_score_gemma":0.051677614,"teacher_disagreement_score":0.0729873,"about_ca_system_score_codex":0.012503527,"about_ca_system_score_gemma":0.0059030186,"threshold_uncertainty_score":0.14512497},"labels":[],"label_agreement":null},{"id":"W2113430343","doi":"10.1287/trsc.36.3.349.7830","title":"A Note on the Single Leg, Multifare Seat Allocation Problem","year":2002,"lang":"en","type":"article","venue":"Transportation Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Equivalence (formal languages); Mathematical optimization; Class (philosophy); Computer science; Operations research; Mathematics; Mathematical economics; Artificial intelligence; Discrete mathematics","score_opus":0.03694083480874411,"score_gpt":0.2434600770170304,"score_spread":0.2065192422082863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113430343","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020936161,0.0035184068,0.8682029,0.008558266,0.0016365427,0.00018373069,0.00079570874,0.00023027744,0.09593804],"genre_scores_gemma":[0.62077135,0.013688393,0.3169011,0.0040594325,0.004468673,0.0004229662,0.0009245897,0.00030203882,0.038461514],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986731,0.00049295503,0.00004967988,0.00022025485,0.00036357564,0.00020051489],"domain_scores_gemma":[0.9975545,0.0017858847,0.00020967053,0.00017757263,0.00016568661,0.00010672841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019980131,0.0015053643,0.001091215,0.00076606864,0.0011865044,0.0021674526,0.0021572453,0.0025691153,0.014841462],"category_scores_gemma":[0.0050909757,0.0005678599,0.0018018048,0.0012769562,0.0015153721,0.005072884,0.0029954966,0.0053253886,0.0014759789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014006771,0.00023008976,0.0006092846,0.0003672335,0.000065215354,0.0004108655,0.00017425226,0.19646357,0.0018789475,0.71295637,0.024804309,0.0618999],"study_design_scores_gemma":[0.00009865567,0.00033994945,0.0011532456,0.00019378151,0.00008058648,0.0003476106,0.00019077648,0.39160705,0.0011683172,0.5643448,0.04040566,0.00006948618],"about_ca_topic_score_codex":0.005605051,"about_ca_topic_score_gemma":0.0045450004,"teacher_disagreement_score":0.014841462,"about_ca_system_score_codex":0.001728152,"about_ca_system_score_gemma":0.0020684325,"threshold_uncertainty_score":0.049649656},"labels":[],"label_agreement":null},{"id":"W2115606781","doi":"10.1002/atr.1326","title":"Propensity to participate in a peer‐to‐peer social‐network‐based carpooling system","year":2015,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"Mitacs; University of Calgary","keywords":"Public transport; Mixed logit; Transport engineering; Schedule; Logit; Precinct; Travel behavior; Voucher; Sample (material); Logistic regression; Business; Engineering; Computer science; Economics; Geography; Econometrics; Statistics; Mathematics","score_opus":0.0442349330602748,"score_gpt":0.2862422712089927,"score_spread":0.2420073381487179,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115606781","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99732333,0.000021257778,0.00014352032,0.00013558277,0.0000044982785,0.00002604915,0.000046847126,0.0000062838653,0.0022927027],"genre_scores_gemma":[0.99926335,0.000016198826,0.00006461444,0.000013248018,0.000004647251,0.000008063656,0.000028514436,9.081187e-7,0.0006003191],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999047,0.00036148037,0.000051382598,0.000100001525,0.00022011888,0.00022009181],"domain_scores_gemma":[0.99654144,0.00072497356,0.0009800369,0.00022961698,0.00036924848,0.0011546854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008355157,0.00011231257,0.00012226573,0.00041323912,0.00068395847,0.00078217476,0.000497373,0.0002789127,0.011880893],"category_scores_gemma":[0.0048797526,0.00006851153,0.00021841317,0.00024823222,0.00025739364,0.00056390883,0.0009805748,0.00030947695,0.00069285755],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016743447,0.0011940364,0.92926335,0.000081625796,0.00006785279,0.00034491872,0.0032780438,0.0005503972,0.0016200179,0.0005635452,0.0016419443,0.061226897],"study_design_scores_gemma":[0.000014121837,0.0004257775,0.98335856,0.000030006298,0.000025942494,0.00024084804,0.010289383,0.0021587266,0.00036952877,0.00024204842,0.002829885,0.0000151478025],"about_ca_topic_score_codex":0.005267816,"about_ca_topic_score_gemma":0.01041854,"teacher_disagreement_score":0.011880893,"about_ca_system_score_codex":0.0004375809,"about_ca_system_score_gemma":0.00076942274,"threshold_uncertainty_score":0.03974557},"labels":[],"label_agreement":null},{"id":"W2118568602","doi":"10.3141/2143-19","title":"Impact of Carsharing on Household Vehicle Holdings","year":2010,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":465,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"San José State University; Arizona State University; California Department of Transportation; University of California, Davis; U.S. Department of Transportation","keywords":"Metropolitan area; Car ownership; Business; Car sharing; Distribution (mathematics); Population; Sample (material); Transport engineering; Geography; Agricultural economics; Public transport; Economics; Engineering; Demography","score_opus":0.09140560127732204,"score_gpt":0.3781498309417686,"score_spread":0.28674422966444657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118568602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998836,0.000041926312,0.000044250846,0.000032073567,0.0000022066947,0.0000029953972,0.00012532294,0.0000026007317,0.0009126311],"genre_scores_gemma":[0.99922764,0.000030867865,0.000042008804,0.00000966702,0.0000021954186,0.0000027478611,0.00014477989,0.0000013889088,0.0005387676],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998895,0.0003582145,0.000037144302,0.00013635759,0.00032455218,0.00024876706],"domain_scores_gemma":[0.9958572,0.0014016726,0.0010242292,0.00033052985,0.00091738225,0.00046887933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007674441,0.000187455,0.00024298324,0.0004132966,0.0005543317,0.0007478936,0.00032590123,0.00023369803,0.0032676728],"category_scores_gemma":[0.002906196,0.00012930133,0.0005197045,0.000566259,0.0005256863,0.000434377,0.0007162757,0.0003495282,0.0002588777],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012680414,0.00021821272,0.98480564,0.000015509653,0.00008490362,0.000071858456,0.0004973741,0.0007757054,0.00085563463,0.000125766,0.00025831754,0.012164203],"study_design_scores_gemma":[5.1489775e-7,0.0000923112,0.998665,0.0000024951253,0.000013698099,0.000017895221,0.0005231185,0.00017357014,0.00024201443,0.000020393045,0.00024645965,0.0000026520026],"about_ca_topic_score_codex":0.039512396,"about_ca_topic_score_gemma":0.065148674,"teacher_disagreement_score":0.039512396,"about_ca_system_score_codex":0.00081499893,"about_ca_system_score_gemma":0.00065964455,"threshold_uncertainty_score":0.07856482},"labels":[],"label_agreement":null},{"id":"W2120218454","doi":"10.1287/inte.1100.0510","title":"Approximate Dynamic Programming Captures Fleet Operations for Schneider National","year":2010,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Operations research; Fleet management; Quality (philosophy); Service (business); Dynamic programming; Computer science; Operations management; Engineering; Transport engineering; Business; Marketing","score_opus":0.012657447136643293,"score_gpt":0.2662540256432108,"score_spread":0.2535965785065675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120218454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79053307,0.00014423726,0.17094389,0.00088234525,0.000039769107,0.000116325,0.0036252723,0.00046825444,0.033246778],"genre_scores_gemma":[0.98247176,0.00007529423,0.010579255,0.000034624034,0.0000060307834,0.00006140111,0.0010215937,0.000043964414,0.0057062143],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997631,0.00005923122,0.000009424414,0.00006278729,0.000035106157,0.000070351765],"domain_scores_gemma":[0.9993104,0.00040717685,0.000074826676,0.000043030403,0.00011305108,0.000051510375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005400013,0.00060215004,0.0004478741,0.0005061667,0.00049140415,0.00095749635,0.0006932972,0.0010316471,0.0044669253],"category_scores_gemma":[0.002180769,0.0005015337,0.000540533,0.0007644705,0.00048180678,0.0012046592,0.00041180156,0.0007882437,0.00042088705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009860881,0.0000042628913,0.00036912947,0.0000024492524,0.000002070569,0.0000089959785,0.0000068050945,0.9975726,0.000042377986,0.0012209995,0.00016483507,0.00059559906],"study_design_scores_gemma":[0.000001971529,0.0000044554467,0.00018142234,0.0000010817292,0.000001226838,0.0000022386073,0.00000951413,0.99901855,0.000036183737,0.0005479473,0.00019325904,0.0000021462386],"about_ca_topic_score_codex":0.19047631,"about_ca_topic_score_gemma":0.11592915,"teacher_disagreement_score":0.19047631,"about_ca_system_score_codex":0.003500618,"about_ca_system_score_gemma":0.0022345507,"threshold_uncertainty_score":0.37873518},"labels":[],"label_agreement":null},{"id":"W2122752725","doi":"10.1287/ijoc.1030.0051","title":"Meta-Heuristics for a Class of Demand-Responsive Transit Systems","year":2005,"lang":"en","type":"article","venue":"INFORMS journal on computing","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Heuristics; Computer science; Mathematical optimization; Vehicle routing problem; Tabu search; Class (philosophy); Schedule; Set (abstract data type); Greedy algorithm; Operations research; Constructive; Routing (electronic design automation); Algorithm; Process (computing); Artificial intelligence; Mathematics","score_opus":0.040122124225718085,"score_gpt":0.26618417644949705,"score_spread":0.22606205222377895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122752725","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07792746,0.0019545201,0.90498537,0.00058931124,0.000077948105,0.00050474476,0.00036393892,0.00058889465,0.0130078355],"genre_scores_gemma":[0.64054817,0.0011595967,0.35289538,0.00021159112,0.000066869885,0.0007648545,0.000297948,0.00011526555,0.003940306],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99937207,0.00033292765,0.000026940781,0.000069412745,0.000090290465,0.00010842845],"domain_scores_gemma":[0.99865484,0.0009997453,0.00014868648,0.00006410055,0.00007652644,0.00005601293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013920433,0.0010645082,0.0009120374,0.0012556848,0.00047667758,0.0016441663,0.0013878088,0.001481508,0.0022376252],"category_scores_gemma":[0.0026842668,0.0007296942,0.0008570967,0.0012188089,0.0007380796,0.0008320224,0.00064477633,0.001195749,0.0002323463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033855136,0.000036449783,0.0001322477,0.000053671865,0.000032356405,0.0000478721,0.000037711336,0.9784228,0.00026857387,0.013346167,0.00043338683,0.0071548703],"study_design_scores_gemma":[0.000040917745,0.00004077696,0.00006830725,0.000019652947,0.000015183768,0.000019257228,0.000035817433,0.9909961,0.0002560412,0.0074351677,0.0010676251,0.000005012732],"about_ca_topic_score_codex":0.0037100383,"about_ca_topic_score_gemma":0.0041980958,"teacher_disagreement_score":0.0037100383,"about_ca_system_score_codex":0.001629028,"about_ca_system_score_gemma":0.0015201161,"threshold_uncertainty_score":0.011819482},"labels":[],"label_agreement":null},{"id":"W2123764153","doi":"","title":"U‐Haul Truck","year":2007,"lang":"en","type":"article","venue":"Journal of the Canadian Association for Curriculum Studies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Truck; Automotive engineering; Engineering","score_opus":0.014339872299232968,"score_gpt":0.260484845548991,"score_spread":0.246144973249758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123764153","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032381874,0.0002486578,0.0026715302,0.0008155123,0.00086905307,0.000119457596,0.001378063,0.00060280046,0.9609131],"genre_scores_gemma":[0.09841861,0.0003567474,0.0016268998,0.000317239,0.000055136174,0.000023347551,0.0015163723,0.00014202669,0.89754367],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996076,0.000025049003,0.000013396044,0.00007245079,0.0001358963,0.00014565328],"domain_scores_gemma":[0.9996978,0.00001461556,0.000011301055,0.000051393716,0.00014106536,0.00008375983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033877412,0.00043940794,0.00022998928,0.0012066592,0.0046235565,0.0019946918,0.00080121314,0.0007951205,0.22637837],"category_scores_gemma":[0.00050555944,0.00023036305,0.00045357275,0.00126236,0.00058277254,0.0014111942,0.0019802933,0.0008458014,0.055526767],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034026068,0.0005446858,0.010701403,0.00016964453,0.000021524567,0.00062267814,0.0014162636,0.0010372254,0.0040675625,0.043829456,0.45887443,0.4783749],"study_design_scores_gemma":[0.000009751382,0.000097200515,0.008718327,0.000046512945,0.0000065879735,0.00019781306,0.0018001846,0.00074959063,0.0014713873,0.0013943242,0.9854872,0.000021116526],"about_ca_topic_score_codex":0.040873718,"about_ca_topic_score_gemma":0.08818362,"teacher_disagreement_score":0.22637837,"about_ca_system_score_codex":0.0010345727,"about_ca_system_score_gemma":0.002630454,"threshold_uncertainty_score":0.7573111},"labels":[],"label_agreement":null},{"id":"W2123942270","doi":"10.3141/1841-09","title":"Analytical Model for Paratransit Capacity and Quality-of-Service Analysis","year":2003,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Paratransit; Transport engineering; Service (business); Service quality; Quality (philosophy); Level of service; Quality of service; Highway Capacity Manual; Range (aeronautics); Computer science; Public transport; Operations research; Engineering; Business; Telecommunications; Marketing","score_opus":0.239837348921105,"score_gpt":0.4179190296853057,"score_spread":0.1780816807642007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123942270","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043683004,0.00022582477,0.88286805,0.0010755783,0.00011342736,0.00039673265,0.0028466403,0.0015607534,0.06723011],"genre_scores_gemma":[0.8275672,0.00066282344,0.09088516,0.00021891663,0.00010462386,0.0011952682,0.0025787868,0.00037264999,0.07641446],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918836,0.00015208479,0.000027873917,0.00017964936,0.00029013836,0.00016187086],"domain_scores_gemma":[0.99887973,0.00038462266,0.00014742152,0.0000730467,0.00045772287,0.000057493035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008591957,0.0008770169,0.00066765095,0.0015779269,0.0007955218,0.0018728559,0.0029766299,0.0018421105,0.015906451],"category_scores_gemma":[0.0036443847,0.0006890932,0.0010585987,0.0022968177,0.00081713276,0.0025275047,0.00088920404,0.0015234287,0.004019753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035059922,0.00005351356,0.0010873474,0.000037876183,0.000013227659,0.00011746185,0.00007554636,0.9398393,0.0006079349,0.046958122,0.0030970757,0.008077571],"study_design_scores_gemma":[0.000009224996,0.00001619684,0.00028923614,0.000008122169,0.000009127011,0.000044895474,0.000027944481,0.98702127,0.00021252847,0.007748802,0.0046006055,0.0000119855995],"about_ca_topic_score_codex":0.02876575,"about_ca_topic_score_gemma":0.016000226,"teacher_disagreement_score":0.02876575,"about_ca_system_score_codex":0.0038228636,"about_ca_system_score_gemma":0.0037049798,"threshold_uncertainty_score":0.057196617},"labels":[],"label_agreement":null},{"id":"W2124597594","doi":"10.3141/1857-06","title":"Real-Time Optimization Model for Dynamic Scheduling of Transit Operations","year":2003,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":203,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Scheduling (production processes); Integer programming; Mathematical optimization; Sensitivity (control systems); Computer science; Nonlinear programming; Operations research; Operating cost; Service (business); Nonlinear system; Engineering; Transport engineering; Mathematics","score_opus":0.06180209070748106,"score_gpt":0.3586298005015366,"score_spread":0.29682770979405554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124597594","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029419713,0.0012073669,0.938466,0.0013274567,0.00046871183,0.00022175396,0.0015667777,0.0006923407,0.026629841],"genre_scores_gemma":[0.8808888,0.0016305,0.06417775,0.00031889466,0.0002104442,0.0010797629,0.0016423818,0.0002031373,0.04984826],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99881846,0.00040128725,0.000049586517,0.00024304187,0.00023939641,0.00024825294],"domain_scores_gemma":[0.9985638,0.00083564426,0.00022376077,0.000046265126,0.0002155384,0.00011495655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001634143,0.0020613433,0.0019449458,0.0007339095,0.00062053435,0.0024980523,0.0026168919,0.0030537348,0.010543104],"category_scores_gemma":[0.003362382,0.00095978443,0.0009848262,0.0014162381,0.0011560423,0.0016102178,0.0010023925,0.0028773644,0.0018861558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003478238,0.00001952872,0.00007525924,0.0000351134,0.000014600359,0.000056924277,0.000018594192,0.9877201,0.00020309398,0.009893778,0.00055101543,0.001377253],"study_design_scores_gemma":[0.000014877026,0.000014776675,0.00004505456,0.0000029213973,0.0000051837383,0.000006782283,0.0000072003468,0.9971334,0.000040807645,0.0020046548,0.0007199489,0.0000044097355],"about_ca_topic_score_codex":0.017995177,"about_ca_topic_score_gemma":0.010363925,"teacher_disagreement_score":0.017995177,"about_ca_system_score_codex":0.0024483697,"about_ca_system_score_gemma":0.0023700432,"threshold_uncertainty_score":0.035780847},"labels":[],"label_agreement":null},{"id":"W2125789238","doi":"10.1002/atr.5670360203","title":"Express guideway transit: A case for further development in transit automation","year":2002,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"PricewaterhouseCoopers (Canada)","funders":"","keywords":"Transit (satellite); Train; Doors; Propulsion; Schedule; Automotive engineering; Dwell time; Decoupling (probability); Engineering; Transit system; Transport engineering; Automation; Computer science; Simulation; Public transport; Control engineering; Aerospace engineering","score_opus":0.017484412194747372,"score_gpt":0.2434063754895672,"score_spread":0.22592196329481984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125789238","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27220157,0.004153272,0.047672402,0.23639432,0.0013384429,0.0006705826,0.00018804622,0.0008067514,0.4365746],"genre_scores_gemma":[0.90601784,0.00190412,0.01991631,0.0047212574,0.00022248202,0.00019467805,0.00011265253,0.000051575647,0.066859044],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977678,0.0008728504,0.00008466619,0.00014897478,0.0005272359,0.00059837406],"domain_scores_gemma":[0.9955531,0.0008802493,0.00024621497,0.00047821685,0.0017118404,0.0011303546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030964524,0.00028196632,0.0001696605,0.00051635224,0.0015354047,0.0033798956,0.0010011061,0.0046267896,0.0076882658],"category_scores_gemma":[0.0049849083,0.000113354516,0.00033933463,0.00053092104,0.0020693925,0.0027548412,0.0015519033,0.0019629044,0.0014054712],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003817285,0.0006188551,0.01536977,0.00040877695,0.00001534813,0.026115576,0.0041762283,0.005601417,0.0038249032,0.61788833,0.0656992,0.25989982],"study_design_scores_gemma":[0.00014853892,0.00081355014,0.005667511,0.00038897328,0.000030748713,0.013295478,0.0074826633,0.016042983,0.003414848,0.041587878,0.9110614,0.00006538945],"about_ca_topic_score_codex":0.0062540486,"about_ca_topic_score_gemma":0.005216618,"teacher_disagreement_score":0.0076882658,"about_ca_system_score_codex":0.0014418983,"about_ca_system_score_gemma":0.0054408074,"threshold_uncertainty_score":0.025719762},"labels":[],"label_agreement":null},{"id":"W2134962356","doi":"10.3141/1884-05","title":"Fleet Size and Mix Optimization for Paratransit Services","year":2004,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Paratransit; Service (business); Fleet management; Transport engineering; Process (computing); Heuristic; Computer science; Operations research; Engineering; Business; Public transport; Marketing","score_opus":0.04961655695488381,"score_gpt":0.34668852990415994,"score_spread":0.2970719729492761,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134962356","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3274916,0.00065078016,0.6439031,0.0006288898,0.000056885994,0.00041755146,0.0006989657,0.0005565967,0.025595611],"genre_scores_gemma":[0.88577276,0.0003474602,0.10057781,0.000075044176,0.000020402264,0.0003018401,0.00048598746,0.00018567484,0.012233044],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999665,0.00011171952,0.000009442769,0.000058284746,0.00007065292,0.00008487679],"domain_scores_gemma":[0.9995054,0.00026166305,0.000066945344,0.000022112701,0.00006361572,0.00008019486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006126822,0.0008964485,0.00060303736,0.001474621,0.0005632347,0.0009748557,0.0010669389,0.00079553545,0.005888411],"category_scores_gemma":[0.0018546317,0.00070823904,0.0006147868,0.0011670692,0.0004682772,0.001567111,0.0008764756,0.00077090634,0.0004772871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054582928,0.000033221626,0.00054461934,0.000023017283,0.000013397927,0.000046469104,0.000024533265,0.9795496,0.001010673,0.0039054072,0.00053524773,0.014259287],"study_design_scores_gemma":[0.000009901069,0.000056192323,0.0005073173,0.000006305969,0.000008253882,0.000023495726,0.000046925063,0.99301827,0.0003686571,0.0051111826,0.0008363945,0.0000071773025],"about_ca_topic_score_codex":0.010577577,"about_ca_topic_score_gemma":0.01599889,"teacher_disagreement_score":0.010577577,"about_ca_system_score_codex":0.0021378002,"about_ca_system_score_gemma":0.0010442566,"threshold_uncertainty_score":0.021032035},"labels":[],"label_agreement":null},{"id":"W2135846965","doi":"10.1109/iccw.2009.5208115","title":"An Auction Mechanism for Channel Access in Vehicle-to-Roadside Communications","year":2009,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Bandwidth (computing); Bandwidth allocation; The Internet; Computer network; Channel allocation schemes; Game theory; Combinatorial auction; Internet access; Auction algorithm; Mathematical optimization; Distributed computing; Auction theory; Telecommunications; Common value auction; Wireless; Mathematical economics; Microeconomics; Mathematics; Revenue equivalence","score_opus":0.044070731838767474,"score_gpt":0.3296599672887007,"score_spread":0.2855892354499332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135846965","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042455878,0.000563851,0.9433705,0.0003447038,0.00014441008,0.00034170962,0.00011232197,0.00031853205,0.012348032],"genre_scores_gemma":[0.8977765,0.0003725167,0.093775354,0.000092937255,0.00008514741,0.00029585778,0.00006605447,0.00004793216,0.0074876794],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971955,0.001491593,0.00011611724,0.0002467656,0.00045817884,0.0004919061],"domain_scores_gemma":[0.99707556,0.0017286475,0.0002890305,0.00023823437,0.00040405398,0.0002645404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035568702,0.00078063074,0.0018112028,0.0009260221,0.0011023312,0.002529577,0.0031658255,0.0016073388,0.004483002],"category_scores_gemma":[0.0055610337,0.00056831934,0.0009464221,0.001341031,0.0016358964,0.0034488053,0.001623351,0.0011588549,0.00058326375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007027358,0.00048682914,0.00065138005,0.00036443514,0.00018396197,0.00083302654,0.00036222138,0.56120175,0.006430982,0.37077415,0.005647683,0.05236081],"study_design_scores_gemma":[0.00025249278,0.00019127529,0.00014987763,0.000023289791,0.000042725387,0.0002767553,0.00006339642,0.9238081,0.0008497367,0.07052997,0.0037622734,0.000050032086],"about_ca_topic_score_codex":0.002749334,"about_ca_topic_score_gemma":0.0021620297,"teacher_disagreement_score":0.004483002,"about_ca_system_score_codex":0.001759994,"about_ca_system_score_gemma":0.0024713427,"threshold_uncertainty_score":0.018810809},"labels":[],"label_agreement":null},{"id":"W2137457389","doi":"10.3141/1986-17","title":"Carsharing in North America: Market Growth, Current Developments, and Future Potential","year":2006,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Popularity; Metropolitan area; Business; Market share; Car ownership; Geography; Public transport; Economic growth; Marketing; Transport engineering; Political science; Economics; Engineering","score_opus":0.029445531585583787,"score_gpt":0.3056369949195756,"score_spread":0.2761914633339918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137457389","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6020778,0.09970186,0.0007800315,0.11218791,0.001029947,0.00005450924,0.002102878,0.00026119585,0.18180384],"genre_scores_gemma":[0.91215193,0.055411626,0.0010558934,0.002721427,0.00057157176,0.00003073943,0.0014585063,0.000023433033,0.02657485],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99962366,0.000034289515,0.000012083378,0.00004249895,0.00013077905,0.00015672909],"domain_scores_gemma":[0.9976714,0.0003934627,0.00030808846,0.000034952085,0.00088892045,0.0007031819],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072475564,0.00019940488,0.00014109981,0.0010495356,0.0010836016,0.0034729159,0.000752271,0.00095770176,0.0105185695],"category_scores_gemma":[0.001066127,0.00008360463,0.00016157138,0.0028294055,0.0007361963,0.003269057,0.0005829289,0.00085488183,0.00080853264],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026455722,0.00070600084,0.12451754,0.000872522,0.000024068531,0.00092324085,0.004972749,0.0005563757,0.0027147552,0.02355878,0.15023585,0.69065344],"study_design_scores_gemma":[0.000026331467,0.00037499247,0.4539967,0.0005749794,0.000029854367,0.00083011616,0.04190225,0.0015846164,0.0016929862,0.0044532986,0.49447283,0.000060984858],"about_ca_topic_score_codex":0.076079786,"about_ca_topic_score_gemma":0.18458627,"teacher_disagreement_score":0.076079786,"about_ca_system_score_codex":0.0038173033,"about_ca_system_score_gemma":0.004798686,"threshold_uncertainty_score":0.1512739},"labels":[],"label_agreement":null},{"id":"W2141125834","doi":"10.1002/atr.5670340207","title":"Optimal scheduling of public transport fleet at network level","year":2000,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Scheduling (production processes); Public transport; Operator (biology); TRIPS architecture; Computer science; Operations research; Mathematical optimization; Dynamic programming; Routing (electronic design automation); Service (business); Vehicle routing problem; Fleet management; Transport engineering; Engineering; Computer network; Telecommunications; Mathematics; Economics","score_opus":0.022614286778985783,"score_gpt":0.24560400602730176,"score_spread":0.22298971924831598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141125834","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47066188,0.0002729816,0.49727073,0.00053734146,0.000086190994,0.0001985492,0.00031928832,0.00058993156,0.03006313],"genre_scores_gemma":[0.97441375,0.000065187545,0.021845477,0.000016581775,0.000013051852,0.000046288635,0.000094740004,0.000042037333,0.0034629132],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99963844,0.000120161996,0.000008501228,0.00005201925,0.000043668377,0.00013732174],"domain_scores_gemma":[0.99955755,0.00017753054,0.00007122025,0.00002717326,0.00007509649,0.00009137844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061491923,0.00053275336,0.00065319927,0.00043680109,0.0005295658,0.0010718013,0.0006978572,0.00058707024,0.004338174],"category_scores_gemma":[0.0011963795,0.00036976355,0.0003063222,0.00054421974,0.0005376442,0.00068613776,0.0004602754,0.0004825201,0.0003360608],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007982868,0.000024250345,0.00022282325,0.000017101802,0.0000075198755,0.000030099845,0.000018925348,0.9889053,0.0009126443,0.004620469,0.00044320157,0.004717809],"study_design_scores_gemma":[0.0000088022025,0.000025474803,0.00012621561,0.0000017357345,0.0000032121598,0.000003593138,0.000021579564,0.9973002,0.00029700313,0.0018766988,0.00033308836,0.0000023744255],"about_ca_topic_score_codex":0.021916913,"about_ca_topic_score_gemma":0.014860989,"teacher_disagreement_score":0.021916913,"about_ca_system_score_codex":0.002619001,"about_ca_system_score_gemma":0.0022355183,"threshold_uncertainty_score":0.043578684},"labels":[],"label_agreement":null},{"id":"W2141823663","doi":"","title":"Page d'accueil | Infrastructure et Transports Manitoba | Province du Manitoba","year":2008,"lang":"fr","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Geography; Political science; Regional science","score_opus":0.012515251928823936,"score_gpt":0.20128103073356715,"score_spread":0.1887657788047432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141823663","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047397744,0.04575981,0.0026717298,0.18579821,0.06731178,0.00095431134,0.05141136,0.0017421584,0.59695286],"genre_scores_gemma":[0.034329165,0.009963548,0.001024194,0.009931961,0.0013684026,0.00018499368,0.004243879,0.0002522567,0.93870145],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99931514,0.00009099134,0.000040182982,0.00008925346,0.00025991572,0.00020448993],"domain_scores_gemma":[0.9975261,0.00045717214,0.000098312805,0.00013330154,0.0013008411,0.00048430756],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00081348827,0.0005276964,0.000499115,0.0011731689,0.004079438,0.0027058148,0.0011503614,0.002609789,0.15268402],"category_scores_gemma":[0.0026699454,0.0005633563,0.00039763685,0.0018737315,0.000726768,0.00083783607,0.0012611492,0.0023105643,0.017338676],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008057359,0.00005493798,0.010233985,0.0005422892,0.000018394303,0.00055734016,0.0007548752,0.00014593055,0.0008960583,0.0057266867,0.9416596,0.03932922],"study_design_scores_gemma":[0.00001991531,0.000011477373,0.017360896,0.00013045584,0.0000067765727,0.00007118017,0.00043344637,0.000069942296,0.0002432112,0.000085053834,0.98155516,0.000012502944],"about_ca_topic_score_codex":0.8396931,"about_ca_topic_score_gemma":0.919932,"teacher_disagreement_score":0.84731597,"about_ca_system_score_codex":0.006801631,"about_ca_system_score_gemma":0.031684797,"threshold_uncertainty_score":0.5107789},"labels":[],"label_agreement":null},{"id":"W2141939759","doi":"10.1007/s11116-012-9400-2","title":"Professional workers @ work: importance of work activities for electronic and face-to-face communications in the Netherlands","year":2012,"lang":"en","type":"article","venue":"Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Work (physics); Face (sociological concept); Sample (material); Face-to-face; Information and Communications Technology; Electronic communication; Public relations; Business; Telecommunications; Sociology; Computer science; Engineering; Geography; Political science; World Wide Web; Social science","score_opus":0.02425510950941453,"score_gpt":0.28647577230364174,"score_spread":0.26222066279422723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141939759","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99696726,0.0005538228,0.0000848922,0.00018927177,0.000008815854,0.000009678491,0.00014552189,0.0000018245867,0.0020389901],"genre_scores_gemma":[0.9987803,0.00026109966,0.000073399875,0.000015473503,0.0000036992187,0.000006999315,0.00009563914,0.000004334921,0.00075904565],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99842787,0.0004924759,0.00014552927,0.00021617186,0.00040952672,0.00030844467],"domain_scores_gemma":[0.9976211,0.0006993232,0.0008089338,0.00008769232,0.0003277149,0.00045518024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009877783,0.00015547052,0.0002905847,0.0008822083,0.00057044404,0.0019630566,0.00052659225,0.00045841033,0.0022265564],"category_scores_gemma":[0.006018165,0.00026634353,0.0001862485,0.0013805769,0.000513229,0.0010001237,0.0014854607,0.00032544206,0.0002391536],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019419446,0.0001338729,0.8353094,0.00022704781,0.000074533236,0.0009117614,0.074765325,0.00043628697,0.001174013,0.0008373778,0.0025801356,0.083356075],"study_design_scores_gemma":[0.000005990911,0.000044248187,0.94197494,0.0000802017,0.000012261373,0.00027269058,0.052608825,0.0004053157,0.00009066107,0.00013824586,0.0043446925,0.000021822083],"about_ca_topic_score_codex":0.107345715,"about_ca_topic_score_gemma":0.1581662,"teacher_disagreement_score":0.107345715,"about_ca_system_score_codex":0.0015431157,"about_ca_system_score_gemma":0.001520769,"threshold_uncertainty_score":0.21344173},"labels":[],"label_agreement":null},{"id":"W2142232457","doi":"10.1007/s10479-010-0710-5","title":"Designing the master schedule for demand-adaptive transit systems","year":2010,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; HEC Montréal","funders":"Regione Lombardia; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Reservation; Computer science; Schedule; Operations research; Line (geometry); Theory of computation; Bus rapid transit; Set (abstract data type); Process (computing); Focus (optics); Real-time computing; Transport engineering; Public transport; Computer network; Engineering; Algorithm; Operating system","score_opus":0.2757419418382559,"score_gpt":0.41072793840617094,"score_spread":0.13498599656791505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142232457","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09060372,0.000070396825,0.90402025,0.00025438276,0.000043628177,0.0002945721,0.00018288792,0.00039395416,0.0041362005],"genre_scores_gemma":[0.80231977,0.00012444667,0.19274384,0.00005457883,0.000046636535,0.00029200365,0.0003177266,0.00019359565,0.003907316],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993812,0.00022319512,0.00003614268,0.00013550333,0.000101401594,0.00012258154],"domain_scores_gemma":[0.9984085,0.00094160443,0.00016495919,0.00011550435,0.00022698985,0.00014249669],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016115308,0.00074658124,0.0010072485,0.0007182231,0.00079973025,0.0011176404,0.0011993113,0.00078727497,0.0067540975],"category_scores_gemma":[0.0049973363,0.00090912095,0.0005795504,0.00053745386,0.0006204625,0.0013782589,0.0010487495,0.0011507927,0.00054307043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017945534,0.000053884112,0.00055791787,0.00008064831,0.00002082279,0.000045398992,0.00017253558,0.95444375,0.0033757496,0.012966996,0.0012865594,0.026816223],"study_design_scores_gemma":[0.000019403082,0.000055933848,0.0000901802,0.0000043298423,0.000006382125,0.000005820675,0.000045657143,0.9949071,0.00066521286,0.003633671,0.00056191714,0.000004494824],"about_ca_topic_score_codex":0.0063085537,"about_ca_topic_score_gemma":0.0074916813,"teacher_disagreement_score":0.0067540975,"about_ca_system_score_codex":0.0013385409,"about_ca_system_score_gemma":0.00271485,"threshold_uncertainty_score":0.02259469},"labels":[],"label_agreement":null},{"id":"W2148163198","doi":"10.3141/2110-05","title":"North American Carsharing","year":2009,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":191,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diversification (marketing strategy); Market share; Business; Consolidation (business); Competition (biology); Investment (military); Finance; Marketing; Political science; Politics","score_opus":0.06942661487261073,"score_gpt":0.3624803039621143,"score_spread":0.2930536890895036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148163198","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15918201,0.0045332056,0.002237634,0.0024264408,0.0007912851,0.00024343781,0.024021097,0.0012968642,0.805268],"genre_scores_gemma":[0.26081842,0.006970627,0.0039494173,0.0018829624,0.00028503014,0.00035650365,0.04268756,0.00045018605,0.6825993],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9994004,0.000029041741,0.000018533789,0.00012984386,0.00028340178,0.00013877904],"domain_scores_gemma":[0.99866986,0.00007041289,0.000092247756,0.000108848464,0.0008702336,0.00018830947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036893346,0.00043365985,0.00015580101,0.0019352131,0.0025132871,0.001534438,0.0006203821,0.00034142553,0.068441935],"category_scores_gemma":[0.000722638,0.00024426775,0.00023864704,0.0031312436,0.00026243518,0.0010378294,0.000918587,0.00056505424,0.019892763],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020359436,0.00025935736,0.044076752,0.00023275608,0.000023400591,0.00031755952,0.0012423245,0.00021119362,0.0016536587,0.0073475544,0.66125035,0.2831815],"study_design_scores_gemma":[0.0000064811957,0.00003228124,0.05052154,0.000059492177,0.000010989279,0.00029354825,0.0010443853,0.00013683195,0.00070248265,0.00023443402,0.9469437,0.00001375789],"about_ca_topic_score_codex":0.083046444,"about_ca_topic_score_gemma":0.18599814,"teacher_disagreement_score":0.91695356,"about_ca_system_score_codex":0.0016560056,"about_ca_system_score_gemma":0.0031781755,"threshold_uncertainty_score":0.22896105},"labels":[],"label_agreement":null},{"id":"W2150512128","doi":"","title":"A Comparison of Car Sharing Organizational Models: An Analysis of Feasible Efficiency Increase through a Centralized Model 1","year":2012,"lang":"en","type":"article","venue":"Review of Economics and Finance","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Scope (computer science); Work (physics); Service (business); Phase (matter); Organizational structure; Public transport; Industrial organization; Business; Computer science; Operations research; Economics; Marketing; Transport engineering; Engineering","score_opus":0.05185228145456477,"score_gpt":0.2958691518185344,"score_spread":0.24401687036396963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150512128","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42981115,0.0017236457,0.43933234,0.0010636552,0.000095840274,0.0003302665,0.00030217375,0.00019356086,0.1271474],"genre_scores_gemma":[0.9696007,0.0006052293,0.023000082,0.000044139186,0.000026956484,0.00019224545,0.00012259494,0.0000615052,0.006346682],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9976307,0.0012790866,0.00007381745,0.00024413237,0.00040457438,0.00036758083],"domain_scores_gemma":[0.99423283,0.0036491703,0.00051071856,0.0007337359,0.0005635331,0.00030995146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034423347,0.0007758814,0.00094567135,0.0012247949,0.00084316364,0.0036261843,0.0019082305,0.0014660235,0.009230705],"category_scores_gemma":[0.0076683783,0.00037903915,0.0015338011,0.0012809297,0.0018435383,0.0029083178,0.002107307,0.0010507281,0.00075360056],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016479827,0.0001777851,0.0018680183,0.00017682415,0.000069922,0.0001029975,0.0004063344,0.522207,0.00063698506,0.45373765,0.00095083076,0.019500818],"study_design_scores_gemma":[0.00004512312,0.00034069284,0.0016373604,0.0000986791,0.00009118321,0.00006988966,0.00078037666,0.8882057,0.00049382297,0.1038446,0.004358631,0.000033979286],"about_ca_topic_score_codex":0.003923593,"about_ca_topic_score_gemma":0.0020643922,"teacher_disagreement_score":0.009230705,"about_ca_system_score_codex":0.0038457282,"about_ca_system_score_gemma":0.001817079,"threshold_uncertainty_score":0.030879796},"labels":[],"label_agreement":null},{"id":"W2160422981","doi":"10.1145/1502650.1502700","title":"A bayesian reinforcement learning approach for customizing human-robot interfaces","year":2009,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Reinforcement learning; Computer science; Personalization; Artificial intelligence; Machine learning; Robot; Probabilistic logic; Human–computer interaction; Robot learning; Interface (matter); Wheelchair; Action (physics); Bayesian network; Mobile robot","score_opus":0.021943929036839456,"score_gpt":0.2638350436960582,"score_spread":0.24189111465921875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160422981","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003539775,0.00004561701,0.9951717,0.00008995995,0.000010217463,0.00003317759,0.000006197659,0.00020230336,0.000901084],"genre_scores_gemma":[0.5705674,0.00017377066,0.42534417,0.00016993753,0.000050539773,0.0003192117,0.000043055945,0.00011685351,0.0032150382],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99864596,0.0005814551,0.00006196842,0.00022214021,0.00039377715,0.00009458],"domain_scores_gemma":[0.99720335,0.0017226733,0.00029590086,0.0002387792,0.0003884265,0.00015098802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027210913,0.0009444076,0.0009602394,0.0005390381,0.0004852201,0.00081614597,0.0021124592,0.0013004031,0.002279209],"category_scores_gemma":[0.008857957,0.0007064662,0.00054563873,0.00035143676,0.0013521288,0.0014463858,0.0014569287,0.0016074177,0.00041775164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008867069,0.00015004013,0.00057773927,0.00006182885,0.000045376535,0.00006780598,0.00013855827,0.91637796,0.0030730518,0.01686181,0.0007652378,0.061791904],"study_design_scores_gemma":[0.000013639452,0.000025862382,0.00006195625,0.0000036981146,0.000005432679,0.000011322481,0.000004180047,0.99362624,0.00044172278,0.0054515996,0.0003467659,0.0000075586577],"about_ca_topic_score_codex":0.004713197,"about_ca_topic_score_gemma":0.0047716433,"teacher_disagreement_score":0.004713197,"about_ca_system_score_codex":0.0011861981,"about_ca_system_score_gemma":0.0013372004,"threshold_uncertainty_score":0.014390647},"labels":[],"label_agreement":null},{"id":"W2163360082","doi":"10.12927/hcq.2009.20746","title":"Commentary: Waiting for the Referee or Refereeing the Wait? - CCO's Role in Hosting and Deploying the Wait Time Information System in Ontario","year":2009,"lang":"en","type":"article","venue":"Healthcare Quarterly","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Cancer Care Ontario","funders":"","keywords":"Best practice; Psychology; Medicine; Nursing; Public relations; Political science; Law","score_opus":0.020030902459210752,"score_gpt":0.2404456204779487,"score_spread":0.22041471801873797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163360082","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00023435001,0.0007042999,0.00003741074,0.9732711,0.024674213,0.0000149361285,0.00006758368,0.000011490009,0.0009846853],"genre_scores_gemma":[0.0035474363,0.00091950025,0.00009344929,0.96625316,0.023320135,0.00005913428,0.000027357017,0.000033572454,0.0057462743],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.98271537,0.0036588302,0.0025393693,0.0021376316,0.005519316,0.0034294375],"domain_scores_gemma":[0.8873492,0.05916154,0.0060960846,0.0015953201,0.033546392,0.012251362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015620829,0.0010770146,0.0019200669,0.0017874849,0.017952267,0.009086509,0.008767535,0.101620264,0.014495948],"category_scores_gemma":[0.11674201,0.0019544268,0.0024127718,0.0030482665,0.009403159,0.006827433,0.004195971,0.08116897,0.004114366],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024079434,0.0000065286017,0.0002070282,0.0001288489,0.000012796836,0.00019813296,0.00079135934,0.000027454218,0.000039077477,0.001472869,0.9959352,0.0011566008],"study_design_scores_gemma":[0.00017521139,0.000043885888,0.0026148818,0.0013864017,0.0001642177,0.00047189154,0.0066855256,0.00024873627,0.00018714245,0.0030404725,0.98479384,0.00018778838],"about_ca_topic_score_codex":0.6675482,"about_ca_topic_score_gemma":0.7351191,"teacher_disagreement_score":0.95333683,"about_ca_system_score_codex":0.046663176,"about_ca_system_score_gemma":0.11745989,"threshold_uncertainty_score":0.66881937},"labels":[],"label_agreement":null},{"id":"W2163671928","doi":"10.1177/0894439310370084","title":"Highlights of Contemporary Microsimulation","year":2010,"lang":"en","type":"article","venue":"Social Science Computer Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Statistics Canada","funders":"","keywords":"Microsimulation; Macro; Field (mathematics); Macro level; Economics; Regional science; Computer science; Public economics; Operations research; Econometrics; Sociology; Transport engineering; Macroeconomics; Engineering","score_opus":0.020014327063401824,"score_gpt":0.28457177726460536,"score_spread":0.2645574502012035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163671928","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009594132,0.4730938,0.2480865,0.13743004,0.006892499,0.00007693899,0.0003547144,0.00043492694,0.12403639],"genre_scores_gemma":[0.36626586,0.5200466,0.0508005,0.016110474,0.019984998,0.00050390407,0.00038267625,0.00052842294,0.025376545],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967429,0.0015564625,0.00014212824,0.00039510443,0.0010066198,0.00015684732],"domain_scores_gemma":[0.98625284,0.010638145,0.00039186035,0.0010005842,0.0014686211,0.00024799356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0070026484,0.0008133608,0.0010605125,0.0017329141,0.00093184813,0.003844746,0.0021249864,0.0023135012,0.0066015064],"category_scores_gemma":[0.020403206,0.0004906008,0.0011966759,0.0022841904,0.004153695,0.0069568977,0.0027824845,0.0052204328,0.0018053158],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028160835,0.00002658047,0.00032034997,0.00048467517,0.000044710214,0.00004706213,0.00014822371,0.016677395,0.00009963519,0.90676075,0.016571498,0.058790933],"study_design_scores_gemma":[0.000013172734,0.000049124355,0.0002849086,0.00039487757,0.000021356633,0.00009760186,0.00017202279,0.027497716,0.00031683978,0.7440903,0.22702876,0.000033297038],"about_ca_topic_score_codex":0.0027164435,"about_ca_topic_score_gemma":0.0013286816,"teacher_disagreement_score":0.0070026484,"about_ca_system_score_codex":0.003838505,"about_ca_system_score_gemma":0.0023112998,"threshold_uncertainty_score":0.037033975},"labels":[],"label_agreement":null},{"id":"W2163968342","doi":"10.3141/1702-04","title":"Evaluating Carsharing Benefits","year":2000,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":161,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Business; Incentive; Car ownership; Renting; Service (business); Transport engineering; Public transport; Marketing; Economics; Engineering; Microeconomics","score_opus":0.1730024503169041,"score_gpt":0.41889597468407763,"score_spread":0.24589352436717354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163968342","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95220804,0.0034241942,0.0016341916,0.00068506616,0.00011844972,0.0008988851,0.0036361874,0.000056753932,0.037338264],"genre_scores_gemma":[0.994487,0.0006722797,0.0011686536,0.00006933836,0.00003432485,0.00019508186,0.0011991631,0.000010477485,0.0021635266],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9967602,0.0012730961,0.00020686582,0.00017833644,0.001226389,0.00035511385],"domain_scores_gemma":[0.9799675,0.011858883,0.0019944666,0.0005314303,0.0037078066,0.0019399264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045075733,0.00054279563,0.000611215,0.0020982628,0.00057893316,0.0015035479,0.0006032202,0.0010038657,0.016558666],"category_scores_gemma":[0.022518782,0.0001251913,0.0012704337,0.0015373542,0.00045551104,0.001671998,0.000745971,0.0007358298,0.0013656951],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.021181002,0.010524756,0.41355652,0.0016736168,0.0017102201,0.00036523872,0.0006940393,0.01940818,0.002289216,0.007405497,0.010060805,0.5111309],"study_design_scores_gemma":[0.0013516038,0.041922837,0.87250555,0.00067445176,0.0030825352,0.00052955694,0.004881153,0.020203218,0.008149741,0.008365713,0.038104,0.0002296611],"about_ca_topic_score_codex":0.004052648,"about_ca_topic_score_gemma":0.0069168066,"teacher_disagreement_score":0.016558666,"about_ca_system_score_codex":0.0021894982,"about_ca_system_score_gemma":0.0013103642,"threshold_uncertainty_score":0.055394292},"labels":[],"label_agreement":null},{"id":"W2164966922","doi":"10.1002/atr.1300","title":"A traffic assignment model for a ridesharing transportation market","year":2014,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":83,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Federal Highway Administration","keywords":"Traffic congestion; Congestion pricing; Incentive; Transport engineering; Work (physics); Price elasticity of demand; Computer science; Economics; Microeconomics; Engineering","score_opus":0.011276424793424002,"score_gpt":0.2353125169574056,"score_spread":0.2240360921639816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164966922","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2611805,0.00077402225,0.61933076,0.0030884529,0.00026147856,0.00041515846,0.0020003978,0.00044876875,0.11250043],"genre_scores_gemma":[0.91172427,0.0005976667,0.025698526,0.00026189242,0.00009035271,0.00038134604,0.00064434594,0.00008945427,0.060512263],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99950445,0.0001810514,0.000014470091,0.00010495774,0.000060525366,0.00013459924],"domain_scores_gemma":[0.9992812,0.00032457703,0.00009790302,0.000027080208,0.0001545665,0.00011460135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009213841,0.00094414625,0.0013930425,0.0009755461,0.000984421,0.0028212415,0.0025679034,0.003027347,0.021967685],"category_scores_gemma":[0.002344796,0.00060495007,0.0013126164,0.001216176,0.0010624683,0.0021775248,0.0013540004,0.0018427251,0.0017823211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059851445,0.00008391608,0.00035662207,0.000041733423,0.000013610555,0.00015770711,0.000056921417,0.91774726,0.0004939695,0.07637101,0.0019406872,0.002676716],"study_design_scores_gemma":[0.000013215155,0.000012240193,0.000059495964,0.0000037425266,0.0000047774147,0.000010728517,0.000027324162,0.9917354,0.000022407134,0.007478147,0.00062670204,0.000005847642],"about_ca_topic_score_codex":0.02730175,"about_ca_topic_score_gemma":0.013257267,"teacher_disagreement_score":0.02730175,"about_ca_system_score_codex":0.002656577,"about_ca_system_score_gemma":0.0017661098,"threshold_uncertainty_score":0.07348919},"labels":[],"label_agreement":null},{"id":"W2166031785","doi":"10.1002/atr.5670340103","title":"A review of the state of the art of personal rapid transit","year":2000,"lang":"en","type":"review","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Dependability; Transit (satellite); Reliability (semiconductor); Process (computing); Listing (finance); State (computer science); Computer science; Automotive engineering; Transport engineering; Reliability engineering; Control (management); Power (physics); Operations research; Engineering; Public transport; Business","score_opus":0.01679743452310015,"score_gpt":0.2711167707627472,"score_spread":0.25431933623964703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166031785","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015339757,0.99713826,0.00019545986,0.00037249687,0.00021884099,0.0000044284056,0.000015597103,0.0000051888037,0.0018964512],"genre_scores_gemma":[0.0011604541,0.9976803,0.00022007537,0.00014974437,0.00020614531,0.000004415008,0.00001726162,0.0000015871898,0.00055999245],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99924964,0.00014374255,0.00009932695,0.00013271124,0.00033085782,0.00004367217],"domain_scores_gemma":[0.9982967,0.0009322556,0.000183749,0.000043215667,0.00048289038,0.00006122201],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012225226,0.0007146172,0.0014163717,0.0036775165,0.0004547921,0.0017395167,0.0010184369,0.0013698975,0.0057717795],"category_scores_gemma":[0.0023561788,0.00045583158,0.00047281745,0.005546923,0.0006313256,0.002329311,0.0005342799,0.0011664974,0.0024005189],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005334455,0.00006605491,0.0003141156,0.020289224,0.0000433402,0.00024563778,0.000111897585,0.0008272766,0.0009303419,0.010408089,0.033543758,0.9331669],"study_design_scores_gemma":[0.0000039973506,0.00007368226,0.0008522177,0.004789706,0.000029963123,0.0007099112,0.00009432529,0.00012475424,0.00029065736,0.001410577,0.9916045,0.000015843032],"about_ca_topic_score_codex":0.0041974,"about_ca_topic_score_gemma":0.0049042213,"teacher_disagreement_score":0.0057717795,"about_ca_system_score_codex":0.0012628741,"about_ca_system_score_gemma":0.0020058402,"threshold_uncertainty_score":0.019308567},"labels":[],"label_agreement":null},{"id":"W2166540481","doi":"10.1007/s11116-010-9266-0","title":"Catching a ride on the information super-highway: toward an understanding of internet-based carpool formation and use","year":2010,"lang":"en","type":"article","venue":"Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":87,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Carpool; Transport engineering; Telecommuting; Traffic congestion; Odds; Internet access; Journey to work; The Internet; Business; Engineering; Work (physics); Public transport; Computer science; Logistic regression","score_opus":0.03575358902472999,"score_gpt":0.2273664692633347,"score_spread":0.1916128802386047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166540481","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.61906797,0.0010265524,0.046007972,0.007125795,0.000058265734,0.000077467885,0.00021065948,0.00008768254,0.32633767],"genre_scores_gemma":[0.9914954,0.00042245717,0.0031340446,0.00015295409,0.00001733968,0.000022046077,0.000040220883,0.000020683095,0.004694806],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9995111,0.00017429153,0.000020562811,0.00010213681,0.00009266287,0.00009910926],"domain_scores_gemma":[0.9989011,0.00038124953,0.00023004439,0.00015912477,0.00020040236,0.00012804777],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062404515,0.00019538199,0.00014706924,0.0018196893,0.0017545494,0.0066331713,0.0010144564,0.001634499,0.0061105397],"category_scores_gemma":[0.0024347792,0.00026616454,0.00028226676,0.001832553,0.007416418,0.007925525,0.0018676904,0.0012270887,0.0005183484],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004683983,0.0001376232,0.04946026,0.00009548757,0.000021802456,0.00031886643,0.056321666,0.0050959787,0.0014114215,0.83038867,0.0026167065,0.05408479],"study_design_scores_gemma":[0.000015742922,0.000104434184,0.112379275,0.00037521534,0.000057370286,0.00069637364,0.15648353,0.047672626,0.0022114106,0.5826258,0.09725797,0.00012028396],"about_ca_topic_score_codex":0.034831144,"about_ca_topic_score_gemma":0.02805284,"teacher_disagreement_score":0.034831144,"about_ca_system_score_codex":0.0023242282,"about_ca_system_score_gemma":0.0018111633,"threshold_uncertainty_score":0.06925678},"labels":[],"label_agreement":null},{"id":"W2169196399","doi":"10.1504/ijids.2008.020049","title":"An Analytical Hierarchical Process-based decision-making approach for selecting car-sharing stations in medium size agglomerations","year":2008,"lang":"en","type":"article","venue":"International Journal of Information and Decision Sciences","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Collège de Maisonneuve; University of British Columbia","funders":"","keywords":"Urban agglomeration; Computer science; Analytic hierarchy process; Process (computing); Operations research; Economies of agglomeration; Population; Mathematics; Geography; Economics; Microeconomics","score_opus":0.030088344135568316,"score_gpt":0.35886857744856665,"score_spread":0.3287802333129983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169196399","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009960711,0.00007242784,0.98733056,0.00022520008,0.000013969828,0.0002286215,0.000046275065,0.00009750006,0.002024726],"genre_scores_gemma":[0.38119972,0.00021143479,0.6164631,0.00009024629,0.000029335502,0.00056999153,0.00012028622,0.000023633955,0.0012921306],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9957104,0.0020749068,0.00022974912,0.00043935076,0.001263942,0.0002816164],"domain_scores_gemma":[0.9978648,0.001247602,0.00022076334,0.00006764315,0.0004559297,0.00014325793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048451615,0.0011091077,0.0011211599,0.0029346754,0.002525188,0.0022535298,0.0023688718,0.0012472591,0.0025228758],"category_scores_gemma":[0.005248624,0.0007291576,0.0016956514,0.0025151991,0.0014156677,0.0015735271,0.0020131012,0.0012072783,0.000277654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009190899,0.0001365405,0.0015219061,0.00043927098,0.00016048776,0.00042886887,0.0011994134,0.895957,0.0035127692,0.038138032,0.0011120061,0.057301734],"study_design_scores_gemma":[0.000026763242,0.00005638842,0.00025749387,0.000038373924,0.00004370894,0.00003658391,0.00031769517,0.9739787,0.00090644974,0.022865191,0.0014443024,0.000028420367],"about_ca_topic_score_codex":0.013969739,"about_ca_topic_score_gemma":0.019948851,"teacher_disagreement_score":0.013969739,"about_ca_system_score_codex":0.0036218353,"about_ca_system_score_gemma":0.006039038,"threshold_uncertainty_score":0.027776897},"labels":[],"label_agreement":null},{"id":"W2173830418","doi":"10.1139/cjce-2012-0252","title":"Designing a multimodal feeder network by covering stops with different modes","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Multimodal transport; Computer science; Transit (satellite); Public transport; Metaheuristic; Function (biology); Ant colony optimization algorithms; Transport engineering; Operations research; Engineering; Artificial intelligence","score_opus":0.005086398283225172,"score_gpt":0.157287367156929,"score_spread":0.15220096887370382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2173830418","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22545396,0.00018386933,0.75560075,0.00021167529,0.000033160533,0.0003164063,0.00028195407,0.00079489476,0.017123256],"genre_scores_gemma":[0.7094026,0.00022400232,0.28290755,0.0000447075,0.000016556818,0.00033945634,0.0003963312,0.000074128526,0.0065946155],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997527,0.000084187035,0.000009712836,0.000055973207,0.000042195305,0.00005525361],"domain_scores_gemma":[0.999734,0.00006847344,0.000054709308,0.000026172998,0.00006977556,0.000046934216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036233643,0.0012055971,0.0005194739,0.0008933673,0.0010245998,0.00075300294,0.0009501686,0.0007658642,0.00478002],"category_scores_gemma":[0.0007014638,0.0003375682,0.0007543097,0.0010039317,0.00038383753,0.0009805019,0.00091946305,0.00040929814,0.00062779116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012700485,0.00013114857,0.0038899397,0.00019431137,0.00008517705,0.00045042764,0.00021518055,0.8709036,0.022595858,0.00735371,0.0017701242,0.09228354],"study_design_scores_gemma":[0.00004521792,0.00040033722,0.0024104188,0.000030186822,0.00014266257,0.00037190653,0.00036079675,0.9719535,0.007645016,0.0070869764,0.009516087,0.000036865582],"about_ca_topic_score_codex":0.004792085,"about_ca_topic_score_gemma":0.009458789,"teacher_disagreement_score":0.004792085,"about_ca_system_score_codex":0.0009336718,"about_ca_system_score_gemma":0.0009895194,"threshold_uncertainty_score":0.015990794},"labels":[],"label_agreement":null},{"id":"W2179770505","doi":"10.1007/s10288-015-0301-z","title":"Shared mobility systems","year":2015,"lang":"en","type":"article","venue":"4OR","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":110,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; HEC Montréal","funders":"","keywords":"Popularity; Incentive; Dimensioning; Computer science; Operations research; Open research; Transport engineering; Engineering; World Wide Web; Political science","score_opus":0.041769099620281656,"score_gpt":0.24007361989549858,"score_spread":0.19830452027521692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2179770505","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07403068,0.0014618626,0.67523825,0.002835022,0.001590774,0.00062897266,0.0024829966,0.0065844366,0.23514707],"genre_scores_gemma":[0.81599444,0.00088449864,0.083074704,0.0005050422,0.00036805414,0.0005049637,0.0028945308,0.00035866516,0.095415145],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99762887,0.0004823212,0.00015915842,0.00056628225,0.0006202164,0.0005432744],"domain_scores_gemma":[0.99657464,0.00035980242,0.00020951254,0.0018306392,0.00064881274,0.0003766007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014425438,0.0010766545,0.0009043903,0.001237938,0.0026180334,0.004765798,0.0028351168,0.0017352526,0.03322919],"category_scores_gemma":[0.004165538,0.00049745146,0.0008294936,0.0017730489,0.0012593084,0.006934903,0.01173811,0.0016868213,0.0073431674],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039312243,0.00023645608,0.0021818327,0.00025721957,0.00016474734,0.00049673487,0.00086077815,0.06340215,0.004792965,0.65598506,0.047646128,0.22358279],"study_design_scores_gemma":[0.00014531748,0.00036366057,0.0013971587,0.00016348684,0.00018782295,0.00064990704,0.0011469228,0.25635105,0.005921304,0.39851907,0.3350257,0.00012868104],"about_ca_topic_score_codex":0.0041625425,"about_ca_topic_score_gemma":0.0041169515,"teacher_disagreement_score":0.03322919,"about_ca_system_score_codex":0.0016548693,"about_ca_system_score_gemma":0.0035446873,"threshold_uncertainty_score":0.11116278},"labels":[],"label_agreement":null},{"id":"W2181782723","doi":"","title":"Fleet Services thanks the Divisions, Agencies, Boards and Commissions that are working to green the City's vehicle fl eets. We also thank the Toronto Atmospheric Fund for recent funding for the enhancement of a plug-in hybrid-electric vehicle.","year":2011,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Transport engineering; Engineering; Finance","score_opus":0.08353550246626275,"score_gpt":0.2758452191050449,"score_spread":0.19230971663878216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2181782723","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012096745,0.003279267,0.0044629727,0.120664895,0.008669993,0.00025566213,0.027037147,0.002716093,0.8208171],"genre_scores_gemma":[0.029036744,0.0013382384,0.0021559126,0.002214386,0.00018785927,0.000049191916,0.0067936755,0.0006776702,0.9575463],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99923944,0.00008327081,0.000019338391,0.00007876144,0.00043992282,0.00013934428],"domain_scores_gemma":[0.9960139,0.00017887702,0.00009508843,0.00014390632,0.0022498611,0.0013183383],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000825488,0.00071690464,0.00040618223,0.0010584454,0.0025813486,0.002225797,0.00046280623,0.0007234197,0.20976064],"category_scores_gemma":[0.002834885,0.0003644568,0.000238851,0.0012399512,0.00047808004,0.0014396989,0.0017194754,0.0021110997,0.045008637],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045851197,0.000024698658,0.00096810533,0.000037110225,0.000005809734,0.000079196725,0.00016649025,0.00011779981,0.00035460753,0.003746978,0.9561827,0.03827063],"study_design_scores_gemma":[0.000007031404,0.000013690542,0.001917065,0.000017025275,0.000003173948,0.00004436239,0.0003495916,0.00015011356,0.00013685497,0.00019505738,0.9971608,0.0000053634617],"about_ca_topic_score_codex":0.25655556,"about_ca_topic_score_gemma":0.50231314,"teacher_disagreement_score":0.79023933,"about_ca_system_score_codex":0.0038603626,"about_ca_system_score_gemma":0.012222039,"threshold_uncertainty_score":0.7017192},"labels":[],"label_agreement":null},{"id":"W2183696036","doi":"","title":"Planning a Robot's Search for Multiple Residents in a Retirement Home Environment","year":2014,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Schedule; Robot; USB; Plan (archaeology); Computer science; Order (exchange); Floor plan; Recreation; Artificial intelligence; Engineering; Business; Finance; Geography","score_opus":0.03081902264568869,"score_gpt":0.2577817028629379,"score_spread":0.2269626802172492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2183696036","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32592925,0.00024632103,0.6703576,0.00027243225,0.000023642971,0.00010562005,0.000106866595,0.0005785943,0.0023797376],"genre_scores_gemma":[0.8490821,0.0001239755,0.14787921,0.000040000068,0.000009390788,0.00010869569,0.00010000128,0.000046681627,0.0026098865],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985564,0.000044916836,0.0000056330036,0.00003681393,0.000028918743,0.00002804823],"domain_scores_gemma":[0.9997079,0.00015210352,0.000046351888,0.00002165139,0.000029513954,0.000042388536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036465004,0.00044185377,0.00054146996,0.0003239191,0.0004249097,0.00030919292,0.0006803656,0.0006014787,0.0020309493],"category_scores_gemma":[0.0010632181,0.00033915497,0.00045520088,0.00025131326,0.00047046863,0.00060625304,0.00070542475,0.00036409075,0.00021111683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025436585,0.000083133324,0.0026619195,0.00008855144,0.000039209637,0.0002893271,0.00022622086,0.9404658,0.004674428,0.004035426,0.000794536,0.04638703],"study_design_scores_gemma":[0.000031135758,0.00013737871,0.00074930233,0.000007693848,0.000014937974,0.00007641859,0.00013707276,0.9936912,0.0013919309,0.0028917533,0.00085995765,0.000011089543],"about_ca_topic_score_codex":0.0062105055,"about_ca_topic_score_gemma":0.007674073,"teacher_disagreement_score":0.0062105055,"about_ca_system_score_codex":0.00043417022,"about_ca_system_score_gemma":0.0011091331,"threshold_uncertainty_score":0.0123487115},"labels":[],"label_agreement":null},{"id":"W2187400216","doi":"10.5383/juspn.05.02.002","title":"Simulation of Carpooling Agents with the Janus Platform","year":2014,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"FP7 Information and Communication Technologies","keywords":"Carpool; Computer science; Negotiation; Plan (archaeology); Process (computing); NetLogo; Work (physics); Function (biology); Agent-based model; Traffic congestion; Matching (statistics); Transport engineering; Engineering; Artificial intelligence","score_opus":0.014588978511134037,"score_gpt":0.2217148646401877,"score_spread":0.20712588612905367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2187400216","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8406542,0.0003428866,0.1115747,0.0007971561,0.0002533822,0.00047699947,0.001158046,0.0018444315,0.042898357],"genre_scores_gemma":[0.9584184,0.00016623226,0.03614913,0.0000861753,0.00001473518,0.0003502034,0.0004942422,0.00009884495,0.0042219437],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996124,0.000114668415,0.000023413771,0.00005016702,0.0000928066,0.00010658763],"domain_scores_gemma":[0.99860424,0.00076244696,0.00011498718,0.00012030356,0.00018396907,0.00021416669],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061549916,0.00070928974,0.0008264935,0.0005725283,0.0010183506,0.0014443143,0.0019785725,0.001557364,0.0060758227],"category_scores_gemma":[0.0020898548,0.00048727638,0.0009013037,0.0004521585,0.0009784208,0.0009205075,0.0015402641,0.0013699542,0.0004265326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001095896,0.0001092662,0.0013974007,0.000053080963,0.000023777817,0.00014351761,0.00014499044,0.98744684,0.0008407813,0.0075129685,0.00044129748,0.0017764448],"study_design_scores_gemma":[0.000027760256,0.00002350838,0.00014402153,0.000005408315,0.0000047195563,0.0000073357064,0.00003958055,0.9978509,0.0002690579,0.0008652842,0.0007562608,0.0000062787826],"about_ca_topic_score_codex":0.022382002,"about_ca_topic_score_gemma":0.010777459,"teacher_disagreement_score":0.022382002,"about_ca_system_score_codex":0.0009678847,"about_ca_system_score_gemma":0.0016942152,"threshold_uncertainty_score":0.04450345},"labels":[],"label_agreement":null},{"id":"W2188971127","doi":"","title":"I am writing on behalf of the Canadian Motorcycle Association to inform you that our Board of Directors has awarded the first CMA Government Award to the City of Toronto in recognition of the enactment of a free parking for motorcycles policy in 2005.","year":2009,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Association (psychology); Psychology; Political science; Management; Law; Linguistics; Economics; Philosophy","score_opus":0.023903684903900855,"score_gpt":0.24383982062072346,"score_spread":0.2199361357168226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2188971127","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011201763,0.0045519867,0.0007500807,0.88420784,0.05441336,0.00008382246,0.00036185657,0.00024902375,0.054261733],"genre_scores_gemma":[0.015350824,0.0071134996,0.0021636207,0.32904044,0.00995332,0.0001142105,0.0004412163,0.00024360434,0.63557917],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963057,0.0001517942,0.00007432629,0.00031042504,0.002188837,0.0009688999],"domain_scores_gemma":[0.97548556,0.0012870097,0.00058548077,0.00027852802,0.014630112,0.007733345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026265313,0.000718348,0.00065867545,0.0011064796,0.011376587,0.0067113955,0.0023048269,0.0085341735,0.052267816],"category_scores_gemma":[0.015577197,0.00044953823,0.00051474926,0.0013887329,0.0031925985,0.0024249328,0.0015260741,0.012677912,0.021117488],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005753995,0.0000062170684,0.0002438001,0.000014439231,0.000001321222,0.000028376717,0.00010113645,0.000011335201,0.000057738693,0.0005369867,0.9942702,0.0047226497],"study_design_scores_gemma":[0.0000030595875,0.0000055890678,0.0009860311,0.00003722783,0.0000030775468,0.000026138749,0.0008149903,0.000036865516,0.00007523599,0.00017843729,0.99781466,0.000018577479],"about_ca_topic_score_codex":0.7048406,"about_ca_topic_score_gemma":0.8790632,"teacher_disagreement_score":0.2951594,"about_ca_system_score_codex":0.013417324,"about_ca_system_score_gemma":0.038683042,"threshold_uncertainty_score":0.5937953},"labels":[],"label_agreement":null},{"id":"W2199233512","doi":"10.1007/978-1-4020-8952-7_11","title":"Agent-Based Modelling: A Dynamic Scenario Planning Approach to Tourism PSS","year":2009,"lang":"en","type":"book-chapter","venue":"The Geojournal library","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Tourism; Computer science; Scenario planning; Environmental planning; Business; Geography; Marketing; Archaeology","score_opus":0.024013068764708385,"score_gpt":0.21008428344577523,"score_spread":0.18607121468106685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2199233512","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005975285,0.00075507385,0.9653547,0.0007936497,0.00012818466,0.00011231549,0.0004973474,0.00054465473,0.025838694],"genre_scores_gemma":[0.36927482,0.0030742935,0.6017936,0.00028821916,0.000107111984,0.00066620565,0.001036595,0.00033775522,0.023421472],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995622,0.00023210565,0.00002678659,0.000055819317,0.00009702899,0.000026111215],"domain_scores_gemma":[0.9993925,0.0004288455,0.000037342958,0.000038718157,0.00006719463,0.000035393216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007417052,0.0009946395,0.0007900109,0.0008468085,0.00064296764,0.002574037,0.0025210334,0.0015479111,0.0073574176],"category_scores_gemma":[0.0022879394,0.00091734406,0.0011874031,0.0014097516,0.0008233516,0.0022832332,0.0013460341,0.0013564193,0.0010288277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022291337,0.000032591775,0.00014753213,0.00009201384,0.000047065725,0.00011451284,0.0001162227,0.91178244,0.00024559684,0.070314355,0.0025467924,0.014538606],"study_design_scores_gemma":[0.0000083093655,0.0000065978184,0.000041974195,0.000021157846,0.000014234404,0.000024844,0.000032245927,0.9531395,0.00014237549,0.04045251,0.0061063166,0.000009939263],"about_ca_topic_score_codex":0.02031403,"about_ca_topic_score_gemma":0.023335176,"teacher_disagreement_score":0.02031403,"about_ca_system_score_codex":0.0014897941,"about_ca_system_score_gemma":0.001560777,"threshold_uncertainty_score":0.040391564},"labels":[],"label_agreement":null},{"id":"W2215252086","doi":"10.1017/s1481803500012495","title":"Énoncé de principe de l'ACMU sur l'utilisation du téléphone cellulaire au volant","year":2010,"lang":"fr","type":"article","venue":"Canadian Journal of Emergency Medicine","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Association of Emergency Physicians; Dalhousie University; Royal Alexandra Hospital; University of Ottawa; University of Alberta; University of Saskatchewan","funders":"","keywords":"Medicine; Humanities; Art","score_opus":0.03861367701390963,"score_gpt":0.2720567731583319,"score_spread":0.23344309614442224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2215252086","genre_codex":"methods","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16459939,0.043924663,0.3790159,0.103101976,0.015781509,0.0007811713,0.0023953498,0.0013212806,0.28907886],"genre_scores_gemma":[0.7547611,0.020201769,0.10721447,0.0058327913,0.0075250636,0.0012529918,0.0007195289,0.00028743345,0.10220492],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9943758,0.002767267,0.00027923883,0.0006633601,0.0014998909,0.00041437653],"domain_scores_gemma":[0.98891,0.0065882136,0.0005446125,0.00052195473,0.003027077,0.000408117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005492568,0.0016515708,0.0011089526,0.0024644742,0.0024697338,0.0068072802,0.0018961031,0.0035776992,0.012183971],"category_scores_gemma":[0.018569054,0.00040377048,0.0022408555,0.0012538854,0.003571571,0.0033107435,0.0025731334,0.0056349896,0.0026526724],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00080459006,0.0005087622,0.041501384,0.0016568475,0.0004061993,0.0025085474,0.006917084,0.022666931,0.0070757046,0.6262376,0.034368146,0.2553482],"study_design_scores_gemma":[0.00031925243,0.0016409402,0.08935146,0.0037756527,0.0005758723,0.004285605,0.009502233,0.054089777,0.018548088,0.24961247,0.56775296,0.0005457795],"about_ca_topic_score_codex":0.053102188,"about_ca_topic_score_gemma":0.03416557,"teacher_disagreement_score":0.053102188,"about_ca_system_score_codex":0.005009139,"about_ca_system_score_gemma":0.0057482542,"threshold_uncertainty_score":0.10558623},"labels":[],"label_agreement":null},{"id":"W2238283556","doi":"10.13140/rg.2.1.1595.6966","title":"Data Analytics for Location-Based Services: Enabling User-Based Relocation of Carsharing Vehicles","year":2015,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Relocation; Renting; Idle; Analytics; Flexibility (engineering); Computer science; Destinations; Transport engineering; Business; Engineering; Database","score_opus":0.10925625786249281,"score_gpt":0.2960298036358081,"score_spread":0.18677354577331529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2238283556","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25859195,0.0011296595,0.7073948,0.0017972848,0.00019376875,0.00040154927,0.0038309598,0.020215265,0.006444736],"genre_scores_gemma":[0.85109437,0.00032631375,0.14541548,0.00012263893,0.000054255077,0.000087536246,0.0016999643,0.00019355034,0.0010059093],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991404,0.0002161593,0.00006864246,0.00016673034,0.000349015,0.00005907652],"domain_scores_gemma":[0.9967445,0.001499614,0.00026973223,0.00071242737,0.0006028021,0.000170959],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085868826,0.0007790111,0.0005724172,0.0014335233,0.00040210172,0.0015531271,0.0011465094,0.00051215023,0.0012116388],"category_scores_gemma":[0.0042559346,0.00023503674,0.00040667932,0.0014909174,0.0003536951,0.0017237057,0.0010757933,0.00073440734,0.0005254982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012444425,0.0010349163,0.09388706,0.00078384764,0.00037902838,0.0010113763,0.002014836,0.15356092,0.046453163,0.012915503,0.017549822,0.6691651],"study_design_scores_gemma":[0.000041679697,0.00014263901,0.008690334,0.00005435627,0.000049199803,0.000293671,0.00068126305,0.9402068,0.025195327,0.007243423,0.01733764,0.00006370183],"about_ca_topic_score_codex":0.008434437,"about_ca_topic_score_gemma":0.009000735,"teacher_disagreement_score":0.008434437,"about_ca_system_score_codex":0.00052701356,"about_ca_system_score_gemma":0.0005750829,"threshold_uncertainty_score":0.01677072},"labels":[],"label_agreement":null},{"id":"W2238300491","doi":"","title":"Résolution de problèmes de tournées avec synchronisation : applications au cas multi-échelons et au cross-docking","year":2015,"lang":"fr","type":"dissertation","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Humanities; Physics; Philosophy","score_opus":0.020884835245798875,"score_gpt":0.2850331446779293,"score_spread":0.2641483094321304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2238300491","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.061136544,0.00074690854,0.92946124,0.0009773818,0.00019171635,0.00013480325,0.00014099387,0.00014479102,0.0070655076],"genre_scores_gemma":[0.58289504,0.0008482378,0.40042928,0.00025791797,0.00039210953,0.00043837525,0.0005634011,0.00024247066,0.013933151],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983463,0.0006771237,0.000088839966,0.00037898205,0.00028078113,0.00022800016],"domain_scores_gemma":[0.9914051,0.007003314,0.0004588286,0.00023455555,0.00036880962,0.0005292919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031515711,0.001210495,0.0016158657,0.00093459117,0.0014835792,0.0025468087,0.001606284,0.0020686176,0.0074216183],"category_scores_gemma":[0.010162695,0.0005597403,0.0017188682,0.0010872548,0.001661631,0.0019545523,0.0036125118,0.003035804,0.00036714302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017462729,0.00013359649,0.001361815,0.00025914735,0.000103933184,0.00046509024,0.00035863038,0.857093,0.0018853635,0.090122834,0.0029810886,0.04506086],"study_design_scores_gemma":[0.000074673575,0.000074637624,0.0002978032,0.00002214032,0.000014607186,0.00007847442,0.00020520737,0.93933964,0.00074806804,0.05621322,0.002911187,0.000020257994],"about_ca_topic_score_codex":0.004548892,"about_ca_topic_score_gemma":0.0038783944,"teacher_disagreement_score":0.0074216183,"about_ca_system_score_codex":0.001015343,"about_ca_system_score_gemma":0.0009708701,"threshold_uncertainty_score":0.024827778},"labels":[],"label_agreement":null},{"id":"W2245205505","doi":"","title":"Technological Support for Mobility and Orientation Training: Development of a Smartphone Navigation Aid","year":2013,"lang":"en","type":"article","venue":"E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University","funders":"","keywords":"Training (meteorology); Orientation (vector space); Computer science; Human–computer interaction; Geography; Mathematics; Meteorology","score_opus":0.07192063042238822,"score_gpt":0.2883840918174643,"score_spread":0.2164634613950761,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2245205505","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8477233,0.004530565,0.12682615,0.0011968473,0.0008108726,0.0008844795,0.0006817044,0.0012491378,0.01609703],"genre_scores_gemma":[0.8195664,0.0034930378,0.16051884,0.00072793075,0.00010551818,0.0004731135,0.00042531494,0.00007083562,0.014619059],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99987566,0.000021047059,0.000013268949,0.000025244817,0.000043165055,0.000021608756],"domain_scores_gemma":[0.99980253,0.00004275651,0.000013496803,0.000012795076,0.00009520894,0.000033275945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034602708,0.00039570263,0.0001946182,0.00038210844,0.0001645235,0.00041354235,0.00052161963,0.00053579354,0.0035057815],"category_scores_gemma":[0.0005799201,0.00010800733,0.00032536854,0.0001420926,0.00012195077,0.00035554895,0.0004739686,0.00026309732,0.00071196305],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006822035,0.0012859609,0.013567755,0.0008317255,0.00009146228,0.001100407,0.0006080375,0.0009092243,0.29329836,0.0012962768,0.0042027594,0.68212587],"study_design_scores_gemma":[0.0010829802,0.038900495,0.13287911,0.0010546178,0.0021611014,0.018321214,0.0028368863,0.050234683,0.4623253,0.0017023631,0.2881853,0.00031591122],"about_ca_topic_score_codex":0.0013990826,"about_ca_topic_score_gemma":0.0022227988,"teacher_disagreement_score":0.0035057815,"about_ca_system_score_codex":0.000111305264,"about_ca_system_score_gemma":0.0005735609,"threshold_uncertainty_score":0.011728048},"labels":[],"label_agreement":null},{"id":"W2253813636","doi":"10.1002/atr.1365","title":"Distributed algorithm for empty vehicles management in personal rapid transit (PRT) network","year":2016,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"European Regional Development Fund","keywords":"Set (abstract data type); Heuristic; Function (biology); Space (punctuation); Transit (satellite); Feature (linguistics); Distributed management; Distributed algorithm","score_opus":0.00841323277005404,"score_gpt":0.22924685549663287,"score_spread":0.22083362272657883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2253813636","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04451645,0.0002078405,0.94905114,0.00017920422,0.000049988965,0.0001640329,0.0001547202,0.0011701648,0.004506393],"genre_scores_gemma":[0.6204698,0.00013934086,0.37189364,0.00007198412,0.00003343587,0.00025057947,0.00041202616,0.00013659183,0.006592503],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994646,0.00010312281,0.000026598917,0.00014738072,0.00009917678,0.00015929595],"domain_scores_gemma":[0.99945647,0.00019965436,0.00007305486,0.00007494367,0.0001336571,0.00006217369],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006453979,0.00048527395,0.0008286274,0.00065114663,0.0007649821,0.0010619436,0.0016268487,0.0007339455,0.004772549],"category_scores_gemma":[0.001442616,0.00027540696,0.00042096392,0.00067676714,0.00039408222,0.0009343365,0.0012165797,0.00044319415,0.0005671316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032213557,0.0000779609,0.001108625,0.000103845174,0.000036651152,0.00013346731,0.00013058535,0.8591271,0.0029290908,0.011550072,0.0035481532,0.12093224],"study_design_scores_gemma":[0.00003032791,0.000028252874,0.00010610385,0.0000032572818,0.0000071609134,0.000036347534,0.000025912379,0.9948742,0.0007763534,0.0031854508,0.000922077,0.0000045485813],"about_ca_topic_score_codex":0.0051848013,"about_ca_topic_score_gemma":0.004702988,"teacher_disagreement_score":0.0051848013,"about_ca_system_score_codex":0.0011358308,"about_ca_system_score_gemma":0.0014118939,"threshold_uncertainty_score":0.01596576},"labels":[],"label_agreement":null},{"id":"W2254408903","doi":"10.1088/1748-9326/10/12/124017","title":"Characterizing the GHG emission impacts of carsharing: a case of Vancouver","year":2015,"lang":"en","type":"article","venue":"Environmental Research Letters","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"University of British Columbia; Transport Canada; National Science Foundation","keywords":"Greenhouse gas; TRIPS architecture; Train; Public transport; Transport engineering; Business; Car sharing; Service (business); Environmental economics; Economics; Marketing; Engineering; Geography","score_opus":0.04658413952474841,"score_gpt":0.3000343622897437,"score_spread":0.2534502227649953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2254408903","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99017066,0.00007556535,0.0013896918,0.00017211154,0.0000044524686,0.00005050529,0.00031782448,0.000017808226,0.0078013693],"genre_scores_gemma":[0.9957075,0.0001009054,0.00081641524,0.0000180681,0.0000014766786,0.000017692459,0.00016418847,0.000007935545,0.0031659133],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99977225,0.00004610085,0.000005653878,0.00003425258,0.000044877725,0.0000968834],"domain_scores_gemma":[0.9996063,0.00017759677,0.000021955626,0.00002532462,0.000114897266,0.000053988304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027365852,0.0006295794,0.00039455885,0.0006121303,0.0018717938,0.002163525,0.0012165501,0.0014833213,0.0024051366],"category_scores_gemma":[0.00080676365,0.00039231186,0.0006727137,0.0014866656,0.0009198419,0.0007079573,0.0008985355,0.00093933643,0.00018533527],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028762873,0.0005144922,0.07761743,0.0001295757,0.00009409489,0.005849465,0.0006873256,0.8866855,0.005966323,0.009831575,0.0013913718,0.010945187],"study_design_scores_gemma":[0.000092028866,0.0001503126,0.029272063,0.000025083798,0.00006242978,0.00026185848,0.004165576,0.9569471,0.0028402642,0.0030699424,0.0030477254,0.00006561357],"about_ca_topic_score_codex":0.8190868,"about_ca_topic_score_gemma":0.8142342,"teacher_disagreement_score":0.18091321,"about_ca_system_score_codex":0.009186187,"about_ca_system_score_gemma":0.002822845,"threshold_uncertainty_score":0.36395723},"labels":[],"label_agreement":null},{"id":"W2259318073","doi":"10.5281/zenodo.1112063","title":"The Proposal Of A Shared Mobility City Index To Support Investment Decision Making For Carsharing","year":2016,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Index (typography); Business; Investment (military); Industrial organization; Computer science; World Wide Web; Political science","score_opus":0.036422942597684055,"score_gpt":0.2690360945917751,"score_spread":0.23261315199409102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2259318073","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28910106,0.0007963557,0.35317576,0.01879966,0.0015361068,0.0089308685,0.052087534,0.0064098677,0.26916268],"genre_scores_gemma":[0.3959394,0.0004193466,0.5534727,0.00040442497,0.00015400434,0.0032832345,0.033265356,0.00040153248,0.01266002],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99346644,0.0016184046,0.0011141781,0.0005651042,0.002686472,0.00054933556],"domain_scores_gemma":[0.96960944,0.0054008383,0.0028005743,0.0022896924,0.017383033,0.0025164422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01037609,0.0009986607,0.00085181557,0.009671308,0.0014925544,0.0102204075,0.002738834,0.001316176,0.009805552],"category_scores_gemma":[0.030311741,0.00059713674,0.0011881766,0.012363838,0.00081667776,0.007253937,0.004577706,0.0019552016,0.0032989208],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038782964,0.001055199,0.14124776,0.0012057101,0.00033366782,0.0003326481,0.0029958438,0.03938639,0.0018736251,0.14505473,0.1855619,0.4805647],"study_design_scores_gemma":[0.00024554832,0.0011821679,0.14935888,0.0009902479,0.00029230973,0.00036520534,0.017525978,0.18984021,0.008698585,0.07179828,0.5590835,0.00061894837],"about_ca_topic_score_codex":0.0193686,"about_ca_topic_score_gemma":0.023305027,"teacher_disagreement_score":0.0193686,"about_ca_system_score_codex":0.0070767403,"about_ca_system_score_gemma":0.009920833,"threshold_uncertainty_score":0.05487472},"labels":[],"label_agreement":null},{"id":"W2267840417","doi":"","title":"Jack’s Schedule","year":2002,"lang":"ja","type":"article","venue":"学苑创造：A版","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Schedule; Computer science; Economics; Management","score_opus":0.025423450860539747,"score_gpt":0.22076571899991757,"score_spread":0.19534226813937783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2267840417","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004446907,0.00071078213,0.0030399528,0.007015907,0.013268304,0.00045156843,0.0044475347,0.003275437,0.9673458],"genre_scores_gemma":[0.0013863593,0.0005059688,0.0011618964,0.001095424,0.0008190811,0.0001212941,0.0018217319,0.0007570319,0.99233115],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99828666,0.00021547242,0.00011000354,0.0002629046,0.0008394586,0.00028548806],"domain_scores_gemma":[0.98941565,0.0006113266,0.00024649728,0.0007707019,0.005385146,0.0035707387],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016545831,0.0013322929,0.0010015253,0.0019530728,0.0023743494,0.0046288855,0.0016444777,0.0018147064,0.82435286],"category_scores_gemma":[0.009951075,0.0006777343,0.0007206179,0.0012203064,0.0005018139,0.0022527848,0.0026835087,0.0025328298,0.7355147],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020507026,0.000015477257,0.000039829538,0.000023410135,7.637544e-7,0.000021827991,0.000019227986,0.000021409822,0.00008509278,0.00095437054,0.97715056,0.021647468],"study_design_scores_gemma":[0.000003652104,0.000007692444,0.00014129549,0.000022225797,6.318209e-7,0.000026357415,0.00003801151,0.000022969862,0.00002773605,0.00027051478,0.999435,0.0000038360577],"about_ca_topic_score_codex":0.007504364,"about_ca_topic_score_gemma":0.017055266,"teacher_disagreement_score":0.82435286,"about_ca_system_score_codex":0.0018209775,"about_ca_system_score_gemma":0.00396106,"threshold_uncertainty_score":0.25053924},"labels":[],"label_agreement":null},{"id":"W2267907443","doi":"10.1109/icbdsc.2016.7460378","title":"Pricing vehicle sharing with proximity information","year":2016,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Scheme (mathematics); Computer science; Mathematical optimization; Mathematics","score_opus":0.011040455524189073,"score_gpt":0.20839393779693094,"score_spread":0.19735348227274185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2267907443","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06615691,0.00057072815,0.91759646,0.00097364327,0.0002234816,0.000211248,0.00015455234,0.00023661452,0.01387635],"genre_scores_gemma":[0.9701867,0.00024737374,0.025008667,0.00010661899,0.00014836798,0.00009518988,0.000053376316,0.00003390932,0.004119706],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965155,0.0012707121,0.00012885749,0.0006205585,0.0009462097,0.00051810895],"domain_scores_gemma":[0.9942258,0.0028683452,0.0005562056,0.0015580526,0.00045834674,0.00033330935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023899602,0.0010963728,0.0017282311,0.0005922125,0.00088123156,0.0023370597,0.004050416,0.0023792044,0.0067985174],"category_scores_gemma":[0.014452864,0.00056223274,0.0009838602,0.0014053629,0.0018943758,0.0055798567,0.003615606,0.0021088116,0.0007827373],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038136615,0.0002056609,0.0010527829,0.00018980351,0.000091710666,0.00044685468,0.0002690023,0.4117236,0.0052169943,0.51774156,0.004135131,0.05854548],"study_design_scores_gemma":[0.00004247318,0.00013005633,0.00020654827,0.000015821666,0.000027705515,0.00022899992,0.00006022798,0.8004162,0.0011216787,0.19507001,0.0026476488,0.00003261287],"about_ca_topic_score_codex":0.0010522436,"about_ca_topic_score_gemma":0.0006845849,"teacher_disagreement_score":0.0067985174,"about_ca_system_score_codex":0.0016199526,"about_ca_system_score_gemma":0.00078550423,"threshold_uncertainty_score":0.022743285},"labels":[],"label_agreement":null},{"id":"W2270202954","doi":"","title":"Sammy Snacks (a)","year":2008,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Footprint; Marketing; Labrador Retriever; Pet food; Agricultural science; Commerce; Advertising; Geography; Food science; Environmental science","score_opus":0.008134276449734726,"score_gpt":0.20335426935550235,"score_spread":0.19521999290576764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2270202954","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011659038,0.005615459,0.0016054289,0.044987295,0.0071988213,0.00008244112,0.0009432808,0.00086933293,0.9270388],"genre_scores_gemma":[0.015130006,0.0011847035,0.0006090848,0.0060238387,0.00033243393,0.000018324225,0.00015293031,0.00015032735,0.9763983],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997441,0.00003360829,0.000008550916,0.00007472869,0.00007350049,0.0000654239],"domain_scores_gemma":[0.9996166,0.000043169304,0.000027471684,0.000021779839,0.00011924816,0.00017157118],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00037384016,0.0005549687,0.0002247459,0.00068281614,0.0045665842,0.0023437946,0.00047498645,0.0015759923,0.32463697],"category_scores_gemma":[0.0009638797,0.00029236457,0.00026621277,0.0003956106,0.0005840233,0.002672692,0.0016205775,0.0021080582,0.13010773],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000069922964,0.000042339176,0.0008954245,0.00008143869,0.0000042389534,0.00036958413,0.0007775311,0.00002923297,0.0005353677,0.015552714,0.9136085,0.06803366],"study_design_scores_gemma":[0.0000022298545,0.000015977223,0.0004938125,0.000025545389,0.000001393713,0.00019281688,0.00044342046,0.000021320555,0.00019814644,0.00044106433,0.9981597,0.0000045116954],"about_ca_topic_score_codex":0.00578672,"about_ca_topic_score_gemma":0.019025564,"teacher_disagreement_score":0.67536306,"about_ca_system_score_codex":0.0009879444,"about_ca_system_score_gemma":0.00084471685,"threshold_uncertainty_score":0.9633234},"labels":[],"label_agreement":null},{"id":"W2273854252","doi":"","title":"Connecting in real space : how people share knowledge and technologies in cybercafés","year":2010,"lang":"en","type":"article","venue":"ResearchWorks at the University of Washington (University of Washington)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"International Development Research Centre; Bill and Melinda Gates Foundation","keywords":"Space (punctuation); Computer science; Knowledge management","score_opus":0.013158943111120132,"score_gpt":0.2194653212862595,"score_spread":0.2063063781751394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2273854252","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99278295,0.00040182268,0.0005972883,0.0010408725,0.0000100060215,0.000011944649,0.000012867863,0.0000071585,0.005134925],"genre_scores_gemma":[0.99905676,0.00019106983,0.00015761556,0.0001288078,0.000005655589,0.000008901089,0.000009771926,0.000002551898,0.00043904653],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.99489486,0.0034191662,0.00017730164,0.0003670809,0.00042014048,0.00072156586],"domain_scores_gemma":[0.9946392,0.0025644237,0.0012799774,0.00039100647,0.00029832896,0.00082709594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031997887,0.00033352227,0.00046834658,0.0022441254,0.006026346,0.007908283,0.00095681107,0.0024575875,0.0028932213],"category_scores_gemma":[0.009441711,0.00039754022,0.00038334806,0.0015450426,0.008174773,0.012803621,0.0060724923,0.001322637,0.00029166773],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003433709,0.00007196516,0.041700225,0.000059990067,0.000025154777,0.0004840284,0.94281566,0.00007759309,0.0005317264,0.0020949089,0.00034006254,0.011764437],"study_design_scores_gemma":[0.0000075437474,0.00007586036,0.018346384,0.00005117259,0.000012344867,0.00039050696,0.9718793,0.00017717363,0.000081908285,0.0021282248,0.006829519,0.000020034984],"about_ca_topic_score_codex":0.0064228904,"about_ca_topic_score_gemma":0.008184894,"teacher_disagreement_score":0.007908283,"about_ca_system_score_codex":0.0014542353,"about_ca_system_score_gemma":0.0011237812,"threshold_uncertainty_score":0.016922295},"labels":[],"label_agreement":null},{"id":"W2275948401","doi":"10.14288/1.0092026","title":"A transit-friendly community : integrating a SkyTrain station into the neighborhood","year":2009,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Transport engineering; Public transport; Geography; Computer science; Environmental planning; Engineering","score_opus":0.00640647375107956,"score_gpt":0.17597207145608085,"score_spread":0.1695655977050013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2275948401","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82016444,0.0008750634,0.00607172,0.0045015784,0.000103430306,0.00023339296,0.00003984115,0.0000875854,0.16792291],"genre_scores_gemma":[0.9660145,0.0010306776,0.007388794,0.00033571862,0.000014707381,0.000050752296,0.00003517628,0.000010782841,0.025118832],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999607,0.00015247506,0.0000085720485,0.000030131168,0.00007897879,0.00012283993],"domain_scores_gemma":[0.9996642,0.000027998687,0.000022382848,0.0000151829545,0.00006661573,0.00020365002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033264136,0.00019828815,0.00009840521,0.0004127576,0.005263288,0.002280006,0.0007735073,0.0007594328,0.0032985355],"category_scores_gemma":[0.0005240451,0.0001281088,0.000115897245,0.0005918113,0.0012547707,0.0009868221,0.0020260967,0.0003988057,0.00032627492],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016423894,0.0013537805,0.1051264,0.0009902936,0.00004590747,0.016522449,0.18289253,0.0026946014,0.0120239165,0.078253746,0.023451887,0.57648027],"study_design_scores_gemma":[0.00005574793,0.0010034312,0.0753167,0.000574263,0.00011246495,0.003953837,0.44484818,0.0033696475,0.0027903155,0.0051692473,0.4627378,0.00006844692],"about_ca_topic_score_codex":0.12599397,"about_ca_topic_score_gemma":0.53237516,"teacher_disagreement_score":0.12599397,"about_ca_system_score_codex":0.0029757824,"about_ca_system_score_gemma":0.00789384,"threshold_uncertainty_score":0.25052118},"labels":[],"label_agreement":null},{"id":"W2280134889","doi":"10.3141/2538-08","title":"All-Door Boarding in San Francisco, California","year":2015,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Wood Council","funders":"","keywords":"Ticket; Revenue; Transit (satellite); Boom; Payment; Transport engineering; Public transport; Business; Phone; Service (business); Population; Agency (philosophy); Engineering; Finance; Marketing; Computer science; Computer security","score_opus":0.1168310953144627,"score_gpt":0.3779282250617412,"score_spread":0.2610971297472785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2280134889","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7567573,0.00828009,0.0011802515,0.007965141,0.001337543,0.0004832816,0.00664479,0.0011985817,0.216153],"genre_scores_gemma":[0.75593156,0.0081004985,0.003613098,0.0014814881,0.00032623534,0.0001525063,0.00833221,0.00016634163,0.22189605],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9997844,0.00001672784,0.000007475312,0.000058954596,0.00006379784,0.00006869299],"domain_scores_gemma":[0.99940753,0.000035518722,0.000045333843,0.000031307638,0.00024093977,0.00023939076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004036235,0.00036724156,0.00016139954,0.00062483794,0.0021742822,0.00110967,0.0006551879,0.000372502,0.01748159],"category_scores_gemma":[0.00066934444,0.00021316318,0.00021481297,0.0005428147,0.00037428483,0.00049749913,0.0005956577,0.00075826346,0.00133539],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048057767,0.0017182776,0.21271136,0.0006502197,0.00008813599,0.001884275,0.00424295,0.0013326592,0.0026701242,0.0026530959,0.48169756,0.2898707],"study_design_scores_gemma":[0.00014776729,0.0003815333,0.52028066,0.00035637655,0.00007436572,0.00061312126,0.0076150214,0.00091997755,0.0007030603,0.00040051798,0.46845978,0.000047766036],"about_ca_topic_score_codex":0.5572629,"about_ca_topic_score_gemma":0.72627383,"teacher_disagreement_score":0.5572629,"about_ca_system_score_codex":0.0028598337,"about_ca_system_score_gemma":0.0062553375,"threshold_uncertainty_score":0.89068896},"labels":[],"label_agreement":null},{"id":"W2283537407","doi":"","title":"Ridesharing in North America: Past, Present, and Future","year":2011,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"University of California, Davis","keywords":"Interoperability; Incentive; Business; The Internet; Casual; Computer science; Economics; Political science; World Wide Web","score_opus":0.014667881756487875,"score_gpt":0.18836517575415695,"score_spread":0.1736972939976691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2283537407","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1279515,0.4969761,0.0011010485,0.14002438,0.002629156,0.000042585823,0.0031788514,0.0005488753,0.2275475],"genre_scores_gemma":[0.4808188,0.44461164,0.0038287449,0.012457676,0.0009551098,0.000060360308,0.0024162135,0.0000868475,0.054764625],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9997079,0.00003464951,0.000017356086,0.000056275352,0.00008135709,0.00010239832],"domain_scores_gemma":[0.9991936,0.00009465705,0.00011374336,0.00002878105,0.00034556419,0.00022361253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044952516,0.00024088827,0.000249262,0.0013324649,0.0021711509,0.003217414,0.00093880453,0.001275452,0.012209362],"category_scores_gemma":[0.0006848358,0.0001865284,0.00023397204,0.0038227544,0.0012818554,0.003267648,0.0011861541,0.0015550976,0.0015853558],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010180072,0.00022089064,0.033028685,0.0025545745,0.000035709723,0.00070906186,0.0056741256,0.00042955534,0.0010980614,0.012399211,0.18323708,0.76051116],"study_design_scores_gemma":[0.000005738075,0.000056300672,0.10549112,0.0016641623,0.000031645643,0.0006156667,0.025461368,0.00024416423,0.00029149593,0.0028236203,0.8632652,0.000049458107],"about_ca_topic_score_codex":0.26491272,"about_ca_topic_score_gemma":0.4970211,"teacher_disagreement_score":0.7350873,"about_ca_system_score_codex":0.005613022,"about_ca_system_score_gemma":0.006440525,"threshold_uncertainty_score":0.5267415},"labels":[],"label_agreement":null},{"id":"W2283582176","doi":"","title":"Inégalités sociales dans la diffusion d'une innovation en transport actif : le cas des vélos en libre-service à Montréal","year":2015,"lang":"fr","type":"dissertation","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Philosophy","score_opus":0.029027074054411434,"score_gpt":0.28152689252792684,"score_spread":0.25249981847351544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2283582176","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8957711,0.002199065,0.0015710155,0.0192116,0.000056631558,0.00006813399,0.0004883538,0.000032524546,0.08060163],"genre_scores_gemma":[0.9880918,0.0005392087,0.0002131668,0.0001454348,0.000018837138,0.000022028431,0.000044538563,0.000008770631,0.010916149],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9973992,0.0006393031,0.00005366891,0.00026802663,0.00057110237,0.0010687191],"domain_scores_gemma":[0.99162185,0.003973855,0.0010054115,0.0002479422,0.0015771388,0.00157384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028779418,0.0003453013,0.0005155423,0.0017298177,0.0061742947,0.011483478,0.0013298943,0.0022783286,0.012031642],"category_scores_gemma":[0.009622885,0.0003577568,0.00062464736,0.0026032757,0.0060564,0.0029232204,0.003456901,0.0023718872,0.00036564824],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050065835,0.0004191487,0.23078175,0.00021125644,0.0002734898,0.0022282624,0.11020694,0.00761552,0.001639671,0.5851038,0.012369652,0.04864985],"study_design_scores_gemma":[0.00022766864,0.00023175772,0.5730961,0.0005043444,0.00050772063,0.00037287246,0.21354134,0.012895795,0.0011488929,0.037377566,0.15982507,0.00027084036],"about_ca_topic_score_codex":0.9456276,"about_ca_topic_score_gemma":0.9498299,"teacher_disagreement_score":0.055620488,"about_ca_system_score_codex":0.055620488,"about_ca_system_score_gemma":0.04014656,"threshold_uncertainty_score":0.40355682},"labels":[],"label_agreement":null},{"id":"W2283666941","doi":"10.1109/vtcfall.2015.7390793","title":"A Game Theoretic Approach for the Ride-Sourcing Territory Sharing Problem","year":2015,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Class (philosophy); Computer science; Game theory; Mathematical optimization; Operations research; Mathematical economics; Engineering; Artificial intelligence; Economics; Mathematics","score_opus":0.03205625396771238,"score_gpt":0.23314005249944425,"score_spread":0.20108379853173186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2283666941","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001704013,0.00023095962,0.97435975,0.0006727047,0.000073925294,0.0001669581,0.00008757857,0.00003720368,0.022666868],"genre_scores_gemma":[0.2734758,0.0024310006,0.6833495,0.00067444576,0.00044868022,0.0013387698,0.00031484233,0.00015772885,0.037809223],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976562,0.001085032,0.000093838986,0.00031417992,0.000642139,0.00020858279],"domain_scores_gemma":[0.9992607,0.0004032654,0.00005220302,0.000088993875,0.00011121848,0.00008358702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021664638,0.0013794216,0.0012269644,0.0012035273,0.0020341664,0.002844351,0.0040536546,0.002592551,0.011026402],"category_scores_gemma":[0.0027750954,0.00075354596,0.0020134125,0.0020298432,0.0027706495,0.004132763,0.0034897963,0.003650247,0.0014266777],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007935847,0.000033084892,0.00003663694,0.00009142788,0.00001673616,0.00006834799,0.00011461874,0.09428181,0.00058219,0.8943851,0.0023413575,0.008040683],"study_design_scores_gemma":[0.000026210377,0.00006319409,0.000070480826,0.00006469189,0.000023194969,0.00017325365,0.00016312268,0.35509887,0.000491286,0.61295056,0.030842388,0.000032691063],"about_ca_topic_score_codex":0.0030760816,"about_ca_topic_score_gemma":0.002941372,"teacher_disagreement_score":0.011026402,"about_ca_system_score_codex":0.0028788901,"about_ca_system_score_gemma":0.003114468,"threshold_uncertainty_score":0.03688705},"labels":[],"label_agreement":null},{"id":"W2284072216","doi":"","title":"Modeling Taxi Trip Generation Using GPS Data: The Montreal Case","year":2016,"lang":"en","type":"article","venue":"Transportation Research Board 95th Annual MeetingTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Taxis; TRIPS architecture; Global Positioning System; Trip generation; Transport engineering; Travel survey; Geography; Transit (satellite); Service (business); Public transport; Scale (ratio); Computer science; Travel behavior; Business; Marketing; Engineering; Telecommunications; Cartography","score_opus":0.19204216116432435,"score_gpt":0.39662501522182225,"score_spread":0.2045828540574979,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2284072216","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9518155,0.00072620733,0.021475913,0.0024915526,0.000042419328,0.00033197927,0.008053698,0.00035943373,0.014703245],"genre_scores_gemma":[0.9848252,0.00043589107,0.005765146,0.00006656983,0.00001852195,0.000106482934,0.001776238,0.000035112873,0.006970929],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994204,0.0002506095,0.000015007103,0.000096695454,0.0000604257,0.00015685869],"domain_scores_gemma":[0.99847287,0.0008842608,0.00019859518,0.00008357626,0.00023510061,0.00012561426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013897285,0.0009320586,0.00044949792,0.0012880174,0.00087446935,0.0017320508,0.0020387045,0.0011911086,0.003768982],"category_scores_gemma":[0.004725511,0.0006952275,0.0007520982,0.0024358958,0.0008430089,0.0011802393,0.0008595003,0.0010512281,0.00044875278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012508284,0.000110751316,0.058387984,0.000047365018,0.00010144452,0.0004920129,0.00025531455,0.9192578,0.00022255279,0.008371454,0.0025149195,0.010113339],"study_design_scores_gemma":[0.000042489766,0.000058619888,0.01174014,0.000012906071,0.0000420442,0.00004286911,0.0002455495,0.984562,0.00008498128,0.0015596307,0.0015755978,0.00003318192],"about_ca_topic_score_codex":0.85649246,"about_ca_topic_score_gemma":0.79079884,"teacher_disagreement_score":0.14350754,"about_ca_system_score_codex":0.011042345,"about_ca_system_score_gemma":0.0030168935,"threshold_uncertainty_score":0.28870535},"labels":[],"label_agreement":null},{"id":"W2288670741","doi":"10.14288/1.0102525","title":"Electronic Payment and Access Systems: Ensuring Interoperability in Vancouver Transportation","year":2016,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Interoperability; Payment; Business; Computer security; Internet privacy; Computer science; Transport engineering; World Wide Web; Engineering; Finance","score_opus":0.006337294667853339,"score_gpt":0.16829810534206982,"score_spread":0.16196081067421647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2288670741","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7922742,0.0012418912,0.051622447,0.024394354,0.00022868894,0.0010589041,0.0009236137,0.0008315216,0.12742442],"genre_scores_gemma":[0.96091616,0.000515826,0.021298517,0.0006135653,0.000028777267,0.00012633097,0.00054212153,0.00009369678,0.015865069],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9776114,0.0069180694,0.0017495239,0.00149774,0.00905474,0.0031684833],"domain_scores_gemma":[0.9525582,0.008818266,0.0018067543,0.004284815,0.030072266,0.0024596897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014361423,0.00047265142,0.0005272072,0.0018558415,0.0079104565,0.017809235,0.0026140907,0.003045387,0.004456124],"category_scores_gemma":[0.04789549,0.0008101283,0.0003489399,0.003719151,0.002811995,0.006090437,0.0061183777,0.0032806823,0.0010992269],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009856998,0.0008382896,0.19248047,0.0003767694,0.00014899009,0.0020605223,0.016723236,0.059248254,0.009312201,0.14984499,0.032983106,0.5349974],"study_design_scores_gemma":[0.00031524684,0.00065822183,0.22410527,0.0013618288,0.0002687916,0.0012041242,0.055456452,0.31420884,0.020359328,0.06972192,0.31173408,0.00060590403],"about_ca_topic_score_codex":0.8168597,"about_ca_topic_score_gemma":0.7756921,"teacher_disagreement_score":0.18314028,"about_ca_system_score_codex":0.026901713,"about_ca_system_score_gemma":0.06349988,"threshold_uncertainty_score":0.36843765},"labels":[],"label_agreement":null},{"id":"W2290826992","doi":"","title":"The Internet of Everything: Fridgebots, Smart Sneakers, and Connected Cars","year":2015,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Presentation (obstetrics); The Internet; Technology transfer; Public relations; Library science; Management; Sociology; Media studies; Engineering; Political science; Business; Computer science; Knowledge management; World Wide Web; Economics","score_opus":0.018521999914127164,"score_gpt":0.2128625824823205,"score_spread":0.19434058256819334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2290826992","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042159002,0.03562774,0.008864947,0.05657184,0.0056571946,0.000068660745,0.00020571811,0.0005911771,0.85025376],"genre_scores_gemma":[0.40344694,0.048701577,0.00839656,0.0087812105,0.0018973618,0.00007076083,0.00041325175,0.00028304738,0.52800924],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995684,0.00011142017,0.000011583539,0.00004833347,0.00014425004,0.00011602925],"domain_scores_gemma":[0.9995665,0.00010798184,0.000024593031,0.00002480862,0.00007688846,0.00019934526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005691664,0.0003546547,0.00016227449,0.0006308519,0.0021033168,0.006390325,0.0005604041,0.001352143,0.020994978],"category_scores_gemma":[0.0011499692,0.00020411047,0.00022370135,0.00089916965,0.0022655388,0.009630318,0.0021925576,0.0013922594,0.0033936645],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001629239,0.00015210207,0.0030876223,0.00040888984,0.000023483804,0.000450462,0.0062498013,0.00061201694,0.0011277383,0.22142668,0.37732962,0.38896865],"study_design_scores_gemma":[0.0000051576567,0.000048811016,0.0015141865,0.00033658606,0.000014202094,0.00027974785,0.007856856,0.00041943853,0.00035132474,0.022238621,0.9669138,0.000021212945],"about_ca_topic_score_codex":0.0121330675,"about_ca_topic_score_gemma":0.04276253,"teacher_disagreement_score":0.020994978,"about_ca_system_score_codex":0.0016702804,"about_ca_system_score_gemma":0.001397122,"threshold_uncertainty_score":0.07023525},"labels":[],"label_agreement":null},{"id":"W2295595685","doi":"10.1609/aaai.v28i1.9034","title":"Scheduling for Transfers in Pickup and Delivery Problems with Very Large Neighborhood Search","year":2014,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Office of Naval Research; York University; Center for Urban Science and Progress; National Science Foundation","keywords":"Pickup; Benchmark (surveying); Computer science; Scheduling (production processes); Transfer (computing); Set (abstract data type); Mathematical optimization; Mathematics; Parallel computing; Artificial intelligence","score_opus":0.045937613441096814,"score_gpt":0.2547736107056953,"score_spread":0.2088359972645985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2295595685","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1811171,0.0007286726,0.8114939,0.0005568474,0.0000865559,0.0003073652,0.00026450664,0.00046587831,0.0049791886],"genre_scores_gemma":[0.77247274,0.0002919755,0.22204845,0.00010975615,0.000051515657,0.0005026472,0.0005820681,0.00014022103,0.003800688],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991371,0.0004138029,0.000043282624,0.0001619007,0.00014885832,0.00009506675],"domain_scores_gemma":[0.99784493,0.0016185625,0.00018776763,0.000092791764,0.0001354639,0.00012033849],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018198955,0.00067161315,0.0012473257,0.00062890386,0.0010661158,0.00067766395,0.0015441969,0.0009634941,0.0026352885],"category_scores_gemma":[0.005491047,0.0005634272,0.00074783014,0.00089662656,0.00079352147,0.0015685876,0.0010243151,0.001033304,0.00029268474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009100237,0.000100088095,0.0006177441,0.000055025386,0.000030857966,0.0000670038,0.000060288152,0.9744834,0.00040713628,0.006393295,0.0011794255,0.016514728],"study_design_scores_gemma":[0.00003236811,0.00006357586,0.00016868024,0.000005069379,0.000008319797,0.000017418124,0.00003767575,0.99154073,0.00025069102,0.007129019,0.00074162945,0.0000048824463],"about_ca_topic_score_codex":0.0094419075,"about_ca_topic_score_gemma":0.011964311,"teacher_disagreement_score":0.0094419075,"about_ca_system_score_codex":0.0012397328,"about_ca_system_score_gemma":0.0014503332,"threshold_uncertainty_score":0.018773913},"labels":[],"label_agreement":null},{"id":"W2297545599","doi":"","title":"Recherche à voisinage large pour le problème de tournées de véhicules à voyages multiples","year":2016,"lang":"fr","type":"article","venue":"ORBi (University of Liège)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Physics","score_opus":0.05448977293094563,"score_gpt":0.24752217087906025,"score_spread":0.1930323979481146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2297545599","genre_codex":"editorial","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006335627,0.06790219,0.042504277,0.25815293,0.5876216,0.00019064227,0.0007370366,0.00038206734,0.036173582],"genre_scores_gemma":[0.08443263,0.07058817,0.04726036,0.032797974,0.47289503,0.00035188362,0.0015763743,0.00080225826,0.28929538],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955057,0.001262294,0.00028493395,0.0009053231,0.0016894462,0.00035235353],"domain_scores_gemma":[0.96985596,0.01932007,0.00083401933,0.00078490586,0.0077514504,0.0014535931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007795197,0.0019030493,0.0025876926,0.0020949566,0.0025818225,0.0060301833,0.0030891513,0.00840236,0.031049017],"category_scores_gemma":[0.029463807,0.00066992006,0.0029088613,0.0012657276,0.0032551296,0.005850823,0.0013217076,0.008955877,0.004920796],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021095619,0.00010019715,0.00034837393,0.0012740685,0.00012678033,0.00054295856,0.00024692458,0.0033517622,0.0010343648,0.07492114,0.8583741,0.059468336],"study_design_scores_gemma":[0.00009423531,0.00011832387,0.0008092511,0.00060660124,0.00012384493,0.00043242684,0.00048855407,0.008072586,0.0006426195,0.04235929,0.9461895,0.00006271064],"about_ca_topic_score_codex":0.010600258,"about_ca_topic_score_gemma":0.007795684,"teacher_disagreement_score":0.031049017,"about_ca_system_score_codex":0.004028018,"about_ca_system_score_gemma":0.004799611,"threshold_uncertainty_score":0.10386932},"labels":[],"label_agreement":null},{"id":"W2298962992","doi":"","title":"Plutos Services: Lead Generation System for the Hotel Advertising Industry","year":2010,"lang":"en","type":"article","venue":"Summit (Simon Fraser University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Advertising; Lead (geology); Marketing; Commerce","score_opus":0.013241220115451013,"score_gpt":0.1998232245386349,"score_spread":0.1865820044231839,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2298962992","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12612735,0.00082768605,0.24744423,0.0040658414,0.00063032703,0.0028060568,0.01279605,0.12136672,0.48393568],"genre_scores_gemma":[0.6118007,0.00063918374,0.127309,0.0008504291,0.00029374548,0.0013089696,0.014367508,0.004334337,0.23909608],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99934,0.00015130635,0.000028611585,0.000107618755,0.00025054347,0.00012198432],"domain_scores_gemma":[0.99895513,0.00015194058,0.00006680698,0.00016598777,0.00037097067,0.0002892174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087586197,0.00073873054,0.00025966478,0.0015252583,0.0014682491,0.0024582678,0.0010964455,0.0006764892,0.060991805],"category_scores_gemma":[0.0018113891,0.0002559176,0.0002636334,0.0018382233,0.0003844599,0.0013010299,0.0016689759,0.00056518544,0.02319832],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021466555,0.00068404473,0.024535349,0.00041821398,0.000032766548,0.000952552,0.0023906266,0.016256496,0.0067492453,0.03785613,0.36934653,0.5386313],"study_design_scores_gemma":[0.00040286567,0.0005457264,0.0073769586,0.000092171016,0.0000452148,0.00060672325,0.0011093937,0.078617804,0.0070108846,0.0067831976,0.8973056,0.0001034537],"about_ca_topic_score_codex":0.020508386,"about_ca_topic_score_gemma":0.026757514,"teacher_disagreement_score":0.060991805,"about_ca_system_score_codex":0.002362082,"about_ca_system_score_gemma":0.0032269675,"threshold_uncertainty_score":0.2040379},"labels":[],"label_agreement":null},{"id":"W2304343212","doi":"10.3141/2540-05","title":"Evaluating Pay-on-Entry Versus Proof-of-Payment Ticketing in Light Rail Transit","year":2016,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Revenue; Light rail transit; Payment; Dwell time; Transit system; Transport engineering; Transit (satellite); Business; Finance; Public transport; Engineering","score_opus":0.13731381831139108,"score_gpt":0.4109862042143005,"score_spread":0.27367238590290943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2304343212","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9948813,0.00013922335,0.0009238748,0.0001537715,0.000010077874,0.00018469674,0.00021407794,0.000023027558,0.0034699668],"genre_scores_gemma":[0.99802125,0.000083932384,0.0007144278,0.000024160126,0.000005946985,0.00004397472,0.00019938096,0.000006268199,0.00090064],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99546933,0.002599701,0.00013875369,0.00032614908,0.00065529445,0.0008107885],"domain_scores_gemma":[0.97579783,0.018748038,0.0023495718,0.0004402354,0.0014988858,0.0011655892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0074915923,0.0008989589,0.00095033064,0.00086769165,0.00063102867,0.0030795583,0.0014130473,0.0014913178,0.003393692],"category_scores_gemma":[0.019332778,0.00048595932,0.0011490494,0.0011944392,0.0012352272,0.002911547,0.0010326736,0.002110003,0.0003553717],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0060232054,0.0038946692,0.09336762,0.00044130845,0.00034514745,0.00033688726,0.00043172532,0.8529893,0.0016693543,0.010319699,0.0017274119,0.028453672],"study_design_scores_gemma":[0.00052344566,0.009071095,0.06717422,0.0000773206,0.000284574,0.00006823798,0.0014324251,0.9159879,0.0017315914,0.0018260415,0.0017317334,0.00009142274],"about_ca_topic_score_codex":0.13524523,"about_ca_topic_score_gemma":0.10605377,"teacher_disagreement_score":0.13524523,"about_ca_system_score_codex":0.012020503,"about_ca_system_score_gemma":0.0051445314,"threshold_uncertainty_score":0.268916},"labels":[],"label_agreement":null},{"id":"W2314873538","doi":"10.1068/b130063p","title":"A Prism-Based and Gap-Based Approach to Shopping Location Choice","year":2014,"lang":"en","type":"article","venue":"Environment and Planning B Planning and Design","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; IBI Group (Canada)","funders":"","keywords":"Scheduling (production processes); Computer science; Operations research; Mathematical optimization; Mathematics","score_opus":0.036440957031648916,"score_gpt":0.22310526175619422,"score_spread":0.18666430472454532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2314873538","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077976743,0.00014735956,0.9766104,0.0006240106,0.0000702616,0.00008059075,0.00060135114,0.00014513337,0.013923221],"genre_scores_gemma":[0.52324647,0.00071790727,0.45327523,0.00044496916,0.00009825889,0.0004926955,0.0009308125,0.0001607799,0.020632934],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99798346,0.0008432253,0.0001055537,0.00038764343,0.00043494464,0.0002452185],"domain_scores_gemma":[0.99802005,0.0008548818,0.00023753988,0.0002989647,0.00031407637,0.0002743962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025395125,0.00082181493,0.001125394,0.000899596,0.0008331501,0.0023746532,0.004257371,0.0015744824,0.009686441],"category_scores_gemma":[0.005107527,0.00080263405,0.0025269398,0.0019448032,0.001825009,0.0032148028,0.0039793923,0.0031421802,0.0015918224],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006669705,0.000059427584,0.00095466024,0.00008708497,0.00004472728,0.0001451439,0.00022792222,0.48623595,0.0004483766,0.5016892,0.0016294064,0.008411357],"study_design_scores_gemma":[0.000021034426,0.000045421708,0.00017340847,0.000014990179,0.000016632855,0.00006258722,0.00008340201,0.80937994,0.00016362118,0.18348348,0.0065338435,0.000021681526],"about_ca_topic_score_codex":0.013710515,"about_ca_topic_score_gemma":0.009790008,"teacher_disagreement_score":0.013710515,"about_ca_system_score_codex":0.0026246721,"about_ca_system_score_gemma":0.0031176927,"threshold_uncertainty_score":0.032404363},"labels":[],"label_agreement":null},{"id":"W2315255139","doi":"10.11175/easts.11.1346","title":"Paratransit Transport in Indonesia: Characteristics and User Perceptions","year":2015,"lang":"en","type":"article","venue":"Journal of the Eastern Asia Society for transportation studies/Journal of the Eastern Asia Society for Transportation Studies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Paratransit; Metropolitan area; Public transport; Indonesian; Business; Perception; Service (business); Transport engineering; Mode (computer interface); Marketing; Advertising; Geography; Engineering; Computer science; Psychology","score_opus":0.04994268169490921,"score_gpt":0.30229235167299995,"score_spread":0.2523496699780907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2315255139","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988104,0.00001749854,0.000027481772,0.00003302625,0.0000017483167,0.000005335511,0.000056532266,0.0000019814047,0.0010458571],"genre_scores_gemma":[0.9992912,0.000054003925,0.000054955424,0.00001863274,0.0000015893191,0.000007600729,0.000054446642,0.0000015073813,0.0005161346],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999811,0.000039726438,0.000022666114,0.000022474587,0.00005976728,0.00004453038],"domain_scores_gemma":[0.9993599,0.00014756457,0.00017678693,0.000022770562,0.00012848024,0.00016453746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025004012,0.00011468224,0.00014870429,0.0003115275,0.00055522664,0.0008061025,0.00013855142,0.00017961307,0.0023555357],"category_scores_gemma":[0.00084606616,0.00010586114,0.0001531328,0.0006559173,0.00022769374,0.0004207362,0.00035312722,0.00031917225,0.0003496492],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010345462,0.00026371417,0.96059424,0.00007498406,0.000013421701,0.0007986105,0.022095919,0.00013588223,0.002157855,0.00016369531,0.0006027499,0.012995387],"study_design_scores_gemma":[0.0000030419296,0.00019833235,0.9361155,0.000022268938,0.00001254768,0.0006915564,0.060134485,0.000607414,0.00034155964,0.000032361953,0.0018261948,0.000014708653],"about_ca_topic_score_codex":0.0120416675,"about_ca_topic_score_gemma":0.014623926,"teacher_disagreement_score":0.0120416675,"about_ca_system_score_codex":0.00039893537,"about_ca_system_score_gemma":0.00031888662,"threshold_uncertainty_score":0.023943126},"labels":[],"label_agreement":null},{"id":"W2334220800","doi":"10.3166/jesa.46.835-854","title":"Chargement de véhicules à l’aide d’un convoyeur","year":2012,"lang":"fr","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Political science","score_opus":0.027434148498230757,"score_gpt":0.2512344908575013,"score_spread":0.22380034235927057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2334220800","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90812564,0.0010390626,0.052877676,0.00093019096,0.00042562597,0.00013712297,0.00058080745,0.0005500403,0.03533378],"genre_scores_gemma":[0.97194517,0.00022722788,0.004083116,0.000056564782,0.00004527483,0.00003241762,0.00038395444,0.000043656924,0.023182577],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989513,0.00018562874,0.00003114734,0.00018143191,0.00037653383,0.00027386055],"domain_scores_gemma":[0.99932444,0.00017695977,0.000052873853,0.0000624709,0.00026505694,0.000118137905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070768583,0.0008861016,0.0008498949,0.0010247764,0.001406391,0.002654651,0.0012432087,0.0017970958,0.013524786],"category_scores_gemma":[0.0025929937,0.0003221578,0.0011348044,0.00091438886,0.0006167993,0.0015235498,0.0014609535,0.0009267074,0.0018764132],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006373104,0.0018764779,0.09196543,0.00079656654,0.00068386825,0.007918672,0.0043800846,0.3252053,0.07692195,0.061544538,0.021519635,0.4008144],"study_design_scores_gemma":[0.0006606896,0.0031991731,0.17136484,0.00025063346,0.0004550599,0.003886082,0.0064029857,0.6057054,0.06910934,0.025783027,0.11268753,0.00049530674],"about_ca_topic_score_codex":0.055184703,"about_ca_topic_score_gemma":0.026072234,"teacher_disagreement_score":0.055184703,"about_ca_system_score_codex":0.0022627057,"about_ca_system_score_gemma":0.0017066849,"threshold_uncertainty_score":0.109726965},"labels":[],"label_agreement":null},{"id":"W2338617271","doi":"","title":"Understanding When Carsharing Displaces Vehicle Ownership","year":2016,"lang":"en","type":"article","venue":"Transportation Research Board 95th Annual MeetingTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Car ownership; Renting; Business; Apartment; Service (business); Car sharing; Bivariate analysis; Work (physics); Public transport; Marketing; Demographic economics; Transport engineering; Economics; Engineering","score_opus":0.1753700899669245,"score_gpt":0.3622454076263934,"score_spread":0.1868753176594689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2338617271","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9919193,0.00045594302,0.0004182676,0.0016524845,0.000017767652,0.000009213149,0.000049241517,0.0000037270165,0.005474077],"genre_scores_gemma":[0.99938095,0.00015652944,0.000089560075,0.0000634941,0.0000049390123,0.0000023175703,0.000017471888,0.0000012511264,0.00028359686],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989391,0.00031208046,0.000049519538,0.00016667608,0.00020219457,0.0003303934],"domain_scores_gemma":[0.99458164,0.002100592,0.0019066939,0.00013445398,0.0005451931,0.0007314637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013546945,0.00013504646,0.0001676943,0.0009063856,0.00060556905,0.0027215327,0.00055514515,0.0007264934,0.004536127],"category_scores_gemma":[0.008307706,0.00019791491,0.0002319384,0.00064907,0.0017320294,0.003748103,0.0012769476,0.0009210658,0.00023842165],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052682622,0.00013585077,0.9378234,0.00006923442,0.00003068171,0.0002795301,0.020365862,0.00015490752,0.0005725679,0.006004307,0.00072591583,0.03378512],"study_design_scores_gemma":[0.0000029131577,0.000080657745,0.8517094,0.00020895983,0.000025351346,0.00030936353,0.13606927,0.0007022435,0.00050158036,0.0041329092,0.006229646,0.000027596261],"about_ca_topic_score_codex":0.014477009,"about_ca_topic_score_gemma":0.018300008,"teacher_disagreement_score":0.014477009,"about_ca_system_score_codex":0.0010087822,"about_ca_system_score_gemma":0.00092028634,"threshold_uncertainty_score":0.028785527},"labels":[],"label_agreement":null},{"id":"W2343438745","doi":"10.18260/p.24456","title":"MAKER: Star Car 2014","year":2015,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Star (game theory); Computer science; Physics; Astrophysics","score_opus":0.021662041534082244,"score_gpt":0.22415284937400556,"score_spread":0.20249080783992332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2343438745","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013845785,0.0010781967,0.0015994846,0.009629902,0.007627443,0.00011814685,0.0050784126,0.002877232,0.9706067],"genre_scores_gemma":[0.002658501,0.0001876732,0.00022374016,0.0003624587,0.00023586773,0.00001266151,0.0013892866,0.0003250914,0.99460477],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.998993,0.000080597645,0.000023131768,0.00019025707,0.00049540325,0.00021769354],"domain_scores_gemma":[0.998643,0.00006819354,0.000034545756,0.00011582747,0.0006959447,0.0004425401],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013377157,0.001053218,0.0007080947,0.0012447644,0.0022621935,0.0070734536,0.0015153418,0.0036721586,0.697934],"category_scores_gemma":[0.0027445157,0.00046918445,0.00050290494,0.0009930917,0.00063226494,0.0031170659,0.002147502,0.0026256035,0.47714987],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008651254,0.000029584691,0.000094865776,0.00002957826,0.0000023446275,0.00003907463,0.000017636099,0.00009065962,0.00012724345,0.0043539302,0.97334665,0.02178192],"study_design_scores_gemma":[0.000011503931,0.000012721287,0.00023992162,0.000016595863,0.0000018781856,0.0000177939,0.00004192158,0.00014787387,0.00014863993,0.0010472827,0.99830794,0.0000059941262],"about_ca_topic_score_codex":0.006909955,"about_ca_topic_score_gemma":0.019828914,"teacher_disagreement_score":0.697934,"about_ca_system_score_codex":0.0022599827,"about_ca_system_score_gemma":0.0032804438,"threshold_uncertainty_score":0.43086052},"labels":[],"label_agreement":null},{"id":"W2354939290","doi":"","title":"Analysis of the Taxi Industry Regulation and Relaxation Regulation","year":2014,"lang":"en","type":"article","venue":"Technology and Economy in Areas of Communications","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Status quo; Cournot competition; Social Welfare; Competition (biology); Stackelberg competition; Industrial organization; Welfare; Game theory; Business; Economics; Perspective (graphical); Deregulation; Public economics; Microeconomics; Market economy; Computer science; Political science","score_opus":0.010496268064261467,"score_gpt":0.2219949088415496,"score_spread":0.21149864077728814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2354939290","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27349934,0.0023353656,0.22443932,0.010880539,0.00045406393,0.00021636173,0.0006218941,0.00021300725,0.48734006],"genre_scores_gemma":[0.9748351,0.00075896876,0.0041685044,0.0004541467,0.00010531656,0.000091205795,0.00010965842,0.000018255168,0.019458925],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9985506,0.00030019556,0.000045330406,0.00024174522,0.000551276,0.0003108051],"domain_scores_gemma":[0.99873,0.00037642132,0.00023933436,0.00010992516,0.00048242873,0.000061941144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012304174,0.00021533342,0.0002766478,0.0007757857,0.001069863,0.002114234,0.0007296775,0.0010222845,0.0072527183],"category_scores_gemma":[0.0028883545,0.00016155103,0.0007686774,0.00060882693,0.0015623717,0.0017113457,0.00073558127,0.0013647245,0.00044055673],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001822509,0.000036309615,0.0016922061,0.000042276642,0.000017667935,0.0001083638,0.00015305971,0.018069232,0.00079273054,0.9673023,0.0026881013,0.009079496],"study_design_scores_gemma":[0.000039883496,0.00011957355,0.01287457,0.00016474686,0.00009390037,0.00023498287,0.0010397617,0.21068543,0.002881213,0.70678383,0.06500766,0.00007444691],"about_ca_topic_score_codex":0.011507119,"about_ca_topic_score_gemma":0.0050718402,"teacher_disagreement_score":0.011507119,"about_ca_system_score_codex":0.0034239045,"about_ca_system_score_gemma":0.0035234753,"threshold_uncertainty_score":0.024842262},"labels":[],"label_agreement":null},{"id":"W2383973243","doi":"","title":"Theories and practices of Car Sharing in foreign countries","year":2006,"lang":"en","type":"article","venue":"Urban Problems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Per capita; Car ownership; China; Car sharing; Business; Public transport; Private transport; Population; Transport engineering; Geography; Engineering","score_opus":0.010890448267097898,"score_gpt":0.228140374301534,"score_spread":0.2172499260344361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2383973243","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19860277,0.0058559277,0.018583037,0.0076407497,0.0001477584,0.000071265036,0.00006390173,0.000028353492,0.76900625],"genre_scores_gemma":[0.9877038,0.0022372408,0.002171847,0.00020368301,0.000024439243,0.000042153715,0.000021481546,0.000008922455,0.00758633],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9974637,0.0015661208,0.00008368812,0.00026737482,0.0002294027,0.0003896708],"domain_scores_gemma":[0.9974796,0.0011967978,0.0004477236,0.0003938525,0.00031372733,0.00016836695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031778053,0.0004898569,0.00026234533,0.0025443644,0.0050151097,0.00728599,0.0012594608,0.0016618075,0.0048271692],"category_scores_gemma":[0.0044959052,0.00026537423,0.0004370229,0.0035054684,0.015908752,0.005486888,0.0030311518,0.0014825948,0.00041183297],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006495496,0.000017000948,0.001195144,0.000029422865,0.000004166699,0.00010584582,0.019410923,0.0007706916,0.000026543117,0.9706979,0.0005432755,0.007192462],"study_design_scores_gemma":[0.000023528577,0.000067485926,0.00614892,0.0010144408,0.000029424498,0.000514508,0.11280183,0.0050895093,0.0005711799,0.68767256,0.18601821,0.000048489113],"about_ca_topic_score_codex":0.01171176,"about_ca_topic_score_gemma":0.0052498966,"teacher_disagreement_score":0.01171176,"about_ca_system_score_codex":0.00695587,"about_ca_system_score_gemma":0.003259991,"threshold_uncertainty_score":0.050468683},"labels":[],"label_agreement":null},{"id":"W2395308537","doi":"","title":"Transport's digital age transition","year":2015,"lang":"en","type":"article","venue":"UWE Research Repository (UWE Bristol)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Information Age; Digital Revolution; Quarter (Canadian coin); Business; Political science; Economy; Economics; History; Law","score_opus":0.06956769841725469,"score_gpt":0.30302686843646,"score_spread":0.2334591700192053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2395308537","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.105948865,0.023091674,0.0049933614,0.19243571,0.0054197875,0.00007914841,0.0014467736,0.00034350192,0.66624117],"genre_scores_gemma":[0.79166114,0.020995768,0.0020504722,0.012470294,0.0010952979,0.00009118586,0.00061524374,0.000104156294,0.17091647],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99921167,0.00016046091,0.00005126145,0.00013598986,0.00023720827,0.00020346642],"domain_scores_gemma":[0.99943537,0.000119141856,0.00007564693,0.000054599008,0.00012141609,0.00019375462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088110694,0.0002163907,0.00014533085,0.00091730955,0.0025072645,0.007514979,0.00043308493,0.0026901762,0.018823676],"category_scores_gemma":[0.0022280249,0.00012956583,0.000298776,0.0015121383,0.0037242696,0.008714556,0.0046381303,0.0023727696,0.0030338978],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044547593,0.000033168664,0.0024894718,0.00015471176,0.000004852348,0.0004133113,0.012259033,0.00014867945,0.0005911413,0.81435454,0.089669466,0.079837136],"study_design_scores_gemma":[0.0000022942295,0.000026969816,0.0029632698,0.00012131297,0.0000019111417,0.00023830979,0.0058861617,0.00009640557,0.00016843458,0.0186268,0.9718608,0.0000073620145],"about_ca_topic_score_codex":0.012543733,"about_ca_topic_score_gemma":0.010964758,"teacher_disagreement_score":0.018823676,"about_ca_system_score_codex":0.005855715,"about_ca_system_score_gemma":0.00289164,"threshold_uncertainty_score":0.06297147},"labels":[],"label_agreement":null},{"id":"W2398231527","doi":"10.1080/03155986.2006.11732749","title":"The Pickup And Delivery Problem With Time Windows And Transshipment","year":2006,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":122,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"HEC Montréal; Simon Fraser University","funders":"","keywords":"Transshipment (information security); Pickup; Computer science; Service (business); Point (geometry); Operations research; Business; Transport engineering; Operations management; Engineering; Marketing; Computer security; Mathematics; Artificial intelligence","score_opus":0.01759764908911724,"score_gpt":0.24845575447519772,"score_spread":0.23085810538608048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2398231527","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7846605,0.0021015208,0.19231646,0.0025893794,0.00014151364,0.000363491,0.0006795538,0.000313684,0.016833775],"genre_scores_gemma":[0.93586487,0.0011264954,0.05305994,0.00012507998,0.00012308022,0.00019721901,0.0006131627,0.00011801703,0.00877213],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9946173,0.0024753541,0.00047418659,0.0007601176,0.0008132043,0.00085987465],"domain_scores_gemma":[0.9401584,0.046482217,0.0076124026,0.002690061,0.0010722103,0.001984607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052619576,0.0009952765,0.0012103243,0.0011170715,0.0018882692,0.0026394664,0.0021134093,0.0025654912,0.011040304],"category_scores_gemma":[0.035986207,0.0009526378,0.0010274614,0.002831513,0.0020391839,0.00947801,0.0022762257,0.0028556813,0.0006985688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0039409613,0.0019306652,0.05977181,0.0011805837,0.00049339316,0.005554743,0.005760322,0.3793436,0.0063671293,0.29886198,0.014497515,0.22229736],"study_design_scores_gemma":[0.0006411144,0.0012608891,0.018875584,0.00021469903,0.00030807234,0.0051944936,0.0059864484,0.7796365,0.005887157,0.15030743,0.031447243,0.00024040406],"about_ca_topic_score_codex":0.009065403,"about_ca_topic_score_gemma":0.0044005956,"teacher_disagreement_score":0.011040304,"about_ca_system_score_codex":0.0015192414,"about_ca_system_score_gemma":0.0016246252,"threshold_uncertainty_score":0.03693348},"labels":[],"label_agreement":null},{"id":"W2407427287","doi":"10.1080/03155986.2003.11732670","title":"Vehicle Park Management Through The Goal Programming Model","year":2003,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Laurentian University; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère des Transports","keywords":"Goal programming; Process management; Computer science; Environmental resource management; Business; Operations research; Engineering; Environmental science","score_opus":0.05251683076713118,"score_gpt":0.3234098341968244,"score_spread":0.27089300342969325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2407427287","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022675723,0.0002739316,0.9590875,0.0007131476,0.000040901898,0.00014102928,0.00027590504,0.00027912325,0.016512787],"genre_scores_gemma":[0.6999321,0.00066823745,0.28565457,0.00019525836,0.000039593477,0.00056860695,0.0004602068,0.00010221663,0.012379106],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99891865,0.00052861887,0.000038590228,0.00016101514,0.00018439732,0.00016864315],"domain_scores_gemma":[0.99916565,0.00048360624,0.00009214027,0.00002894195,0.00015511547,0.00007459348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014583312,0.0008686019,0.00059306057,0.0007856491,0.0006435099,0.0027718223,0.0012792088,0.0010430203,0.0040435833],"category_scores_gemma":[0.0015923672,0.00054588146,0.0010675371,0.0010113472,0.0008153334,0.0013413964,0.0011702775,0.0012794647,0.0003838968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029400237,0.000060095746,0.00042849383,0.000052855765,0.000024157884,0.00006797307,0.00005289358,0.94950414,0.00024349387,0.040644478,0.0006543403,0.008237723],"study_design_scores_gemma":[0.000009620672,0.000017370601,0.000049049213,0.000012461015,0.000008834287,0.0000072266503,0.000029641189,0.9874257,0.00011789939,0.010963331,0.0013534543,0.000005410307],"about_ca_topic_score_codex":0.022358632,"about_ca_topic_score_gemma":0.02042863,"teacher_disagreement_score":0.022358632,"about_ca_system_score_codex":0.0021996798,"about_ca_system_score_gemma":0.0034527045,"threshold_uncertainty_score":0.04445696},"labels":[],"label_agreement":null},{"id":"W2418424010","doi":"10.1016/j.proeng.2016.01.327","title":"Which One is More Attractive to Traveler, Taxi or Tailored Taxi? An Empirical Study in China","year":2016,"lang":"en","type":"article","venue":"Procedia Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"National Natural Science Foundation of China","keywords":"China; Binary logit model; Public transport; Preference; Transport engineering; Market penetration; Travel behavior; Service quality; The Internet; Revealed preference; Business; Marketing; Computer science; Advertising; Service (business); Engineering; Geography; World Wide Web; Economics","score_opus":0.0287188448215753,"score_gpt":0.2907492033778731,"score_spread":0.26203035855629775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2418424010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999648,0.00001925166,0.00003163859,0.00002573188,9.745344e-7,0.00000849055,0.000041379022,7.6220033e-7,0.00022381601],"genre_scores_gemma":[0.99931324,0.00005053672,0.000045929242,0.000019000294,0.0000019030061,0.000010585913,0.00011162802,0.0000012748744,0.00044592144],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99905795,0.00023048701,0.00008882923,0.00017999425,0.00016372542,0.00027901804],"domain_scores_gemma":[0.9967591,0.0013862364,0.0006282276,0.00020634975,0.00043463297,0.00058549206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001893798,0.00037278872,0.0005063301,0.0011993787,0.0011060601,0.00077999535,0.0007333366,0.00046988687,0.0035107178],"category_scores_gemma":[0.003555481,0.00033473526,0.0009926122,0.0022986238,0.00080972153,0.0009315632,0.0005691816,0.0007723667,0.0004292226],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013523131,0.00041750545,0.9874536,0.00004925648,0.00007876795,0.0004486332,0.003973633,0.00059709034,0.00029502355,0.00037703873,0.00053062476,0.005643542],"study_design_scores_gemma":[0.000013054881,0.00016121387,0.9889408,0.000011769091,0.000043030253,0.00009756161,0.006260937,0.0037854172,0.0001541381,0.00007010466,0.0004462602,0.000015800655],"about_ca_topic_score_codex":0.08780287,"about_ca_topic_score_gemma":0.08091917,"teacher_disagreement_score":0.08780287,"about_ca_system_score_codex":0.0016115583,"about_ca_system_score_gemma":0.001357804,"threshold_uncertainty_score":0.17458361},"labels":[],"label_agreement":null},{"id":"W244822173","doi":"10.3141/2536-04","title":"What about Free-Floating Carsharing?","year":2015,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Taxis; Public transport; Service (business); Popularity; Business; Transport engineering; Level of service; Car ownership; Mode (computer interface); Marketing; Advertising; Engineering; Computer science","score_opus":0.12787621178648903,"score_gpt":0.379834400963469,"score_spread":0.25195818917698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W244822173","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026027685,0.20857117,0.0005960983,0.7192034,0.016722212,0.000054551852,0.0010121102,0.00007186808,0.027740963],"genre_scores_gemma":[0.24661583,0.3821525,0.0015063682,0.30382112,0.02401412,0.000113247675,0.0011127031,0.0001470032,0.040517215],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9982828,0.00036414983,0.00007508574,0.00018997482,0.00072344736,0.00036459375],"domain_scores_gemma":[0.99254274,0.0016326746,0.0006728534,0.00015567825,0.0027299349,0.0022660873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019020204,0.0002688348,0.00063852133,0.0011005014,0.0027570769,0.0047677592,0.00135627,0.0035792666,0.014806497],"category_scores_gemma":[0.011123046,0.00019019758,0.00045351093,0.0026362222,0.003385522,0.005373271,0.0007682834,0.0033079893,0.0025571305],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018985925,0.0002596915,0.041182194,0.003356134,0.00007793844,0.0007676478,0.0075047086,0.00011174435,0.00037454144,0.009030088,0.42949456,0.50765073],"study_design_scores_gemma":[0.00002803283,0.00019233463,0.05902409,0.0066408566,0.000095924996,0.0017588389,0.047999498,0.00011769531,0.00037743078,0.006261407,0.87741786,0.00008597415],"about_ca_topic_score_codex":0.2234071,"about_ca_topic_score_gemma":0.3162691,"teacher_disagreement_score":0.2234071,"about_ca_system_score_codex":0.006810879,"about_ca_system_score_gemma":0.010056797,"threshold_uncertainty_score":0.44421345},"labels":[],"label_agreement":null},{"id":"W2460734736","doi":"10.2139/ssrn.2797557","title":"Has Uber Made it Easier to Get a Ride in the Rain?","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Rheinische Friedrich-Wilhelms-Universität Bonn","keywords":"Complaint; Agricultural economics; Geography; Toxicology; Economics; Political science; Biology","score_opus":0.012233982633197965,"score_gpt":0.23216047783669158,"score_spread":0.2199264952034936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2460734736","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27605233,0.0248545,0.0023416246,0.30125776,0.016731419,0.000076538025,0.0017449062,0.00020123212,0.3767397],"genre_scores_gemma":[0.8279593,0.014539349,0.0014582175,0.034641415,0.0030696902,0.000044340624,0.000562769,0.00026855135,0.1174564],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9980586,0.0005065447,0.00007432986,0.00020699805,0.0003509134,0.0008025328],"domain_scores_gemma":[0.99717855,0.0004595364,0.00044584772,0.00020004302,0.0010193291,0.00069667434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032389653,0.00032471467,0.0006500082,0.00060184626,0.0032672784,0.0050978856,0.00091337186,0.0023933493,0.05180938],"category_scores_gemma":[0.010375508,0.00020777549,0.00044460982,0.0012202901,0.0025706247,0.00635194,0.0015786543,0.0026435768,0.007613943],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016371198,0.0007944801,0.12473957,0.0015217809,0.00031422492,0.0013741374,0.026477223,0.0006175203,0.0015704184,0.11342042,0.29936296,0.42817017],"study_design_scores_gemma":[0.000076362165,0.00027372094,0.10567766,0.0010574638,0.00013241202,0.00052746857,0.07170952,0.00026318588,0.00087963295,0.012154533,0.807134,0.0001141006],"about_ca_topic_score_codex":0.053300075,"about_ca_topic_score_gemma":0.073454596,"teacher_disagreement_score":0.053300075,"about_ca_system_score_codex":0.0021192753,"about_ca_system_score_gemma":0.002387819,"threshold_uncertainty_score":0.17331964},"labels":[],"label_agreement":null},{"id":"W2470846596","doi":"10.11575/prism/24763","title":"A Hybrid Search Method for Evolutionary Dynamic Optimization of the 3-dimensional Personnel Assignment Problem and its Case Study Evaluation at The City of Calgary","year":2015,"lang":"en","type":"dissertation","venue":"PRISM (University of Calgary)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Operations research; Mathematical optimization; Engineering; Mathematics","score_opus":0.02413469520998493,"score_gpt":0.2716541686138119,"score_spread":0.247519473403827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2470846596","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12531297,0.000820813,0.8511375,0.0006566181,0.00012355992,0.00037309184,0.0001916338,0.00038660876,0.020997122],"genre_scores_gemma":[0.5048991,0.00046270338,0.48410967,0.00020176497,0.000037010923,0.00075697084,0.00026788772,0.000091169415,0.009173738],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999572,0.00018887705,0.000019539882,0.000058084508,0.00010133838,0.000060276685],"domain_scores_gemma":[0.99938464,0.0004066861,0.00003892099,0.00002480425,0.000109028326,0.000035843554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013050479,0.00075310626,0.0008012044,0.0010918836,0.00056335656,0.0010465871,0.0010897772,0.0015387653,0.003415852],"category_scores_gemma":[0.0019177729,0.00036430327,0.0009354611,0.0010621136,0.0004941772,0.0004962894,0.00094762945,0.0007852232,0.00023651434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039649145,0.000050616163,0.0005389042,0.00006083656,0.000033320044,0.00009284947,0.000052944917,0.96196,0.0008754815,0.006332243,0.0007183454,0.029244825],"study_design_scores_gemma":[0.000014317844,0.000028515547,0.00012408604,0.000007409314,0.0000069954567,0.000014163754,0.000025165555,0.9980813,0.00016502832,0.0007337261,0.00079502515,0.0000042042343],"about_ca_topic_score_codex":0.015963735,"about_ca_topic_score_gemma":0.015595466,"teacher_disagreement_score":0.98403627,"about_ca_system_score_codex":0.0011700373,"about_ca_system_score_gemma":0.0013724111,"threshold_uncertainty_score":0.03174162},"labels":[],"label_agreement":null},{"id":"W2471645431","doi":"10.1016/j.trpro.2016.05.232","title":"Public Views towards Implementation of Automated Vehicles in Urban Areas","year":2016,"lang":"en","type":"article","venue":"Transportation research procedia","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":246,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Taxis; Transport engineering; Public transport; Headway; Quarter (Canadian coin); Computer science; Pooling; Computer security; Business; Engineering; Geography","score_opus":0.12286919997083195,"score_gpt":0.3863738640748951,"score_spread":0.26350466410406315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2471645431","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99292916,0.00016248284,0.00012426724,0.0009362931,0.000014467264,0.0000072962675,0.00003499177,0.000004150185,0.005786892],"genre_scores_gemma":[0.99883026,0.00018112453,0.000037175807,0.00012377148,0.000012045094,0.0000040397485,0.000020040066,0.0000015125902,0.0007900462],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99820554,0.0008586537,0.00007603838,0.000089714034,0.00046391186,0.00030602666],"domain_scores_gemma":[0.99198455,0.002438312,0.0027277828,0.00018069867,0.0018134484,0.00085532374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022221399,0.000120727214,0.000141622,0.0007316442,0.0009613704,0.0014394938,0.00024134044,0.00049735117,0.002838384],"category_scores_gemma":[0.0050408132,0.00014523152,0.0002047998,0.00060204073,0.0010446879,0.00079793535,0.0009140209,0.0007860872,0.00021989424],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043121108,0.00026022003,0.7917607,0.00035756378,0.000093047835,0.0018737575,0.1350355,0.0013033716,0.0049095233,0.0028252383,0.003380758,0.057769075],"study_design_scores_gemma":[0.000023215951,0.0007247783,0.64587927,0.00026303434,0.00007150819,0.00085619977,0.3179666,0.00092598994,0.0017817604,0.00045768407,0.030968145,0.00008178034],"about_ca_topic_score_codex":0.009286974,"about_ca_topic_score_gemma":0.007770136,"teacher_disagreement_score":0.009286974,"about_ca_system_score_codex":0.0010170839,"about_ca_system_score_gemma":0.00055119576,"threshold_uncertainty_score":0.018465817},"labels":[],"label_agreement":null},{"id":"W2473821854","doi":"","title":"Integrating traveller services: the ride points system","year":2005,"lang":"en","type":"article","venue":"BIBSYS Brage (BIBSYS (Norway))","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ministère des Transports; Public Works and Government Services Canada; Transport Canada","keywords":"Computer science; Business","score_opus":0.00930185674789388,"score_gpt":0.205952425134774,"score_spread":0.1966505683868801,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2473821854","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32132316,0.0017502527,0.23256472,0.0028700952,0.00050797104,0.002260386,0.0044098934,0.064689584,0.369624],"genre_scores_gemma":[0.7757957,0.0010655914,0.08309797,0.00059216935,0.00018512513,0.00046210256,0.0065985275,0.0012455714,0.13095723],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987203,0.0003233601,0.00007347285,0.0002603828,0.00040360924,0.00021893876],"domain_scores_gemma":[0.99924964,0.000070276285,0.000035207122,0.00017762926,0.00026969032,0.00019749661],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008431334,0.0005335405,0.0004619787,0.0010317385,0.00092653354,0.0024548967,0.0014161188,0.0012019239,0.025310071],"category_scores_gemma":[0.0014990411,0.00027829935,0.00037311367,0.0009927191,0.00041560887,0.002531606,0.004271632,0.00070564967,0.012517041],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012301038,0.0013287655,0.018753642,0.00062292157,0.000168953,0.00091616163,0.0019496583,0.012591814,0.028015884,0.029016586,0.07820915,0.82719636],"study_design_scores_gemma":[0.00035269558,0.0015964959,0.015956847,0.00020195643,0.00027858987,0.0015413178,0.0024500154,0.088619374,0.022656871,0.0065315864,0.8595109,0.00030331916],"about_ca_topic_score_codex":0.014174678,"about_ca_topic_score_gemma":0.008061068,"teacher_disagreement_score":0.025310071,"about_ca_system_score_codex":0.00081386126,"about_ca_system_score_gemma":0.0014587722,"threshold_uncertainty_score":0.0846706},"labels":[],"label_agreement":null},{"id":"W2484984088","doi":"10.1007/978-3-642-38085-3","title":"Augmented Environments for Computer-Assisted Interventions","year":2013,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials","funders":"","keywords":"Computer science; Conjunction (astronomy); Psychological intervention; Nice; Human–computer interaction; Multimedia; World Wide Web; Programming language; Medicine; Nursing","score_opus":0.021901189694276065,"score_gpt":0.25293279392344087,"score_spread":0.2310316042291648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2484984088","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0064707673,0.13066538,0.6965993,0.00077813555,0.005470486,0.00018754462,0.0012766771,0.0058342167,0.15271758],"genre_scores_gemma":[0.0904412,0.10302015,0.3252816,0.0006927863,0.0016096586,0.0005553711,0.0026636147,0.0011696389,0.47456595],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99969673,0.00006806255,0.000017123486,0.000040375984,0.0001586137,0.000019023073],"domain_scores_gemma":[0.9997807,0.00011978547,0.000012780968,0.00003886863,0.000036517944,0.00001139635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021419265,0.0014867499,0.0006654622,0.0006900244,0.00024920353,0.0015443381,0.0011947858,0.0012098529,0.048918948],"category_scores_gemma":[0.00053891813,0.00041164653,0.0005304825,0.00089539343,0.00036201705,0.0015017542,0.0018664136,0.0009505946,0.010838209],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018592297,0.000057469668,0.00007269102,0.001242159,0.00005450842,0.00024891132,0.00015449745,0.0040359665,0.013865984,0.02159128,0.08837172,0.870119],"study_design_scores_gemma":[0.000051888535,0.00027359548,0.0008939094,0.0008795786,0.00007876971,0.002489568,0.00014693207,0.01375329,0.00831777,0.026314406,0.9467272,0.00007306069],"about_ca_topic_score_codex":0.00024707758,"about_ca_topic_score_gemma":0.0006327743,"teacher_disagreement_score":0.048918948,"about_ca_system_score_codex":0.00015870114,"about_ca_system_score_gemma":0.00018247323,"threshold_uncertainty_score":0.16365016},"labels":[],"label_agreement":null},{"id":"W2486230375","doi":"","title":"Truck Wapiti truck pick-up Canada 3 personnes","year":2016,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Truck; Business; Engineering; Automotive engineering","score_opus":0.008183600970818808,"score_gpt":0.18465114243311206,"score_spread":0.17646754146229326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2486230375","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15928167,0.0013335071,0.08885141,0.0028779702,0.000920972,0.0013701519,0.03314571,0.010360668,0.7018581],"genre_scores_gemma":[0.2045801,0.0007549759,0.016097672,0.00015976187,0.000022988546,0.00015516108,0.008775879,0.00067013316,0.7687833],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992762,0.000023944505,0.000008753404,0.000105682775,0.0003841511,0.00020130102],"domain_scores_gemma":[0.9997532,0.000012787626,0.000007623798,0.000026950489,0.00013867718,0.00006073902],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00018674711,0.00108201,0.00066993246,0.0009445831,0.004215932,0.002643318,0.0011828915,0.0012353273,0.15029322],"category_scores_gemma":[0.00036926757,0.0009403855,0.00095739466,0.0012614789,0.0006858445,0.00084392395,0.0013388795,0.0011192423,0.03047315],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013070041,0.0004026069,0.036077224,0.00044257246,0.0001355344,0.0023474908,0.0018593031,0.079759695,0.03612453,0.04403206,0.5152094,0.28230262],"study_design_scores_gemma":[0.00012815035,0.00019900591,0.026046166,0.00014806235,0.000064684384,0.0005877615,0.0018817276,0.078223236,0.014777923,0.0020987035,0.8756441,0.00020050457],"about_ca_topic_score_codex":0.9423054,"about_ca_topic_score_gemma":0.9664923,"teacher_disagreement_score":0.84970677,"about_ca_system_score_codex":0.008605384,"about_ca_system_score_gemma":0.012729862,"threshold_uncertainty_score":0.5027809},"labels":[],"label_agreement":null},{"id":"W2493313720","doi":"","title":"Location de Camping-car a Toronto | Location de Van et Truck","year":2016,"lang":"fr","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Truck; Geography; Engineering","score_opus":0.011705865005568163,"score_gpt":0.2551034440350075,"score_spread":0.24339757902943934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2493313720","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14009143,0.0072022895,0.00321658,0.049515616,0.004175081,0.00024915184,0.015326205,0.0010083261,0.7792154],"genre_scores_gemma":[0.18259534,0.0018511026,0.0011868554,0.0012009292,0.00018430181,0.00003397025,0.0024599885,0.00019904152,0.8102885],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99911195,0.00006898853,0.00001666152,0.0000950688,0.00039493595,0.00031233754],"domain_scores_gemma":[0.998672,0.00004920069,0.000044337605,0.000046119032,0.00053464354,0.00065373123],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005561586,0.0004718652,0.00024922256,0.0004439483,0.007753424,0.00459726,0.00065745815,0.0013849746,0.096320994],"category_scores_gemma":[0.0009065247,0.00040655799,0.00028270978,0.0011713633,0.0018813368,0.0011101284,0.0015827361,0.001715841,0.010878577],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001453171,0.0000711771,0.023703448,0.00014722648,0.000015348945,0.0007756704,0.010050838,0.0004611408,0.0021200785,0.009696287,0.8825301,0.070283316],"study_design_scores_gemma":[0.00001037606,0.00003325942,0.037331555,0.00005562436,0.000005976967,0.00009527572,0.0061129294,0.00010538942,0.00029663966,0.00011918703,0.9558098,0.000024027617],"about_ca_topic_score_codex":0.983327,"about_ca_topic_score_gemma":0.99650455,"teacher_disagreement_score":0.903679,"about_ca_system_score_codex":0.02552641,"about_ca_system_score_gemma":0.03735728,"threshold_uncertainty_score":0.3222258},"labels":[],"label_agreement":null},{"id":"W2497451661","doi":"10.4018/978-1-60566-772-0.ch003","title":"A Review of Recent Contribution in Agent-Based Health Care Modeling","year":2010,"lang":"en","type":"review","venue":"IGI Global eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Health care; Computer science; Management science; Data science; Systems engineering; Risk analysis (engineering); Engineering; Medicine; Political science","score_opus":0.046775720258070023,"score_gpt":0.3420761612549752,"score_spread":0.29530044099690517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2497451661","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005991118,0.9586457,0.028905692,0.0027395808,0.0008521923,0.00003646159,0.00009094364,0.00011389387,0.008016519],"genre_scores_gemma":[0.006967354,0.9758045,0.014240768,0.00051344465,0.0008535559,0.000036436515,0.0001438689,0.000022541548,0.0014174653],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99931157,0.00022323045,0.00008710797,0.00010101387,0.00024587617,0.000031191095],"domain_scores_gemma":[0.99802136,0.0014243986,0.000093889896,0.00006402814,0.00033945712,0.000056938465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015081464,0.0010241952,0.0015133353,0.0019648091,0.0003821119,0.0019514516,0.0015958757,0.0015988628,0.0040657003],"category_scores_gemma":[0.0032007897,0.0006020568,0.0009184495,0.0041722767,0.00054978067,0.0019218259,0.00083075213,0.001443459,0.0021683336],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005474439,0.00012915733,0.0009726661,0.013729918,0.00022839982,0.00023359152,0.00021077972,0.021345459,0.00071024447,0.045053072,0.039830156,0.87750185],"study_design_scores_gemma":[0.000024220095,0.00010017653,0.0009317771,0.005401246,0.00023156327,0.0007209863,0.00020957639,0.017939582,0.0006026801,0.028913883,0.94484854,0.00007565342],"about_ca_topic_score_codex":0.0041470686,"about_ca_topic_score_gemma":0.003197555,"teacher_disagreement_score":0.0041470686,"about_ca_system_score_codex":0.0012825766,"about_ca_system_score_gemma":0.0019451206,"threshold_uncertainty_score":0.013601124},"labels":[],"label_agreement":null},{"id":"W2498040910","doi":"10.4018/978-1-59904-885-7.ch125","title":"Mobile Virtual Communities of Commuters","year":2008,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Taxis; Public transport; Global Positioning System; Telephony; Telecommunications; Computer science; The Internet; Passenger information; Transport engineering; Engineering; World Wide Web","score_opus":0.018821989511938073,"score_gpt":0.22520508564902722,"score_spread":0.20638309613708916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2498040910","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07505268,0.0072391327,0.06626385,0.005563159,0.001189652,0.00034577327,0.00037077488,0.0016099008,0.842365],"genre_scores_gemma":[0.47851527,0.004969133,0.03364239,0.0009400491,0.0005255543,0.00046495724,0.0006805684,0.00029372697,0.47996834],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996069,0.00017146824,0.000014775166,0.000070366674,0.00007866441,0.000057799636],"domain_scores_gemma":[0.999233,0.00020178781,0.0000456721,0.00013563734,0.00008254562,0.0003014379],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005941143,0.0003775015,0.00020928979,0.0009964634,0.0025507933,0.005352463,0.0010640114,0.0011636291,0.037110023],"category_scores_gemma":[0.0016002923,0.00021041028,0.0002532387,0.0010191381,0.0011515141,0.0061321175,0.004730762,0.0007034021,0.0055687656],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012133917,0.00016914758,0.0016210743,0.00050979166,0.000019519493,0.0010805832,0.02555947,0.0016084237,0.002494154,0.42928123,0.10720746,0.4303278],"study_design_scores_gemma":[0.000017769336,0.00004525554,0.0005259481,0.0001264734,0.000008426122,0.0006493496,0.004842524,0.0015415442,0.00035460334,0.034284603,0.9575904,0.000013081437],"about_ca_topic_score_codex":0.0010950727,"about_ca_topic_score_gemma":0.0019969305,"teacher_disagreement_score":0.037110023,"about_ca_system_score_codex":0.0007135454,"about_ca_system_score_gemma":0.00066228607,"threshold_uncertainty_score":0.12414545},"labels":[],"label_agreement":null},{"id":"W2508209418","doi":"10.1093/arclin/acw043.22","title":"A-22Performance on the MoCA and Driving Abilities in Parkinson's Disease","year":2016,"lang":"en","type":"article","venue":"Archives of Clinical Neuropsychology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Parkinson's disease; Disease; Audiology; Psychology; Medicine; Physical medicine and rehabilitation; Neuroscience; Internal medicine","score_opus":0.03300907411913889,"score_gpt":0.31497397654494713,"score_spread":0.28196490242580824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2508209418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988776,0.00017461948,0.000030900756,0.000021916827,0.0000053458075,0.000008736738,0.00015031938,0.0000037860302,0.0007266853],"genre_scores_gemma":[0.99945015,0.00005442488,0.000057973448,0.000010161211,0.000004377424,0.000006338665,0.00017386953,9.116329e-7,0.000241778],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999647,0.000077561475,0.00006462607,0.000045518358,0.00011504043,0.000050315994],"domain_scores_gemma":[0.9979589,0.00038980774,0.00088131684,0.000056672277,0.00045590443,0.0002574976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006733282,0.0004216816,0.0002913584,0.0008496337,0.0004350019,0.00074407965,0.00021987496,0.0004225113,0.002085329],"category_scores_gemma":[0.0037857704,0.00011039159,0.0003249655,0.00045661046,0.00025177567,0.00035247288,0.0004956942,0.00037389365,0.0005026437],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004964204,0.000033842407,0.9981523,0.000006258419,0.00002791968,0.000038838753,0.000037956608,0.000029744107,0.00008463971,0.000004552641,0.000057454563,0.0014768025],"study_design_scores_gemma":[0.000002920102,0.0001315168,0.99922764,0.000004049496,0.000012394518,0.0002842034,0.00006141776,0.000088651854,0.000058819584,0.000011539782,0.00011468366,0.0000021117864],"about_ca_topic_score_codex":0.0045256657,"about_ca_topic_score_gemma":0.0071049035,"teacher_disagreement_score":0.0045256657,"about_ca_system_score_codex":0.00024568036,"about_ca_system_score_gemma":0.00021564243,"threshold_uncertainty_score":0.008998632},"labels":[],"label_agreement":null},{"id":"W2509040115","doi":"10.7748/ns.24.5.28.s33","title":"Simplify mileage allowances without delay","year":2009,"lang":"en","type":"article","venue":"Nursing Standard","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Environmental science; Business; Physical medicine and rehabilitation; Medicine","score_opus":0.009615473999060414,"score_gpt":0.27332411403582035,"score_spread":0.2637086400367599,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2509040115","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020780774,0.003054447,0.01753692,0.50117373,0.033884153,0.00025924123,0.0007154394,0.0029142387,0.41968113],"genre_scores_gemma":[0.21842854,0.0021603506,0.012827731,0.2713178,0.008398815,0.0002320966,0.0008802193,0.0006877386,0.4850667],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9957216,0.00046383552,0.00020120744,0.00040521534,0.0023335165,0.00087469904],"domain_scores_gemma":[0.9924907,0.002382793,0.00039298917,0.00091646,0.0028130622,0.0010038939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035395003,0.00077775866,0.00045799368,0.00084653025,0.0035316583,0.0048516174,0.0017104953,0.007792129,0.032563236],"category_scores_gemma":[0.025309704,0.0005417309,0.0010471492,0.0005600792,0.0011255998,0.003440217,0.0017080301,0.0076140906,0.011697849],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000093971605,0.0001346506,0.0015137506,0.00005024869,0.00002872906,0.00016230471,0.00023850972,0.0010260753,0.0011739725,0.02184352,0.9222948,0.051439513],"study_design_scores_gemma":[0.00004775403,0.000061331375,0.0031496843,0.000085014835,0.000028388493,0.00019729591,0.0005366957,0.00117755,0.0008958584,0.0060685035,0.9877011,0.00005085073],"about_ca_topic_score_codex":0.031510722,"about_ca_topic_score_gemma":0.042952366,"teacher_disagreement_score":0.032563236,"about_ca_system_score_codex":0.0026980876,"about_ca_system_score_gemma":0.008223904,"threshold_uncertainty_score":0.10893488},"labels":[],"label_agreement":null},{"id":"W2509984179","doi":"10.1007/978-3-319-44896-1_23","title":"Service Network Design of Bike Sharing Systems with Resource Constraints","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"Deutsche Forschungsgemeinschaft","keywords":"Computer science; TRIPS architecture; Bike sharing; Service (business); Operations research; Shared resource; Redistribution (election); Service level; Network planning and design; Heuristic; Transport engineering; Simulation; Computer network","score_opus":0.020031583761178758,"score_gpt":0.20935597776489678,"score_spread":0.18932439400371803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2509984179","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047740974,0.00076968427,0.92793024,0.00060308387,0.00015516477,0.00021626026,0.00026187414,0.00023574685,0.022087047],"genre_scores_gemma":[0.8994196,0.0011053162,0.07991928,0.00021725916,0.00012547283,0.00036300742,0.00030283927,0.00022856588,0.018318634],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991373,0.00025848852,0.000033120305,0.00014325742,0.00020363528,0.00022414328],"domain_scores_gemma":[0.9991167,0.00045173874,0.000056420104,0.000043575757,0.0002539371,0.0000776208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010846944,0.0010755878,0.0013529023,0.0006945268,0.0011864546,0.0024412328,0.0018684265,0.0012633409,0.008554398],"category_scores_gemma":[0.0027557425,0.000685906,0.0006299915,0.0013299241,0.00076816994,0.001826815,0.0015042566,0.0010112769,0.00078693073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016414195,0.000040071296,0.00022621754,0.00015385293,0.00003256866,0.000091198664,0.000122023346,0.92023605,0.0032553326,0.049866233,0.0025092282,0.023302983],"study_design_scores_gemma":[0.0000087384715,0.000027598348,0.0000491052,0.0000107605865,0.000009843808,0.000024912495,0.00004010492,0.98488194,0.00032273447,0.013697876,0.0009201081,0.000006321335],"about_ca_topic_score_codex":0.01205772,"about_ca_topic_score_gemma":0.009037136,"teacher_disagreement_score":0.01205772,"about_ca_system_score_codex":0.0025789754,"about_ca_system_score_gemma":0.0022149729,"threshold_uncertainty_score":0.028617322},"labels":[],"label_agreement":null},{"id":"W2511288762","doi":"10.1007/s00291-016-0457-8","title":"A continuous approximation model for the fleet composition problem on the rectangular grid","year":2016,"lang":"en","type":"article","venue":"OR Spectrum","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Grid; Computer science; Computation; Constraint (computer-aided design); Mathematical optimization; Heuristic; Sensitivity (control systems); Service (business); Limit (mathematics); Mathematics; Algorithm; Geometry","score_opus":0.01910561187786955,"score_gpt":0.22390535650125223,"score_spread":0.20479974462338268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2511288762","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028874239,0.0005122774,0.9618077,0.0010081199,0.00010001807,0.00004973136,0.0003943824,0.00017013356,0.007083384],"genre_scores_gemma":[0.79961336,0.0012810024,0.17125124,0.00024675738,0.00013137268,0.0002314214,0.0009329073,0.00019783693,0.02611402],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930894,0.00027957218,0.000023718103,0.00015589145,0.000097040494,0.00013476852],"domain_scores_gemma":[0.998376,0.0010391584,0.00015732547,0.000077878336,0.00018922226,0.00016041144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015745583,0.0008812509,0.001780243,0.0007559389,0.00050087506,0.0020466617,0.003038647,0.0022526176,0.008638034],"category_scores_gemma":[0.005124298,0.00079691067,0.0010982272,0.001742876,0.0012459613,0.0021011261,0.0014921253,0.0023871502,0.0006935909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005467912,0.000022559914,0.0002535951,0.00004287616,0.000014107283,0.000056082663,0.000032168547,0.9387013,0.00017961075,0.055924885,0.001302148,0.0034160474],"study_design_scores_gemma":[0.000005629304,0.000005776478,0.000022597349,0.0000034327138,0.0000024695055,0.000006233806,0.000009436558,0.99253947,0.000018258856,0.007081868,0.0003024908,0.0000023472496],"about_ca_topic_score_codex":0.025107106,"about_ca_topic_score_gemma":0.011823099,"teacher_disagreement_score":0.025107106,"about_ca_system_score_codex":0.002023525,"about_ca_system_score_gemma":0.0016713955,"threshold_uncertainty_score":0.04992193},"labels":[],"label_agreement":null},{"id":"W2511688421","doi":"","title":"Planning, Design and Scheduling of Flex-route Transit Service","year":2010,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"FLEX; Scheduling (production processes); Service (business); Transport engineering; Computer science; Transit (satellite); Engineering; Operations research; Operations management; Public transport; Telecommunications; Business","score_opus":0.025309406414140825,"score_gpt":0.30581126393620606,"score_spread":0.28050185752206525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2511688421","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06489804,0.00019732265,0.92294466,0.00013896085,0.000033182427,0.00024720107,0.00015102756,0.0003763626,0.011013203],"genre_scores_gemma":[0.7288782,0.0003409517,0.26565784,0.00003334947,0.000012599799,0.00022781493,0.00022012499,0.00009125646,0.0045378623],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99955624,0.00016551811,0.000016842529,0.00008486067,0.000096827825,0.0000796759],"domain_scores_gemma":[0.99968696,0.00010860588,0.000051741437,0.000023162942,0.000086039436,0.000043492775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000559097,0.0006181257,0.0004318126,0.00045961447,0.0004672572,0.0008250983,0.0008120702,0.00054290326,0.0027359037],"category_scores_gemma":[0.0010406005,0.00035924808,0.0004331642,0.00060272514,0.00044459352,0.0005766541,0.00055933866,0.00047488505,0.00038480788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005374244,0.000022014412,0.000378728,0.000043290598,0.000005622411,0.00004882779,0.000037060807,0.97455806,0.0022068594,0.004606751,0.00038015447,0.01765881],"study_design_scores_gemma":[0.000006338852,0.00004173386,0.00012360203,0.0000033342455,0.0000042162524,0.000014742378,0.00003272,0.99673635,0.0009519217,0.0010844044,0.0009964325,0.0000041553612],"about_ca_topic_score_codex":0.0088222725,"about_ca_topic_score_gemma":0.008725623,"teacher_disagreement_score":0.0088222725,"about_ca_system_score_codex":0.0012262645,"about_ca_system_score_gemma":0.0023929875,"threshold_uncertainty_score":0.017541826},"labels":[],"label_agreement":null},{"id":"W2514006486","doi":"10.1109/ccdc.2016.7531803","title":"Efficient feasibility testing and scheduling for dial-a-ride problem with time-dependent travel time","year":2016,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Science North","funders":"","keywords":"Schedule; Computer science; Scheduling (production processes); Heuristic; Job shop scheduling; Service (business); Public transport; Travel time; Vehicle routing problem; Operations research; Mathematical optimization; Routing (electronic design automation); Real-time computing; Transport engineering; Engineering; Computer network; Mathematics; Artificial intelligence; Economics","score_opus":0.017827799681111693,"score_gpt":0.2204383923499092,"score_spread":0.2026105926687975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2514006486","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1671334,0.0002681978,0.8179331,0.0010476357,0.00010592524,0.0010345022,0.0007600528,0.001312471,0.010404743],"genre_scores_gemma":[0.5645505,0.0002896007,0.42976302,0.00016435473,0.00006371865,0.0005406773,0.0011999934,0.00020314446,0.0032249403],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965681,0.0013883393,0.00016123251,0.00061846006,0.0005990452,0.000664944],"domain_scores_gemma":[0.9886515,0.008702705,0.00087311683,0.0005134843,0.00077081507,0.0004884809],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032195644,0.0014740104,0.0015296638,0.0014815327,0.0014296365,0.0019986834,0.0021517917,0.0015795459,0.00664161],"category_scores_gemma":[0.0126941465,0.0013397275,0.0022148718,0.0014017726,0.001585534,0.0028132522,0.0017471628,0.0016669163,0.00057011266],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005796927,0.00055755844,0.0030858077,0.00034554448,0.000100207064,0.00055893144,0.00019296104,0.91565514,0.0052468157,0.023711087,0.00381191,0.046154458],"study_design_scores_gemma":[0.00007426168,0.00014493521,0.00027294338,0.0000120973755,0.000022246806,0.000057129215,0.00009977223,0.9883074,0.0015441749,0.008842653,0.0006061724,0.000016196262],"about_ca_topic_score_codex":0.014175763,"about_ca_topic_score_gemma":0.010987488,"teacher_disagreement_score":0.014175763,"about_ca_system_score_codex":0.0015410526,"about_ca_system_score_gemma":0.005614552,"threshold_uncertainty_score":0.0281865},"labels":[],"label_agreement":null},{"id":"W2519305231","doi":"10.1016/j.trb.2016.08.006","title":"A comparison of three idling options in long-haul truck scheduling","year":2016,"lang":"en","type":"article","venue":"Transportation Research Part B Methodological","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Truck; Benchmark (surveying); Scheduling (production processes); Engineering; Automotive engineering; Auxiliary power unit; Operations research; Transport engineering; Computer science; Operations management","score_opus":0.5130888821016063,"score_gpt":0.5097444888949701,"score_spread":0.0033443932066361537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2519305231","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8581201,0.0028837458,0.100298226,0.00068441615,0.00038427618,0.00043728758,0.00052016665,0.0005347986,0.036136985],"genre_scores_gemma":[0.98277503,0.00032890323,0.014525787,0.00005581975,0.000018550905,0.00004896358,0.00010060336,0.00005287504,0.0020934276],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998719,0.0006113351,0.000053313073,0.000094009745,0.00021337232,0.00030896213],"domain_scores_gemma":[0.99621826,0.0027186614,0.00015848051,0.0002007863,0.0003312977,0.00037259568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033256032,0.00095415337,0.0014691945,0.0015648379,0.0010630863,0.002579579,0.0018026781,0.0011844011,0.0064327368],"category_scores_gemma":[0.0043704542,0.0003813488,0.000981035,0.0015270312,0.0007233522,0.0020319568,0.00092204666,0.0011577951,0.00041625815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009102231,0.0013793672,0.003930907,0.0007723228,0.00016360142,0.00012263819,0.00039609254,0.75300133,0.00554277,0.021346146,0.002162949,0.20207958],"study_design_scores_gemma":[0.000437091,0.003726396,0.003515945,0.000070743874,0.00021406116,0.00005653279,0.0009267753,0.9756467,0.0037117228,0.008922342,0.002675082,0.000096612814],"about_ca_topic_score_codex":0.0058842422,"about_ca_topic_score_gemma":0.0077716988,"teacher_disagreement_score":0.0064327368,"about_ca_system_score_codex":0.0022843264,"about_ca_system_score_gemma":0.0018739107,"threshold_uncertainty_score":0.021519661},"labels":[],"label_agreement":null},{"id":"W2519373235","doi":"10.1002/atr.1400","title":"Fixed‐route taxi system: route network design and fleet size minimization problems","year":2016,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Taxis; Service (business); Heuristic; Transport engineering; Computer science; Operations research; Minification; Transfer (computing); Linear programming; Total cost; Travel time; Flow network; Fleet management; Public transport; Mathematical optimization; Engineering; Mathematics; Business","score_opus":0.009416222295791983,"score_gpt":0.20611101534969678,"score_spread":0.1966947930539048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2519373235","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11197932,0.0011775139,0.8576804,0.0010147155,0.00011396133,0.00041156597,0.0010062287,0.00034388478,0.02627253],"genre_scores_gemma":[0.76463693,0.0010048733,0.21838813,0.00011013416,0.00006768365,0.0005023726,0.00084740104,0.00015349947,0.014288869],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942386,0.00024517602,0.000016282873,0.000124814,0.00008009553,0.0001097759],"domain_scores_gemma":[0.9992225,0.00039830216,0.00011368452,0.000041106436,0.00013959463,0.000084875384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010039556,0.0010489059,0.00089065684,0.0007402368,0.0005475239,0.0014856636,0.0016944371,0.0014588278,0.006850471],"category_scores_gemma":[0.0021560611,0.0007306416,0.0009427992,0.0013391102,0.0007165461,0.001165319,0.000816547,0.0010167394,0.00053039374],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002946743,0.000022158218,0.00020751156,0.000055373705,0.000014574268,0.000054657805,0.000019619134,0.9859418,0.00037221506,0.004432673,0.0008091589,0.008040723],"study_design_scores_gemma":[0.000018095825,0.000056281337,0.00022464838,0.000012037071,0.000012619148,0.000042245494,0.0000490697,0.99199766,0.00030607352,0.005448216,0.0018247252,0.000008347877],"about_ca_topic_score_codex":0.01386829,"about_ca_topic_score_gemma":0.010650094,"teacher_disagreement_score":0.01386829,"about_ca_system_score_codex":0.0022139351,"about_ca_system_score_gemma":0.0019632399,"threshold_uncertainty_score":0.027575135},"labels":[],"label_agreement":null},{"id":"W2529318302","doi":"10.71781/10043","title":"Recherche tabou pour un problème de tournées de véhicules avec une flotte privée et un transporteur externe","year":2008,"lang":"fr","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Philosophy; Humanities","score_opus":0.01687007936372153,"score_gpt":0.20533662903775474,"score_spread":0.1884665496740332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2529318302","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4891125,0.004636909,0.44648305,0.014128704,0.0013459618,0.00089065154,0.0060400004,0.0010349638,0.03632733],"genre_scores_gemma":[0.7226749,0.0018825275,0.2093581,0.0006828644,0.0005502202,0.0006101795,0.005757541,0.0005377199,0.05794595],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99749494,0.00073372317,0.00010857473,0.00064908806,0.0003788615,0.0006348349],"domain_scores_gemma":[0.97002083,0.025804993,0.000893953,0.0005440801,0.0015495424,0.0011865841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005187328,0.0021396524,0.0034714362,0.0023337232,0.0033852533,0.0061306353,0.0032389697,0.00745131,0.023451177],"category_scores_gemma":[0.038960587,0.0015721791,0.0034160647,0.0020668507,0.0022965884,0.0045399093,0.0019692397,0.00333899,0.001208381],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010948329,0.0005535661,0.016327413,0.0007740794,0.00039761845,0.0011741201,0.0007662908,0.86261517,0.001987823,0.051103495,0.023616564,0.039589122],"study_design_scores_gemma":[0.00019022588,0.00023866135,0.003530878,0.00011584433,0.0001152595,0.00032198537,0.0008532043,0.96726984,0.0006593489,0.021965165,0.0046801283,0.00005957959],"about_ca_topic_score_codex":0.14733003,"about_ca_topic_score_gemma":0.08478433,"teacher_disagreement_score":0.14733003,"about_ca_system_score_codex":0.00374417,"about_ca_system_score_gemma":0.0054119923,"threshold_uncertainty_score":0.29294497},"labels":[],"label_agreement":null},{"id":"W2532844227","doi":"10.1002/atr.1419","title":"A cooperative waiting strategy based on elliptical areas for the Dynamic Pickup and Delivery Problem with Time Windows","year":2016,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Pickup; Computer science; Dynamism; Scheduling (production processes); Dynamic priority scheduling; Mathematical optimization; Operations research; Mathematics; Artificial intelligence; Operating system; Schedule","score_opus":0.007386659979765405,"score_gpt":0.21919153676284023,"score_spread":0.21180487678307483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2532844227","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09895863,0.000195217,0.89825916,0.00010686649,0.000019751373,0.00009921793,0.000026216821,0.00012793881,0.0022069782],"genre_scores_gemma":[0.82944167,0.00019708977,0.1679895,0.000037790927,0.0000164938,0.00015884542,0.00005575318,0.000037665926,0.0020651198],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995683,0.00013617988,0.000021671609,0.000081035694,0.00009958516,0.00009320998],"domain_scores_gemma":[0.9990256,0.00058678415,0.00012813837,0.00004709153,0.000108326174,0.00010406902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012312252,0.00058101275,0.00054138014,0.0006242941,0.00047445408,0.0007202197,0.0012553595,0.00058856024,0.0015744203],"category_scores_gemma":[0.0022263655,0.00028604298,0.0005663211,0.0006146474,0.000548016,0.0009318388,0.0008843455,0.0005984702,0.00015444228],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000109834866,0.00007084604,0.00058963423,0.00005684437,0.000022514085,0.00006850753,0.00012842442,0.94347566,0.0037119272,0.018565597,0.00041249636,0.03278771],"study_design_scores_gemma":[0.000012891733,0.000072943716,0.00009936213,0.0000032848202,0.000008623347,0.00001860681,0.00003283065,0.99587554,0.00060894585,0.0028760862,0.0003857907,0.0000052029122],"about_ca_topic_score_codex":0.005008787,"about_ca_topic_score_gemma":0.0031132586,"teacher_disagreement_score":0.005008787,"about_ca_system_score_codex":0.0008041177,"about_ca_system_score_gemma":0.0011904576,"threshold_uncertainty_score":0.0099592805},"labels":[],"label_agreement":null},{"id":"W2534899703","doi":"","title":"Handbook of Teen and Novice Drivers : Research, Practice, Policy, and Directions","year":2016,"lang":"en","type":"book","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Psychology; Political science; Regional science; Applied psychology; Geography","score_opus":0.024914948408762204,"score_gpt":0.310996295255879,"score_spread":0.28608134684711684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2534899703","genre_codex":"review","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002102442,0.571807,0.0072464556,0.033077903,0.013654503,0.00022099144,0.002223585,0.0006573299,0.3690098],"genre_scores_gemma":[0.006996801,0.32797346,0.00869093,0.0066480953,0.0017089702,0.0003242341,0.001557037,0.00025054583,0.64584994],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99955565,0.00009813615,0.00003617085,0.000038119528,0.00023868759,0.000033240834],"domain_scores_gemma":[0.99871314,0.00047065158,0.00007667336,0.00004986966,0.00045359408,0.00023608432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089885015,0.0007995874,0.0006647111,0.0018978385,0.00071777456,0.0028646418,0.0011490121,0.0014630591,0.04621052],"category_scores_gemma":[0.0024899428,0.0003937439,0.00028303047,0.0024897475,0.0005984994,0.0036126424,0.001337889,0.0022587217,0.017321063],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007208917,0.00006828616,0.00024114929,0.00035410147,0.0000029737807,0.00003504012,0.00058543653,0.000071298215,0.00007862912,0.015119971,0.7764626,0.20697336],"study_design_scores_gemma":[0.000002055633,0.000011806789,0.00036261327,0.00049063726,0.0000019892666,0.00014098363,0.00035168463,0.000025518868,0.000027857328,0.0034912373,0.9950896,0.0000039966103],"about_ca_topic_score_codex":0.0056405654,"about_ca_topic_score_gemma":0.019924402,"teacher_disagreement_score":0.04621052,"about_ca_system_score_codex":0.0010658051,"about_ca_system_score_gemma":0.005701067,"threshold_uncertainty_score":0.1545896},"labels":[],"label_agreement":null},{"id":"W2540409407","doi":"10.14288/1.0220795","title":"Transportation network companies and the ridesourcing industry : a review of impacts and emerging regulatory frameworks for Uber","year":2015,"lang":"en","type":"review","venue":"cIRcle (University of British Columbia)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Business; Transportation industry; Industrial organization; Risk analysis (engineering); Transport engineering; Engineering","score_opus":0.015030419698932977,"score_gpt":0.22364590362712944,"score_spread":0.20861548392819645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2540409407","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011284007,0.9984768,0.000036784833,0.0003610684,0.00006425725,0.0000031005181,0.000008421212,0.0000012791126,0.0009354298],"genre_scores_gemma":[0.0012381928,0.9981792,0.00007645352,0.00018511999,0.000033320088,0.0000034224147,0.000010986541,7.227292e-7,0.00027249492],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99881834,0.00031213707,0.00016651867,0.00014098818,0.00048676954,0.00007515877],"domain_scores_gemma":[0.9960245,0.0024360605,0.00044409337,0.00005850424,0.0009361732,0.00010064886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024404144,0.0006425624,0.0010253931,0.0062681525,0.00066728715,0.0023072385,0.0008998077,0.0016850028,0.0029652272],"category_scores_gemma":[0.0039132433,0.00043693898,0.0008187129,0.009556876,0.0010842346,0.002238054,0.00076517597,0.0014666687,0.00062184955],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044436005,0.00007169266,0.0006094585,0.08805673,0.00019015885,0.00020764988,0.00062352704,0.00065959006,0.00063250423,0.024169175,0.032651998,0.8520831],"study_design_scores_gemma":[0.0000073181186,0.000050231476,0.0021376808,0.038858198,0.00021316894,0.00030437962,0.000487809,0.00010424167,0.00022978937,0.0018507938,0.955733,0.000023359895],"about_ca_topic_score_codex":0.021868479,"about_ca_topic_score_gemma":0.054785565,"teacher_disagreement_score":0.021868479,"about_ca_system_score_codex":0.0031805465,"about_ca_system_score_gemma":0.009608908,"threshold_uncertainty_score":0.043482363},"labels":[],"label_agreement":null},{"id":"W2564833931","doi":"","title":"Dynamic Optimization Models for Ridesharing and Carsharing","year":2014,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Toronto","keywords":"Revenue; Benchmark (surveying); Car sharing; Transport engineering; Revenue management; Service (business); Operations research; Computer science; Fuel efficiency; Business; Engineering; Marketing; Automotive engineering","score_opus":0.014320483251624438,"score_gpt":0.28530251926805805,"score_spread":0.2709820360164336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2564833931","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04138423,0.0034740334,0.8575518,0.0027819157,0.0003749005,0.00022301226,0.0016019837,0.00042792736,0.09218022],"genre_scores_gemma":[0.79123515,0.0050928025,0.10748762,0.00051620835,0.00021851221,0.0008305507,0.0018498064,0.00032439563,0.09244487],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994147,0.00017985566,0.0000215963,0.00013909637,0.00011091582,0.00013384897],"domain_scores_gemma":[0.99897325,0.000657512,0.00012034067,0.000035757734,0.0001450531,0.00006809624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085402775,0.001637872,0.0014937979,0.0007889321,0.00076701015,0.0024937275,0.0019706283,0.0020022038,0.012474823],"category_scores_gemma":[0.0028354728,0.0007612979,0.0014878709,0.0012216031,0.0008519588,0.0014781562,0.0014463464,0.0023214445,0.0011919105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014152606,0.000023112805,0.00013123198,0.00003830102,0.000014759193,0.000031585914,0.000023203576,0.9658409,0.000099535435,0.02940757,0.0014929255,0.002882864],"study_design_scores_gemma":[0.0000067081014,0.000008687082,0.0000715939,0.000007490018,0.0000063583693,0.000007637046,0.000016547874,0.98963404,0.000033915814,0.008219625,0.001982279,0.0000051523084],"about_ca_topic_score_codex":0.030076554,"about_ca_topic_score_gemma":0.019181492,"teacher_disagreement_score":0.030076554,"about_ca_system_score_codex":0.0029579196,"about_ca_system_score_gemma":0.0019946832,"threshold_uncertainty_score":0.05980301},"labels":[],"label_agreement":null},{"id":"W2565613554","doi":"10.1080/15568318.2016.1266425","title":"Where no cars go: Free-floating carshare and inequality of access","year":2016,"lang":"en","type":"article","venue":"International Journal of Sustainable Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Incentive; Business; Census tract; Demographics; Transport engineering; Inequality; Service provider; Service (business); Census; Marketing; Economics; Engineering; Population; Environmental health; Microeconomics","score_opus":0.013849161074805164,"score_gpt":0.2659096923940248,"score_spread":0.2520605313192196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2565613554","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99167305,0.00028964004,0.00035533766,0.0010926418,0.000011261709,0.000008395956,0.00046303286,0.0000031805182,0.0061033755],"genre_scores_gemma":[0.99955946,0.000037044305,0.000032284064,0.000025619225,0.000006640677,0.0000033159322,0.00008810082,0.0000012853702,0.00024615537],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99891233,0.00029043024,0.00005097124,0.00016025658,0.00016352569,0.000422474],"domain_scores_gemma":[0.99669385,0.0009302663,0.0011032503,0.00021315481,0.0002782084,0.00078125246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005274528,0.00011413066,0.0002847315,0.0014925416,0.0011612551,0.0017329092,0.0006376347,0.0005853653,0.007840376],"category_scores_gemma":[0.004390208,0.00009925271,0.0002824964,0.0025236716,0.0015137201,0.0017797514,0.0027611481,0.0008155668,0.0002429253],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008036548,0.00011514425,0.9760079,0.000018442259,0.00004885251,0.00012366919,0.0024127702,0.00039336615,0.00009651807,0.010050851,0.0010778265,0.009574399],"study_design_scores_gemma":[0.0000065585646,0.000044756693,0.9827155,0.00006102458,0.000023104385,0.000098818586,0.008557046,0.001749436,0.000088360866,0.004027703,0.0026133251,0.000014431437],"about_ca_topic_score_codex":0.050857477,"about_ca_topic_score_gemma":0.08422681,"teacher_disagreement_score":0.050857477,"about_ca_system_score_codex":0.0012249151,"about_ca_system_score_gemma":0.00060010096,"threshold_uncertainty_score":0.101122916},"labels":[],"label_agreement":null},{"id":"W2569113864","doi":"10.2139/ssrn.2859018","title":"Shared Mobility for Last-Mile Delivery: Design, Operational Prescriptions and Environmental Impact","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; McGill University","funders":"","keywords":"Mile; Medical prescription; Last mile (transportation); Business; Transport engineering; Environmental planning; Engineering; Environmental science; Geography; Medicine; Nursing","score_opus":0.015123272716129675,"score_gpt":0.24489774548245954,"score_spread":0.22977447276632987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2569113864","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68042916,0.0009164194,0.25384903,0.0036542322,0.00021342162,0.0006607816,0.00035237247,0.0005115165,0.059413146],"genre_scores_gemma":[0.97796005,0.00022558458,0.01864237,0.00005864327,0.00002111959,0.00018660267,0.00007936681,0.000050413313,0.0027758242],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99584454,0.002238233,0.00018732403,0.0003719189,0.0007601267,0.00059785886],"domain_scores_gemma":[0.99273854,0.003084361,0.00084470276,0.0010796507,0.0016056508,0.00064700044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038101913,0.00062101625,0.0004396084,0.0010305793,0.0016234153,0.0042810594,0.002150635,0.0008713673,0.009665801],"category_scores_gemma":[0.014337347,0.0003376733,0.00065284176,0.0014175713,0.0015343394,0.004606762,0.004482895,0.0008929154,0.00090255286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011559413,0.0010523318,0.052059464,0.00093123066,0.00021877684,0.0005172298,0.008047935,0.16922177,0.008957279,0.3455573,0.0066054715,0.40567532],"study_design_scores_gemma":[0.00042112882,0.006776333,0.055859134,0.0011951348,0.0009920298,0.0014004613,0.04636656,0.48762462,0.016462348,0.28380755,0.09875648,0.00033817455],"about_ca_topic_score_codex":0.006680487,"about_ca_topic_score_gemma":0.011088625,"teacher_disagreement_score":0.009665801,"about_ca_system_score_codex":0.0033316698,"about_ca_system_score_gemma":0.0050136684,"threshold_uncertainty_score":0.03233528},"labels":[],"label_agreement":null},{"id":"W2574807367","doi":"10.3166/ria.31.379-400","title":"Patrouille multi-agent dynamique, application robotique pour le service de personnes mobiles","year":2017,"lang":"fr","type":"article","venue":"Revue d intelligence artificielle","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.05040777142758754,"score_gpt":0.2957988296798052,"score_spread":0.24539105825221766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2574807367","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.073336326,0.004829582,0.8647201,0.003616798,0.0012408303,0.00032224567,0.0002452004,0.0024250029,0.049263895],"genre_scores_gemma":[0.6417033,0.0043951916,0.20449728,0.000500477,0.0007599871,0.00039103106,0.00028777905,0.00036743493,0.14709756],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999632,0.000112156275,0.000010086443,0.00008734874,0.0001280247,0.000030409634],"domain_scores_gemma":[0.9995764,0.0002075894,0.000025296536,0.000035182617,0.00011323604,0.000042351287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066549645,0.0005488273,0.0006715239,0.00047934407,0.00068686134,0.002094857,0.00054543826,0.0016660802,0.008176455],"category_scores_gemma":[0.0014446004,0.0002630301,0.0006048391,0.00036780373,0.00075383007,0.00092674507,0.0005879135,0.0014344245,0.0020118477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088999316,0.0004202932,0.0030422802,0.001039699,0.00018070586,0.001308413,0.0006289079,0.3151961,0.15161116,0.14701656,0.022690259,0.3559756],"study_design_scores_gemma":[0.00012410038,0.00025828974,0.004473777,0.000085734304,0.00003352767,0.0008233158,0.00025611845,0.891251,0.014923343,0.010041453,0.07768081,0.0000485027],"about_ca_topic_score_codex":0.0072629014,"about_ca_topic_score_gemma":0.0035783043,"teacher_disagreement_score":0.008176455,"about_ca_system_score_codex":0.00099838,"about_ca_system_score_gemma":0.0007549252,"threshold_uncertainty_score":0.02735293},"labels":[],"label_agreement":null},{"id":"W2581306059","doi":"10.29379/jedem.v8i2.414","title":"Open or Closed? Open Licensing of Real-time Public Sector Transit Data","year":2016,"lang":"en","type":"article","venue":"JeDEM - eJournal of eDemocracy and Open Government","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs","keywords":"Open data; Real-time data; Global Positioning System; Openness to experience; Transit (satellite); Computer science; Context (archaeology); Public transport; Transport engineering; Engineering; World Wide Web; Telecommunications; Geography","score_opus":0.09017034028354912,"score_gpt":0.3115166954050352,"score_spread":0.22134635512148607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2581306059","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31477514,0.0013586621,0.2768581,0.03000546,0.0010044392,0.00059296883,0.00080286874,0.0034819383,0.37112054],"genre_scores_gemma":[0.9455605,0.00048077066,0.017419217,0.0025979537,0.00034708058,0.00035432668,0.0004814488,0.0011280336,0.03163067],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9651604,0.012232973,0.003201993,0.0039962893,0.012040544,0.0033677814],"domain_scores_gemma":[0.880766,0.05027452,0.008239415,0.043887567,0.013494584,0.0033379782],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.022515018,0.00036725678,0.00066251744,0.0023528298,0.0037757938,0.021081986,0.0043670507,0.0034804728,0.010028643],"category_scores_gemma":[0.112952776,0.0008667665,0.0010602833,0.00336477,0.013497699,0.04514361,0.01701398,0.006638534,0.0027492885],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023285743,0.0002788502,0.015108388,0.0002363756,0.000030467183,0.0010444784,0.027208606,0.0014412089,0.0028281244,0.85175854,0.009968317,0.089863814],"study_design_scores_gemma":[0.00009854636,0.00028279237,0.010449413,0.0010636534,0.00007227933,0.0018278946,0.024119496,0.011552595,0.009428298,0.4277146,0.51315206,0.00023829637],"about_ca_topic_score_codex":0.0062453714,"about_ca_topic_score_gemma":0.002673076,"teacher_disagreement_score":0.99563295,"about_ca_system_score_codex":0.0042696716,"about_ca_system_score_gemma":0.00638208,"threshold_uncertainty_score":0.1190722},"labels":[],"label_agreement":null},{"id":"W2582538247","doi":"","title":"Catching a Ride on the Information Super-Highway: Toward an Understanding of Cyber-mediated Carpool Formation and Use","year":2010,"lang":"en","type":"article","venue":"Transportation Research Board 89th Annual MeetingTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Carpool; Transport engineering; Telecommuting; Traffic congestion; Odds; Business; Internet access; The Internet; Work (physics); Engineering; Computer science; Logistic regression","score_opus":0.08809496861271195,"score_gpt":0.3349781359474768,"score_spread":0.24688316733476484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2582538247","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8493695,0.0061977548,0.0166827,0.020630289,0.00008741843,0.00005680663,0.0003166995,0.000040400657,0.1066184],"genre_scores_gemma":[0.99159896,0.0036046274,0.0013190827,0.0004917403,0.000043320895,0.000029171331,0.00007071312,0.00001327219,0.002829187],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99932075,0.0002851024,0.00001878624,0.000130038,0.000095848896,0.00014938804],"domain_scores_gemma":[0.9978847,0.0010427987,0.0004647022,0.00019399641,0.00020934806,0.0002044486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094369834,0.0003407763,0.00021148776,0.0020203614,0.0017037367,0.006729523,0.00073199114,0.0010075335,0.0037696322],"category_scores_gemma":[0.0023083107,0.00032668142,0.00031139268,0.0014926377,0.008292453,0.0076332474,0.0023133087,0.001411549,0.0002959379],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007941526,0.00024895556,0.37000877,0.00046554022,0.00008577253,0.00077973504,0.22331563,0.002733138,0.001597223,0.2860756,0.005375294,0.109234996],"study_design_scores_gemma":[0.000010244221,0.00010778328,0.5144788,0.0009848248,0.000076661265,0.00080521725,0.2725345,0.008006496,0.0012096883,0.11305502,0.088628136,0.00010266358],"about_ca_topic_score_codex":0.11403215,"about_ca_topic_score_gemma":0.09260141,"teacher_disagreement_score":0.11403215,"about_ca_system_score_codex":0.0040304675,"about_ca_system_score_gemma":0.0034209867,"threshold_uncertainty_score":0.22673684},"labels":[],"label_agreement":null},{"id":"W2583606068","doi":"10.1109/icdcs.2017.185","title":"An Optimization Framework for Online Ride-Sharing Markets","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Matching (statistics); Computer science; Sharing economy; Product (mathematics); TRACE (psycholinguistics); Supply and demand; World Wide Web; Microeconomics; Economics","score_opus":0.04042061715132785,"score_gpt":0.3253422715268093,"score_spread":0.28492165437548145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2583606068","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007810941,0.0005841062,0.97860366,0.000696227,0.00009538988,0.00013344885,0.00027023765,0.00022376585,0.011582324],"genre_scores_gemma":[0.52809656,0.0019955856,0.44398093,0.00060311944,0.00040868713,0.00075890374,0.00078312313,0.00044537897,0.022927796],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874157,0.00055276457,0.00004299373,0.00025618912,0.00019100535,0.00021556854],"domain_scores_gemma":[0.99756217,0.0016874042,0.00016037731,0.00011939549,0.000267062,0.00020352435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028150384,0.0018782342,0.0020953852,0.00085936434,0.0008310965,0.002927553,0.0024866716,0.0024493155,0.011121],"category_scores_gemma":[0.0072291153,0.0007997871,0.0013026412,0.0014629498,0.0013971806,0.0034084565,0.0023677757,0.003008193,0.001228985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006604085,0.0000941152,0.00026785117,0.00014975663,0.000035045276,0.00009303231,0.000058719856,0.78709143,0.00048380863,0.19010764,0.005404737,0.016147824],"study_design_scores_gemma":[0.00001630792,0.0000147533665,0.000035310844,0.000008410962,0.0000053637473,0.000010461584,0.000011556044,0.9592024,0.000063336425,0.039369583,0.0012570387,0.000005474621],"about_ca_topic_score_codex":0.0063204654,"about_ca_topic_score_gemma":0.004326308,"teacher_disagreement_score":0.011121,"about_ca_system_score_codex":0.0021958787,"about_ca_system_score_gemma":0.0029517622,"threshold_uncertainty_score":0.03720349},"labels":[],"label_agreement":null},{"id":"W2585554529","doi":"","title":"Pay-as-you-drive pricing in British Columbia: backgrounder","year":2007,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Economics; Business","score_opus":0.0079989448557734,"score_gpt":0.2210361419751342,"score_spread":0.21303719711936078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2585554529","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7766801,0.009062194,0.00048407394,0.047447853,0.00037774644,0.00018903108,0.009272529,0.00006008968,0.1564264],"genre_scores_gemma":[0.88631135,0.0065849572,0.00037237737,0.0026491259,0.00014871993,0.000051531253,0.0017058274,0.000036444035,0.10213967],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99884474,0.00012037293,0.00004163978,0.00009643794,0.00025747388,0.00063927786],"domain_scores_gemma":[0.99701643,0.0005948663,0.00023343625,0.000065127904,0.001403222,0.0006869204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062863634,0.00022824646,0.00029248165,0.0012456973,0.003168216,0.0031624371,0.0011822291,0.0012615366,0.014418483],"category_scores_gemma":[0.0034677447,0.0002742394,0.00023142435,0.0045722774,0.0009520666,0.0010664958,0.00091800425,0.002526394,0.0010454276],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005708668,0.0018163567,0.5164743,0.0005072995,0.00008475359,0.0022318198,0.007832022,0.005060753,0.0007518068,0.04234842,0.24290906,0.17941257],"study_design_scores_gemma":[0.00007992519,0.00009869735,0.80084825,0.00043349853,0.00006908721,0.00024290143,0.03233761,0.0040100683,0.0005154861,0.0034376662,0.15779583,0.00013100375],"about_ca_topic_score_codex":0.9937981,"about_ca_topic_score_gemma":0.99732566,"teacher_disagreement_score":0.042988066,"about_ca_system_score_codex":0.042988066,"about_ca_system_score_gemma":0.043919753,"threshold_uncertainty_score":0.3119017},"labels":[],"label_agreement":null},{"id":"W2585983673","doi":"","title":"A Branch-Price-and-Cut Algorithm for the Min-Max k-Vehicle Windy Rural Postman Problem","year":2011,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Branch and cut; Set (abstract data type); Algorithm; Vehicle routing problem; Mathematical optimization; Graph; Mathematics; Computer science; Combinatorics; Integer programming; Routing (electronic design automation)","score_opus":0.011223364350089766,"score_gpt":0.20848542268345766,"score_spread":0.19726205833336788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2585983673","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03486217,0.00064768665,0.9511181,0.0006425421,0.00010158778,0.00051369035,0.0005731365,0.00068366365,0.010857313],"genre_scores_gemma":[0.14395906,0.0004475361,0.846327,0.00017338061,0.000071365124,0.00060683466,0.0011569627,0.00027930478,0.0069784657],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951005,0.00015512854,0.000023900913,0.00011539516,0.0000864588,0.00010898295],"domain_scores_gemma":[0.9989949,0.000649369,0.000108451226,0.00005842364,0.00008965518,0.00009911949],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011546039,0.001538977,0.0017945452,0.0010571746,0.0011692573,0.0013194104,0.0019394562,0.0019285373,0.012044084],"category_scores_gemma":[0.0023998087,0.00079047517,0.0009084979,0.0019683272,0.0006839184,0.002192393,0.0013964928,0.001941865,0.0015447072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038770554,0.00046869373,0.0010188965,0.00036779756,0.00009564196,0.0002501653,0.000168842,0.73044455,0.0017800656,0.031052208,0.01689074,0.21707472],"study_design_scores_gemma":[0.00012595333,0.00015173166,0.00022761224,0.000025082241,0.000029653283,0.00011040987,0.00007836748,0.9637601,0.00079437357,0.030458838,0.0042208647,0.000016921216],"about_ca_topic_score_codex":0.0044936375,"about_ca_topic_score_gemma":0.0067162523,"teacher_disagreement_score":0.012044084,"about_ca_system_score_codex":0.0012251899,"about_ca_system_score_gemma":0.002392324,"threshold_uncertainty_score":0.04029143},"labels":[],"label_agreement":null},{"id":"W2588780433","doi":"10.5539/ijsp.v6n2p9","title":"Evaluating the Influence of Taxi Subsidy Programs on Mitigating Difficulty Getting a Taxi in Basis of Taxi Empty-loaded Rate","year":2017,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Subsidy; Service (business); Mobile internet; Computer science; The Internet; Business; Transport engineering; Marketing; Engineering; Economics; World Wide Web","score_opus":0.042070631256739745,"score_gpt":0.3317755246302274,"score_spread":0.28970489337348765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2588780433","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9967012,0.00030091446,0.0011207082,0.00014061207,0.000020620073,0.000050202085,0.00008017414,0.000027266095,0.0015583177],"genre_scores_gemma":[0.9988404,0.00014347502,0.00057687383,0.000014961335,0.000007884776,0.000020551186,0.00008155328,0.0000036959927,0.00031063065],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99884593,0.00045246902,0.00005583494,0.00013376783,0.00020390585,0.00030807778],"domain_scores_gemma":[0.9901361,0.006372529,0.0013496728,0.00028022684,0.0011622171,0.0006992045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017406754,0.0005587642,0.0005619309,0.0007919624,0.00041893925,0.00091131905,0.0004657475,0.00047111305,0.0017600625],"category_scores_gemma":[0.011267466,0.00013790926,0.0006544561,0.0005908858,0.0003539189,0.0009318366,0.000448549,0.00066842005,0.00017998542],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0043703425,0.0043199514,0.7396899,0.0006318077,0.0006568414,0.0008622604,0.00090409204,0.09325375,0.00629639,0.0026124967,0.0029140697,0.1434881],"study_design_scores_gemma":[0.00013426239,0.005356279,0.75131464,0.0001209897,0.0013263272,0.0001724853,0.005830839,0.22661802,0.005439834,0.0010786677,0.0025178895,0.00008975641],"about_ca_topic_score_codex":0.015074582,"about_ca_topic_score_gemma":0.013520308,"teacher_disagreement_score":0.015074582,"about_ca_system_score_codex":0.0008512338,"about_ca_system_score_gemma":0.0015810685,"threshold_uncertainty_score":0.029973686},"labels":[],"label_agreement":null},{"id":"W2589807974","doi":"","title":"Truckload earnings mixed in 3rd quarter; Roadrunner gains, others report declines","year":2016,"lang":"en","type":"article","venue":"Transport topics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Earnings; Quarter (Canadian coin); Truck; Economics; Business; Transport engineering; Engineering; Finance; Automotive engineering; Geography","score_opus":0.015546837609065715,"score_gpt":0.24207572269361605,"score_spread":0.22652888508455032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2589807974","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7904427,0.0004989378,0.0004844699,0.0066352184,0.0003444754,0.00014701087,0.023139518,0.00043934668,0.17786829],"genre_scores_gemma":[0.71052265,0.00065427506,0.00035967256,0.0016752164,0.0002526272,0.0001246265,0.02238344,0.00010434645,0.26392308],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986181,0.00009814215,0.000086119086,0.00013776131,0.00057694846,0.00048295327],"domain_scores_gemma":[0.99451363,0.0004197995,0.0017867625,0.0003572494,0.001906518,0.0010160545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014096302,0.00031515164,0.00039060795,0.0029408073,0.0019522615,0.0035523016,0.0008924986,0.0009605304,0.034229126],"category_scores_gemma":[0.0056148637,0.00023109316,0.00044278495,0.003197242,0.00042659786,0.0015938157,0.0017004464,0.0016477329,0.0065913233],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023316432,0.00082594116,0.7917373,0.000074684445,0.000064456355,0.00023167019,0.0025262411,0.0002861666,0.0004054067,0.0032133453,0.14609683,0.054304715],"study_design_scores_gemma":[0.0000110700375,0.000086184315,0.94109875,0.000036603855,0.000028777586,0.00008309111,0.004721831,0.0002247696,0.0005002288,0.00038149022,0.05281539,0.000011740134],"about_ca_topic_score_codex":0.078621656,"about_ca_topic_score_gemma":0.16300781,"teacher_disagreement_score":0.078621656,"about_ca_system_score_codex":0.0013618369,"about_ca_system_score_gemma":0.0023409752,"threshold_uncertainty_score":0.15632808},"labels":[],"label_agreement":null},{"id":"W2591264567","doi":"","title":"Modeling Car Sharing and Its Impact on Auto Ownership: Evidence from Vancouver and Seattle","year":2016,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Sharing economy; Metropolitan area; Car ownership; Car sharing; Context (archaeology); Business; Service (business); Agency (philosophy); Population; Marketing; Geography; Transport engineering; Public transport; Computer science; Engineering; Sociology","score_opus":0.03630446888624745,"score_gpt":0.27285126851212366,"score_spread":0.23654679962587621,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2591264567","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99782395,0.0001959589,0.0001622542,0.00014857722,0.000004107167,0.000012102135,0.00041608198,0.000009486256,0.0012274852],"genre_scores_gemma":[0.9951735,0.00042635918,0.0003022166,0.000042967342,0.0000050393382,0.00001870166,0.0016328703,0.0000120442555,0.0023864193],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989222,0.00049176917,0.000043661486,0.00018479461,0.00017885302,0.00017870196],"domain_scores_gemma":[0.99129945,0.004688364,0.0008159693,0.00062948384,0.0016934145,0.00087328267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001855724,0.0005477993,0.00053263403,0.0010054187,0.0012492179,0.0023021607,0.002040206,0.00076106656,0.0034618885],"category_scores_gemma":[0.010110406,0.0005641978,0.000890287,0.0022822449,0.0006582901,0.00080120855,0.0012240106,0.0010659554,0.0006341448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002445554,0.0003189272,0.97587603,0.0000446829,0.00031123697,0.00044054768,0.001147891,0.008588872,0.00016581504,0.00048705155,0.0019016872,0.010472662],"study_design_scores_gemma":[0.000063276435,0.00023357678,0.93536866,0.00013490916,0.0003665858,0.00017829268,0.009131749,0.04886034,0.00020712079,0.00056469254,0.0048416215,0.000049077502],"about_ca_topic_score_codex":0.90472835,"about_ca_topic_score_gemma":0.92442846,"teacher_disagreement_score":0.09527165,"about_ca_system_score_codex":0.0044281995,"about_ca_system_score_gemma":0.0028809921,"threshold_uncertainty_score":0.19166541},"labels":[],"label_agreement":null},{"id":"W2593716746","doi":"","title":"Designing the Master Schedule for Demand-Adaptive Transit Systems","year":2008,"lang":"en","type":"article","venue":"Espace ÉTS (ETS)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Reservation; Schedule; Computer science; Operations research; Set (abstract data type); Process (computing); Service (business); Scheme (mathematics); Line (geometry); Mathematical optimization; Industrial engineering; Engineering","score_opus":0.03393582200085201,"score_gpt":0.22878241072697425,"score_spread":0.19484658872612223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2593716746","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020391844,0.000054886365,0.9774584,0.000055360062,0.000006947844,0.00007420156,0.00004264387,0.00009256851,0.0018231376],"genre_scores_gemma":[0.6361384,0.00022800504,0.36010247,0.000027776883,0.00002713276,0.00029864404,0.00017606604,0.0000913882,0.0029101502],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994821,0.00016508368,0.00003434998,0.00010190297,0.00014600866,0.000070637165],"domain_scores_gemma":[0.99891317,0.0005659659,0.00020253749,0.0000858501,0.00016879187,0.00006377465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013688972,0.0005579218,0.00049146137,0.00057558465,0.00036643652,0.00096208,0.0007732994,0.00051483687,0.00215918],"category_scores_gemma":[0.0034270498,0.0004507659,0.0004657966,0.00044984173,0.0006651655,0.00095862197,0.0008384746,0.00072976126,0.00039580642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000640231,0.000029589066,0.00059490313,0.00011134863,0.00001622973,0.00005680962,0.00018102748,0.90098953,0.007952057,0.060061924,0.0005446471,0.029398007],"study_design_scores_gemma":[0.000012998554,0.00006762349,0.00012449412,0.000009855835,0.0000060315347,0.000016273578,0.00003787276,0.9853042,0.0027638914,0.009908286,0.0017408708,0.000007472625],"about_ca_topic_score_codex":0.001664429,"about_ca_topic_score_gemma":0.0018135424,"teacher_disagreement_score":0.00215918,"about_ca_system_score_codex":0.0011641075,"about_ca_system_score_gemma":0.0020544776,"threshold_uncertainty_score":0.008446217},"labels":[],"label_agreement":null},{"id":"W2595829551","doi":"10.1155/2017/2619810","title":"Modeling and Analyzing Taxi Congestion Premium in Congested Cities","year":2017,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Fok Ying Tong Education Foundation; National Natural Science Foundation of China","keywords":"Beijing; Congestion pricing; Traffic congestion; Supply and demand; Singapore Area Licensing Scheme; Transport engineering; Economics; Microeconomics; Engineering; China","score_opus":0.015245780325229984,"score_gpt":0.2560637193243276,"score_spread":0.2408179389990976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2595829551","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7986124,0.0007287675,0.17719117,0.0011312342,0.00010958186,0.00013306302,0.0006679818,0.0002520093,0.021173751],"genre_scores_gemma":[0.9946221,0.00020512083,0.0027903893,0.000026712962,0.00002208563,0.000035227364,0.00011665028,0.000021091466,0.0021607066],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997161,0.00006608424,0.000012458507,0.000058120422,0.000036155623,0.0001110223],"domain_scores_gemma":[0.999539,0.00016657209,0.0000857519,0.000018821982,0.00012644383,0.00006339758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061878975,0.0007263751,0.00063765934,0.000669243,0.00056272786,0.0013912614,0.0010858853,0.0012822944,0.0021723981],"category_scores_gemma":[0.001344975,0.0004615966,0.0008764,0.00056142284,0.0006454502,0.0011554274,0.0008506265,0.00090429425,0.00012335599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012153153,0.000030723073,0.0026091998,0.000013962816,0.000013278077,0.00011107531,0.000039007427,0.989267,0.00034128435,0.0062076943,0.00035182197,0.00100287],"study_design_scores_gemma":[0.0000027090548,0.00000334338,0.00035313735,0.0000012558497,0.0000045153906,0.0000047779117,0.000018696828,0.9987723,0.000028655937,0.0007066497,0.00010093712,0.000003033893],"about_ca_topic_score_codex":0.08863218,"about_ca_topic_score_gemma":0.035122238,"teacher_disagreement_score":0.08863218,"about_ca_system_score_codex":0.0021037033,"about_ca_system_score_gemma":0.0016740175,"threshold_uncertainty_score":0.17623252},"labels":[],"label_agreement":null},{"id":"W2600505068","doi":"10.1109/vtcfall.2016.7880881","title":"A Solution to the Congestion Problem: Profiles Driven Trip Planning","year":2016,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"TRIPS architecture; Computer science; Traffic congestion; Personalization; Plan (archaeology); Transportation planning; GRASP; Operations research; Transport engineering; Engineering; World Wide Web","score_opus":0.020315326685376358,"score_gpt":0.23794859438056015,"score_spread":0.2176332676951838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2600505068","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017013442,0.00020569828,0.9751507,0.0008901726,0.00009362846,0.00015605496,0.00020332568,0.00036769206,0.0059192535],"genre_scores_gemma":[0.55695826,0.00048747333,0.43471304,0.00029326114,0.000099283694,0.00028233623,0.0004918676,0.00021124845,0.0064632804],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989466,0.0004861489,0.00004121267,0.00020393748,0.00019377792,0.00012838008],"domain_scores_gemma":[0.9983909,0.0007675677,0.00013302834,0.00022713246,0.0002853888,0.00019598108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015444644,0.0008227171,0.00088799145,0.0007009512,0.00084684003,0.0016363724,0.0022872537,0.0014893522,0.0049745105],"category_scores_gemma":[0.0053958027,0.0007055179,0.00093414966,0.0012663087,0.00073393405,0.002475431,0.0021796518,0.0019586028,0.0008710104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002717108,0.00022124601,0.0017373991,0.00020092682,0.000113977985,0.00019632441,0.0005598109,0.7679939,0.001670297,0.09547975,0.009890276,0.12166427],"study_design_scores_gemma":[0.000027012024,0.00005251696,0.00016483414,0.000013645961,0.00001646435,0.00006547671,0.00011072036,0.9571127,0.0003705714,0.038812898,0.0032374517,0.000015594316],"about_ca_topic_score_codex":0.008383767,"about_ca_topic_score_gemma":0.008334371,"teacher_disagreement_score":0.008383767,"about_ca_system_score_codex":0.0010816071,"about_ca_system_score_gemma":0.0023176288,"threshold_uncertainty_score":0.016669989},"labels":[],"label_agreement":null},{"id":"W2604191868","doi":"","title":"Truckload companies post lower profits in 4th quarter","year":2017,"lang":"en","type":"article","venue":"Transport topics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Truck; Business; Automotive industry; Operations management; Engineering; Transport engineering; Automotive engineering; Geography","score_opus":0.015299396029015047,"score_gpt":0.24041606287983694,"score_spread":0.22511666685082188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604191868","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9089598,0.0005342581,0.00059208454,0.00948733,0.0011366039,0.00007342302,0.004135173,0.0006535366,0.074427925],"genre_scores_gemma":[0.8104603,0.00047218057,0.0002301503,0.0034702725,0.000358991,0.00006337535,0.007135968,0.00015399822,0.1776547],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99911314,0.000048225513,0.000020238715,0.000055235487,0.00031358728,0.000449478],"domain_scores_gemma":[0.99775934,0.00023594908,0.000723237,0.00006595376,0.00063134934,0.00058404804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005733092,0.0002987888,0.00038302073,0.0010630985,0.0014384956,0.0038781585,0.00037838533,0.0016359611,0.025266511],"category_scores_gemma":[0.0032265242,0.00024115668,0.00036127324,0.0009780099,0.00030434885,0.0011495979,0.001132883,0.0019116183,0.0069820946],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018083057,0.0013322642,0.35315084,0.00018844065,0.00011737601,0.0007773511,0.0027169194,0.0012106302,0.0042970367,0.0068498226,0.508189,0.11936194],"study_design_scores_gemma":[0.00008606531,0.00041735297,0.8465912,0.000048094902,0.000036639933,0.00011419822,0.010779063,0.00095209974,0.003011036,0.0011139511,0.13681352,0.000036905334],"about_ca_topic_score_codex":0.02710279,"about_ca_topic_score_gemma":0.0420235,"teacher_disagreement_score":0.02710279,"about_ca_system_score_codex":0.0017958841,"about_ca_system_score_gemma":0.0014380333,"threshold_uncertainty_score":0.08452487},"labels":[],"label_agreement":null},{"id":"W2604985641","doi":"","title":"Travel behaviour of potential Electric Vehicle drivers. The need for changing: A contribution to the Edison project","year":2010,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Transport engineering; Engineering; Computer science; Environmental science","score_opus":0.007956721086095802,"score_gpt":0.23282372280244415,"score_spread":0.22486700171634835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604985641","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99616253,0.00014033572,0.00007468201,0.00038407624,0.000014161717,0.000016851653,0.000113778,0.0000015748301,0.003092068],"genre_scores_gemma":[0.9912457,0.00059703185,0.00024416062,0.00022703798,0.000014823497,0.00004650635,0.00019394765,0.0000033276344,0.0074273753],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99973005,0.00015183094,0.000008503499,0.00002764161,0.0000324342,0.00004962794],"domain_scores_gemma":[0.9989692,0.00037031257,0.00012647074,0.00004650318,0.00027172433,0.00021579128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082397164,0.00017698597,0.000106559666,0.00031830408,0.00069334405,0.0007716413,0.0002649139,0.00066564203,0.00225073],"category_scores_gemma":[0.002562472,0.00012008013,0.00015425302,0.00039894148,0.00022323367,0.00077444763,0.0005955904,0.0005506452,0.0004001769],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051397417,0.0014727846,0.82364905,0.0001751969,0.00005946148,0.0014470487,0.07100902,0.00038324296,0.0012479993,0.0010831752,0.011393465,0.08756547],"study_design_scores_gemma":[0.00001619646,0.000895035,0.8090072,0.000073082396,0.000056562963,0.0005625174,0.17239538,0.00046495243,0.0005657885,0.0003096055,0.01561787,0.00003581685],"about_ca_topic_score_codex":0.023341192,"about_ca_topic_score_gemma":0.046046853,"teacher_disagreement_score":0.023341192,"about_ca_system_score_codex":0.00049512426,"about_ca_system_score_gemma":0.0005303578,"threshold_uncertainty_score":0.04641062},"labels":[],"label_agreement":null},{"id":"W2606152668","doi":"10.1155/2017/8512728","title":"Dealing with the Empty Vehicle Movements in Personal Rapid Transit System with Batteries Constraints in a Dynamic Context","year":2017,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Context (archaeology); Personal mobility; Benchmark (surveying); Transit system; Public transport; Set (abstract data type); Computer science; Simulation; Personal computer; Transport engineering; Operations research; Engineering; Telecommunications","score_opus":0.007398213496717838,"score_gpt":0.22286765807785822,"score_spread":0.21546944458114037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606152668","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49913895,0.00034678043,0.49261245,0.00035952602,0.000055578024,0.00011916259,0.00026809177,0.00023286545,0.0068666986],"genre_scores_gemma":[0.98744303,0.00012503655,0.010841236,0.000014501165,0.00001336458,0.00003961551,0.00008993581,0.000021376954,0.0014117836],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996232,0.00012686143,0.000019638293,0.00007309186,0.000055617027,0.00010150898],"domain_scores_gemma":[0.9990387,0.0005789448,0.00016918602,0.000039739763,0.00009186054,0.0000815463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006722916,0.00077547116,0.0009099325,0.00041456323,0.0006603886,0.0010420459,0.0009399949,0.0009206293,0.0018736288],"category_scores_gemma":[0.0017714942,0.00039823548,0.00065168453,0.00056098076,0.00049925136,0.0010614278,0.0008559851,0.00069564336,0.0000921167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034933728,0.000012911781,0.00059459737,0.000027072732,0.000012101603,0.00014486493,0.000030324563,0.9944172,0.0005109064,0.0019148203,0.00014357729,0.0021566818],"study_design_scores_gemma":[0.0000038950593,0.000020478039,0.00019534964,0.0000019473487,0.000006283697,0.000020283578,0.000036242727,0.9985586,0.00019122442,0.0008098241,0.0001516847,0.0000041653325],"about_ca_topic_score_codex":0.015648725,"about_ca_topic_score_gemma":0.008587682,"teacher_disagreement_score":0.015648725,"about_ca_system_score_codex":0.0008575039,"about_ca_system_score_gemma":0.000978688,"threshold_uncertainty_score":0.031115294},"labels":[],"label_agreement":null},{"id":"W2611232456","doi":"","title":"Lâcher le volant sans perdre le contrôle de nos villes","year":2016,"lang":"fr","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Humanities; Political science; Philosophy","score_opus":0.023047649480808202,"score_gpt":0.2845375472824885,"score_spread":0.2614898978016803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2611232456","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11133937,0.003441329,0.09317,0.04820203,0.0066827,0.00027485247,0.00066442316,0.0023266962,0.73389864],"genre_scores_gemma":[0.3885872,0.0016336301,0.008156241,0.002860044,0.0016451236,0.00017006476,0.00025732574,0.0005715134,0.5961188],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99678445,0.00089937163,0.00007302233,0.0007982411,0.0009929896,0.0004518214],"domain_scores_gemma":[0.9964696,0.0008972845,0.0002777286,0.0006397802,0.0007839267,0.000931674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021309846,0.0016100729,0.0010753435,0.0014099147,0.004807256,0.010600473,0.0013981529,0.004069005,0.074666746],"category_scores_gemma":[0.0076081194,0.0005930773,0.0012655997,0.00120628,0.004160774,0.0067494507,0.0031227206,0.0054167556,0.012340295],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006132779,0.00043830223,0.006486426,0.00034626186,0.00014633976,0.0022462595,0.0063120974,0.009501936,0.016879575,0.7550361,0.06797056,0.13402297],"study_design_scores_gemma":[0.000090221336,0.00026887454,0.006517956,0.00019367748,0.00005065265,0.0007193671,0.0047524106,0.007632551,0.0034709794,0.048320636,0.9278757,0.00010685558],"about_ca_topic_score_codex":0.02804974,"about_ca_topic_score_gemma":0.026964407,"teacher_disagreement_score":0.074666746,"about_ca_system_score_codex":0.004560376,"about_ca_system_score_gemma":0.0026712103,"threshold_uncertainty_score":0.24978513},"labels":[],"label_agreement":null},{"id":"W2612862912","doi":"10.1139/juvs-2016-0028","title":"Public acceptance of autonomous and connected cars","year":2017,"lang":"en","type":"article","venue":"Journal of Unmanned Vehicle Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Business; Internet privacy; Computer science","score_opus":0.03636665095962314,"score_gpt":0.24578285634963085,"score_spread":0.20941620539000771,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612862912","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9580024,0.00027284384,0.0003952481,0.0057578534,0.00014876977,0.000040838167,0.00019266088,0.000024702418,0.03516469],"genre_scores_gemma":[0.9981357,0.000050009658,0.000027567592,0.00019630279,0.00003509798,0.000009580843,0.000041880583,0.000004063041,0.0014997234],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9943395,0.0021065657,0.00018556483,0.00042022608,0.001787583,0.0011605731],"domain_scores_gemma":[0.9658057,0.014898111,0.0061448207,0.0021776515,0.007788284,0.0031854447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036372412,0.00021581234,0.00024058232,0.0010845999,0.0012644063,0.0032548015,0.0006940968,0.0017630006,0.015230574],"category_scores_gemma":[0.028020868,0.00016932565,0.00041152275,0.00070328277,0.0013872994,0.0024541775,0.0022244013,0.0018586534,0.0012164082],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025685874,0.0016073518,0.701679,0.0003406233,0.00019532145,0.0012121802,0.04067251,0.0010541371,0.003091077,0.030164583,0.024309939,0.19310465],"study_design_scores_gemma":[0.00014659084,0.0008647355,0.87644845,0.00026566663,0.0001431757,0.0004488393,0.06257947,0.0036670335,0.0021312903,0.007200281,0.046013586,0.00009088328],"about_ca_topic_score_codex":0.008496901,"about_ca_topic_score_gemma":0.0072301514,"teacher_disagreement_score":0.015230574,"about_ca_system_score_codex":0.0015309986,"about_ca_system_score_gemma":0.0014348092,"threshold_uncertainty_score":0.050951302},"labels":[],"label_agreement":null},{"id":"W2613400532","doi":"10.1021/cen-09422-scitech1","title":"Firm footing for cloud seeding","year":2016,"lang":"en","type":"article","venue":"C&EN Global Enterprise","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Seeding; Cloud seeding; Cloud computing; Computer science; Business; Engineering; Aerospace engineering; Operating system","score_opus":0.008896096730993484,"score_gpt":0.24240146520535438,"score_spread":0.2335053684743609,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2613400532","genre_codex":"other","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010884175,0.004108667,0.01128489,0.13134117,0.03295025,0.0003751831,0.00086219434,0.0025857359,0.80560774],"genre_scores_gemma":[0.082707986,0.0027299344,0.009349601,0.03642299,0.004189072,0.00010951053,0.00094585126,0.00094505824,0.86259997],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99869967,0.00010674725,0.00003820049,0.00021963543,0.0005519881,0.00038372667],"domain_scores_gemma":[0.99606675,0.00019992673,0.00010538233,0.0003841532,0.0010006372,0.002243114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013402279,0.00063400913,0.00037993342,0.00080594345,0.0063912873,0.004729085,0.001084279,0.002606792,0.22031014],"category_scores_gemma":[0.0039978204,0.0003246831,0.00041499364,0.0005185844,0.0011580548,0.0027882154,0.005173284,0.0049963547,0.079620495],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061675186,0.00011434387,0.0013457584,0.000078716774,0.000007660722,0.0005111007,0.00045736477,0.000101467034,0.002104719,0.019760463,0.85636514,0.11909154],"study_design_scores_gemma":[0.000008202455,0.0000470892,0.00077323965,0.00004994629,0.0000022529039,0.0001421568,0.00038277733,0.000082061604,0.00036396302,0.002585966,0.99555415,0.000008219102],"about_ca_topic_score_codex":0.007958866,"about_ca_topic_score_gemma":0.025147147,"teacher_disagreement_score":0.22031014,"about_ca_system_score_codex":0.0016569849,"about_ca_system_score_gemma":0.003610475,"threshold_uncertainty_score":0.73701084},"labels":[],"label_agreement":null},{"id":"W2614609561","doi":"","title":"Longitudinal Analysis of Bikesharing Usage in Montreal, Canada","year":2017,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Political science; Business","score_opus":0.013136048896057382,"score_gpt":0.23134026629809745,"score_spread":0.21820421740204007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2614609561","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96362334,0.0020026914,0.00054103014,0.0013695722,0.00008378349,0.00008947962,0.027444376,0.00009115695,0.0047545703],"genre_scores_gemma":[0.9848964,0.0008132589,0.00043196918,0.0001460917,0.000017951796,0.00006109297,0.0069013704,0.000034722194,0.0066971024],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986517,0.00018952267,0.00007182981,0.0002945157,0.0003988051,0.00039370244],"domain_scores_gemma":[0.99479574,0.00021834853,0.0005909906,0.00020955442,0.0031615018,0.0010239037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011208176,0.00068790914,0.00058338576,0.0022086725,0.0027806605,0.0018938386,0.0020910315,0.00087180495,0.0057200408],"category_scores_gemma":[0.0031949996,0.00054436113,0.0008992527,0.00747101,0.00077281176,0.0007758256,0.001086486,0.0013562171,0.0007993006],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014345998,0.00008664133,0.985378,0.000037106234,0.00025567508,0.000083887535,0.001191245,0.0004281813,0.00034762724,0.00047871942,0.0059690317,0.0056003984],"study_design_scores_gemma":[0.0000051022766,0.000014251508,0.9969964,0.000019260639,0.000026757712,0.000010644934,0.000677797,0.0003248287,0.000045351146,0.0000120158265,0.0018517929,0.000015690866],"about_ca_topic_score_codex":0.9977139,"about_ca_topic_score_gemma":0.99847597,"teacher_disagreement_score":0.033477746,"about_ca_system_score_codex":0.033477746,"about_ca_system_score_gemma":0.037450694,"threshold_uncertainty_score":0.24289918},"labels":[],"label_agreement":null},{"id":"W2620856797","doi":"","title":"Méthodologie de génération de trajets multimodaux dans un contexte de covoiturage","year":2016,"lang":"fr","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Humanities; TRIPS architecture; Public transport; Computer science; Political science; Geography; Art","score_opus":0.022675484593426033,"score_gpt":0.2551558410601628,"score_spread":0.2324803564667368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620856797","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007237928,0.00009066827,0.99044424,0.00006330553,0.000036722107,0.000072709285,0.00006459945,0.00052722945,0.0014626372],"genre_scores_gemma":[0.21040596,0.0002720184,0.7793912,0.00006373094,0.000051186005,0.00029912268,0.0004157246,0.00054570707,0.008555358],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99807525,0.0005436025,0.00007653966,0.00052537635,0.00060574745,0.00017352108],"domain_scores_gemma":[0.99750996,0.0015119911,0.00009717715,0.00029792808,0.0004889136,0.0000939469],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017946289,0.0014477079,0.001003111,0.0013580667,0.0011052882,0.0031396959,0.0019351533,0.002017217,0.006756596],"category_scores_gemma":[0.00652537,0.0008100959,0.0021053124,0.00091494794,0.0016458388,0.0017137685,0.0018969967,0.0022663418,0.0016418985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025755563,0.00013680762,0.0031274483,0.00042661908,0.00012990329,0.00067152805,0.000919244,0.721893,0.01145803,0.0799221,0.0021485055,0.1789093],"study_design_scores_gemma":[0.000028359818,0.000043515567,0.00031953547,0.000027015845,0.0000117506415,0.00012319906,0.0001305841,0.97994024,0.003340942,0.011628379,0.004383961,0.000022522654],"about_ca_topic_score_codex":0.016718775,"about_ca_topic_score_gemma":0.010221985,"teacher_disagreement_score":0.016718775,"about_ca_system_score_codex":0.0015564826,"about_ca_system_score_gemma":0.0014175491,"threshold_uncertainty_score":0.03324294},"labels":[],"label_agreement":null},{"id":"W2621047429","doi":"10.1287/msom.2020.0925","title":"Incentivized Actions in Freemium Games","year":2020,"lang":"en","type":"article","venue":"Manufacturing & Service Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Cannibalization; Revenue; Computer science; Software deployment; Incentive; Entertainment; Set (abstract data type); Process (computing); Revenue management; Markov decision process; Variety (cybernetics); Key (lock); Marketing; License; Business; Microeconomics; Economics; Markov process; Computer security","score_opus":0.021750118646327924,"score_gpt":0.22209659663680353,"score_spread":0.2003464779904756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621047429","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12040386,0.0012534127,0.8157346,0.0061664428,0.00034493644,0.0018292718,0.0016532509,0.00063004665,0.051984206],"genre_scores_gemma":[0.88866866,0.0010837882,0.08923845,0.0011476208,0.00018688777,0.0014286726,0.0005143763,0.00018073268,0.017550927],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99500847,0.0025592681,0.0002436166,0.0009078508,0.00047188308,0.00080886704],"domain_scores_gemma":[0.9645131,0.030198894,0.0021215451,0.00061549153,0.00083238364,0.0017185687],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051128096,0.002857625,0.003137316,0.0013995237,0.0011751149,0.004167837,0.0032618279,0.0051852907,0.011002239],"category_scores_gemma":[0.028872753,0.001410143,0.0015521366,0.0010868696,0.004208326,0.0051329103,0.0028613177,0.0054101427,0.0009595918],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038145378,0.00037543385,0.001843489,0.00039955296,0.00011775913,0.00043943615,0.00035225958,0.68781,0.0010179854,0.2886061,0.006144671,0.012511765],"study_design_scores_gemma":[0.00023789192,0.00017401674,0.00048714358,0.00009974469,0.000044880915,0.00015122439,0.0001973258,0.782832,0.0004797592,0.2113859,0.0038533546,0.000056781562],"about_ca_topic_score_codex":0.0073030754,"about_ca_topic_score_gemma":0.0053837555,"teacher_disagreement_score":0.011002239,"about_ca_system_score_codex":0.0044131023,"about_ca_system_score_gemma":0.004733661,"threshold_uncertainty_score":0.036806166},"labels":[],"label_agreement":null},{"id":"W2621124960","doi":"10.13189/ujm.2017.050505","title":"OSeMOSYS: Introducing Elasticity","year":2017,"lang":"en","type":"article","venue":"Universal Journal of Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College Saint-Jean","funders":"","keywords":"Elasticity (physics); Economics; Mathematical economics; Thermodynamics; Physics","score_opus":0.008193834900647422,"score_gpt":0.211347460176888,"score_spread":0.20315362527624056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621124960","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0059354496,0.00017192024,0.96706545,0.0008450856,0.00025913696,0.00012430018,0.0007283898,0.005315784,0.019554516],"genre_scores_gemma":[0.19595467,0.00086509995,0.7697388,0.00070040365,0.0002487179,0.00060243666,0.0019440616,0.005685142,0.024260772],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987355,0.0003721412,0.00008845739,0.0001895666,0.00046456826,0.00014976157],"domain_scores_gemma":[0.9982299,0.0008650933,0.00015626551,0.00037454488,0.0002600545,0.000114184644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020935524,0.0014157257,0.0005554863,0.0011741001,0.00082648365,0.0028403075,0.002229325,0.0012819188,0.024236834],"category_scores_gemma":[0.005240452,0.0009962526,0.0022448099,0.0009795116,0.0013220601,0.0054126983,0.005879438,0.0032560378,0.0038448644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011872686,0.00009250197,0.0018873002,0.00025042743,0.00007817511,0.0002543599,0.00045429115,0.13469623,0.0029517682,0.78353435,0.014988764,0.06069316],"study_design_scores_gemma":[0.00004441327,0.000044456367,0.00030278167,0.00015528181,0.000036446847,0.00017220927,0.00016883377,0.45761883,0.0036020207,0.34539273,0.19240373,0.000058246005],"about_ca_topic_score_codex":0.002732219,"about_ca_topic_score_gemma":0.002662819,"teacher_disagreement_score":0.024236834,"about_ca_system_score_codex":0.0008428033,"about_ca_system_score_gemma":0.0016753944,"threshold_uncertainty_score":0.08108026},"labels":[],"label_agreement":null},{"id":"W2621301896","doi":"10.3166/ria.32.223-247","title":"Approches multiagents pour l’allocation de courses à une flotte de taxis autonomes","year":2018,"lang":"fr","type":"preprint","venue":"Revue d intelligence artificielle","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Taxis; Computer science; Transport engineering; Engineering","score_opus":0.04689782167666528,"score_gpt":0.28973704565111863,"score_spread":0.24283922397445334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621301896","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043121293,0.00045883926,0.9510705,0.00049491995,0.000119384145,0.00010654204,0.00005987523,0.00042327252,0.0041454635],"genre_scores_gemma":[0.5986223,0.0004429207,0.3866615,0.00017624108,0.00017567743,0.00032906703,0.0001646413,0.00016261642,0.013264971],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985689,0.00052701676,0.00005833316,0.00039163124,0.0002671192,0.00018701142],"domain_scores_gemma":[0.9980361,0.0010541711,0.00013072601,0.00022343999,0.00033911882,0.00021653365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020116111,0.0010954045,0.0012713785,0.0010816832,0.0013747428,0.0032368694,0.0020475667,0.0022749072,0.006118418],"category_scores_gemma":[0.0039937366,0.00074833207,0.0010876858,0.00086655095,0.00093103613,0.0019724935,0.001865156,0.0017767146,0.0011642616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006073771,0.0002906367,0.0014472338,0.00016042052,0.00018546899,0.00015678257,0.00022841552,0.84120154,0.006836096,0.025848959,0.0031619854,0.11987512],"study_design_scores_gemma":[0.0000497574,0.000046247023,0.0002763379,0.000011874784,0.00002044641,0.00002275218,0.000051467905,0.9910034,0.0008991923,0.0056974073,0.0019128255,0.00000829188],"about_ca_topic_score_codex":0.007347941,"about_ca_topic_score_gemma":0.007341464,"teacher_disagreement_score":0.007347941,"about_ca_system_score_codex":0.0017744572,"about_ca_system_score_gemma":0.001019767,"threshold_uncertainty_score":0.020468116},"labels":[],"label_agreement":null},{"id":"W2621304967","doi":"","title":"Fedora Unleashed, 2008 Edition : Covering Fedora 7 and Fedora 8","year":2008,"lang":"en","type":"book","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Operating system; Computer science; Installation; Upgrade; Scripting language; GNU/Linux; Linux kernel; Workstation; World Wide Web; OS X; Software; Database","score_opus":0.008117544051594023,"score_gpt":0.17831778146368973,"score_spread":0.17020023741209572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621304967","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015990193,0.027829977,0.020509083,0.006048328,0.014054022,0.00016732146,0.005914998,0.023392433,0.90048486],"genre_scores_gemma":[0.0028414049,0.010685762,0.0068349657,0.002800532,0.0019861178,0.00013244328,0.0044937516,0.0063761338,0.9638489],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99913836,0.000052916264,0.000041700074,0.0001144084,0.00056008715,0.00009258751],"domain_scores_gemma":[0.9988997,0.00014032074,0.00005264367,0.00011124437,0.00064914796,0.00014698663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065203366,0.00085590436,0.0007588187,0.00238663,0.001313874,0.005209852,0.0007839332,0.001181291,0.17680582],"category_scores_gemma":[0.0031202205,0.0006604116,0.000587328,0.0037509298,0.00046225204,0.005839017,0.001756635,0.0023940667,0.21881914],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010539089,0.000011672831,0.000044817687,0.00007157953,0.0000011656917,0.000017837174,0.000043969154,0.00005397452,0.00032740497,0.0026334135,0.91271454,0.08406908],"study_design_scores_gemma":[7.6533286e-7,0.0000029326125,0.00008830958,0.000036397454,6.4497294e-7,0.000048972524,0.000008324102,0.000029402927,0.00008455684,0.00031809113,0.99937797,0.0000035243206],"about_ca_topic_score_codex":0.0042906804,"about_ca_topic_score_gemma":0.006319593,"teacher_disagreement_score":0.17680582,"about_ca_system_score_codex":0.0018324554,"about_ca_system_score_gemma":0.0016807712,"threshold_uncertainty_score":0.5914744},"labels":[],"label_agreement":null},{"id":"W2621605989","doi":"10.1109/tits.2017.2704418","title":"A Bargaining-Based Solution to the Team Mobility Planning Game","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Game theory; Computer science; Mathematical economics; Operations research; Engineering; Economics","score_opus":0.042923152266871545,"score_gpt":0.28469604135951154,"score_spread":0.24177288909264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621605989","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0059543466,0.00006533782,0.9813517,0.00020776637,0.000041881056,0.00008837644,0.00004248346,0.000042122072,0.012205985],"genre_scores_gemma":[0.47905263,0.0003555459,0.50524116,0.00014098342,0.0000575215,0.00060665223,0.00015263261,0.00006454949,0.014328374],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932504,0.00028947133,0.00002754656,0.00011697138,0.00014088466,0.00010007592],"domain_scores_gemma":[0.99962926,0.00019942413,0.0000411156,0.000019289562,0.00006111817,0.000049723552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011576478,0.000798211,0.0007179018,0.0005288457,0.0009360651,0.0012017613,0.0018800469,0.0016627817,0.0061281547],"category_scores_gemma":[0.0019361473,0.0003804133,0.00091171684,0.0006687272,0.0009041413,0.0010488034,0.0019907893,0.001300613,0.000703373],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005586208,0.000044296703,0.00017469433,0.00010082493,0.000029570958,0.00020565657,0.00023456968,0.7427308,0.0017212593,0.23226173,0.0019551744,0.02048556],"study_design_scores_gemma":[0.000025414496,0.000060029546,0.00004975319,0.00001835889,0.000011155265,0.000060859613,0.0000836609,0.9497852,0.0003774152,0.0459282,0.0035878662,0.00001204482],"about_ca_topic_score_codex":0.0023002306,"about_ca_topic_score_gemma":0.0019186072,"teacher_disagreement_score":0.0061281547,"about_ca_system_score_codex":0.00094721466,"about_ca_system_score_gemma":0.0018902329,"threshold_uncertainty_score":0.02050072},"labels":[],"label_agreement":null},{"id":"W2621850047","doi":"","title":"Mobility Applications, Maritime Applications","year":2013,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science","score_opus":0.010798226868360409,"score_gpt":0.219614545979862,"score_spread":0.20881631911150159,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621850047","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017229943,0.060591776,0.20331113,0.023930723,0.012948258,0.0003412622,0.004944589,0.008769108,0.6679332],"genre_scores_gemma":[0.15376367,0.044106353,0.07235838,0.003916718,0.00787432,0.00034765486,0.0057031196,0.0015115709,0.7104182],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99943596,0.000087025066,0.000044134093,0.00012883861,0.000237281,0.000066689],"domain_scores_gemma":[0.9994074,0.00012680283,0.00005213416,0.00013363831,0.00020982492,0.000070144546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041774902,0.0012712011,0.0005419514,0.001352702,0.0009941662,0.0037778676,0.0008421306,0.0024624423,0.0702334],"category_scores_gemma":[0.0020840494,0.00029278384,0.00039467512,0.0030645267,0.0006795229,0.0036678044,0.0017129398,0.0012989535,0.04160732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000881848,0.00006361031,0.0007284515,0.0010693547,0.000018987963,0.0004220582,0.0003522642,0.0022966305,0.010194062,0.19418971,0.32914993,0.4614268],"study_design_scores_gemma":[0.000009957398,0.000034442794,0.00082207046,0.00014887073,0.000015458014,0.0005590661,0.0001871402,0.00492126,0.0016327634,0.052266046,0.9393881,0.000014920978],"about_ca_topic_score_codex":0.0025818225,"about_ca_topic_score_gemma":0.002672523,"teacher_disagreement_score":0.0702334,"about_ca_system_score_codex":0.00071237166,"about_ca_system_score_gemma":0.0006976949,"threshold_uncertainty_score":0.23495412},"labels":[],"label_agreement":null},{"id":"W2622676764","doi":"","title":"Car use within the household","year":2013,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Computer science","score_opus":0.025977829406454784,"score_gpt":0.19041177618438562,"score_spread":0.16443394677793083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2622676764","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9122148,0.0009726782,0.00095622486,0.00062484655,0.000044414395,0.00006846678,0.0061192755,0.0000550208,0.07894436],"genre_scores_gemma":[0.9805356,0.00050494174,0.00020852519,0.00006543739,0.000020604084,0.000023119383,0.0013789306,0.000010223311,0.017252577],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99921775,0.00018612805,0.000041964187,0.00020640038,0.00014535576,0.00020243238],"domain_scores_gemma":[0.99906856,0.00014641877,0.00026346307,0.00010184041,0.00020885357,0.00021089551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002099974,0.00020656601,0.0002976166,0.0013367522,0.0012792983,0.002115332,0.00042462646,0.00048920827,0.03105634],"category_scores_gemma":[0.0014951648,0.00018446399,0.00049774814,0.0023035991,0.0003352293,0.0012832833,0.0012602445,0.00049610756,0.0041808444],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031574062,0.000351055,0.88809097,0.0001497608,0.0002571303,0.0005807666,0.009020577,0.0013314186,0.001516092,0.005365303,0.008332604,0.08468854],"study_design_scores_gemma":[0.0000036432962,0.000095187366,0.9515653,0.000062109364,0.00006157081,0.0004519029,0.01777268,0.00059586647,0.000644691,0.00048070235,0.02824303,0.000023252283],"about_ca_topic_score_codex":0.062039286,"about_ca_topic_score_gemma":0.09146682,"teacher_disagreement_score":0.062039286,"about_ca_system_score_codex":0.0012528689,"about_ca_system_score_gemma":0.0008255654,"threshold_uncertainty_score":0.12335634},"labels":[],"label_agreement":null},{"id":"W2622701941","doi":"","title":"The Tube Challenge","year":2014,"lang":"fr","type":"article","venue":"Les Cahiers du GERAD","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Travelling salesman problem; Graph; Mathematical optimization; Computer science; Mathematics; Combinatorics; Operations research","score_opus":0.007399020629852008,"score_gpt":0.19636572500793276,"score_spread":0.18896670437808075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2622701941","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1013421,0.0047120713,0.2492933,0.10589776,0.003441238,0.00048601924,0.0061155837,0.001421845,0.5272901],"genre_scores_gemma":[0.7239856,0.004466211,0.066735744,0.009713457,0.0020910373,0.00066221284,0.0065029413,0.00078224967,0.18506052],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99774903,0.0011087293,0.000066091096,0.00041940846,0.0003245281,0.00033220762],"domain_scores_gemma":[0.9950216,0.0031362737,0.00018942934,0.00040497858,0.00052839064,0.000719323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013710009,0.0007191532,0.0014158007,0.00048031803,0.0027361808,0.0039448314,0.0024167818,0.0044093304,0.049887843],"category_scores_gemma":[0.008293073,0.00034680316,0.0010958455,0.0014760675,0.0030040387,0.0071905055,0.0031249716,0.004450289,0.005935088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022235922,0.00011010761,0.00042650176,0.00025836492,0.000034010256,0.0002889616,0.00028557205,0.022745136,0.0003624672,0.7547845,0.18661743,0.033864614],"study_design_scores_gemma":[0.000087329616,0.00008722966,0.00032317126,0.00012476354,0.000019407295,0.00022388855,0.0007042021,0.050488062,0.00045729353,0.7747942,0.1726515,0.00003892054],"about_ca_topic_score_codex":0.005674047,"about_ca_topic_score_gemma":0.0051210024,"teacher_disagreement_score":0.049887843,"about_ca_system_score_codex":0.0023637074,"about_ca_system_score_gemma":0.0024338227,"threshold_uncertainty_score":0.16689146},"labels":[],"label_agreement":null},{"id":"W2626391197","doi":"10.1016/j.ejor.2017.06.028","title":"The static bike relocation problem with multiple vehicles and visits","year":2017,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":124,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"Luonnontieteiden ja Tekniikan Tutkimuksen Toimikunta; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Relocation; Iterated local search; Computer science; Integer programming; Metaheuristic; Bike sharing; Scheme (mathematics); Vehicle routing problem; Service (business); Mathematical optimization; Iterated function; Operations research; Transport engineering; Routing (electronic design automation); Algorithm; Computer network; Mathematics; Engineering","score_opus":0.056017343068158795,"score_gpt":0.32570382956338184,"score_spread":0.26968648649522303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2626391197","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6033159,0.0028306306,0.34240115,0.0063107195,0.0007502556,0.00061610114,0.0041179815,0.00078554644,0.038871747],"genre_scores_gemma":[0.9195183,0.0011222489,0.037273638,0.0003439344,0.00030986243,0.00025507846,0.0018967587,0.00025010735,0.03903008],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99753463,0.0008641446,0.00011945746,0.0006180202,0.00020463979,0.00065903045],"domain_scores_gemma":[0.9954737,0.0026950077,0.0005153946,0.00030088745,0.00026724936,0.00074773456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019210842,0.002250105,0.00536497,0.0016924468,0.0025705146,0.0038562992,0.006288537,0.007183323,0.01833704],"category_scores_gemma":[0.0080300225,0.0027178365,0.002216668,0.0041827303,0.00221659,0.0065619457,0.0033940084,0.0029308202,0.0018113815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015701047,0.00047050434,0.0026755494,0.0006744492,0.00035212457,0.0019267097,0.0002447366,0.9143754,0.0011868167,0.041755576,0.0134006925,0.021367306],"study_design_scores_gemma":[0.00025414047,0.0002807817,0.001435717,0.00007885829,0.00016082227,0.00082409347,0.0007908906,0.9328182,0.00053300493,0.058995612,0.0037324892,0.0000954007],"about_ca_topic_score_codex":0.0135778515,"about_ca_topic_score_gemma":0.009348203,"teacher_disagreement_score":0.01833704,"about_ca_system_score_codex":0.0019209298,"about_ca_system_score_gemma":0.002002726,"threshold_uncertainty_score":0.06134349},"labels":[],"label_agreement":null},{"id":"W2626807142","doi":"","title":"The Dial-a-Ride Problem: Models and Algorithms","year":2006,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Computer science; Set (abstract data type); Pickup; Algorithm; Plan (archaeology); Operations research; Engineering; Artificial intelligence; Programming language","score_opus":0.008736416109186509,"score_gpt":0.1934707794960693,"score_spread":0.1847343633868828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2626807142","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.059464987,0.0140802255,0.8583684,0.022482842,0.00094673736,0.0005710374,0.005413697,0.0012193987,0.037452567],"genre_scores_gemma":[0.6481407,0.0155728,0.24726792,0.00232895,0.0017450874,0.0016870801,0.0076242792,0.000802783,0.07483037],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99566156,0.0020685655,0.00018311372,0.001016495,0.00035052394,0.0007197636],"domain_scores_gemma":[0.96195465,0.031894904,0.0019765364,0.0015898215,0.0012513223,0.0013328359],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00818268,0.002263733,0.0060147606,0.0031272306,0.00276765,0.007618239,0.00884774,0.009643151,0.025251798],"category_scores_gemma":[0.039830394,0.0022393698,0.0030353304,0.006087961,0.0038260154,0.014346609,0.0042004087,0.0069460543,0.003467608],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042151485,0.00047250124,0.0030752283,0.00061514985,0.000278031,0.00020683648,0.00033838802,0.57081544,0.00011073239,0.31058657,0.065362655,0.047716975],"study_design_scores_gemma":[0.00012354078,0.00004281676,0.00034425122,0.00010032882,0.00006614876,0.00008752654,0.00020008026,0.7038392,0.00008038439,0.28832188,0.006756381,0.00003749797],"about_ca_topic_score_codex":0.027116902,"about_ca_topic_score_gemma":0.022609424,"teacher_disagreement_score":0.027116902,"about_ca_system_score_codex":0.004956165,"about_ca_system_score_gemma":0.0047039567,"threshold_uncertainty_score":0.084475696},"labels":[],"label_agreement":null},{"id":"W2654326085","doi":"10.1299/jsmermd.2011._2p1-g07_1","title":"2P1-G07 Advanced Community Model with Information Transmission Supporting System for Lonely Elderly Person and Aging Welfare Society(Welfare Robotics and Mechatronics(1))","year":2011,"lang":"en","type":"article","venue":"The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Welfare; Mechatronics; Government (linguistics); Robotics; Plan (archaeology); Transmission (telecommunications); Artificial intelligence; Engineering; Computer science; Sociology; Robot; Economics; Telecommunications; Geography; Market economy","score_opus":0.026188983296182522,"score_gpt":0.22717729489910288,"score_spread":0.20098831160292036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2654326085","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.121194325,0.0002229643,0.84249973,0.0010912715,0.00015061865,0.00015989951,0.00051987596,0.0005073938,0.03365394],"genre_scores_gemma":[0.9282585,0.00023083898,0.051499527,0.00007984926,0.00005254101,0.0003289308,0.0004879738,0.00004216566,0.019019682],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973327,0.00006989492,0.00001132853,0.00007075094,0.000072458104,0.000042272382],"domain_scores_gemma":[0.9997577,0.000041812084,0.00002413509,0.00002393252,0.00010310132,0.000049278235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034126267,0.00040099683,0.00038789154,0.00046472176,0.00094590645,0.0010255113,0.0009775665,0.0008485464,0.005876997],"category_scores_gemma":[0.0007277691,0.00016337808,0.0007286713,0.00036226184,0.0005390612,0.0019770288,0.0011158765,0.0005983761,0.0006152619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020674341,0.00017204203,0.0055793826,0.00019179612,0.00006907558,0.00076958584,0.0010040556,0.6206789,0.0073009795,0.30294695,0.008252739,0.052827753],"study_design_scores_gemma":[0.000026626294,0.000072450006,0.00056159566,0.00001231761,0.000020822126,0.000093907154,0.00015024535,0.9688035,0.00047424264,0.025057385,0.0047100014,0.000016935164],"about_ca_topic_score_codex":0.014692738,"about_ca_topic_score_gemma":0.0067845993,"teacher_disagreement_score":0.014692738,"about_ca_system_score_codex":0.0008749182,"about_ca_system_score_gemma":0.0013499355,"threshold_uncertainty_score":0.029214382},"labels":[],"label_agreement":null},{"id":"W2698846","doi":"10.1139/g89-155","title":"Verbesserung von GPS-basierter Ortung durch GSM-Geschwindigkeitsschaetzungen","year":2009,"lang":"en","type":"article","venue":"Genome","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Global Positioning System; Computer science; Telecommunications","score_opus":0.010154025078356586,"score_gpt":0.21724703771927226,"score_spread":0.20709301264091567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2698846","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37064204,0.0038576322,0.50433475,0.00202128,0.0012296296,0.0004497607,0.001688311,0.007714591,0.10806198],"genre_scores_gemma":[0.93201745,0.0014134651,0.05157203,0.00022181317,0.00006381217,0.0002424587,0.00065339665,0.00047420632,0.013341393],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984646,0.0003322481,0.00008938115,0.0003451489,0.00047230016,0.00029636864],"domain_scores_gemma":[0.9985122,0.000603899,0.00013462151,0.00037014423,0.0002888932,0.00009025933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015657777,0.000897669,0.0006865626,0.0011969752,0.0008900902,0.0024694966,0.0009864104,0.0010566249,0.022749083],"category_scores_gemma":[0.0051265154,0.00045255953,0.00068098516,0.0011639617,0.0014074583,0.0019907192,0.003381565,0.0020597598,0.008391874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002288563,0.00037628456,0.008000761,0.00067253184,0.00014943226,0.0010977042,0.00214104,0.110409826,0.13141496,0.22361843,0.010062049,0.5097685],"study_design_scores_gemma":[0.00044227755,0.0017093137,0.007119363,0.00049721193,0.00019744178,0.0012298024,0.0017729459,0.52904755,0.17744102,0.15806845,0.12214013,0.0003345459],"about_ca_topic_score_codex":0.0022616498,"about_ca_topic_score_gemma":0.0012350884,"teacher_disagreement_score":0.022749083,"about_ca_system_score_codex":0.0013327263,"about_ca_system_score_gemma":0.0008265935,"threshold_uncertainty_score":0.07610333},"labels":[],"label_agreement":null},{"id":"W2711624128","doi":"10.1299/jsmermd.2012._1p1-n08_1","title":"1P1-N08 Pilot Program Report of Sustainable and Feasible Advanced Community Model with the Welfare Support Sensor System for the Aging Society(Welfare Robotics and Mechatronics (1))","year":2012,"lang":"en","type":"article","venue":"The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Mechatronics; Robotics; Welfare; Social Welfare; Welfare system; Computer science; Sustainable development; Pilot program; Artificial intelligence; Engineering; Engineering management; Simulation; Robot; Economics; Medical education; Medicine; Political science","score_opus":0.025770395779679062,"score_gpt":0.2571495111094428,"score_spread":0.2313791153297637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2711624128","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48183653,0.00084226206,0.3141394,0.010758697,0.0029785994,0.040830504,0.022491133,0.008205899,0.117917046],"genre_scores_gemma":[0.71310157,0.0007597991,0.15954454,0.0012300876,0.0005833153,0.015561573,0.02483405,0.0008102764,0.0835748],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9961075,0.0012697546,0.0001008703,0.0002874651,0.001812108,0.00042243736],"domain_scores_gemma":[0.9944616,0.0007913124,0.00015054863,0.0005822681,0.0031165336,0.00089766603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007828782,0.0010121284,0.00064916996,0.0011015796,0.0015628373,0.0008710718,0.0023421182,0.0014366338,0.010927588],"category_scores_gemma":[0.005304023,0.0003267842,0.0007016981,0.00034154323,0.00068405597,0.0010066887,0.0021219593,0.0011261452,0.0023983812],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0061534294,0.015013629,0.02402725,0.0014058547,0.00033009434,0.0028666828,0.0025437265,0.025019694,0.1213079,0.009204178,0.3230388,0.4690887],"study_design_scores_gemma":[0.0042503085,0.07705546,0.05659699,0.00027590225,0.0005186317,0.001881683,0.0042323614,0.09973667,0.23105724,0.00457165,0.5194409,0.00038213978],"about_ca_topic_score_codex":0.013295928,"about_ca_topic_score_gemma":0.0130282445,"teacher_disagreement_score":0.013295928,"about_ca_system_score_codex":0.001230213,"about_ca_system_score_gemma":0.004731525,"threshold_uncertainty_score":0.041403055},"labels":[],"label_agreement":null},{"id":"W2728395416","doi":"10.1177/1687814017706433","title":"Vehicle routing and scheduling of demand-responsive connector with on-demand stations","year":2017,"lang":"en","type":"article","venue":"Advances in Mechanical Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Routing (electronic design automation); Scheduling (production processes); Computer science; Transit (satellite); On demand; Public transport; Demand management; Transport engineering; Operations research; Computer network; Engineering; Operations management; Economics","score_opus":0.008058166270838127,"score_gpt":0.2491272821381033,"score_spread":0.24106911586726518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2728395416","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4974952,0.00018592454,0.48523992,0.0003684374,0.000113226815,0.00027279518,0.00042134637,0.0006331144,0.015270127],"genre_scores_gemma":[0.9737638,0.00007464766,0.022396768,0.000022142538,0.000010083299,0.00005325475,0.0002719884,0.000047200083,0.0033600852],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961346,0.000112301685,0.000011422666,0.00007028103,0.000054682638,0.00013787943],"domain_scores_gemma":[0.99973124,0.00006968738,0.000047313475,0.000022566777,0.000060562663,0.000068656074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004544632,0.0007296052,0.00057464646,0.00037359237,0.0006016733,0.0008392668,0.0011475857,0.0006996085,0.0031474226],"category_scores_gemma":[0.0007522423,0.00042604376,0.00047285756,0.00065897463,0.00033179353,0.0005838692,0.0005552335,0.00038461166,0.00024740666],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000088561574,0.0000533769,0.001016231,0.000028748635,0.000014052476,0.00011863117,0.000034136952,0.98151577,0.0026605062,0.0034753175,0.001079104,0.009915631],"study_design_scores_gemma":[0.0000070564433,0.00003336601,0.00023577975,7.165902e-7,0.0000042200813,0.000009769117,0.00003306139,0.99831164,0.00041502243,0.0006098779,0.00033576926,0.0000037131442],"about_ca_topic_score_codex":0.021419918,"about_ca_topic_score_gemma":0.018058097,"teacher_disagreement_score":0.021419918,"about_ca_system_score_codex":0.0015860467,"about_ca_system_score_gemma":0.0014858237,"threshold_uncertainty_score":0.0425905},"labels":[],"label_agreement":null},{"id":"W2728943345","doi":"10.17645/up.v2i2.937","title":"Investigating the Potential of Ridesharing to Reduce Vehicle Emissions","year":2017,"lang":"en","type":"article","venue":"Urban Planning","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; George Cedric Metcalf Charitable Foundation","keywords":"Transport engineering; Greenhouse gas; Traffic congestion; TRIPS architecture; Fuel efficiency; Population; Public transport; Environmental economics; Business; Engineering; Automotive engineering; Economics","score_opus":0.031690488448788585,"score_gpt":0.2768858287099361,"score_spread":0.24519534026114753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2728943345","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97840655,0.0014612613,0.0027835385,0.00044305233,0.000020626514,0.00007085088,0.00036432172,0.00004411087,0.016405707],"genre_scores_gemma":[0.99546033,0.0011499882,0.0017814822,0.00003616392,0.000007956388,0.000022504082,0.00017361679,0.0000040512004,0.0013640276],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997452,0.00006233309,0.000012631809,0.000041834934,0.000077900324,0.00006005072],"domain_scores_gemma":[0.9996147,0.00014592879,0.00005546274,0.000027984328,0.00013693857,0.000018991534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005516131,0.00030814734,0.00018009565,0.0006878662,0.00028627625,0.00073553855,0.00049953314,0.00040073597,0.0015207264],"category_scores_gemma":[0.0010980519,0.00010549574,0.00045752415,0.00091981044,0.00021382578,0.0008335642,0.00030042094,0.00021319387,0.00020777807],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009450304,0.00094435195,0.38980412,0.0021796157,0.0005833446,0.0015352097,0.0012124466,0.17237827,0.04342844,0.021355612,0.0038992006,0.36173436],"study_design_scores_gemma":[0.00011931097,0.0062061655,0.5641999,0.0005287034,0.0011697126,0.000747128,0.011854421,0.2521737,0.075072,0.017733626,0.07002362,0.00017169888],"about_ca_topic_score_codex":0.023794632,"about_ca_topic_score_gemma":0.02738781,"teacher_disagreement_score":0.023794632,"about_ca_system_score_codex":0.00076700945,"about_ca_system_score_gemma":0.00088010967,"threshold_uncertainty_score":0.04731226},"labels":[],"label_agreement":null},{"id":"W2729612135","doi":"10.55016/ojs/sppp.v9i1.42559","title":"Mind the Gap: Transportation Challenges for Individuals Living with Autism Spectrum Disorder","year":2016,"lang":"en","type":"article","venue":"The School of Public Policy Publications","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Autism spectrum disorder; Psychology; Spectrum (functional analysis); Psychiatry; Autism; Physics","score_opus":0.03542079449180737,"score_gpt":0.2696538472078106,"score_spread":0.23423305271600323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2729612135","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13356562,0.033539575,0.0018152009,0.7684155,0.0077917525,0.00010215823,0.00092017197,0.0002573367,0.05359264],"genre_scores_gemma":[0.7823605,0.047936216,0.004191565,0.13685107,0.0036329273,0.0002668551,0.0013254978,0.00014568903,0.023289714],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99909616,0.00026268658,0.00007371489,0.00007545709,0.0002115871,0.0002803381],"domain_scores_gemma":[0.9976897,0.00042604288,0.00023803125,0.00005265905,0.00059927406,0.0009942753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012849774,0.0004048634,0.00042498382,0.00070968224,0.006116972,0.002333256,0.0011057631,0.0034901379,0.010660062],"category_scores_gemma":[0.005772543,0.00019148132,0.00062473014,0.00062465365,0.001535271,0.004877241,0.0050075036,0.0036699767,0.0014919016],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008036121,0.0003168832,0.06682939,0.0010892056,0.00006758128,0.005011297,0.025166828,0.00031774232,0.0004667651,0.0065400098,0.52504927,0.36906472],"study_design_scores_gemma":[0.000038514485,0.00044105627,0.10163509,0.0062567163,0.00016491176,0.013814031,0.28116333,0.0007402317,0.0004165118,0.025862189,0.569317,0.00015045547],"about_ca_topic_score_codex":0.030911451,"about_ca_topic_score_gemma":0.07113296,"teacher_disagreement_score":0.030911451,"about_ca_system_score_codex":0.002850854,"about_ca_system_score_gemma":0.006357434,"threshold_uncertainty_score":0.061463058},"labels":[],"label_agreement":null},{"id":"W2731854017","doi":"10.1016/j.trb.2017.06.015","title":"An agent-based day-to-day adjustment process for modeling ‘Mobility as a Service’ with a two-sided flexible transport market","year":2017,"lang":"en","type":"article","venue":"Transportation Research Part B Methodological","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":147,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"University of Toronto; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Carpool; Network effect; Service (business); Externality; Process (computing); Operations research; Computer science; Operator (biology); Last mile (transportation); Sharing economy; Microeconomics; Economics; Mile; Transport engineering; Engineering; Economy","score_opus":0.43098929574541495,"score_gpt":0.5023408898337678,"score_spread":0.07135159408835284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2731854017","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13742383,0.0006102267,0.8491553,0.0017595901,0.00026258442,0.00013434657,0.00060977583,0.00045609864,0.009588168],"genre_scores_gemma":[0.967132,0.00026675928,0.022908749,0.00012874366,0.00006993066,0.00013001675,0.00023752365,0.00007473244,0.0090514785],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991528,0.00036021258,0.000039481143,0.00021303122,0.00007885471,0.00015572087],"domain_scores_gemma":[0.99774665,0.0013807825,0.00027897413,0.00008713943,0.00023507573,0.00027148006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020556767,0.001171654,0.0024873363,0.0007580702,0.0009889331,0.002856879,0.0031936455,0.004652161,0.0063815988],"category_scores_gemma":[0.0056865434,0.0014025297,0.0015593627,0.00094105006,0.0019828395,0.0026647397,0.0025130492,0.0032153942,0.0006422991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045469904,0.000027992846,0.00042685727,0.000016159183,0.000033750974,0.00006863702,0.000041945445,0.98676646,0.00012770604,0.01092569,0.00031368667,0.0012056826],"study_design_scores_gemma":[0.0000046894233,0.000004691378,0.000039186587,0.0000011343915,0.0000036826382,0.0000025806874,0.000004681447,0.9985751,0.00001169327,0.0012638667,0.00008572493,0.0000030377087],"about_ca_topic_score_codex":0.03744237,"about_ca_topic_score_gemma":0.017111812,"teacher_disagreement_score":0.03744237,"about_ca_system_score_codex":0.0020925724,"about_ca_system_score_gemma":0.0020558985,"threshold_uncertainty_score":0.07444888},"labels":[],"label_agreement":null},{"id":"W2732232436","doi":"10.1007/978-3-319-60934-8_17","title":"Understanding the Effects of Autonomous Vehicles on Urban Form","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in mobility","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Government (linguistics); Order (exchange); Competition (biology); Quality (philosophy); Business; Risk analysis (engineering); Disruptive technology; Computer science; Marketing; Management science; Engineering","score_opus":0.029162236736851945,"score_gpt":0.23741052154463488,"score_spread":0.20824828480778293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2732232436","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36139998,0.005897862,0.13619539,0.006705226,0.00036627866,0.00004524092,0.0008621401,0.000280552,0.4882473],"genre_scores_gemma":[0.97052664,0.003378994,0.0053682174,0.00011603446,0.00007733912,0.000018346627,0.00014201866,0.000078440695,0.0202941],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998553,0.000040651943,0.000003043469,0.000033685512,0.000036450525,0.000030742052],"domain_scores_gemma":[0.9996331,0.00020844056,0.000039075723,0.000045384393,0.000045266865,0.000028687142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020510545,0.00046541487,0.00027665493,0.0004089764,0.0004408869,0.0023932687,0.00067224936,0.0006722138,0.015355851],"category_scores_gemma":[0.0014588333,0.00040939706,0.0004075568,0.0005724058,0.0015472296,0.0029084785,0.0012320417,0.00082233426,0.0009672638],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006503798,0.000051471015,0.0048742075,0.00016700005,0.00003252046,0.00016974368,0.0015822115,0.14431313,0.0046972665,0.772234,0.0056307507,0.06618269],"study_design_scores_gemma":[0.000012607178,0.000050957842,0.013430419,0.000066266366,0.000034944307,0.000113261885,0.002634189,0.09432299,0.001607735,0.8457045,0.041985646,0.00003654826],"about_ca_topic_score_codex":0.0072390935,"about_ca_topic_score_gemma":0.008916974,"teacher_disagreement_score":0.015355851,"about_ca_system_score_codex":0.0008452704,"about_ca_system_score_gemma":0.00042848205,"threshold_uncertainty_score":0.051370442},"labels":[],"label_agreement":null},{"id":"W2736194638","doi":"10.1177/171516350513800201","title":"Stepping in Front of a Truck: In Hindsight, a Poor Choice","year":2005,"lang":"en","type":"article","venue":"Canadian Pharmacists Journal / Revue des Pharmaciens du Canada","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Hindsight bias; Truck; Front (military); Aeronautics; Psychology; Engineering; Automotive engineering; Cognitive psychology; Mechanical engineering","score_opus":0.019816065664841696,"score_gpt":0.23898269790283616,"score_spread":0.21916663223799446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2736194638","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41349837,0.002149572,0.002383812,0.5000852,0.0014226235,0.00006242401,0.0003373516,0.00010971303,0.0799509],"genre_scores_gemma":[0.8964795,0.001800286,0.0015256355,0.06637979,0.00021985738,0.00002157229,0.00008970976,0.00012382238,0.033359893],"study_design_codex":"not_applicable","study_design_gemma":"case_report","domain_scores_codex":[0.9955851,0.0012219043,0.00016990374,0.00031788973,0.0008732481,0.001831925],"domain_scores_gemma":[0.98889416,0.0014742524,0.0011178115,0.00049605215,0.0021535659,0.0058642407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033830355,0.000241497,0.00055681256,0.0008512087,0.011164073,0.0046940083,0.0011728219,0.0037360804,0.019967733],"category_scores_gemma":[0.018326608,0.00038390557,0.00047642842,0.0012027038,0.0062029674,0.003229565,0.0023231162,0.00867492,0.0030570347],"study_design_candidate":"case_report","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003615086,0.0008147945,0.22081004,0.00020745452,0.00013905276,0.013628192,0.068086155,0.00045075914,0.001851683,0.036569584,0.47485033,0.18223041],"study_design_scores_gemma":[0.0000871123,0.00030633833,0.12309319,0.001426111,0.00016694804,0.027893495,0.40644535,0.0020456032,0.0012143244,0.04986138,0.38709888,0.0003612833],"about_ca_topic_score_codex":0.17339005,"about_ca_topic_score_gemma":0.32156077,"teacher_disagreement_score":0.17339005,"about_ca_system_score_codex":0.0037497415,"about_ca_system_score_gemma":0.013204294,"threshold_uncertainty_score":0.34476155},"labels":[],"label_agreement":null},{"id":"W2736502516","doi":"","title":"A Tabu Search Heuristic for the Static Multi-Vehicle Dial-a-Ride Problem","year":2002,"lang":"fr","type":"article","venue":"RePEc: Research Papers in Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Tabu search; Heuristic; Duration (music); Computer science; Set (abstract data type); Vehicle routing problem; Window (computing); Operations research; Mathematical optimization; Transport engineering; Engineering; Computer network; Routing (electronic design automation); Artificial intelligence; Mathematics","score_opus":0.05883653785243593,"score_gpt":0.3097767019214566,"score_spread":0.2509401640690207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2736502516","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.062001172,0.0035199353,0.9107873,0.0005299723,0.0002550982,0.00064524054,0.0007893323,0.0023713757,0.019100532],"genre_scores_gemma":[0.26364645,0.0010800684,0.7250799,0.0003940536,0.00008760464,0.0007978385,0.0012357305,0.0005379204,0.0071405154],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988551,0.00065170985,0.00003273575,0.00011871247,0.00016456936,0.00017713766],"domain_scores_gemma":[0.9982679,0.0012438509,0.000108553526,0.0000919542,0.00020486131,0.00008297607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017805286,0.0011261827,0.0017251266,0.0022670622,0.0012155778,0.0015684547,0.0021947725,0.0020109937,0.00818597],"category_scores_gemma":[0.004249475,0.0007905602,0.0009561832,0.0032061434,0.0012097596,0.0014907065,0.00088129746,0.0010396864,0.0014988341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015837347,0.00018496181,0.0005017269,0.00016137995,0.0000673391,0.000101320074,0.00011066051,0.87871075,0.0005850223,0.010923967,0.0060858172,0.10240866],"study_design_scores_gemma":[0.000112933114,0.00012669989,0.00019297366,0.000041653162,0.000034042132,0.000057507517,0.00007942147,0.98636925,0.0004291648,0.008380384,0.004153353,0.000022586599],"about_ca_topic_score_codex":0.009834957,"about_ca_topic_score_gemma":0.009057331,"teacher_disagreement_score":0.009834957,"about_ca_system_score_codex":0.0017112406,"about_ca_system_score_gemma":0.0024677506,"threshold_uncertainty_score":0.027384818},"labels":[],"label_agreement":null},{"id":"W2736563843","doi":"10.2495/dne-v12-n4-505-515","title":"More space and improved living conditions in cities with autonomous vehicles","year":2018,"lang":"en","type":"article","venue":"International Journal of Design & Nature and Ecodynamics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Externality; Transport engineering; Megacity; Bottleneck; Sustainable transport; Business; Public transport; Space (punctuation); Investment (military); Traffic congestion; Sustainability; Environmental economics; Engineering; Computer science; Operations management; Economics","score_opus":0.0060191839468581275,"score_gpt":0.23222367036496247,"score_spread":0.22620448641810434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2736563843","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8549396,0.0034827944,0.003032994,0.013038924,0.0010599473,0.00009034172,0.0010885508,0.00022732274,0.12303961],"genre_scores_gemma":[0.97433305,0.0011018575,0.0018324107,0.0016175858,0.00016187462,0.0000762135,0.00065722613,0.000026824888,0.02019297],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966097,0.00008422275,0.000016558559,0.000053832897,0.00006353503,0.00012084735],"domain_scores_gemma":[0.9995741,0.000014510291,0.00007269316,0.000031672,0.00009124828,0.000215732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002543484,0.00017900766,0.0002175579,0.00042025401,0.0016219767,0.00239769,0.00047913988,0.00068993063,0.011925053],"category_scores_gemma":[0.00070456,0.000080596576,0.00030795205,0.0005256387,0.001211217,0.0013006185,0.0025769742,0.00073106115,0.0016861077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053521764,0.0014861742,0.3234552,0.0008051174,0.00018862681,0.0045683887,0.021019697,0.0028850546,0.009535701,0.077553265,0.13090353,0.4270639],"study_design_scores_gemma":[0.00012443571,0.0007080683,0.48821324,0.00027775357,0.00008282638,0.0022012964,0.023887493,0.0012135949,0.0011080891,0.027177872,0.45489237,0.00011292019],"about_ca_topic_score_codex":0.009349533,"about_ca_topic_score_gemma":0.015144278,"teacher_disagreement_score":0.011925053,"about_ca_system_score_codex":0.00079969066,"about_ca_system_score_gemma":0.0009990304,"threshold_uncertainty_score":0.03989321},"labels":[],"label_agreement":null},{"id":"W2738783740","doi":"10.3141/2668-06","title":"Who is Picking Up the Child from Day Care?: Understanding the Intrahousehold Dynamics in Drop-Off and Pickup Allocation for Households with Dependent Children","year":2017,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Pickup; Budget constraint; Econometric model; Economics; Drop (telecommunication); Computer science; Constraint (computer-aided design); Location-allocation; Resource allocation; Operations research; Econometrics; Microeconomics; Engineering","score_opus":0.0702547736823752,"score_gpt":0.3284438237645714,"score_spread":0.25818905008219617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2738783740","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9653777,0.00025450494,0.026297856,0.0021819414,0.000014438336,0.00005262199,0.0004710165,0.000018051207,0.0053318553],"genre_scores_gemma":[0.99384886,0.00026828924,0.0028062644,0.000056192195,0.000009080367,0.000038762617,0.00016656583,0.000008755703,0.0027971794],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9995803,0.00017127655,0.000011971961,0.00007117612,0.000028223641,0.00013708569],"domain_scores_gemma":[0.99870765,0.00077805604,0.00026428874,0.000043702756,0.000051508086,0.00015472916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092292734,0.00031145415,0.0006200038,0.00036531026,0.00053323497,0.0017652131,0.0013408528,0.0011358984,0.005896771],"category_scores_gemma":[0.0034790505,0.0004885375,0.0006657528,0.00069938955,0.0009255119,0.0019654592,0.0012331194,0.001286086,0.00051184476],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046422414,0.0006830066,0.2730795,0.00015165372,0.0001582608,0.0014135351,0.0043287165,0.56928545,0.0012390459,0.112388745,0.0038455066,0.032962386],"study_design_scores_gemma":[0.000051965915,0.00016342751,0.07569609,0.00005068299,0.000059804588,0.00019989004,0.007408989,0.86975855,0.00032042686,0.04296919,0.0032749404,0.000046023753],"about_ca_topic_score_codex":0.057429917,"about_ca_topic_score_gemma":0.048529085,"teacher_disagreement_score":0.057429917,"about_ca_system_score_codex":0.0025031096,"about_ca_system_score_gemma":0.0012281856,"threshold_uncertainty_score":0.114191234},"labels":[],"label_agreement":null},{"id":"W2741912721","doi":"10.1109/icc.2017.7996577","title":"Resource assignment in vehicular clouds","year":2017,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; University of Lethbridge","funders":"","keywords":"Computer science; Scheduling (production processes); Cloud computing; Distributed computing; Grid; Workload; Grid computing; Job shop scheduling; Schedule; Greedy algorithm; Dynamic priority scheduling; Mathematical optimization; Algorithm; Mathematics","score_opus":0.015232181113655534,"score_gpt":0.2392782892919394,"score_spread":0.22404610817828385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2741912721","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10769875,0.0017883655,0.87382174,0.0010456658,0.00031219647,0.000101876096,0.00030351593,0.00038168524,0.014546217],"genre_scores_gemma":[0.9576264,0.0007999462,0.03779083,0.000110020046,0.00008745435,0.00005824954,0.00015733784,0.000059333244,0.0033104778],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990963,0.0002837065,0.000030991134,0.00013132018,0.0001639814,0.0002937025],"domain_scores_gemma":[0.99897015,0.0005429669,0.00011411032,0.000108613516,0.00014641385,0.00011779592],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069765234,0.0006575161,0.00076277705,0.00050635566,0.00090244366,0.0012945067,0.0012592173,0.0006612568,0.0026178355],"category_scores_gemma":[0.0035313244,0.00037633535,0.00044299607,0.0013882066,0.0007477949,0.0014962358,0.0013608081,0.00070670154,0.00040796163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007133472,0.000023318205,0.00051511667,0.000074842035,0.000021957296,0.00010481656,0.00006112397,0.92020255,0.0010419168,0.063344814,0.0024172165,0.012120984],"study_design_scores_gemma":[0.00001029053,0.0000185575,0.00018496625,0.0000079368665,0.0000071754225,0.000035584642,0.000083225445,0.96289265,0.00046385397,0.033435944,0.0028527589,0.000006947207],"about_ca_topic_score_codex":0.0091960225,"about_ca_topic_score_gemma":0.005236402,"teacher_disagreement_score":0.0091960225,"about_ca_system_score_codex":0.0013377399,"about_ca_system_score_gemma":0.0012230251,"threshold_uncertainty_score":0.018284976},"labels":[],"label_agreement":null},{"id":"W2747252153","doi":"10.1109/ms.2018.110154908","title":"Software Engineering for Sustainability: Find the Leverage Points!","year":2018,"lang":"en","type":"article","venue":"IEEE Software","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Engineering and Physical Sciences Research Council","keywords":"Leverage (statistics); Sustainability; Social software engineering; Personal software process; Software development; Software engineering; Software; Software Engineering Process Group; Software system; Computer science; Software construction; Software development process; Systems engineering; Engineering; Engineering management","score_opus":0.012142928146104556,"score_gpt":0.23607399775399163,"score_spread":0.22393106960788706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2747252153","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04132478,0.060076375,0.6181172,0.17558318,0.0017269957,0.00016237142,0.00017912747,0.0018092303,0.1010207],"genre_scores_gemma":[0.6455436,0.056817904,0.26761806,0.0071859057,0.0021364246,0.00030284145,0.00023291516,0.0013523005,0.018810028],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9910801,0.00393695,0.00041585017,0.0009938622,0.002936438,0.0006367928],"domain_scores_gemma":[0.97807956,0.013733605,0.0011637915,0.0035188536,0.0024970118,0.0010071967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011600538,0.0017302643,0.0009699506,0.0037734606,0.003141093,0.010269852,0.0019673242,0.0046626325,0.0066592693],"category_scores_gemma":[0.029500563,0.0010602347,0.0009654546,0.0037195825,0.016640661,0.05083541,0.010320562,0.007753541,0.002953587],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004662136,0.00008757193,0.0029121034,0.0007327436,0.000057613364,0.0004456946,0.006031614,0.001912683,0.0017215871,0.70291185,0.016480757,0.26665914],"study_design_scores_gemma":[0.000011916853,0.00007729677,0.0004337757,0.001019989,0.000027963146,0.00021681082,0.003368329,0.002845092,0.0015350499,0.86842567,0.121992245,0.0000458944],"about_ca_topic_score_codex":0.0020397361,"about_ca_topic_score_gemma":0.0023703903,"teacher_disagreement_score":0.011600538,"about_ca_system_score_codex":0.0020923864,"about_ca_system_score_gemma":0.0032744857,"threshold_uncertainty_score":0.061350226},"labels":[],"label_agreement":null},{"id":"W2747540564","doi":"10.1287/trsc.2017.0774","title":"The Chinese Postman Problem with Load-Dependent Costs","year":2018,"lang":"en","type":"article","venue":"Transportation Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"European Regional Development Fund; Generalitat Valenciana; Ministerio de Economía y Competitividad","keywords":"Traverse; Mathematical optimization; Enhanced Data Rates for GSM Evolution; Metaheuristic; Constant (computer programming); Moment (physics); Computational complexity theory; Computer science; Vehicle routing problem; Mathematics; Algorithm; Routing (electronic design automation); Artificial intelligence","score_opus":0.005575537869462892,"score_gpt":0.24059947576609805,"score_spread":0.23502393789663517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2747540564","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07822338,0.0009891466,0.88960963,0.0021974759,0.0004003825,0.0003860313,0.0010127741,0.0002299203,0.026951233],"genre_scores_gemma":[0.5624243,0.0016004619,0.39598078,0.000474333,0.00037015887,0.00074190414,0.0009851193,0.0002493331,0.037173606],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915314,0.00026852536,0.0000417055,0.00019425672,0.00015378612,0.00018860339],"domain_scores_gemma":[0.9985927,0.00087749894,0.00017620565,0.00010441044,0.00012444454,0.00012482656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013558135,0.0013876422,0.0014221267,0.0005915522,0.0009486122,0.0016299635,0.0023435515,0.0020113871,0.00877984],"category_scores_gemma":[0.0030701929,0.0005631362,0.0011017292,0.0014597519,0.0014295406,0.0037265262,0.0014883216,0.0019471694,0.0006135935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018840973,0.00014710776,0.00059531786,0.0003340007,0.00006588754,0.0004895378,0.00015065048,0.677334,0.0021095609,0.27295575,0.008847616,0.036782045],"study_design_scores_gemma":[0.0000933153,0.00016529705,0.00038371922,0.000033205455,0.000039400576,0.0002034395,0.00009370733,0.8122032,0.0017388585,0.17313728,0.011868241,0.00004026921],"about_ca_topic_score_codex":0.0047245985,"about_ca_topic_score_gemma":0.004218147,"teacher_disagreement_score":0.00877984,"about_ca_system_score_codex":0.0016903019,"about_ca_system_score_gemma":0.0033645174,"threshold_uncertainty_score":0.02937156},"labels":[],"label_agreement":null},{"id":"W2748025624","doi":"10.13034/jsst.v10i1.177","title":"SimpleTech: Simplifying Technology for the Elderly","year":2017,"lang":"en","type":"article","venue":"Journal of Student Science and Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Android (operating system); Computer science; User interface; Humanities; Phone; Multimedia; World Wide Web; Art; Operating system; Philosophy","score_opus":0.02905001162460183,"score_gpt":0.3282994328703621,"score_spread":0.29924942124576026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2748025624","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28771967,0.023021625,0.22133842,0.018084208,0.008880979,0.006856529,0.006823755,0.06408166,0.3631932],"genre_scores_gemma":[0.441129,0.015214152,0.21269512,0.012711139,0.0021803463,0.002790999,0.008371178,0.0067568105,0.29815125],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99847084,0.00035210245,0.00014469036,0.00011261471,0.00076513476,0.00015457893],"domain_scores_gemma":[0.9969326,0.0007685711,0.00024642376,0.00049468287,0.0012184068,0.00033920808],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014077707,0.0010509439,0.00034308818,0.0009890364,0.00063332124,0.0016581528,0.0010165016,0.0014378389,0.02360315],"category_scores_gemma":[0.010293779,0.00039119,0.0009249076,0.00045440794,0.0004971746,0.0029614517,0.0031557607,0.00089021446,0.020540446],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005799487,0.0002636822,0.0039868625,0.0018209198,0.000053456555,0.0012362543,0.004213308,0.00022125199,0.022455396,0.0030768523,0.2978845,0.66420764],"study_design_scores_gemma":[0.00011835906,0.0008647562,0.017071636,0.00076882425,0.00014760776,0.005280238,0.0016741161,0.0010079041,0.010197854,0.0022319802,0.96047664,0.0001601711],"about_ca_topic_score_codex":0.0014468865,"about_ca_topic_score_gemma":0.0024328528,"teacher_disagreement_score":0.02360315,"about_ca_system_score_codex":0.00034871395,"about_ca_system_score_gemma":0.00068304886,"threshold_uncertainty_score":0.07896036},"labels":[],"label_agreement":null},{"id":"W2748694329","doi":"","title":"A Data Set for the Simultaneous Vehicle Scheduling and Passenger Service Problem","year":2008,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Scheduling (production processes); Computer science; Operations research; Operations management; Mathematics; Engineering","score_opus":0.0633057167912173,"score_gpt":0.2691607137060821,"score_spread":0.20585499691486478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2748694329","genre_codex":"empirical","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5036077,0.0010066765,0.014818542,0.0019861874,0.0002845938,0.0005374912,0.47088474,0.0015508485,0.0053232163],"genre_scores_gemma":[0.39645943,0.0004702948,0.03465387,0.00023465132,0.000065139815,0.00071110664,0.56524557,0.00011525146,0.0020447152],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99867,0.0002934249,0.00015125854,0.00029811502,0.00044588224,0.00014139162],"domain_scores_gemma":[0.99235266,0.004351795,0.00043556126,0.0011414214,0.0013033042,0.00041524958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013460771,0.00097337074,0.0009226016,0.002038853,0.0010462522,0.0009932015,0.0017573878,0.0023190712,0.004127236],"category_scores_gemma":[0.0082222475,0.0005314886,0.0011481106,0.0036221212,0.00059561135,0.0011085116,0.00069808733,0.0016467888,0.0017850174],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031814254,0.006569889,0.07784499,0.0031454372,0.00077794516,0.0026750078,0.0004851927,0.3943337,0.012996959,0.013679631,0.36150452,0.12280527],"study_design_scores_gemma":[0.0022200427,0.0014800228,0.17056894,0.0002608865,0.0003592914,0.0025698065,0.0017375415,0.615358,0.018033423,0.016285302,0.17084597,0.0002808725],"about_ca_topic_score_codex":0.023167051,"about_ca_topic_score_gemma":0.026710946,"teacher_disagreement_score":0.023167051,"about_ca_system_score_codex":0.0013987349,"about_ca_system_score_gemma":0.0021672784,"threshold_uncertainty_score":0.046064377},"labels":[],"label_agreement":null},{"id":"W2751557127","doi":"","title":"Toward an Understanding of the Built Environment Influences on the Carpool Formation and Use Process: A Case Study of Employer-based Users within the Service Sector of Smart Commute’s Carpool Zone","year":2011,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"University of Toronto Mississauga; University of Toronto","keywords":"Carpool; Transport engineering; Service (business); Engineering; Public transport; Process (computing); Odds; Business; Computer science; Marketing","score_opus":0.10201861369054395,"score_gpt":0.297236152415841,"score_spread":0.19521753872529707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2751557127","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99778926,0.000029579376,0.00018655666,0.00020682576,0.0000013188272,0.000013607389,0.000013420016,0.0000013430932,0.0017581884],"genre_scores_gemma":[0.99844617,0.00011069806,0.00028001628,0.00005996766,0.0000016880999,0.000011381441,0.000014028414,0.000002522391,0.0010735667],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.99911016,0.00045631462,0.000022728642,0.00007147702,0.0000946135,0.0002447088],"domain_scores_gemma":[0.99783844,0.0012663909,0.00029124296,0.00009910649,0.00017687165,0.0003280465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010841463,0.00019331601,0.00024703378,0.00076412555,0.00474325,0.0025218271,0.0007273943,0.0010230878,0.0032572374],"category_scores_gemma":[0.002363721,0.0002684754,0.00025369762,0.000967073,0.0021078265,0.0014543684,0.0016029708,0.0011894045,0.00027517704],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009923446,0.00097343256,0.22807927,0.00010860446,0.000022646846,0.0066855657,0.73741144,0.00031440728,0.0020321733,0.0021260122,0.000765172,0.021382112],"study_design_scores_gemma":[0.0000067372894,0.00012841407,0.074163504,0.000043148906,0.000011081462,0.0008029804,0.91963804,0.0005828729,0.00045558755,0.00032961447,0.0038207225,0.00001731158],"about_ca_topic_score_codex":0.049290188,"about_ca_topic_score_gemma":0.15352412,"teacher_disagreement_score":0.049290188,"about_ca_system_score_codex":0.0020923864,"about_ca_system_score_gemma":0.0030295886,"threshold_uncertainty_score":0.09800655},"labels":[],"label_agreement":null},{"id":"W2753149031","doi":"","title":"Driving Decision-Making: An Analysis of Policy Diffusion and Its Role in the Development and Implementation of Ridesharing Regulations in Four Canadian Municipalities","year":2016,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Public economics; Business; Risk analysis (engineering); Economics; Computer science; Environmental planning; Environmental science","score_opus":0.05335808588981929,"score_gpt":0.3201469319616715,"score_spread":0.2667888460718522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2753149031","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9506641,0.0002896505,0.00182184,0.0029322277,0.000013780826,0.0002328639,0.00013951285,0.000018011095,0.043888006],"genre_scores_gemma":[0.99793744,0.00016572556,0.0005330124,0.00006726037,0.0000021866304,0.000025021796,0.000046451783,0.0000038100286,0.001219194],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99308467,0.0021811053,0.00019317598,0.0004273114,0.0012373247,0.0028764065],"domain_scores_gemma":[0.9812433,0.010215441,0.0016878529,0.00049478916,0.0046603605,0.0016982963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008200555,0.00032830497,0.0004831421,0.0022603525,0.009394866,0.0073226644,0.0021187104,0.0017986208,0.0023687098],"category_scores_gemma":[0.02424545,0.00028688443,0.0006478319,0.0040283203,0.007408254,0.0021122673,0.0030957153,0.0025479249,0.00010955746],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007055829,0.0010597982,0.29783884,0.00047645706,0.00026867873,0.00244949,0.19535162,0.0813734,0.0018432292,0.31255153,0.0055816397,0.10049984],"study_design_scores_gemma":[0.00015401808,0.00028179536,0.28773418,0.00040784467,0.00028308894,0.00011994093,0.53017193,0.07405738,0.0013818836,0.032711737,0.07244049,0.0002556991],"about_ca_topic_score_codex":0.97460324,"about_ca_topic_score_gemma":0.9725592,"teacher_disagreement_score":0.12904614,"about_ca_system_score_codex":0.12904614,"about_ca_system_score_gemma":0.12286938,"threshold_uncertainty_score":0.9362997},"labels":[],"label_agreement":null},{"id":"W2760724745","doi":"10.1109/tits.2018.2839265","title":"Improving Viability of Electric Taxis by Taxi Service Strategy Optimization: A Big Data Study of New York City","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"McGill University","keywords":"Taxis; Transport engineering; Big data; Service (business); Computer science; Operations research; Engineering; Business; Marketing; Data mining","score_opus":0.07961515222159872,"score_gpt":0.2686616073186632,"score_spread":0.18904645509706447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2760724745","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9951126,0.0002144488,0.00055238046,0.00047200313,0.000008463676,0.000030638308,0.003160207,0.000030045938,0.0004193837],"genre_scores_gemma":[0.99187964,0.00021117034,0.00093656196,0.00004950629,0.00001688025,0.000032491953,0.006640924,0.0000101170635,0.0002226359],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994722,0.00017015508,0.00003484402,0.00013160333,0.000106617204,0.00008461232],"domain_scores_gemma":[0.9931734,0.0039755884,0.0009831004,0.0004885028,0.00094147277,0.00043781716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009910814,0.0005516452,0.0005089908,0.0015104789,0.0005167811,0.0013704102,0.0011646932,0.0007792309,0.00077510806],"category_scores_gemma":[0.0059140734,0.00029523874,0.0005758086,0.0027692216,0.000863146,0.0019562182,0.0007804634,0.00111458,0.00012374311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006186289,0.0010149613,0.77203995,0.00028075982,0.0006758688,0.0009938811,0.0006309088,0.19160312,0.0011879381,0.0031317777,0.0123216,0.015500682],"study_design_scores_gemma":[0.00007032506,0.00015020274,0.3912071,0.000055174085,0.0001435529,0.00013216367,0.0022144776,0.6004001,0.0011333341,0.001112196,0.0032969278,0.00008443451],"about_ca_topic_score_codex":0.19872707,"about_ca_topic_score_gemma":0.19529073,"teacher_disagreement_score":0.19872707,"about_ca_system_score_codex":0.0027444775,"about_ca_system_score_gemma":0.0012102419,"threshold_uncertainty_score":0.3951407},"labels":[],"label_agreement":null},{"id":"W2766064529","doi":"10.3141/2650-12","title":"UberHOP in Seattle","year":2017,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Evening; Public transport; Transport engineering; Service (business); Advertising; Business; Telecommunications; Engineering; Geography; Marketing","score_opus":0.11051010669752084,"score_gpt":0.39788517175793203,"score_spread":0.2873750650604112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766064529","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024693128,0.0055191293,0.0009965119,0.004298899,0.003287312,0.00017077518,0.0065053194,0.0014282333,0.95310056],"genre_scores_gemma":[0.039482974,0.003643657,0.00091997505,0.0008928689,0.00028401698,0.0001376935,0.0034943533,0.00023726886,0.95090705],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99977964,0.000028880771,0.000008230555,0.00009097472,0.000047685367,0.000044562286],"domain_scores_gemma":[0.9995345,0.00005572868,0.000028927985,0.000039274353,0.00010908992,0.00023245475],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00023054122,0.0008001396,0.00019936876,0.001150911,0.0019947763,0.0022345188,0.0005847834,0.001084324,0.32201412],"category_scores_gemma":[0.0007965898,0.00024908787,0.00018868821,0.00095613586,0.0004521671,0.0014049588,0.0019882785,0.0011841615,0.10042204],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025320647,0.00023038358,0.006220989,0.0005014005,0.000015112837,0.0024679773,0.0013153817,0.00018883708,0.0017796258,0.012091902,0.71496916,0.25996605],"study_design_scores_gemma":[0.000013297394,0.000060313487,0.0048730923,0.00028283533,0.000003917671,0.00030609014,0.0010787563,0.00007913057,0.00032336806,0.0006558115,0.99231166,0.0000117680365],"about_ca_topic_score_codex":0.014261817,"about_ca_topic_score_gemma":0.02650916,"teacher_disagreement_score":0.32201412,"about_ca_system_score_codex":0.0008210232,"about_ca_system_score_gemma":0.0015337755,"threshold_uncertainty_score":0.96706456},"labels":[],"label_agreement":null},{"id":"W2766547583","doi":"10.1155/2017/7217309","title":"Dynamic Vehicle Scheduling for Working Service Network with Dual Demands","year":2017,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Scheduling (production processes); Mathematical optimization; Integer programming; Computer science; Piecewise; Dual (grammatical number); Dynamic programming; Job shop scheduling; Integer (computer science); Control (management); Service (business); Operations research; Mathematics; Artificial intelligence; Computer network; Routing (electronic design automation)","score_opus":0.01222975034611959,"score_gpt":0.252809379611082,"score_spread":0.24057962926496243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766547583","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06107362,0.00022260554,0.93329746,0.0001887255,0.000045686385,0.00004648473,0.00019452753,0.00014434913,0.0047866553],"genre_scores_gemma":[0.9273405,0.00033082828,0.066313185,0.00004441957,0.000035440622,0.00012885655,0.0002995173,0.000072812494,0.005434384],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99956566,0.000115385395,0.000013118487,0.000098851015,0.0000804449,0.00012652972],"domain_scores_gemma":[0.9995821,0.0001820269,0.00008887625,0.00002606024,0.000058298312,0.00006264823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006473267,0.00097371585,0.00093860994,0.00059182174,0.00048395075,0.0011799813,0.0015200835,0.000791805,0.0027061095],"category_scores_gemma":[0.0011734433,0.0006084777,0.0008404964,0.0009164975,0.0005622454,0.001195401,0.0008201665,0.0010058805,0.00023159872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035869227,0.000014491843,0.00021018901,0.000025863987,0.000006597395,0.00005423188,0.00002032327,0.98937315,0.00060189044,0.005525826,0.00027956933,0.0038519315],"study_design_scores_gemma":[0.0000024784888,0.0000070619785,0.00003333373,0.000001122829,0.0000016812538,0.000004816384,0.0000071665354,0.9983651,0.000083821295,0.0013365691,0.00015501986,0.0000018284069],"about_ca_topic_score_codex":0.011573654,"about_ca_topic_score_gemma":0.006524245,"teacher_disagreement_score":0.011573654,"about_ca_system_score_codex":0.0014428323,"about_ca_system_score_gemma":0.0011814102,"threshold_uncertainty_score":0.023012578},"labels":[],"label_agreement":null},{"id":"W2766907090","doi":"10.1111/gec3.12349","title":"Promoting innovation locally: Municipal regulation as barrier or boost?","year":2017,"lang":"en","type":"article","venue":"Geography Compass","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Convergence (economics); Key (lock); Political science; Economic system; Economy; Business; Economic growth; Economics; Computer science","score_opus":0.02107385801040155,"score_gpt":0.2668897412033211,"score_spread":0.24581588319291955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766907090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42458597,0.0078382,0.03960823,0.12492428,0.00089811865,0.0001726751,0.00012575326,0.00034756408,0.40149927],"genre_scores_gemma":[0.9897211,0.0009037572,0.0011121276,0.0019538542,0.00007959521,0.000045632944,0.000012600157,0.00002764554,0.0061436794],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9933015,0.003425769,0.0002286353,0.0005980205,0.0012391929,0.0012069389],"domain_scores_gemma":[0.9918943,0.0037466087,0.0014018798,0.0009862868,0.0011611999,0.00080969126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063308203,0.00023368643,0.00047881345,0.0010725193,0.0038886226,0.01184411,0.0015772224,0.002962664,0.0071574296],"category_scores_gemma":[0.012488752,0.00031514053,0.00045867718,0.0015535341,0.015983066,0.0062346053,0.008062945,0.00312426,0.0006639713],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038337064,0.000054163113,0.004544974,0.00022427241,0.00001897627,0.0002903743,0.01163979,0.0012634547,0.00088469894,0.9507775,0.0043746727,0.025888754],"study_design_scores_gemma":[0.000046662957,0.00018732964,0.012404965,0.001568963,0.000092622824,0.0003165558,0.055911053,0.0028422175,0.0038265318,0.24118528,0.6815091,0.00010874458],"about_ca_topic_score_codex":0.007961622,"about_ca_topic_score_gemma":0.012492534,"teacher_disagreement_score":0.01184411,"about_ca_system_score_codex":0.008625132,"about_ca_system_score_gemma":0.009029879,"threshold_uncertainty_score":0.06258005},"labels":[],"label_agreement":null},{"id":"W2768501536","doi":"10.1049/pbhe010e_ch9","title":"AALaaS/ELEaaS platforms","year":2017,"lang":"en","type":"book-chapter","venue":"IET eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science","score_opus":0.023313016393671504,"score_gpt":0.2177528638995613,"score_spread":0.1944398475058898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2768501536","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0028560231,0.0055268626,0.051666245,0.0013705964,0.0018058707,0.00016170907,0.0016898607,0.007805398,0.92711747],"genre_scores_gemma":[0.013873851,0.0066746445,0.034692254,0.00053425645,0.00034041834,0.00015324335,0.0030297928,0.0017944374,0.9389072],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995684,0.000032968168,0.000022960554,0.00007064428,0.00024653584,0.000058417394],"domain_scores_gemma":[0.9997706,0.000042018088,0.000011556395,0.000040551546,0.00008400881,0.000051326722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037396885,0.0009815941,0.00030872368,0.0015010178,0.0012213534,0.0041228053,0.001228632,0.001736702,0.12969096],"category_scores_gemma":[0.00086236175,0.0004719491,0.0005970263,0.0016563626,0.00037922274,0.005107266,0.0024607505,0.0014012601,0.08542269],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007293988,0.000098395954,0.0002284698,0.00059275195,0.0000091280335,0.0004018291,0.00075453985,0.0013346213,0.008166983,0.1794105,0.28756836,0.5213615],"study_design_scores_gemma":[0.0000019289953,0.000006405338,0.000052155323,0.00006521107,0.0000014160692,0.00014986655,0.00004404968,0.0003282587,0.0005904604,0.004383236,0.9943711,0.0000059627496],"about_ca_topic_score_codex":0.0020286497,"about_ca_topic_score_gemma":0.0029276032,"teacher_disagreement_score":0.12969096,"about_ca_system_score_codex":0.0009295869,"about_ca_system_score_gemma":0.00099809,"threshold_uncertainty_score":0.43385947},"labels":[],"label_agreement":null},{"id":"W2769413113","doi":"10.1007/978-3-319-71150-8_29","title":"Efficient Algorithms for Ridesharing of Personal Vehicles","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Algorithm","score_opus":0.026504039771946663,"score_gpt":0.2586471151874957,"score_spread":0.23214307541554907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2769413113","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022634663,0.0006300005,0.95567584,0.00022085568,0.00013746184,0.0002362894,0.0004696683,0.0030525385,0.016942576],"genre_scores_gemma":[0.2132555,0.00068283564,0.7623772,0.00009540834,0.00011360794,0.00020804052,0.0017121754,0.000711182,0.020844014],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882287,0.00018822037,0.000070647955,0.0003142733,0.00034211326,0.00026190662],"domain_scores_gemma":[0.9983076,0.00067949604,0.00009062237,0.0006326711,0.0002040147,0.000085683416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007614023,0.0015859561,0.0023096157,0.0014110585,0.0018372079,0.0033982736,0.0043204213,0.0022281394,0.023374422],"category_scores_gemma":[0.0049356427,0.0009986393,0.002081531,0.0026815967,0.0010675564,0.0041046534,0.003837894,0.0023434132,0.0050989063],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003620022,0.00022946927,0.0006572966,0.0004654909,0.00008697155,0.0001048202,0.00032914625,0.28506547,0.0053968867,0.06606258,0.02241585,0.618824],"study_design_scores_gemma":[0.000090386326,0.000095288975,0.00030636613,0.000043534124,0.000043371765,0.0001632283,0.00021091125,0.85276836,0.0036115851,0.13019279,0.012444411,0.000029797126],"about_ca_topic_score_codex":0.0073535177,"about_ca_topic_score_gemma":0.008360003,"teacher_disagreement_score":0.023374422,"about_ca_system_score_codex":0.001725281,"about_ca_system_score_gemma":0.0016360054,"threshold_uncertainty_score":0.078195214},"labels":[],"label_agreement":null},{"id":"W2772170845","doi":"","title":"Driving Changes: Automated Vehicles in Toronto","year":2015,"lang":"en","type":"article","venue":"TSpace (University of Toronto)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"University of Toronto","keywords":"Computer science; Transport engineering; Engineering","score_opus":0.01817221334662606,"score_gpt":0.23920754226676988,"score_spread":0.22103532892014383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2772170845","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7972655,0.004150595,0.00048488364,0.011320468,0.0004376698,0.00009603915,0.05167781,0.00015843363,0.13440861],"genre_scores_gemma":[0.93131524,0.0016205497,0.00019106647,0.00021382721,0.000059964088,0.000017053653,0.009918289,0.000036469708,0.056627475],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996797,0.000030342975,0.000010279516,0.000046261466,0.00011313256,0.00012038088],"domain_scores_gemma":[0.9993825,0.000048635917,0.00008949388,0.000024674575,0.0002755478,0.0001791622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018646456,0.00027942663,0.0001547498,0.00076819153,0.0018280004,0.001911622,0.0005909869,0.0006019311,0.018312065],"category_scores_gemma":[0.0009326449,0.00020252937,0.00024488778,0.0033601983,0.0006308606,0.00062260363,0.0008453546,0.00086057914,0.001051032],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006997387,0.00018918286,0.45741236,0.00057347,0.0002186726,0.0025843105,0.021902064,0.011421894,0.0013241628,0.021016493,0.38290888,0.09974886],"study_design_scores_gemma":[0.000025312867,0.000054944307,0.8400794,0.00009569124,0.000036463807,0.00012285744,0.015208847,0.0032326858,0.00024343807,0.00042809587,0.14043564,0.000036542275],"about_ca_topic_score_codex":0.98582655,"about_ca_topic_score_gemma":0.9915479,"teacher_disagreement_score":0.022993742,"about_ca_system_score_codex":0.022993742,"about_ca_system_score_gemma":0.014007388,"threshold_uncertainty_score":0.16683209},"labels":[],"label_agreement":null},{"id":"W2777257784","doi":"10.1155/2017/8524960","title":"Multiple Depots Vehicle Routing Problem in the Context of Total Urban Traffic Equilibrium","year":2017,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Context (archaeology); TRIPS architecture; Truck; Transport engineering; Bilevel optimization; Vehicle routing problem; Traffic network; Computer science; Routing (electronic design automation); Iterated function; Operations research; Mathematical optimization; Mathematics; Engineering; Optimization problem; Geography; Computer network; Automotive engineering","score_opus":0.012254826955204273,"score_gpt":0.24176284224092676,"score_spread":0.22950801528572248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2777257784","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13450679,0.0007576415,0.84807104,0.0007920008,0.0001301135,0.00009388775,0.00038814964,0.00015528339,0.015105125],"genre_scores_gemma":[0.9318083,0.00067499856,0.057972707,0.000100424215,0.00007614922,0.00011878463,0.0002897779,0.000071944014,0.008886849],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990808,0.0003684159,0.00003345403,0.00021109307,0.00009281972,0.00021348566],"domain_scores_gemma":[0.99925417,0.00043380618,0.0000890935,0.000028730141,0.000097736,0.00009653021],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094734825,0.00086618937,0.0013523006,0.00071511115,0.000893598,0.0018153725,0.0015442931,0.0012890943,0.0027338201],"category_scores_gemma":[0.0020798312,0.00051559386,0.0010470115,0.0011970936,0.0008871754,0.001652118,0.001870587,0.0011296624,0.0001961963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056237186,0.000028799124,0.000505034,0.000090975365,0.000033324643,0.00041647445,0.00007926306,0.91922325,0.0005867672,0.07206036,0.00094174006,0.005977806],"study_design_scores_gemma":[0.000011906427,0.000038162238,0.0001953833,0.000009977732,0.00001873973,0.00008807573,0.00011755515,0.9637345,0.00023438327,0.03418476,0.001356657,0.00000986018],"about_ca_topic_score_codex":0.008701754,"about_ca_topic_score_gemma":0.005985097,"teacher_disagreement_score":0.008701754,"about_ca_system_score_codex":0.0012081935,"about_ca_system_score_gemma":0.0014182682,"threshold_uncertainty_score":0.017302155},"labels":[],"label_agreement":null},{"id":"W2779699899","doi":"10.1109/allerton.2017.8262818","title":"The merits of sharing a ride","year":2017,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Matching (statistics); Core (optical fiber); Key (lock); Reduction (mathematics); Optimization problem; Travel time; Optimal matching; Public transport","score_opus":0.017488312295609446,"score_gpt":0.2521820716822813,"score_spread":0.23469375938667186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2779699899","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5528071,0.0041454,0.3121277,0.010286597,0.0003003538,0.00016751775,0.0005364142,0.00044184912,0.11918711],"genre_scores_gemma":[0.970831,0.00042098036,0.024983656,0.00012675406,0.000071462404,0.000028843948,0.000109131164,0.000067313376,0.0033608722],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99698037,0.0015047572,0.00011698274,0.0004976406,0.0006205236,0.0002797663],"domain_scores_gemma":[0.9903289,0.0049532047,0.0007964458,0.0026133338,0.00062768505,0.00068038044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027464842,0.0005100413,0.0007224614,0.00058721664,0.0016196789,0.003281331,0.0019832142,0.0017761319,0.01053647],"category_scores_gemma":[0.01622448,0.0004351628,0.00070152764,0.0013384753,0.0016085759,0.009617074,0.0027435133,0.0016585271,0.0010224326],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011616967,0.00043383858,0.021558976,0.00035384804,0.00021230173,0.00032698343,0.0009381907,0.24161123,0.007517199,0.3906712,0.007989136,0.32722548],"study_design_scores_gemma":[0.00012068384,0.00089391397,0.013532965,0.00009782424,0.00030173335,0.0015614739,0.0032952,0.527601,0.00775913,0.4045304,0.040189687,0.000115980525],"about_ca_topic_score_codex":0.0045382744,"about_ca_topic_score_gemma":0.0053182533,"teacher_disagreement_score":0.01053647,"about_ca_system_score_codex":0.0015565909,"about_ca_system_score_gemma":0.0012059117,"threshold_uncertainty_score":0.03524798},"labels":[],"label_agreement":null},{"id":"W2780812725","doi":"10.1016/j.trb.2018.05.011","title":"Multiple depot vehicle scheduling with controlled trip shifting","year":2018,"lang":"en","type":"article","venue":"Transportation Research Part B Methodological","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"TRIPS architecture; Column generation; Scheduling (production processes); Computer science; Integer programming; Public transport; Context (archaeology); Operations research; Heuristic; Transport engineering; Vehicle routing problem; Mathematical optimization; Engineering; Mathematics; Routing (electronic design automation)","score_opus":0.3399829489445791,"score_gpt":0.4341285298538593,"score_spread":0.09414558090928021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2780812725","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2847139,0.00036640427,0.705911,0.00023325902,0.00035604867,0.0004719639,0.00034638276,0.0005243368,0.0070767757],"genre_scores_gemma":[0.96733284,0.00005438336,0.030748578,0.000024428067,0.00004004551,0.00007622449,0.00007211512,0.000032868455,0.001618555],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991923,0.00025199685,0.0000329475,0.00022312612,0.000117007825,0.00018267467],"domain_scores_gemma":[0.9987056,0.00062552904,0.00015187684,0.00018284639,0.00014506918,0.00018899575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001047918,0.00076555857,0.0016592765,0.0005540607,0.0006453244,0.0010708403,0.002030762,0.00050470216,0.0031518885],"category_scores_gemma":[0.0018706536,0.00054988783,0.00065080257,0.0010593816,0.000561089,0.000940921,0.0008896844,0.00075871777,0.0003106484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009361055,0.00025344657,0.00058109016,0.00009794924,0.00006738331,0.000086905755,0.000057445694,0.95271987,0.004851076,0.0051333653,0.0009417711,0.0342736],"study_design_scores_gemma":[0.000060674072,0.0001627432,0.00026028746,0.000002499479,0.00001737612,0.000015703976,0.0000247617,0.9956448,0.0010777756,0.0023271784,0.00039683402,0.000009358002],"about_ca_topic_score_codex":0.0061224964,"about_ca_topic_score_gemma":0.0046846163,"teacher_disagreement_score":0.0061224964,"about_ca_system_score_codex":0.0009882993,"about_ca_system_score_gemma":0.0017689157,"threshold_uncertainty_score":0.012173712},"labels":[],"label_agreement":null},{"id":"W2782254836","doi":"10.1155/2018/6197549","title":"Taxi Driver’s Operation Behavior and Passengers’ Demand Analysis Based on GPS Data","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Heilongjiang Province; China Postdoctoral Science Foundation; National Natural Science Foundation of China; Arizona State University","keywords":"Global Positioning System; Transport engineering; Computer science; License; Beijing; Geographic coordinate system; Automatic vehicle location; Real-time data; Travel time; Duration (music); Operations research; China; Geography; Engineering; Telecommunications","score_opus":0.01799102290776922,"score_gpt":0.2755851313875251,"score_spread":0.2575941084797559,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782254836","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9930479,0.000045350665,0.0015650585,0.00004573492,0.000004826884,0.000014799224,0.0039120438,0.00004603379,0.0013182558],"genre_scores_gemma":[0.9934853,0.0000709433,0.00076232414,0.0000063844896,0.000003152081,0.000016141586,0.005151713,0.0000047333237,0.00049931894],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981266,0.000029304612,0.000016210235,0.000050533006,0.000056442823,0.000034852834],"domain_scores_gemma":[0.99973875,0.0000646812,0.000052372037,0.000030314253,0.000090972724,0.000022980832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015958535,0.00037324015,0.00018505874,0.0013293384,0.00019029988,0.0004080054,0.00023248613,0.00019190408,0.0010805031],"category_scores_gemma":[0.0005672359,0.00013635439,0.0004036674,0.0023696688,0.00012169393,0.00038903437,0.00023638361,0.00016766042,0.00028330882],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014829115,0.00009430401,0.95278716,0.00011128876,0.00015464904,0.00023120808,0.0005885718,0.015483375,0.0043231766,0.00048467104,0.0015991797,0.023993963],"study_design_scores_gemma":[0.000005843718,0.00006546024,0.9281968,0.000011620501,0.00007587462,0.00010816361,0.0014986822,0.06581547,0.0017323738,0.00018656836,0.002276334,0.000026864906],"about_ca_topic_score_codex":0.05129656,"about_ca_topic_score_gemma":0.06566161,"teacher_disagreement_score":0.05129656,"about_ca_system_score_codex":0.000460176,"about_ca_system_score_gemma":0.00041003473,"threshold_uncertainty_score":0.101995945},"labels":[],"label_agreement":null},{"id":"W2783920686","doi":"10.1016/j.jth.2017.11.116","title":"The Impact of Connected and Automated Vehicles on Pedestrians ( symposia )","year":2017,"lang":"en","type":"article","venue":"Journal of Transport & Health","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Stantec (Canada)","funders":"","keywords":"Pedestrian; Countdown; Walkability; Schema crosswalk; Transport engineering; Downtown; Computer science; Notice; Engineering; Built environment; Geography; Civil engineering","score_opus":0.019893792703706448,"score_gpt":0.32286061056590787,"score_spread":0.3029668178622014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2783920686","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70257473,0.103427626,0.0014340157,0.019319993,0.029488055,0.00027681168,0.0031543155,0.00015372298,0.14017066],"genre_scores_gemma":[0.8962974,0.052644666,0.0010858926,0.0020817753,0.011275845,0.000091974245,0.0009527755,0.0000640214,0.03550554],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9994592,0.00014619691,0.00002575523,0.00007904706,0.00011843451,0.00017141775],"domain_scores_gemma":[0.99812645,0.000478119,0.00015399835,0.00005938054,0.00057153736,0.00061062403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010629557,0.0005787837,0.00019553164,0.0013379494,0.0010932012,0.0016022057,0.00049149484,0.0010591656,0.024340797],"category_scores_gemma":[0.0022470518,0.00020507474,0.00069159456,0.0010311955,0.0005316885,0.00066238554,0.0018147383,0.0008603029,0.0014508428],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035814873,0.0023509392,0.19674589,0.002846946,0.0006547951,0.004223079,0.0050621927,0.0026715065,0.003672365,0.009154523,0.22506362,0.54397273],"study_design_scores_gemma":[0.0001436444,0.0045613255,0.5454801,0.0035322066,0.00091957353,0.0037486965,0.016112722,0.000976312,0.00323113,0.0044883485,0.41670334,0.00010268289],"about_ca_topic_score_codex":0.010987523,"about_ca_topic_score_gemma":0.020572552,"teacher_disagreement_score":0.024340797,"about_ca_system_score_codex":0.0009389172,"about_ca_system_score_gemma":0.0011602616,"threshold_uncertainty_score":0.08142811},"labels":[],"label_agreement":null},{"id":"W2788256597","doi":"10.1155/2018/2385936","title":"Research on Taxi Driver Strategy Game Evolution with Carpooling Detour","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Youth Science Foundation of Lanzhou Jiaotong University; Lanzhou Jiaotong University; National Natural Science Foundation of China","keywords":"Complaint; Limiting; Mechanism (biology); Computer science; Game theory; Transport engineering; Traffic congestion; Operations research; Engineering; Economics; Microeconomics","score_opus":0.02642230384634119,"score_gpt":0.3098594856562183,"score_spread":0.2834371818098771,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2788256597","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43081108,0.0021269799,0.52867156,0.0029318978,0.00017164374,0.00017890985,0.00018930159,0.00009801535,0.03482055],"genre_scores_gemma":[0.9833013,0.00081926637,0.010257701,0.000106242966,0.000031615957,0.00008041144,0.00005644006,0.000009424169,0.005337575],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944085,0.00021641597,0.000021535287,0.00011906414,0.00009609565,0.000105942185],"domain_scores_gemma":[0.9990262,0.0005518003,0.00014247732,0.000036467078,0.00012908447,0.00011407733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080204767,0.0005390186,0.00067071384,0.0004885887,0.000634774,0.0011469437,0.001055197,0.0011026091,0.0024494159],"category_scores_gemma":[0.003368205,0.00021653746,0.0009976109,0.0004900752,0.0009265587,0.0020799094,0.0007188188,0.0011616047,0.0001207606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001405998,0.00019486017,0.015258466,0.0004043274,0.00022406332,0.0010900013,0.0011656533,0.6104499,0.0047131795,0.33351624,0.0020918276,0.030750869],"study_design_scores_gemma":[0.00002087489,0.00010220107,0.0019706518,0.000020212812,0.000053922682,0.00013327194,0.0003261816,0.94023657,0.00037132707,0.05472322,0.0020130305,0.000028565046],"about_ca_topic_score_codex":0.010428706,"about_ca_topic_score_gemma":0.004906465,"teacher_disagreement_score":0.010428706,"about_ca_system_score_codex":0.0015813629,"about_ca_system_score_gemma":0.0014711224,"threshold_uncertainty_score":0.02073598},"labels":[],"label_agreement":null},{"id":"W2789212782","doi":"10.1177/0361198118776810","title":"Virtual Immersive Reality for Stated Preference Travel Behavior Experiments: A Case Study of Autonomous Vehicles on Urban Roads","year":2018,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Preference; Human–computer interaction; Virtual reality; Realism; Pedestrian; Computer science; Transport engineering; Engineering; Mathematics; Statistics; Art; Visual arts","score_opus":0.18955690152505114,"score_gpt":0.41657588652751,"score_spread":0.22701898500245885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789212782","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978976,0.0000141732935,0.00089824386,0.00003965147,0.0000029712862,0.00023692411,0.00013652082,0.000006949986,0.0007667642],"genre_scores_gemma":[0.9919978,0.000074112475,0.005964165,0.000049520168,0.0000073952388,0.000487993,0.00021879515,0.000010581589,0.0011895159],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961493,0.0029583557,0.00009554034,0.00024043451,0.0002775991,0.00027867468],"domain_scores_gemma":[0.9901176,0.007491235,0.0004981653,0.0005892245,0.0008597922,0.00044399532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003476081,0.0005765886,0.00045413038,0.00065798435,0.0013986696,0.000892026,0.0010676108,0.0014281486,0.0031012075],"category_scores_gemma":[0.008564313,0.00039379497,0.0006846025,0.00093975314,0.00093317596,0.00093668257,0.00092642184,0.0009670178,0.0004814808],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0055566463,0.10996861,0.36137748,0.0027690679,0.00062925013,0.016688282,0.23629987,0.044963308,0.04548889,0.009262206,0.007919907,0.15907645],"study_design_scores_gemma":[0.0022152218,0.07590504,0.45174927,0.0003562885,0.0004596947,0.004055272,0.31264943,0.07387392,0.042189617,0.005895101,0.029769775,0.0008813501],"about_ca_topic_score_codex":0.018951302,"about_ca_topic_score_gemma":0.04465075,"teacher_disagreement_score":0.018951302,"about_ca_system_score_codex":0.0011569831,"about_ca_system_score_gemma":0.0009685789,"threshold_uncertainty_score":0.037681997},"labels":[],"label_agreement":null},{"id":"W2790153274","doi":"10.1177/0361198118794057","title":"Spatially Clustered Autonomous Vehicle Malware: Producing New Urban Geographies of Inequity","year":2018,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Malware; Computer security; Software; Computer science; Internet privacy; Business; Risk analysis (engineering)","score_opus":0.06896632466084561,"score_gpt":0.3428289831123327,"score_spread":0.27386265845148705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790153274","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97070843,0.00027819283,0.008890234,0.0015791794,0.000029653189,0.000029569825,0.00069558254,0.00008954582,0.017699724],"genre_scores_gemma":[0.9976514,0.000083089726,0.001308877,0.000041010266,0.0000072770326,0.000012200738,0.00015593147,0.000013773318,0.0007264386],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999579,0.00015109219,0.000009726971,0.00008519556,0.00008814895,0.00008669828],"domain_scores_gemma":[0.9987016,0.00035240068,0.00034437966,0.00025570803,0.00024024752,0.000105565305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004817021,0.00021131741,0.00018841997,0.0022196854,0.0015906434,0.001705699,0.00049737154,0.00033955954,0.004050947],"category_scores_gemma":[0.0023395012,0.0002037564,0.00023745045,0.002489287,0.0019850205,0.001479585,0.00294425,0.00049772963,0.0002659517],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001656332,0.00012727971,0.7838426,0.00012424724,0.00007495865,0.0006360339,0.029654004,0.0070908642,0.002057914,0.08212128,0.007357587,0.08674762],"study_design_scores_gemma":[0.000018224322,0.00013220392,0.7930228,0.00014764609,0.0000861125,0.000746689,0.10294687,0.016468802,0.0019304691,0.048183113,0.036230665,0.000086389366],"about_ca_topic_score_codex":0.030627826,"about_ca_topic_score_gemma":0.08176903,"teacher_disagreement_score":0.030627826,"about_ca_system_score_codex":0.0019824838,"about_ca_system_score_gemma":0.00072324194,"threshold_uncertainty_score":0.06089908},"labels":[],"label_agreement":null},{"id":"W2791617440","doi":"10.1016/j.tranpol.2017.11.001","title":"Vehicle ownership reduction: A comparison of one-way and two-way carsharing systems","year":2018,"lang":"en","type":"article","venue":"Transport Policy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":109,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canada Research Chairs; National Science Foundation","keywords":"Car ownership; Business; Service (business); Car sharing; Level of service; Marketing; Advertising; Transport engineering; Public transport; Engineering","score_opus":0.046174388539934615,"score_gpt":0.30074466658592114,"score_spread":0.25457027804598653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791617440","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9820839,0.0008541622,0.0020774887,0.0005093912,0.00009997397,0.00022728932,0.00078784325,0.000064879954,0.013295001],"genre_scores_gemma":[0.99677664,0.00024384641,0.00041314407,0.000062433806,0.000014642717,0.000059031485,0.00033213306,0.000009639897,0.002088583],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9958484,0.0015476034,0.00015609784,0.0003800005,0.0008628904,0.001204884],"domain_scores_gemma":[0.9961073,0.0018333282,0.0006496772,0.0004394867,0.000655757,0.0003145393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002428725,0.00044568934,0.0009999302,0.0011792656,0.00047997775,0.00222596,0.0014768154,0.0009150613,0.008305828],"category_scores_gemma":[0.005728041,0.0002476141,0.0019044816,0.0019800295,0.00076244504,0.0025124934,0.0014243114,0.0008767729,0.00047646888],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.039101206,0.013377587,0.25193122,0.0041354303,0.005108484,0.00057036424,0.0029258553,0.18398875,0.014647402,0.08376288,0.012330793,0.38812006],"study_design_scores_gemma":[0.0027544312,0.025645578,0.83388776,0.0003185021,0.003904011,0.00022570495,0.009293848,0.07007765,0.012532654,0.014605178,0.026527293,0.00022739863],"about_ca_topic_score_codex":0.01723189,"about_ca_topic_score_gemma":0.021712344,"teacher_disagreement_score":0.01723189,"about_ca_system_score_codex":0.0026328007,"about_ca_system_score_gemma":0.0023699305,"threshold_uncertainty_score":0.034263134},"labels":[],"label_agreement":null},{"id":"W2792935258","doi":"10.1016/j.ejor.2018.03.016","title":"Shipment consolidation with two demand classes: Rationing the dispatch capacity","year":2018,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Rationing; Markov decision process; Computer science; Consolidation (business); Mathematical optimization; Operations research; Order (exchange); Holding cost; Total cost; Process (computing); Markov process; Economic dispatch; Economics; Mathematics; Microeconomics; Finance","score_opus":0.08171851194323396,"score_gpt":0.33988747636341365,"score_spread":0.25816896442017967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792935258","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.67322993,0.00056114607,0.30579856,0.000909351,0.00036157857,0.00040021693,0.0003724964,0.0003057755,0.018060971],"genre_scores_gemma":[0.9876193,0.00009268183,0.009365181,0.000050332652,0.00006156948,0.000037802212,0.00007245531,0.00004561496,0.002655127],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977946,0.0006715794,0.000120613215,0.00042551963,0.0001975454,0.0007901085],"domain_scores_gemma":[0.9961112,0.0017313282,0.00040407723,0.000629064,0.00055341405,0.0005710041],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031372476,0.00095771946,0.002557278,0.000998128,0.0006836297,0.0036885377,0.0025017683,0.0016852772,0.010417105],"category_scores_gemma":[0.008268766,0.00091252715,0.0014670674,0.001479387,0.0013250761,0.004448899,0.0020879454,0.0019378454,0.0008585995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022621858,0.0007943341,0.006659535,0.00030137732,0.00019787006,0.0007582918,0.00021092508,0.8471371,0.013575919,0.04895787,0.0026563378,0.076488376],"study_design_scores_gemma":[0.00010919382,0.0003765231,0.0023721654,0.00002945955,0.00009481759,0.00019661318,0.0002663301,0.97409815,0.0033052138,0.01778875,0.0013183523,0.000044548146],"about_ca_topic_score_codex":0.0037613572,"about_ca_topic_score_gemma":0.0020711669,"teacher_disagreement_score":0.010417105,"about_ca_system_score_codex":0.0016171171,"about_ca_system_score_gemma":0.0014473984,"threshold_uncertainty_score":0.03484869},"labels":[],"label_agreement":null},{"id":"W2795059094","doi":"10.1021/acs.est.7b04732","title":"Cost, Energy, and Environmental Impact of Automated Electric Taxi Fleets in Manhattan","year":2018,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":192,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; Argonne National Laboratory; Vehicle Technologies Office; U.S. Department of Energy; Office of Energy Efficiency and Renewable Energy; McGill University; University of Virginia; University of California Berkeley","keywords":"Revenue; Taxis; Automotive engineering; Fleet management; Energy consumption; Environmental science; Mile; Internal combustion engine; Vehicle miles of travel; Transport engineering; Engineering; Electrical engineering; Business","score_opus":0.005261558090638101,"score_gpt":0.23081788962894453,"score_spread":0.22555633153830643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795059094","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9956644,0.0000875361,0.0009472147,0.00012530191,0.0000075558155,0.000021724576,0.0005406437,0.000026210739,0.0025794134],"genre_scores_gemma":[0.998389,0.00006305665,0.00029149008,0.000010515969,0.0000014460084,0.0000096529675,0.00031334985,0.000003875998,0.0009176557],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973077,0.00009513549,0.0000089623,0.00003545642,0.000048514838,0.00008121127],"domain_scores_gemma":[0.9993986,0.0002921187,0.00008345223,0.000037503894,0.00011698066,0.00007138851],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042590368,0.0005759842,0.00021513723,0.0007261162,0.0004997727,0.0009933104,0.00057476043,0.0004527796,0.0016933793],"category_scores_gemma":[0.0012755357,0.00034294592,0.00056527223,0.00083464955,0.00045458364,0.0010534012,0.0005380125,0.00037237385,0.0001368675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013593995,0.000057838646,0.037652634,0.00001722134,0.00006944988,0.00024687694,0.000030171288,0.9555956,0.0004414947,0.0011047593,0.0005468817,0.004101204],"study_design_scores_gemma":[0.000032631353,0.00017443542,0.043177005,0.000013864688,0.00006486723,0.00007972531,0.00048374248,0.9533949,0.00086792593,0.00071366306,0.00096187944,0.000035316167],"about_ca_topic_score_codex":0.33519995,"about_ca_topic_score_gemma":0.3232418,"teacher_disagreement_score":0.33519995,"about_ca_system_score_codex":0.0066524534,"about_ca_system_score_gemma":0.0017756571,"threshold_uncertainty_score":0.6664977},"labels":[],"label_agreement":null},{"id":"W2795097441","doi":"10.4000/netcom.2756","title":"Les plateformes numériques révolutionnent-elles la mobilité urbaine ?","year":2017,"lang":"fr","type":"article","venue":"Netcom","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Humanities; Locale (computer software); Political science; Art","score_opus":0.024888072125560837,"score_gpt":0.28320205487478034,"score_spread":0.2583139827492195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795097441","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17771855,0.009026259,0.037593547,0.029407961,0.0011443488,0.00011966663,0.0011211453,0.00073712424,0.74313134],"genre_scores_gemma":[0.81127167,0.006667861,0.00839861,0.00144814,0.00025363083,0.00012020636,0.00045641008,0.00052557385,0.17085789],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99788886,0.00057743315,0.00009927052,0.0003407132,0.0007846577,0.0003090512],"domain_scores_gemma":[0.9966647,0.0012740951,0.00039150636,0.00039868022,0.0010666255,0.0002044356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016509262,0.00064744515,0.00041622896,0.0020680458,0.0037475864,0.011303352,0.0011412922,0.001971693,0.032263044],"category_scores_gemma":[0.009063714,0.0004053635,0.00037830055,0.0029308898,0.009685686,0.007414379,0.002316522,0.001965417,0.009219266],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015794465,0.0000550277,0.016957244,0.000880211,0.000044166605,0.00080481096,0.10490322,0.0015542087,0.0032260865,0.6856406,0.03162239,0.1541541],"study_design_scores_gemma":[0.000015338772,0.000039762308,0.017573891,0.0009424155,0.000029071363,0.00047409683,0.057318673,0.001094581,0.0018863576,0.026421811,0.89411646,0.000087600674],"about_ca_topic_score_codex":0.12614442,"about_ca_topic_score_gemma":0.15701647,"teacher_disagreement_score":0.12614442,"about_ca_system_score_codex":0.007027048,"about_ca_system_score_gemma":0.004855311,"threshold_uncertainty_score":0.25082034},"labels":[],"label_agreement":null},{"id":"W2795392204","doi":"","title":"Intact Financial corporation's ridesharing insurance policy gets go-ahead in Ontario","year":2017,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corporation; Finance; Business; Economics; Actuarial science","score_opus":0.025673129638747846,"score_gpt":0.2529449861270443,"score_spread":0.22727185648829645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795392204","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4774214,0.0011968543,0.0005413389,0.178338,0.00070467347,0.00018901062,0.0035153455,0.00014066063,0.3379527],"genre_scores_gemma":[0.6790363,0.00062466174,0.00040146455,0.018436959,0.00015897164,0.00006218737,0.00064006576,0.00008097291,0.3005584],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9950564,0.00018930594,0.000097992735,0.00021168975,0.0014342413,0.0030104185],"domain_scores_gemma":[0.9908937,0.0009868849,0.0005137772,0.00025825726,0.0027630483,0.0045843692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018563927,0.00016375426,0.00036443525,0.00091091054,0.013299287,0.0070051886,0.0013001115,0.004667198,0.02075934],"category_scores_gemma":[0.008369587,0.00044654854,0.00056865014,0.0013775483,0.0023442016,0.0016434306,0.002562378,0.0035312206,0.0009320466],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005017697,0.00027227696,0.16828205,0.00021926267,0.0001000223,0.0020420384,0.022027416,0.001484568,0.0016538413,0.23564182,0.51959926,0.048175663],"study_design_scores_gemma":[0.000094206465,0.00007484381,0.2536082,0.0001771853,0.00007433989,0.00014444902,0.023772473,0.0010669562,0.00051442126,0.0040629874,0.7163121,0.00009784868],"about_ca_topic_score_codex":0.9920934,"about_ca_topic_score_gemma":0.998259,"teacher_disagreement_score":0.10347425,"about_ca_system_score_codex":0.10347425,"about_ca_system_score_gemma":0.19969626,"threshold_uncertainty_score":0.75076175},"labels":[],"label_agreement":null},{"id":"W2799283280","doi":"10.1177/0739456x18769133","title":"Expanding Seniors’ Mobility through Phone Apps: Potential Responses from the Private and Public Sectors","year":2018,"lang":"en","type":"article","venue":"Journal of Planning Education and Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Taxis; Phone; Public transport; Business; Mobile phone; Private sector; Private transport; Internet privacy; Marketing; Advertising; Public relations; Transport engineering; Economic growth; Engineering; Economics; Computer science; Telecommunications; Political science","score_opus":0.07289751286457503,"score_gpt":0.3900699087366873,"score_spread":0.31717239587211227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799283280","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98565626,0.00032152658,0.0004869324,0.0062609767,0.00012384598,0.0000815817,0.00007958538,0.000012717918,0.0069765886],"genre_scores_gemma":[0.9927366,0.000530305,0.0004279551,0.0034771871,0.000044009408,0.00015717628,0.000035175206,0.000011130356,0.0025806017],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.99497473,0.002819983,0.00017059899,0.0002787964,0.0006669154,0.0010889557],"domain_scores_gemma":[0.9873245,0.0069359373,0.0010708849,0.00034555173,0.0017009098,0.0026222689],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069068857,0.0004946287,0.0004221514,0.00092789804,0.0039034549,0.004178042,0.0006998299,0.0022269397,0.0044834227],"category_scores_gemma":[0.019919612,0.00040324967,0.00045196782,0.00066466734,0.0022127589,0.0039617093,0.0057997075,0.002661767,0.0006857099],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012944876,0.00022869871,0.059817467,0.00042337275,0.000025597545,0.00091528083,0.8916667,0.000068035515,0.0011694185,0.0015397165,0.0068741,0.037142105],"study_design_scores_gemma":[0.000014462976,0.00021612989,0.011578058,0.00026274336,0.000017162356,0.00020384407,0.9740615,0.00011287429,0.00012788967,0.00036923084,0.013013489,0.00002253429],"about_ca_topic_score_codex":0.004993416,"about_ca_topic_score_gemma":0.009387711,"teacher_disagreement_score":0.0069068857,"about_ca_system_score_codex":0.0013938745,"about_ca_system_score_gemma":0.00244772,"threshold_uncertainty_score":0.036527514},"labels":[],"label_agreement":null},{"id":"W2799787002","doi":"10.1177/0361198118777064","title":"Estimation of a Long-Distance Travel Demand Model using Trip Surveys, Location-Based Big Data, and Trip Planning Services","year":2018,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Technische Universität München; European Commission","keywords":"TRIPS architecture; Travel survey; Trip generation; Transport engineering; Mode choice; Destinations; Travel behavior; Attractiveness; Computer science; Modal; Demand forecasting; Transportation planning; Geography; Tourism; Public transport; Operations research; Engineering","score_opus":0.1659144685001015,"score_gpt":0.39488473441204763,"score_spread":0.22897026591194614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799787002","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85383856,0.0002403563,0.1328605,0.001025079,0.000037103182,0.00020590707,0.0078104734,0.0003691765,0.003612781],"genre_scores_gemma":[0.97270614,0.00015757947,0.018963862,0.000056348214,0.000017552835,0.00013875899,0.0046358914,0.00003199181,0.0032920043],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995332,0.00016668647,0.000026971938,0.00011746597,0.000055087858,0.00010067865],"domain_scores_gemma":[0.99861157,0.00077189854,0.00017915569,0.00007009959,0.00026042497,0.000106736814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010774775,0.0006949599,0.0006026013,0.00082426885,0.0005310306,0.0010773327,0.0013055439,0.00082722266,0.0019672436],"category_scores_gemma":[0.0026981144,0.0008472557,0.0008106974,0.0014502883,0.0005169082,0.00083926396,0.0007218544,0.0010657939,0.00034342354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000088603534,0.00011592526,0.050412104,0.000068509566,0.000112504014,0.00014627211,0.00016222919,0.932115,0.0004043362,0.0049548647,0.001967975,0.009451791],"study_design_scores_gemma":[0.000013552278,0.000013567718,0.0069170627,0.0000067340366,0.000015606061,0.000010188437,0.00016813783,0.9911464,0.000072101575,0.0010314637,0.0005943594,0.000010887297],"about_ca_topic_score_codex":0.63689226,"about_ca_topic_score_gemma":0.558984,"teacher_disagreement_score":0.63689226,"about_ca_system_score_codex":0.005884515,"about_ca_system_score_gemma":0.005064151,"threshold_uncertainty_score":0.7304923},"labels":[],"label_agreement":null},{"id":"W2799969917","doi":"10.1109/tits.2018.2825654","title":"A Game Theoretic Solution for the Territory Sharing Problem in Social Taxi Networks","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Taxis; Negotiation; Game theory; Profit (economics); Computer science; Operations research; Regret; Service (business); Service provider; Business; Microeconomics; Transport engineering; Engineering; Economics; Marketing","score_opus":0.027062457933279178,"score_gpt":0.2576498317726761,"score_spread":0.2305873738393969,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799969917","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018876076,0.00024458754,0.95113033,0.00078563485,0.000086726184,0.00023299792,0.00021044209,0.00008267724,0.028350586],"genre_scores_gemma":[0.6561074,0.00087241945,0.31420517,0.0003631881,0.00014793334,0.000901604,0.00039670232,0.00011687668,0.026888797],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989623,0.0004656228,0.000033262313,0.00018254782,0.0001719752,0.000184389],"domain_scores_gemma":[0.99904615,0.0005681805,0.00008748347,0.00004636001,0.00010469123,0.00014706116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012873595,0.0013747005,0.0012282032,0.00076376303,0.001547175,0.0022801666,0.00247923,0.0026111347,0.0073763863],"category_scores_gemma":[0.0028872835,0.00057030155,0.0012568824,0.0012000712,0.0016533753,0.0025553228,0.0025155486,0.002213878,0.00069822505],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058231886,0.00007644917,0.00026454605,0.00010912733,0.00003944031,0.00023006965,0.00019302272,0.6977027,0.0007386348,0.28621563,0.0037005441,0.010671506],"study_design_scores_gemma":[0.000028068805,0.000040928728,0.00008441961,0.000018555673,0.000012573359,0.00006797618,0.00014433426,0.8998335,0.00015741457,0.09598539,0.0036115951,0.000015127477],"about_ca_topic_score_codex":0.007919641,"about_ca_topic_score_gemma":0.0071498025,"teacher_disagreement_score":0.007919641,"about_ca_system_score_codex":0.0025436287,"about_ca_system_score_gemma":0.0028023124,"threshold_uncertainty_score":0.024676442},"labels":[],"label_agreement":null},{"id":"W2800396553","doi":"10.1136/oemed-2018-icohabstracts.1407","title":"285 The sharing economy: hazards of being an uber driver","year":2018,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Work & Health; University of Waterloo","funders":"","keywords":"Incentive; Business; Work (physics); Focus group; Order (exchange); Finance; Transport engineering; Computer security; Marketing; Computer science; Engineering; Economics","score_opus":0.011751534695237797,"score_gpt":0.2344753754898076,"score_spread":0.2227238407945698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800396553","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.960378,0.0004570647,0.001794916,0.008712924,0.000090096706,0.000072802606,0.00017208127,0.00003077087,0.02829137],"genre_scores_gemma":[0.9959027,0.0001760581,0.00029367165,0.00056679704,0.000017514447,0.000017212338,0.00003670036,0.0000086166265,0.002980617],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.99699616,0.0014033795,0.00010980288,0.00019481104,0.0006416808,0.0006541082],"domain_scores_gemma":[0.99474865,0.001233228,0.0018251585,0.0004310141,0.0011348154,0.00062717684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002982398,0.00028937266,0.00017487067,0.0007415401,0.010740349,0.004368502,0.0012557451,0.0013776611,0.0070539396],"category_scores_gemma":[0.0077708233,0.00024570685,0.00025642585,0.0007959426,0.0063524093,0.003179186,0.0037863639,0.0013798604,0.0006840318],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006549611,0.000040907464,0.13244282,0.000102706676,0.000010990361,0.0025823547,0.8280071,0.00016500556,0.0007117728,0.009476237,0.0068623377,0.019532254],"study_design_scores_gemma":[0.0000016915484,0.000030358844,0.03348143,0.000120376426,0.000007354951,0.0007482148,0.9419009,0.00027593804,0.0002810002,0.0017075841,0.021420896,0.000024307976],"about_ca_topic_score_codex":0.19564697,"about_ca_topic_score_gemma":0.19844657,"teacher_disagreement_score":0.19564697,"about_ca_system_score_codex":0.006399845,"about_ca_system_score_gemma":0.0057442193,"threshold_uncertainty_score":0.38901633},"labels":[],"label_agreement":null},{"id":"W2801210630","doi":"10.1016/j.procs.2018.04.066","title":"Investigation of the Impacts of Shared Autonomous Vehicle Operation in Halifax, Canada Using a Dynamic Traffic Microsimulation Model","year":2018,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Nova Scotia Department of Energy","keywords":"Microsimulation; Computer science; TRIPS architecture; Operations research; Transport engineering; Service (business); Simulation; Business","score_opus":0.015391457140526428,"score_gpt":0.22727348909150108,"score_spread":0.21188203195097466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801210630","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9790862,0.00011337998,0.010936884,0.00031492155,0.000014679379,0.000044667333,0.00041469466,0.00010142063,0.008973133],"genre_scores_gemma":[0.99807113,0.000049424492,0.00073414174,0.000008925204,0.0000011779173,0.000012183345,0.000105726795,0.000005604544,0.0010116876],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997087,0.00007558288,0.0000064077294,0.0000409618,0.000055231423,0.00011314469],"domain_scores_gemma":[0.99936134,0.00020444013,0.00006982922,0.000025764792,0.0002581569,0.00008049982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037410134,0.00077774836,0.0003665109,0.00035614954,0.0007509717,0.001064879,0.0009072579,0.000493103,0.0012840867],"category_scores_gemma":[0.0009897004,0.00027281605,0.0004240852,0.00033467016,0.0006255416,0.0006083208,0.0006884404,0.00046158012,0.00007640279],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055925007,0.00002376287,0.0051598595,0.000012319107,0.000017118153,0.00011323201,0.000033639128,0.99109006,0.00067383185,0.0015710051,0.00022336705,0.001025845],"study_design_scores_gemma":[0.0000052902233,0.00003030435,0.0017445278,0.0000019012916,0.000010935857,0.0000061060414,0.0001359265,0.9974355,0.0002714301,0.00016450636,0.00018857187,0.0000049773266],"about_ca_topic_score_codex":0.8044634,"about_ca_topic_score_gemma":0.63913906,"teacher_disagreement_score":0.19553661,"about_ca_system_score_codex":0.006963924,"about_ca_system_score_gemma":0.005350877,"threshold_uncertainty_score":0.3933763},"labels":[],"label_agreement":null},{"id":"W2801893945","doi":"10.1016/j.procs.2018.04.146","title":"Passenger Safety in Ride-Sharing Services","year":2018,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Computer security; Computer science; Internet privacy; Order (exchange); Business; Telecommunications; Finance","score_opus":0.007511607910921255,"score_gpt":0.22439624526664015,"score_spread":0.2168846373557189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801893945","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08015858,0.018594723,0.0317088,0.045815203,0.0039683008,0.0007414893,0.0028586073,0.0040974845,0.81205684],"genre_scores_gemma":[0.7489651,0.01627086,0.014070535,0.013070934,0.0014943179,0.00032005413,0.00455332,0.0007491639,0.2005058],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99666315,0.0008515757,0.00013385652,0.0003576798,0.0013012728,0.00069247535],"domain_scores_gemma":[0.99667835,0.0005234646,0.0002695305,0.00023901109,0.0017754558,0.0005142112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019984886,0.00076438516,0.00025924674,0.001140784,0.0026825187,0.0052965484,0.0014921892,0.00236547,0.040183984],"category_scores_gemma":[0.0064350744,0.00029973776,0.00071119785,0.0013006019,0.00078190194,0.005098365,0.0051468136,0.001831347,0.013443361],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027604212,0.00034686763,0.020601414,0.0017926389,0.000059398673,0.0015184345,0.007476313,0.0020898136,0.003130841,0.059562698,0.35435885,0.5487867],"study_design_scores_gemma":[0.000015145006,0.00016569771,0.009795059,0.0009680915,0.00005648371,0.0014238453,0.007758386,0.0022966412,0.0015117951,0.009382077,0.9665562,0.0000706177],"about_ca_topic_score_codex":0.026908303,"about_ca_topic_score_gemma":0.01600838,"teacher_disagreement_score":0.040183984,"about_ca_system_score_codex":0.0031605333,"about_ca_system_score_gemma":0.0032620279,"threshold_uncertainty_score":0.13442886},"labels":[],"label_agreement":null},{"id":"W2802246998","doi":"","title":"Commande collaborative d'un fauteuil roulant dans unenvironnement partiellement connu","year":2017,"lang":"fr","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Humanities; Art; Political science","score_opus":0.01196252045255347,"score_gpt":0.23471179867904218,"score_spread":0.2227492782264887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802246998","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32338357,0.0019269171,0.5809186,0.0011601198,0.00045223924,0.0007395686,0.00096234283,0.0097135175,0.08074321],"genre_scores_gemma":[0.77282494,0.0007131151,0.12835029,0.00022242236,0.000060517395,0.00035762636,0.0013133055,0.00054096075,0.095616885],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990495,0.00013552165,0.00003658005,0.00024959884,0.0003532303,0.00017553971],"domain_scores_gemma":[0.9985538,0.00018469738,0.00008272049,0.00024563234,0.00074119953,0.0001918989],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085149094,0.0008532473,0.00075617945,0.0007877515,0.0015159032,0.002118888,0.0013073575,0.000970847,0.016164683],"category_scores_gemma":[0.0016755029,0.0004290416,0.00045848178,0.0006456095,0.0010483938,0.001539981,0.0017507417,0.00066843285,0.0036517715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013770874,0.0004303827,0.013537038,0.0010579773,0.00013930176,0.0027033305,0.008943075,0.14350231,0.2311643,0.028523725,0.027615208,0.5410063],"study_design_scores_gemma":[0.00018984849,0.0014161704,0.03507934,0.0004287006,0.00019283743,0.001076793,0.0061410745,0.4227504,0.09465981,0.008613784,0.42906404,0.00038715944],"about_ca_topic_score_codex":0.11977092,"about_ca_topic_score_gemma":0.12161266,"teacher_disagreement_score":0.11977092,"about_ca_system_score_codex":0.0023406255,"about_ca_system_score_gemma":0.0035061915,"threshold_uncertainty_score":0.23814756},"labels":[],"label_agreement":null},{"id":"W2802248265","doi":"10.1155/2018/5913981","title":"On‐Demand Mobile Data Collection in Cyber‐Physical Systems","year":2018,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Key Research and Development Program of China; Government of Jiangsu Province; Natural Sciences and Engineering Research Council of Canada; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Computer science; Data collection; Queueing theory; Cyber-physical system; Latency (audio); Dimension (graph theory); Construct (python library); Real-time computing; Mobile device; Distributed computing; Computer network; Telecommunications; World Wide Web; Operating system","score_opus":0.028112581302185413,"score_gpt":0.29246114614330637,"score_spread":0.26434856484112096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802248265","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08613434,0.0020012604,0.89736056,0.0017680154,0.00019177255,0.00018710607,0.00021769485,0.0004272634,0.01171196],"genre_scores_gemma":[0.9560362,0.0010751243,0.038488556,0.00016943696,0.00009260944,0.00013158741,0.00009350141,0.00005544744,0.003857458],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904174,0.0003443278,0.000035831188,0.00018930782,0.00020182195,0.0001868671],"domain_scores_gemma":[0.99830437,0.0009967388,0.00017290933,0.00018938615,0.00022068668,0.00011598989],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011083764,0.00079502125,0.0008205468,0.00052585866,0.0010866543,0.0017832137,0.0014283784,0.0014309842,0.0021309361],"category_scores_gemma":[0.0028453805,0.0006370874,0.00078513083,0.0009601086,0.0012212947,0.002906847,0.0015394789,0.0012735826,0.00034436712],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001430138,0.00014497696,0.0020478293,0.0002822504,0.00005081692,0.00043354466,0.00041930642,0.80068946,0.004098292,0.14998297,0.0037888836,0.03791868],"study_design_scores_gemma":[0.000006561419,0.000034829114,0.00024390407,0.000010650244,0.0000059888494,0.00004079698,0.000094446645,0.9852541,0.0005222755,0.012156056,0.0016192679,0.000011170198],"about_ca_topic_score_codex":0.009443972,"about_ca_topic_score_gemma":0.0071004713,"teacher_disagreement_score":0.009443972,"about_ca_system_score_codex":0.0019495562,"about_ca_system_score_gemma":0.001481278,"threshold_uncertainty_score":0.018778026},"labels":[],"label_agreement":null},{"id":"W2802816641","doi":"","title":"Estimating Consumer Interest in Private Ownership and Shared Use of Autonomous Vehicles in the Greater Toronto-Hamilton Area","year":2018,"lang":"en","type":"article","venue":"Transportation Research Board 97th Annual MeetingTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Marketing; Economics; Labour economics","score_opus":0.14242343406718222,"score_gpt":0.3582887590626615,"score_spread":0.21586532499547928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802816641","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99856985,0.000049341124,0.000056859466,0.00005230262,0.000001033041,0.000007182779,0.0005722779,0.0000025502213,0.00068852433],"genre_scores_gemma":[0.9985372,0.00005363993,0.00008587461,0.000008901263,0.0000018107206,0.0000055352116,0.00040639995,0.0000012190364,0.0008994597],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99973565,0.00005712467,0.000014050148,0.000052652016,0.000068995854,0.00007151202],"domain_scores_gemma":[0.998374,0.00042450696,0.00036801188,0.00007277656,0.00037515073,0.00038554167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030084257,0.00022586728,0.0001792907,0.0006814552,0.00067262235,0.0010876195,0.0006088069,0.00035554334,0.0020598117],"category_scores_gemma":[0.0016895304,0.00028290178,0.00040004472,0.001635606,0.000517412,0.0004174656,0.00054519635,0.00034262092,0.0002076151],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013600798,0.000037436275,0.9928283,0.000016148118,0.00007489594,0.00012715599,0.0014879901,0.0011031282,0.0003460156,0.00027879974,0.00057719386,0.002986897],"study_design_scores_gemma":[0.000004209279,0.000013268061,0.9968183,0.0000045981456,0.000016479913,0.000012481616,0.001547023,0.0012351588,0.000047644662,0.000017021293,0.00027928234,0.000004506217],"about_ca_topic_score_codex":0.9694715,"about_ca_topic_score_gemma":0.9862131,"teacher_disagreement_score":0.030528486,"about_ca_system_score_codex":0.010393463,"about_ca_system_score_gemma":0.003234965,"threshold_uncertainty_score":0.07541013},"labels":[],"label_agreement":null},{"id":"W2803655597","doi":"10.1016/j.trc.2018.05.015","title":"A slack arrival strategy to promote flex-route transit services","year":2018,"lang":"en","type":"article","venue":"Transportation Research Part C Emerging Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Natural Science Foundation of China","keywords":"FLEX; Transit (satellite); Idle; Computer science; Transport engineering; Service (business); Arrival time; Function (biology); Public transport; Engineering; Business; Telecommunications","score_opus":0.05986715836716154,"score_gpt":0.35649667556756953,"score_spread":0.296629517200408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803655597","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38113973,0.0004916297,0.2971801,0.015386231,0.0012236721,0.00086006435,0.0004262909,0.0022759072,0.30101645],"genre_scores_gemma":[0.9452202,0.00017532709,0.027144771,0.0011063701,0.00011444494,0.00014848035,0.00011370517,0.00011897781,0.025857648],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991812,0.0002376045,0.00003124776,0.00012449983,0.00016991326,0.00025552526],"domain_scores_gemma":[0.99675673,0.0006834988,0.00033001133,0.00024427864,0.00090899854,0.0010765054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001882554,0.0005205421,0.00026178316,0.001227833,0.0015222011,0.003749485,0.0014896918,0.0010775853,0.03518307],"category_scores_gemma":[0.004812739,0.0002277378,0.0003815077,0.0011289776,0.00068908173,0.0027846857,0.002516652,0.0016843715,0.0035279535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011190039,0.0039455616,0.016647626,0.0004925994,0.00008315314,0.0005641984,0.0030810419,0.05014878,0.018641878,0.46897513,0.057214413,0.3790866],"study_design_scores_gemma":[0.00089172326,0.0035325864,0.02877727,0.0004937199,0.00042836345,0.00063566945,0.01906532,0.34913048,0.016945707,0.26250798,0.3173696,0.00022167257],"about_ca_topic_score_codex":0.0035783723,"about_ca_topic_score_gemma":0.010214119,"teacher_disagreement_score":0.03518307,"about_ca_system_score_codex":0.0022593203,"about_ca_system_score_gemma":0.007187055,"threshold_uncertainty_score":0.11769909},"labels":[],"label_agreement":null},{"id":"W2803842131","doi":"","title":"Don't get taken for a ride! : designing and Implementing effective autonomous vehicle regulation in Toronto, Ontario","year":2018,"lang":"en","type":"dissertation","venue":"DSpace@MIT (Massachusetts Institute of Technology)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Engineering; Automotive engineering; Aeronautics; Computer science","score_opus":0.007967891685457485,"score_gpt":0.24971859895120355,"score_spread":0.24175070726574607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803842131","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82985425,0.0013479982,0.029454095,0.0089925565,0.00009125175,0.00081123953,0.00039527818,0.00027891522,0.12877446],"genre_scores_gemma":[0.94781005,0.0010128616,0.014978307,0.00047337692,0.0000074134055,0.00027144267,0.00025832662,0.00008618507,0.03510202],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.99771774,0.0006271159,0.00006185606,0.0002918316,0.00071378116,0.0005877522],"domain_scores_gemma":[0.9979303,0.0004618507,0.00014081286,0.0001270962,0.0008561286,0.0004837367],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00221334,0.00040106694,0.00023868345,0.00028238734,0.007846729,0.0032422643,0.0014090455,0.0009801731,0.0041434625],"category_scores_gemma":[0.005198001,0.00048028852,0.0002715784,0.0006169557,0.0050370265,0.0011845315,0.001934146,0.00089977257,0.00056019396],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00093622616,0.00086724985,0.12555258,0.0011493675,0.00015081455,0.0017350058,0.34307534,0.04494304,0.022550745,0.06718988,0.06737943,0.3244703],"study_design_scores_gemma":[0.0003171282,0.0012220396,0.15787672,0.0007543299,0.00038120023,0.00021352642,0.3280057,0.054511014,0.015298727,0.009455426,0.43164518,0.00031902466],"about_ca_topic_score_codex":0.97342896,"about_ca_topic_score_gemma":0.993804,"teacher_disagreement_score":0.060189307,"about_ca_system_score_codex":0.060189307,"about_ca_system_score_gemma":0.12138076,"threshold_uncertainty_score":0.436706},"labels":[],"label_agreement":null},{"id":"W2804345352","doi":"10.1155/2018/5493632","title":"Locating Station of One-Way Carsharing Based on Spatial Demand Characteristics","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Algorithm; Computer science; Statistics; Database; Mathematics","score_opus":0.011453872814397175,"score_gpt":0.23993599488484596,"score_spread":0.2284821220704488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804345352","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99640995,0.00002563985,0.001958994,0.000015805943,0.0000021028934,0.000008058809,0.00080894976,0.000025199166,0.0007452079],"genre_scores_gemma":[0.99626726,0.000034685843,0.0011724245,0.0000028193463,0.0000029740004,0.000009958343,0.0018465003,0.0000076288998,0.00065584754],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957937,0.00005500284,0.00002812825,0.00014532478,0.000113231086,0.00007895416],"domain_scores_gemma":[0.99856335,0.00041771377,0.00041997156,0.00014889818,0.0003219733,0.00012804854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025028005,0.00027434298,0.00032662504,0.0014724314,0.00022190377,0.0007201463,0.00046273656,0.00025392437,0.0031545132],"category_scores_gemma":[0.0014520357,0.0002059968,0.00039952985,0.003107488,0.00018540776,0.000720791,0.00045857576,0.00019503226,0.0007563348],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010536718,0.000055096865,0.9771787,0.000043518794,0.000044969827,0.00014499047,0.00024210947,0.007913441,0.0030182202,0.00024734964,0.00034510338,0.0106611],"study_design_scores_gemma":[0.000005108108,0.00007414657,0.942229,0.000009185628,0.000055993056,0.000112106376,0.0015100286,0.052597,0.0019773587,0.00019188077,0.0012168109,0.000021472451],"about_ca_topic_score_codex":0.014434414,"about_ca_topic_score_gemma":0.035145823,"teacher_disagreement_score":0.014434414,"about_ca_system_score_codex":0.0005000646,"about_ca_system_score_gemma":0.00044924003,"threshold_uncertainty_score":0.028700829},"labels":[],"label_agreement":null},{"id":"W2804442660","doi":"10.1155/2018/8969353","title":"Shared Autonomous Vehicles Effect on Vehicle-Km Traveled and Average Trip Duration","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":117,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Seventh Framework Programme; Technische Universität München; Deutsche Forschungsgemeinschaft; European Commission","keywords":"Metropolitan area; TRIPS architecture; Duration (music); Transport engineering; Occupancy; Public transport; Vehicle miles of travel; Population; Computer science; Geography; Engineering; Civil engineering","score_opus":0.006788451526456153,"score_gpt":0.23034495278685496,"score_spread":0.2235565012603988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804442660","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99967265,0.000012974573,0.00012535891,0.0000027729222,6.4469566e-7,0.0000015755817,0.00005179367,0.0000024182903,0.00012980409],"genre_scores_gemma":[0.9997758,0.000007832334,0.000062806,8.181311e-7,3.16379e-7,0.0000021852145,0.000055945307,8.9940636e-7,0.000093493596],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971133,0.00009141795,0.000014495076,0.00006738346,0.00004933689,0.00006594617],"domain_scores_gemma":[0.9976361,0.0013849086,0.00035849583,0.00018781751,0.00022177848,0.00021089679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038487135,0.00022742903,0.00021357616,0.00029526016,0.00013553075,0.00042574838,0.00025270082,0.0002160036,0.002141544],"category_scores_gemma":[0.0023817148,0.00011191264,0.00046827676,0.00031131253,0.000254829,0.0003987422,0.000547945,0.00020799928,0.00013659161],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020004786,0.00037894354,0.8628567,0.00008840956,0.00040767845,0.00038504982,0.00033121492,0.10403323,0.009121524,0.0004485006,0.00019020963,0.019758115],"study_design_scores_gemma":[0.00002171573,0.0016140916,0.9337742,0.00000777626,0.00019584177,0.00015913171,0.0010138704,0.058843352,0.0037936675,0.00023472766,0.0003136561,0.000027966933],"about_ca_topic_score_codex":0.00730039,"about_ca_topic_score_gemma":0.0071211453,"teacher_disagreement_score":0.00730039,"about_ca_system_score_codex":0.0003168085,"about_ca_system_score_gemma":0.0002196721,"threshold_uncertainty_score":0.014515758},"labels":[],"label_agreement":null},{"id":"W2804598473","doi":"10.3390/wevj8010151","title":"EVS29 Symposium Montréal, Québec, Canada, June 19-22, 2016","year":2016,"lang":"en","type":"article","venue":"World Electric Vehicle Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Control reconfiguration; Electricity; Sustainability; Work (physics); State (computer science); Mains electricity; Electric cars; Business; Political science; Engineering; Geography; Computer science; Automotive engineering; Electrical engineering","score_opus":0.003953602768491876,"score_gpt":0.17742003162546324,"score_spread":0.17346642885697136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804598473","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008634434,0.023690691,0.00537293,0.023968771,0.019524356,0.00033311316,0.016267814,0.001601704,0.9006061],"genre_scores_gemma":[0.012540343,0.004639065,0.0015798192,0.0005779714,0.00046537336,0.000033463533,0.0053781075,0.00029251797,0.97449344],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99884987,0.00007363609,0.000023561379,0.00010607318,0.0006776646,0.00026919116],"domain_scores_gemma":[0.99821174,0.00003154641,0.000021265538,0.00006276674,0.0013037273,0.00036895543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016836053,0.0011715256,0.0006088925,0.0015359545,0.004322483,0.0048588077,0.0017626338,0.0014589361,0.241085],"category_scores_gemma":[0.0012912012,0.0003931007,0.00060422946,0.001569496,0.0010279479,0.0012123014,0.001920556,0.0012007636,0.065985255],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000081439895,0.000030222267,0.0011919029,0.00008900091,0.000011261702,0.00018607124,0.00014925672,0.0004225171,0.0007291197,0.0032488063,0.942007,0.05185347],"study_design_scores_gemma":[0.0000046666346,0.0000061332157,0.0012471518,0.00007138841,0.0000035422236,0.00003339245,0.00020548893,0.00015073974,0.00017807088,0.00024015958,0.99785054,0.000008795905],"about_ca_topic_score_codex":0.837903,"about_ca_topic_score_gemma":0.9541195,"teacher_disagreement_score":0.241085,"about_ca_system_score_codex":0.017770624,"about_ca_system_score_gemma":0.03224306,"threshold_uncertainty_score":0.8065096},"labels":[],"label_agreement":null},{"id":"W2804610802","doi":"","title":"Best Practice in Labour Ward Management","year":2000,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women's Health Research Institute","funders":"","keywords":"Best practice; Business; Economics; Management","score_opus":0.006391836445577352,"score_gpt":0.23767028314755073,"score_spread":0.23127844670197337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804610802","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014235451,0.09191971,0.0293135,0.7898207,0.010029627,0.00021628158,0.000113134294,0.00033376977,0.064017914],"genre_scores_gemma":[0.5189687,0.16894794,0.15784355,0.117122665,0.0067923,0.000966608,0.0005669074,0.00039966253,0.028391665],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.916256,0.052653734,0.0057743434,0.002934097,0.019317184,0.003064583],"domain_scores_gemma":[0.8902552,0.05121291,0.0057663172,0.009874047,0.028542876,0.014348646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0655285,0.000907736,0.0009954248,0.0050855153,0.004173414,0.012184332,0.0052462122,0.014991064,0.00813648],"category_scores_gemma":[0.12339547,0.0008281478,0.00094607554,0.0042824335,0.010505739,0.0067058327,0.007630073,0.0109164715,0.0032187828],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013049717,0.0012264197,0.0051415954,0.0036309436,0.00009645346,0.001124401,0.01100712,0.0023379568,0.0005407155,0.041219063,0.16790287,0.765642],"study_design_scores_gemma":[0.00024244141,0.00074445363,0.01669237,0.051884804,0.00015830023,0.0028041701,0.029971415,0.0025963648,0.0019537946,0.18693963,0.7057306,0.0002816535],"about_ca_topic_score_codex":0.013239189,"about_ca_topic_score_gemma":0.02892615,"teacher_disagreement_score":0.0655285,"about_ca_system_score_codex":0.010563688,"about_ca_system_score_gemma":0.035492003,"threshold_uncertainty_score":0.34655195},"labels":[],"label_agreement":null},{"id":"W2805000289","doi":"10.1016/j.tra.2018.05.010","title":"Policy formulation for highly automated vehicles: Emerging importance, research frontiers and insights","year":2018,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":72,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"National Natural Science Foundation of China","keywords":"Risk analysis (engineering); Government (linguistics); Backcasting; Adaptation (eye); Management science; Computer science; Engineering; Business; Sustainability","score_opus":0.09793036755088128,"score_gpt":0.44424868086664926,"score_spread":0.346318313315768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805000289","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11403043,0.029080352,0.48418546,0.19254337,0.0023000569,0.00028573885,0.0008434267,0.00015307142,0.17657804],"genre_scores_gemma":[0.93602926,0.010786866,0.02917098,0.0025864628,0.0015923157,0.00019788994,0.00024280485,0.00008760627,0.019305773],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99653196,0.001990504,0.00011412944,0.00049082056,0.0003915205,0.00048091958],"domain_scores_gemma":[0.97452307,0.02205894,0.001022866,0.0003880166,0.0012738558,0.00073323306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005489889,0.00085181027,0.0016428118,0.0009918583,0.0013192049,0.008364894,0.0025362028,0.0072557433,0.012120523],"category_scores_gemma":[0.019748751,0.0008231347,0.0009195388,0.0017789367,0.0047079925,0.007625701,0.0018634915,0.006242531,0.00055462157],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023435354,0.000074600524,0.00029355037,0.00017945845,0.000024500783,0.00006858445,0.00014824969,0.060435887,0.000061227285,0.9270774,0.004685116,0.006927974],"study_design_scores_gemma":[0.00001800008,0.000017971606,0.0001543456,0.00011460686,0.000010255639,0.000021972537,0.000412874,0.06133635,0.00007772939,0.92873996,0.00908202,0.000013948385],"about_ca_topic_score_codex":0.012752708,"about_ca_topic_score_gemma":0.009088059,"teacher_disagreement_score":0.012752708,"about_ca_system_score_codex":0.0064586317,"about_ca_system_score_gemma":0.0095444,"threshold_uncertainty_score":0.046860814},"labels":[],"label_agreement":null},{"id":"W2806992506","doi":"10.3390/jrfm11020028","title":"Customer Preferences and Implicit Tradeoffs in Accident Scenarios for Self-Driving Vehicle Algorithms","year":2018,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Massachusetts Institute of Technology","keywords":"Self driving; Computer science; Respondent; Automotive industry; Process (computing); Software deployment; Selection (genetic algorithm); Scale (ratio); Accident (philosophy); Operations research; Marketing; Transport engineering; Computer security; Business; Engineering; Artificial intelligence","score_opus":0.008102373173911008,"score_gpt":0.22755123405624245,"score_spread":0.21944886088233143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806992506","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960484,0.000025722078,0.0013800691,0.00010256912,0.0000028862398,0.000018936666,0.000052087187,0.000005485276,0.0023639365],"genre_scores_gemma":[0.999073,0.000012275798,0.0005491626,0.000014081762,0.0000017715482,0.0000126668265,0.00007369378,0.0000035511898,0.00025978856],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99672073,0.0021400864,0.00015209628,0.00019144855,0.00048033314,0.0003152431],"domain_scores_gemma":[0.9783357,0.017213115,0.0013218203,0.0009017685,0.0013601321,0.0008674862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004470075,0.00035655522,0.00030391797,0.00044703728,0.00056196057,0.0028166373,0.00054582703,0.0012843957,0.0069571347],"category_scores_gemma":[0.029270919,0.00020300728,0.00041656438,0.0005718163,0.00058071484,0.0018406371,0.0008105437,0.0011432198,0.00047214684],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009226405,0.0029925643,0.5950637,0.0003609675,0.00043256037,0.001702551,0.0070417947,0.27357253,0.006851054,0.030375307,0.0034008813,0.068979695],"study_design_scores_gemma":[0.00023853376,0.003393457,0.2631984,0.000097656375,0.00019461745,0.0009698364,0.014969374,0.6854695,0.003736933,0.02323668,0.0042605377,0.00023442457],"about_ca_topic_score_codex":0.00201333,"about_ca_topic_score_gemma":0.0024469052,"teacher_disagreement_score":0.0069571347,"about_ca_system_score_codex":0.0011530069,"about_ca_system_score_gemma":0.00031141227,"threshold_uncertainty_score":0.023640335},"labels":[],"label_agreement":null},{"id":"W2808038377","doi":"10.1155/2018/7687852","title":"Understanding the Effect of an E-Hailing App Subsidy War on Taxicab Operation Zones","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China; Wuhan University; National Natural Science Foundation of China","keywords":"Subsidy; Context (archaeology); China; Economics; Government (linguistics); Business; Economy; Geography; Market economy; Political science; Law","score_opus":0.019632420989331035,"score_gpt":0.2617254407587767,"score_spread":0.24209301976944564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808038377","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99542457,0.00008205632,0.00035950993,0.00012097451,0.000009072898,0.000012452307,0.0001262007,0.000007550351,0.0038576701],"genre_scores_gemma":[0.99919003,0.00006588647,0.000097517455,0.000015062106,0.000002655108,0.000005391651,0.00007975677,0.0000015456358,0.000542201],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995183,0.00009328277,0.000026524605,0.00007935673,0.00008023529,0.00020233999],"domain_scores_gemma":[0.9988041,0.00023244733,0.00048633944,0.00008270621,0.00017154832,0.000222789],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037978622,0.00023262762,0.00019027918,0.0006113164,0.00073763664,0.0010688936,0.00033114097,0.0003376432,0.0040180944],"category_scores_gemma":[0.0019312348,0.00011638075,0.00031643963,0.00080832466,0.00092914817,0.0008996629,0.0010070393,0.0005089561,0.00036078622],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023832222,0.00011616792,0.9505796,0.0000696439,0.0001005152,0.00078060915,0.0022952,0.007805299,0.003941825,0.0023726453,0.0009474814,0.03075263],"study_design_scores_gemma":[0.0000030493795,0.00007324139,0.9889839,0.000012647153,0.000017795026,0.00006727472,0.0058227303,0.0025916689,0.00040347857,0.0002833025,0.0017296372,0.000011182009],"about_ca_topic_score_codex":0.037748326,"about_ca_topic_score_gemma":0.060890753,"teacher_disagreement_score":0.037748326,"about_ca_system_score_codex":0.0011499801,"about_ca_system_score_gemma":0.00084407313,"threshold_uncertainty_score":0.07505721},"labels":[],"label_agreement":null},{"id":"W2808920086","doi":"10.1016/j.jebo.2018.06.004","title":"An empirical analysis of taxi, Lyft and Uber rides: Evidence from weather shocks in NYC","year":2018,"lang":"en","type":"article","venue":"Journal of Economic Behavior & Organization","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":87,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada; University of Ottawa","funders":"","keywords":"Taxis; Advertising; Economics; Demographic economics; Business; Transport engineering; Engineering","score_opus":0.02421444976889435,"score_gpt":0.30023992128898724,"score_spread":0.2760254715200929,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808920086","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99644935,0.00018998976,0.00007179495,0.00018101653,0.000008489136,0.000018569619,0.0021831307,0.0000048678253,0.0008927616],"genre_scores_gemma":[0.9911311,0.0003590787,0.00006200281,0.000079485275,0.000023229464,0.000029603068,0.0058005336,0.0000080107875,0.0025068275],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994979,0.00011494804,0.000033800236,0.00009036636,0.00008954033,0.00017343267],"domain_scores_gemma":[0.9947438,0.0017163231,0.0019411411,0.00024660747,0.0006742108,0.00067777326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008651332,0.00032838792,0.00044169545,0.0013928164,0.0010069459,0.0015864847,0.0007689074,0.0011961289,0.0053457147],"category_scores_gemma":[0.0043001105,0.00028685218,0.0004291661,0.0028839372,0.00072393974,0.0012172479,0.0012977824,0.0017024283,0.00083680847],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003729774,0.00037887963,0.98809206,0.000039829883,0.00015925163,0.00025325106,0.00078976405,0.0014155086,0.00033988163,0.0006161623,0.0041900715,0.0033523543],"study_design_scores_gemma":[0.000018370416,0.000059150978,0.9938497,0.00001897924,0.000048771013,0.000026174397,0.0020162973,0.0023748954,0.00011966821,0.000055054436,0.0014009464,0.000011863208],"about_ca_topic_score_codex":0.34786144,"about_ca_topic_score_gemma":0.46613458,"teacher_disagreement_score":0.34786144,"about_ca_system_score_codex":0.0018196668,"about_ca_system_score_gemma":0.0014652543,"threshold_uncertainty_score":0.6916733},"labels":[],"label_agreement":null},{"id":"W2810013613","doi":"10.1111/cag.12481","title":"Good or bad? Ridesharing's impact on Canadian cities","year":2018,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Institute on Governance; University of Toronto","funders":"","keywords":"Economic surplus; Public economics; Business; Economics; Marketing; Advertising; Market economy; Welfare","score_opus":0.009659066023551927,"score_gpt":0.20799619054856042,"score_spread":0.19833712452500848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810013613","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19243099,0.031320628,0.0009708604,0.30140033,0.0018942138,0.00010694446,0.0033810742,0.00018277373,0.46831217],"genre_scores_gemma":[0.8891629,0.02764307,0.0010945026,0.023002638,0.00027809094,0.000031505562,0.0009630659,0.00011455696,0.05770952],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9927025,0.0005489519,0.00012483058,0.0003935715,0.0032755428,0.0029546127],"domain_scores_gemma":[0.99035794,0.00080590224,0.0003694793,0.00017716397,0.0066230483,0.0016664558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003229217,0.0005711031,0.0005849389,0.0029972047,0.024737012,0.013806236,0.002307403,0.0027915027,0.0110594025],"category_scores_gemma":[0.008684923,0.00034996652,0.00086174475,0.008079009,0.008961736,0.0025210571,0.0035511015,0.004176209,0.00050809985],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024182514,0.00009210003,0.043518715,0.0013208294,0.00011564763,0.00097632385,0.03862056,0.0031033277,0.0014409837,0.37243986,0.3908295,0.14730038],"study_design_scores_gemma":[0.000025968757,0.000062347455,0.07299026,0.0009282487,0.00016590905,0.00014225859,0.067105815,0.000759599,0.000931912,0.00674487,0.84985554,0.00028713685],"about_ca_topic_score_codex":0.99877614,"about_ca_topic_score_gemma":0.9993679,"teacher_disagreement_score":0.24131224,"about_ca_system_score_codex":0.24131224,"about_ca_system_score_gemma":0.26998487,"threshold_uncertainty_score":0.87997025},"labels":[],"label_agreement":null},{"id":"W2814677075","doi":"10.1155/2018/6430950","title":"Ridesharing Problem with Flexible Pickup and Delivery Locations for App-Based Transportation Service: Mathematical Modeling and Decomposition Methods","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Beijing Municipal Natural Science Foundation; Fundamental Research Funds for the Central Universities; State Key Laboratory of Rail Traffic Control and Safety; National Natural Science Foundation of China","keywords":"Pickup; Lagrangian relaxation; Routing (electronic design automation); Inefficiency; Service (business); Computer science; Flow network; Transport engineering; Vehicle routing problem; Matching (statistics); Operations research; Simulation; Engineering; Mathematical optimization; Computer network; Artificial intelligence","score_opus":0.01923468197354277,"score_gpt":0.3071344920800607,"score_spread":0.28789981010651794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2814677075","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011366368,0.0014887189,0.97707283,0.0006604452,0.00012940407,0.00012704574,0.0002547817,0.0000855759,0.0088148555],"genre_scores_gemma":[0.6426528,0.007089508,0.3195275,0.00053930766,0.00042577312,0.0015060989,0.0010084197,0.0002538158,0.02699677],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913436,0.00034584274,0.000034618242,0.00014837872,0.00014532963,0.00019148107],"domain_scores_gemma":[0.99834085,0.0011287954,0.00017167066,0.00004593302,0.00021378945,0.000099064135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021556867,0.0021714142,0.0021896241,0.0015365193,0.00087362947,0.0026402548,0.0019650206,0.0023757706,0.0055424008],"category_scores_gemma":[0.003920702,0.0012123672,0.0032490615,0.0016922799,0.0012268539,0.0023484575,0.0019604352,0.0028895014,0.00059326325],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026019557,0.000059159414,0.00042742406,0.00013690731,0.000032095413,0.00009697791,0.00006120019,0.95297945,0.0003920166,0.03824622,0.001958521,0.0055840393],"study_design_scores_gemma":[0.0000037168584,0.000008760442,0.00004201825,0.000008515864,0.000007079843,0.000009022621,0.000022832271,0.99430424,0.000038548515,0.005118063,0.00043264742,0.000004509244],"about_ca_topic_score_codex":0.022776965,"about_ca_topic_score_gemma":0.011162531,"teacher_disagreement_score":0.022776965,"about_ca_system_score_codex":0.0026758232,"about_ca_system_score_gemma":0.002826888,"threshold_uncertainty_score":0.04528874},"labels":[],"label_agreement":null},{"id":"W2883626560","doi":"10.1111/poms.12928","title":"A Smart‐City Scope of Operations Management","year":2018,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":111,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Scope (computer science); Smart city; Sustainability; Business; Smart grid; Scale (ratio); Business model; Computer science; Process management; Knowledge management; Marketing; Computer security; Engineering; Geography","score_opus":0.013514808525007154,"score_gpt":0.2369885796424463,"score_spread":0.22347377111743913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883626560","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05022132,0.07316542,0.15513808,0.13664305,0.0022939395,0.00021379511,0.00024083373,0.0002654196,0.58181816],"genre_scores_gemma":[0.9078644,0.040933743,0.023448389,0.008106571,0.0020745734,0.00023217728,0.00015509191,0.00008090543,0.01710417],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9973308,0.0011850299,0.00015519667,0.00037682717,0.0006093209,0.00034287016],"domain_scores_gemma":[0.9976126,0.001124394,0.00030687856,0.0003045131,0.00037226485,0.00027943798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035259572,0.0005311463,0.00042657656,0.001538213,0.002302004,0.011359047,0.0009516266,0.002478269,0.0038156644],"category_scores_gemma":[0.0030905616,0.00035289285,0.00059967244,0.003077176,0.013729292,0.015123901,0.003852083,0.0034640753,0.00054482854],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000070758256,0.000009690997,0.00035062237,0.000095771305,0.000006496828,0.000033894525,0.0010556245,0.001450388,0.000097887365,0.9815231,0.0025913997,0.012777956],"study_design_scores_gemma":[0.0000068881122,0.000019976113,0.0012412261,0.00040476964,0.0000092984765,0.000061022412,0.0038413,0.0029000605,0.00020283426,0.80985105,0.18144304,0.000018545583],"about_ca_topic_score_codex":0.0035848168,"about_ca_topic_score_gemma":0.0036673362,"teacher_disagreement_score":0.011359047,"about_ca_system_score_codex":0.005997865,"about_ca_system_score_gemma":0.007081242,"threshold_uncertainty_score":0.04351777},"labels":[],"label_agreement":null},{"id":"W2883981179","doi":"10.2139/ssrn.3208616","title":"A Theory of Multihoming in Rideshare Competition","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Multihoming; Competition (biology); Engineering; Operations research; Computer science; World Wide Web; Biology; The Internet","score_opus":0.007757955699169154,"score_gpt":0.22312973868162472,"score_spread":0.21537178298245557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883981179","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08139568,0.002025458,0.6510342,0.010864168,0.0005887537,0.0001358337,0.0004026134,0.00023642412,0.25331682],"genre_scores_gemma":[0.9424968,0.0013344823,0.020732755,0.0008317265,0.0005898797,0.00015686457,0.00015916412,0.00006644852,0.03363178],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984812,0.0005241679,0.000052804156,0.00023859616,0.00032589654,0.00037725535],"domain_scores_gemma":[0.9950203,0.0032574604,0.0003735819,0.00048709277,0.0004344227,0.00042715258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018836404,0.000685772,0.001440074,0.0015436411,0.0035017177,0.005877574,0.003088752,0.004505552,0.02545185],"category_scores_gemma":[0.007173193,0.0006649189,0.0013954259,0.002281471,0.0048843557,0.010722485,0.0029708475,0.0039537656,0.001742549],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008074906,0.000013104567,0.0000895345,0.000014395928,0.0000037280224,0.000026128639,0.000084365834,0.0062789666,0.000056315752,0.9904805,0.0011940605,0.0017508987],"study_design_scores_gemma":[0.0000128625,0.000017175786,0.00009554903,0.000014439179,0.000005890274,0.00004343508,0.00013788628,0.046380542,0.00003825259,0.95070034,0.0025427986,0.000010884223],"about_ca_topic_score_codex":0.0055712797,"about_ca_topic_score_gemma":0.0029900956,"teacher_disagreement_score":0.02545185,"about_ca_system_score_codex":0.0026733796,"about_ca_system_score_gemma":0.0021436685,"threshold_uncertainty_score":0.08514488},"labels":[],"label_agreement":null},{"id":"W2884381115","doi":"10.1016/j.cor.2018.07.015","title":"Route and speed optimization for autonomous trucks","year":2018,"lang":"en","type":"article","venue":"Computers & Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Truck; Computer science; Fuel efficiency; Set (abstract data type); Process (computing); Mathematical optimization; Operations research; Stochastic programming; Automotive engineering; Engineering; Mathematics","score_opus":0.05719349064869754,"score_gpt":0.34939420081477907,"score_spread":0.2922007101660815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884381115","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23923822,0.00083762413,0.743738,0.00075056497,0.00015272811,0.00022447824,0.00074156956,0.0005292142,0.013787685],"genre_scores_gemma":[0.87436545,0.00031538372,0.11036323,0.000086237065,0.00007218899,0.00017638896,0.000625811,0.00024291838,0.013752333],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999668,0.00009458691,0.000012859716,0.00008174659,0.000059920807,0.0000828956],"domain_scores_gemma":[0.9992336,0.00047029724,0.00008180245,0.000036253914,0.00011524075,0.00006283662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073197094,0.001091293,0.0015425875,0.0012199257,0.0007742624,0.0013373118,0.0012550175,0.0017627815,0.0038876405],"category_scores_gemma":[0.002597768,0.00112972,0.0010419893,0.0010394225,0.0008122671,0.0010733033,0.0012564588,0.001044281,0.00045808536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044978424,0.000021670574,0.00020295948,0.000018638531,0.000012937772,0.0000149819225,0.000017291648,0.99239326,0.00024903307,0.0018581188,0.0003521454,0.0048139617],"study_design_scores_gemma":[0.0000065294603,0.000016485785,0.000088130735,0.0000017094986,0.000003085396,0.0000035525934,0.000008476311,0.99822575,0.000070549446,0.0014041538,0.00016900532,0.0000025994204],"about_ca_topic_score_codex":0.031431515,"about_ca_topic_score_gemma":0.015847392,"teacher_disagreement_score":0.031431515,"about_ca_system_score_codex":0.0013024893,"about_ca_system_score_gemma":0.0017976244,"threshold_uncertainty_score":0.06249714},"labels":[],"label_agreement":null},{"id":"W2884871736","doi":"10.1155/2018/3486741","title":"Vehicle Relocation Triggering Thresholds Determination in Electric Carsharing System under Stochastic Demand","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China; Ministry of Education of the People's Republic of China; Fok Ying Tong Education Foundation; National Natural Science Foundation of China","keywords":"Relocation; Electric vehicle; Dual (grammatical number); Pareto principle; Computer science; Stochastic modelling; Mathematical optimization; Stochastic optimization; Stochastic process; Mathematics; Statistics","score_opus":0.009585391598117814,"score_gpt":0.24217242836389044,"score_spread":0.23258703676577264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884871736","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5673121,0.00015768303,0.42810872,0.00014374123,0.000022358152,0.00006259159,0.000119740616,0.0002992064,0.0037738043],"genre_scores_gemma":[0.9944431,0.000021264173,0.005259191,0.000005838682,0.0000018018475,0.000009764403,0.000035842302,0.0000070192323,0.0002161881],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994221,0.00014906104,0.0000329198,0.00012630768,0.00013245494,0.00013716205],"domain_scores_gemma":[0.9989507,0.00048155108,0.00022079462,0.00007914039,0.0002018511,0.00006595209],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087172614,0.00044672654,0.00044432256,0.00052437634,0.00031835507,0.0008491085,0.00060386275,0.00040982384,0.0007704466],"category_scores_gemma":[0.002527358,0.00023931966,0.00029761693,0.0004720377,0.00031592057,0.00086821924,0.0006358642,0.000424899,0.00009227758],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013178408,0.00004517601,0.005203887,0.00005726266,0.000013786316,0.00011410749,0.00007497153,0.968623,0.0038351489,0.0033434478,0.00037381952,0.018183628],"study_design_scores_gemma":[0.00000479998,0.000033140306,0.0012164131,0.0000037044356,0.0000057959364,0.000023376655,0.00007563483,0.9955069,0.0017627595,0.0012029549,0.00015632123,0.0000081256585],"about_ca_topic_score_codex":0.0052736867,"about_ca_topic_score_gemma":0.0038008979,"teacher_disagreement_score":0.0052736867,"about_ca_system_score_codex":0.0007220439,"about_ca_system_score_gemma":0.0007828697,"threshold_uncertainty_score":0.010486007},"labels":[],"label_agreement":null},{"id":"W2884908887","doi":"10.2139/ssrn.3120544","title":"Ride-Hailing Networks with Strategic Drivers: The Impact of Platform Control Capabilities on Performance","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":113,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Business; Control (management); Industrial organization; Economics; Management","score_opus":0.008364431315599991,"score_gpt":0.21731508624573764,"score_spread":0.20895065493013765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884908887","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9772125,0.00012733904,0.006478365,0.0003089666,0.000037359958,0.00004224545,0.00009412378,0.00007212875,0.015626946],"genre_scores_gemma":[0.9988612,0.00003119322,0.0003788052,0.0000073413344,0.0000041166863,0.0000068553127,0.000033923137,0.000005083826,0.0006714281],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894816,0.00031391968,0.00003218442,0.00017285295,0.0001588957,0.00037405163],"domain_scores_gemma":[0.98885214,0.0063854884,0.00097047654,0.0007643351,0.0017956147,0.0012318644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019872945,0.00073816045,0.00032538126,0.0005819974,0.00068949984,0.002617361,0.0010538539,0.0009717932,0.008032173],"category_scores_gemma":[0.016740983,0.0001932994,0.00024564474,0.000527106,0.0006828845,0.004871151,0.0021874,0.0008646749,0.0009920922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005081866,0.0024934127,0.12124238,0.00037354184,0.0003511773,0.0007477328,0.0020392323,0.647504,0.012682704,0.03475139,0.003201182,0.16953145],"study_design_scores_gemma":[0.00018445983,0.0053877304,0.06338281,0.00012848544,0.0003420986,0.0003468601,0.010519356,0.8718853,0.012859314,0.029413985,0.005402701,0.00014689977],"about_ca_topic_score_codex":0.006483298,"about_ca_topic_score_gemma":0.006196322,"teacher_disagreement_score":0.008032173,"about_ca_system_score_codex":0.0007216295,"about_ca_system_score_gemma":0.0011333158,"threshold_uncertainty_score":0.02687031},"labels":[],"label_agreement":null},{"id":"W2885172856","doi":"10.1155/2018/3853012","title":"Clustering Algorithm for Urban Taxi Carpooling Vehicle Based on Data Field Energy","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Cluster analysis; CURE data clustering algorithm; Data stream clustering; Computer science; Algorithm; Field (mathematics); Data mining; k-medians clustering; Canopy clustering algorithm; Point (geometry); Outlier; Cluster (spacecraft); Correlation clustering; Mathematics; Artificial intelligence","score_opus":0.016964386368003986,"score_gpt":0.2621754864829335,"score_spread":0.2452111001149295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885172856","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.040700503,0.00040990682,0.9546403,0.00015365255,0.00007193779,0.00025900186,0.0004066205,0.0015184934,0.0018395652],"genre_scores_gemma":[0.27305374,0.00040931397,0.71842676,0.0000816886,0.000051923646,0.0005282587,0.0026688715,0.00024726434,0.0045322464],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909425,0.00007549487,0.000075184194,0.0003268704,0.000316836,0.00011146242],"domain_scores_gemma":[0.99932027,0.00009134072,0.00006589248,0.000060814127,0.00042515458,0.000036552265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064115145,0.00086242036,0.0012808748,0.003179774,0.0014045574,0.0011384891,0.0022504313,0.0009943831,0.0012961482],"category_scores_gemma":[0.0016082029,0.0004240367,0.0013341682,0.0035900187,0.0004940491,0.0012264387,0.00092672074,0.0007721496,0.0007881314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022495366,0.00012167846,0.005300446,0.00019186958,0.00019579909,0.00011827552,0.00035545434,0.4665933,0.010270063,0.006203247,0.00827565,0.5021493],"study_design_scores_gemma":[0.000022208591,0.000031760323,0.0017588049,0.00001247626,0.000025838348,0.00008113067,0.0001322002,0.98811346,0.0038375568,0.003111191,0.0028386146,0.000034783094],"about_ca_topic_score_codex":0.030030506,"about_ca_topic_score_gemma":0.020570328,"teacher_disagreement_score":0.030030506,"about_ca_system_score_codex":0.0016142358,"about_ca_system_score_gemma":0.0023819052,"threshold_uncertainty_score":0.059711456},"labels":[],"label_agreement":null},{"id":"W2885531863","doi":"10.1155/2018/8919721","title":"Shared Autonomous Taxi System and Utilization of Collected Travel-Time Information","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; China Scholarship Council","keywords":"Taxis; Travel time; Flexibility (engineering); Computer science; Transport engineering; Information system; Operations research; Convergence (economics); Path (computing); Information sharing; Simulation; Computer network; Engineering; Statistics; World Wide Web; Mathematics","score_opus":0.008126484301803285,"score_gpt":0.21695691142296603,"score_spread":0.20883042712116273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885531863","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9879242,0.000068974456,0.010453417,0.000036752117,0.000011488148,0.000031291165,0.00016325219,0.00009032966,0.0012202254],"genre_scores_gemma":[0.9979804,0.000020434882,0.0017854634,0.0000027540902,9.571824e-7,0.000008873524,0.0000971923,0.000002646449,0.00010126081],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992539,0.0002253286,0.00005033772,0.00015140504,0.00018508494,0.00013378086],"domain_scores_gemma":[0.9970798,0.0011765742,0.0004060228,0.00052116637,0.0006171431,0.00019928692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008722329,0.00045585897,0.00045660915,0.00060958025,0.0004695417,0.00087438273,0.0009858495,0.0004105561,0.0008089099],"category_scores_gemma":[0.0041842544,0.00023949132,0.00036886206,0.0010096816,0.00045617562,0.0018056836,0.00075197144,0.0004123018,0.00010515718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003856324,0.0002361878,0.043995373,0.000103464925,0.00013340375,0.00028198835,0.0001878046,0.9196827,0.005902942,0.0017388049,0.00036868712,0.026983023],"study_design_scores_gemma":[0.000021770169,0.0003769781,0.013526724,0.0000080685495,0.000064538144,0.00011247518,0.0002383601,0.9806567,0.00378594,0.0006105185,0.0005708906,0.000027083623],"about_ca_topic_score_codex":0.0173469,"about_ca_topic_score_gemma":0.017327297,"teacher_disagreement_score":0.0173469,"about_ca_system_score_codex":0.00092231284,"about_ca_system_score_gemma":0.0012340747,"threshold_uncertainty_score":0.034491837},"labels":[],"label_agreement":null},{"id":"W2887050495","doi":"10.11159/icmie18.101","title":"Theoretical Formulation and Demand Parameters Optimization for a Proposed Extra-Baggage Service","year":2018,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Service (business); Business","score_opus":0.007641650245773698,"score_gpt":0.20572574377741631,"score_spread":0.1980840935316426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2887050495","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015109138,0.00042652953,0.95417637,0.0016853008,0.00021949077,0.00012220869,0.00027998086,0.0001806124,0.027800504],"genre_scores_gemma":[0.7142816,0.0011132602,0.22134022,0.00071184395,0.00045842407,0.00055948424,0.0006045819,0.0004339316,0.06049662],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991555,0.00028426907,0.000022341184,0.00014294723,0.00018874292,0.00020603099],"domain_scores_gemma":[0.9991203,0.00045834557,0.00004964149,0.000055484812,0.00023488786,0.000081385755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013755077,0.0014117507,0.0019901008,0.0011904213,0.0014199426,0.0035816962,0.0030778092,0.0038368972,0.020169364],"category_scores_gemma":[0.0033118653,0.0010587015,0.001624114,0.0018060171,0.0014274307,0.002469008,0.0021475162,0.0024800908,0.0018920051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006365795,0.000073147596,0.00023972214,0.000097636825,0.000014930159,0.000121722194,0.00006481618,0.8617942,0.0008428946,0.12018479,0.005079121,0.011423298],"study_design_scores_gemma":[0.000004803529,0.000009478924,0.00003302631,0.0000065989657,0.0000037164702,0.000015790065,0.000019871755,0.98967665,0.00006987658,0.009351937,0.0008032562,0.000005116608],"about_ca_topic_score_codex":0.017089305,"about_ca_topic_score_gemma":0.01197344,"teacher_disagreement_score":0.020169364,"about_ca_system_score_codex":0.0037532272,"about_ca_system_score_gemma":0.0031174954,"threshold_uncertainty_score":0.06747329},"labels":[],"label_agreement":null},{"id":"W2890360845","doi":"","title":"Guide québécois du chauffeur de taxi / réalisée par la Direction du transport terrestre des personnes","year":2017,"lang":"fr","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Political science","score_opus":0.012946829994854766,"score_gpt":0.23552991746169546,"score_spread":0.2225830874668407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890360845","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08740726,0.015180505,0.08966855,0.04833578,0.005831091,0.0022429079,0.00729987,0.005158145,0.73887587],"genre_scores_gemma":[0.09130598,0.006005649,0.051707152,0.0031155294,0.0001299954,0.00057689485,0.0022469955,0.00047836822,0.8444335],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99838805,0.00036312698,0.00007151506,0.00016957319,0.0008128064,0.00019494092],"domain_scores_gemma":[0.9973099,0.00023681959,0.000060615665,0.00007510985,0.001978635,0.0003388881],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018417966,0.0009861374,0.00049023476,0.0014727454,0.0036651953,0.003957933,0.0010182337,0.0020295861,0.033133432],"category_scores_gemma":[0.0038339854,0.0005362634,0.00042853106,0.0010332996,0.001313488,0.0014862402,0.0010320054,0.002213757,0.010808896],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018313533,0.0003369179,0.015733594,0.00041011898,0.000038359834,0.0011661468,0.013883498,0.0027501113,0.007067172,0.031599537,0.5064862,0.4203452],"study_design_scores_gemma":[0.000016211981,0.00005431414,0.0070950924,0.00025043997,0.000007994126,0.00016575378,0.0036784045,0.00063803175,0.0007697288,0.00050843396,0.9867792,0.000036491925],"about_ca_topic_score_codex":0.8827614,"about_ca_topic_score_gemma":0.9359572,"teacher_disagreement_score":0.11723858,"about_ca_system_score_codex":0.009298193,"about_ca_system_score_gemma":0.04168835,"threshold_uncertainty_score":0.23585802},"labels":[],"label_agreement":null},{"id":"W2891821371","doi":"10.1111/poms.13262","title":"Adoption of Electric Vehicles in Car Sharing Market","year":2020,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":101,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Waterloo","funders":"","keywords":"Renting; Subsidy; Driving range; Business; Profit (economics); TRIPS architecture; Market share; Electric vehicle; Microeconomics; Environmental economics; Transport engineering; Economics; Marketing","score_opus":0.01390622771757167,"score_gpt":0.21191314342994474,"score_spread":0.19800691571237308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891821371","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9160545,0.0008808848,0.015165426,0.0014234335,0.000042048392,0.00011588176,0.00013794923,0.000039403585,0.06614047],"genre_scores_gemma":[0.99619734,0.00023231917,0.00074050756,0.00006918498,0.000020664935,0.000013298079,0.00003197073,0.0000036414049,0.0026910808],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99931574,0.0001923008,0.000019366407,0.00012101443,0.00014287216,0.00020870312],"domain_scores_gemma":[0.99845576,0.0006741266,0.0004223087,0.00007232302,0.00019050851,0.00018490833],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008477802,0.00035974933,0.00036732206,0.00046296394,0.0005594994,0.0021690477,0.0008708855,0.0013637196,0.013240436],"category_scores_gemma":[0.00275465,0.0002110464,0.0005442337,0.0005448545,0.0008565889,0.0030492016,0.0008922295,0.0010316299,0.00040535576],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005470092,0.0019537061,0.120511405,0.00058283715,0.00022000345,0.004016517,0.0014070529,0.25276092,0.013542242,0.4993829,0.004851535,0.10022384],"study_design_scores_gemma":[0.00027890477,0.0015834973,0.1023385,0.00023272539,0.000252772,0.0019460601,0.010955695,0.6113401,0.005955086,0.20426229,0.060603987,0.00025042275],"about_ca_topic_score_codex":0.0037575767,"about_ca_topic_score_gemma":0.004922644,"teacher_disagreement_score":0.013240436,"about_ca_system_score_codex":0.0012918402,"about_ca_system_score_gemma":0.0008638478,"threshold_uncertainty_score":0.044293642},"labels":[],"label_agreement":null},{"id":"W2895155046","doi":"10.1109/mce.2018.2851745","title":"Montreal Chapter Event on Smart Assistant Technology [Society News]","year":2018,"lang":"en","type":"article","venue":"IEEE Consumer Electronics Magazine","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Event (particle physics); Computer science; Telecommunications; Data science; Computer security; World Wide Web","score_opus":0.008272064252555706,"score_gpt":0.22910568694980074,"score_spread":0.22083362269724505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2895155046","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017019649,0.006184697,0.0018259827,0.052882306,0.022836704,0.00018440688,0.0073505533,0.0022369942,0.9047965],"genre_scores_gemma":[0.0053106234,0.002777652,0.0005447943,0.0046249055,0.0028296404,0.000029366429,0.0020152074,0.0003345387,0.9815332],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99922764,0.000037171874,0.000010133666,0.000063641055,0.00049499393,0.00016642446],"domain_scores_gemma":[0.9985103,0.00012462262,0.000042446798,0.000062839776,0.0008786994,0.00038104388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085254916,0.0009480507,0.00048942096,0.0014228711,0.0032251289,0.004653451,0.0016438547,0.002918159,0.29784983],"category_scores_gemma":[0.0018919251,0.0005229124,0.0007335491,0.002018158,0.00060888985,0.0018830587,0.0012894075,0.0036412713,0.094107814],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010745343,0.000008795607,0.00007667624,0.000016144199,0.0000016146962,0.000033744185,0.000013147728,0.000016234117,0.00013954149,0.00086904084,0.99161834,0.0071959565],"study_design_scores_gemma":[0.0000034285088,0.000008600115,0.00070152606,0.000014248418,0.0000025320678,0.000014689668,0.00002826732,0.000046113968,0.00017176886,0.00010795785,0.99889475,0.0000062306235],"about_ca_topic_score_codex":0.25605753,"about_ca_topic_score_gemma":0.5278494,"teacher_disagreement_score":0.7439425,"about_ca_system_score_codex":0.0033767282,"about_ca_system_score_gemma":0.006910773,"threshold_uncertainty_score":0.996407},"labels":[],"label_agreement":null},{"id":"W2896479483","doi":"10.1007/s10479-018-3076-8","title":"Shared mobility systems: an updated survey","year":2018,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":128,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"TRIPS architecture; Variety (cybernetics); Field (mathematics); Computer science; Point (geometry); Operations research; Transport engineering; Data science; Telecommunications; Management science; Engineering","score_opus":0.3362647373297932,"score_gpt":0.4692835955316023,"score_spread":0.13301885820180914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896479483","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31415898,0.5656246,0.018122597,0.029002067,0.0015850529,0.00013845549,0.021512795,0.0002211716,0.049634345],"genre_scores_gemma":[0.47426552,0.49828967,0.0050354726,0.0033443773,0.0011303765,0.000091874914,0.01227759,0.0000806064,0.0054844907],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983903,0.00026616908,0.00026289176,0.00030483914,0.0005924604,0.0001833204],"domain_scores_gemma":[0.98511755,0.008191567,0.002067182,0.0008294686,0.0031419292,0.00065221323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002299177,0.00040559022,0.0005691102,0.004277008,0.0003632554,0.0026197012,0.0008264293,0.00078017934,0.0074729132],"category_scores_gemma":[0.014434665,0.00032793146,0.00058330264,0.01028383,0.00062742335,0.00791432,0.0012744095,0.0014500722,0.0011525946],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021787408,0.00027875582,0.1482811,0.0023165364,0.00023952781,0.000096687305,0.0008178413,0.0023577528,0.0002924394,0.013369942,0.08032449,0.75140697],"study_design_scores_gemma":[0.00004075908,0.0004932258,0.35159183,0.0034463876,0.00039852943,0.0018772024,0.00480318,0.0034880869,0.00061374286,0.012799875,0.6203377,0.00010947328],"about_ca_topic_score_codex":0.007954345,"about_ca_topic_score_gemma":0.009340041,"teacher_disagreement_score":0.007954345,"about_ca_system_score_codex":0.0011547959,"about_ca_system_score_gemma":0.0020119136,"threshold_uncertainty_score":0.02499932},"labels":[],"label_agreement":null},{"id":"W2897892437","doi":"10.1109/re.2018.00-21","title":"Software Transparency as a Key Requirement for Self-Driving Cars","year":2018,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Transparency (behavior); Self driving; Commercialization; Computer science; Key (lock); Schedule; Software; Work (physics); Domain (mathematical analysis); Risk analysis (engineering); Computer security; Business; Transport engineering; Engineering; Marketing","score_opus":0.017412327822133943,"score_gpt":0.2574478060158072,"score_spread":0.24003547819367324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897892437","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45678288,0.0002740558,0.50140643,0.005919061,0.00008730058,0.0006069115,0.00031996754,0.0014062483,0.03319711],"genre_scores_gemma":[0.930382,0.00008137983,0.06720856,0.00019620368,0.000017752125,0.00010180466,0.00012456453,0.00010714492,0.0017805197],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9781356,0.00853584,0.0016480978,0.0014049169,0.009137607,0.0011380278],"domain_scores_gemma":[0.8912553,0.06636769,0.012035704,0.015252713,0.013336694,0.0017517934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00831255,0.00039260744,0.00027080247,0.00088237727,0.001024039,0.0024049752,0.0009957047,0.0016807833,0.0016268254],"category_scores_gemma":[0.05001881,0.00060528197,0.0006943191,0.00043077735,0.0028536264,0.004561186,0.002334736,0.0020897803,0.0002750797],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004222038,0.0006685501,0.040343538,0.0015727353,0.00011765383,0.0049915067,0.030608626,0.042778276,0.14812171,0.62617683,0.004565647,0.09963276],"study_design_scores_gemma":[0.00010278466,0.0010301886,0.032243665,0.0009539434,0.00023523043,0.006053375,0.009916704,0.30650738,0.1563344,0.37821317,0.10808707,0.00032214617],"about_ca_topic_score_codex":0.0026420727,"about_ca_topic_score_gemma":0.002377971,"teacher_disagreement_score":0.00831255,"about_ca_system_score_codex":0.001509706,"about_ca_system_score_gemma":0.002684715,"threshold_uncertainty_score":0.043961525},"labels":[],"label_agreement":null},{"id":"W289857799","doi":"","title":"Feasibility and Performance of Flex-Route Transit Service in Suburban Areas","year":2009,"lang":"en","type":"article","venue":"Transportation Research Board 88th Annual MeetingTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"FLEX; Transport engineering; Transit (satellite); Service (business); Level of service; Computer science; Service level; Public transport; Engineering; Business; Telecommunications","score_opus":0.05922850290965606,"score_gpt":0.34600186170996977,"score_spread":0.28677335880031374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W289857799","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9955948,0.000028387678,0.0024414086,0.000028837389,0.0000036349013,0.000017276108,0.000048229653,0.000029253906,0.0018081223],"genre_scores_gemma":[0.9984847,0.000017128139,0.0010224866,0.0000033718138,7.4012365e-7,0.0000053467015,0.000040652198,0.0000047537046,0.00042089657],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9992291,0.00041298717,0.000017518849,0.00006832714,0.00009628313,0.00017587192],"domain_scores_gemma":[0.9981248,0.00078947126,0.00023616046,0.0001960838,0.00044391034,0.0002094987],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010253814,0.00045684408,0.00027809618,0.00034628747,0.00044971393,0.0006300792,0.00067518937,0.00047556273,0.0036849056],"category_scores_gemma":[0.0034376758,0.00020830055,0.00036581577,0.0004239278,0.0004623673,0.0008044235,0.00042928764,0.00025366084,0.00033449536],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003188073,0.00064394705,0.075612955,0.00013307607,0.00007534684,0.0008847203,0.00032520932,0.86439985,0.012264362,0.0043155258,0.000937754,0.03721923],"study_design_scores_gemma":[0.00020650159,0.0030065696,0.03014233,0.000021580125,0.00008910605,0.0002902288,0.0016551034,0.9505105,0.010338879,0.0015624965,0.0021347806,0.0000419243],"about_ca_topic_score_codex":0.022897216,"about_ca_topic_score_gemma":0.031686854,"teacher_disagreement_score":0.022897216,"about_ca_system_score_codex":0.0011913566,"about_ca_system_score_gemma":0.0009074572,"threshold_uncertainty_score":0.045527875},"labels":[],"label_agreement":null},{"id":"W2899735731","doi":"10.1155/2018/4360516","title":"Taxi Efficiency Measurements Based on Motorcade-Sharing Model: Evidence from GPS-Equipped Taxi Data in Sanya","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Office for Philosophy and Social Sciences; Chinese Universities Scientific Fund; Chang'an University","keywords":"Taxis; Global Positioning System; Traffic congestion; Intelligent transportation system; Transport engineering; Computer science; Field (mathematics); Telecommunications; Engineering; Mathematics","score_opus":0.07941476727037314,"score_gpt":0.31303001208995396,"score_spread":0.23361524481958082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899735731","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9962664,0.00003935658,0.001889123,0.000033503326,0.0000052357914,0.0000136918625,0.0002976271,0.000056800625,0.0013982366],"genre_scores_gemma":[0.9986739,0.000036245256,0.0005864062,0.0000032697783,0.0000013633013,0.000008873857,0.00047514308,0.000007935539,0.00020692803],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992581,0.0001706176,0.000048491947,0.0002026565,0.00020526606,0.00011483544],"domain_scores_gemma":[0.99872345,0.00032270586,0.00013109065,0.0003069482,0.00046027746,0.000055576504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009472972,0.00068670197,0.0005824554,0.0008675473,0.0006643286,0.000840776,0.0012173232,0.00060836173,0.00092919945],"category_scores_gemma":[0.0024559712,0.0003528743,0.0006630215,0.0021195163,0.0006405126,0.0016574583,0.00051799405,0.0006101249,0.00036074664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00075957994,0.0004613388,0.5092581,0.00017693805,0.00028143846,0.00041991557,0.0009753474,0.4401215,0.0041188556,0.0021410433,0.0023047896,0.03898111],"study_design_scores_gemma":[0.00006264557,0.00032586162,0.20355742,0.000031012285,0.00016121363,0.00012374535,0.001961383,0.7843188,0.0062243044,0.0008762596,0.0022760949,0.00008124835],"about_ca_topic_score_codex":0.10400265,"about_ca_topic_score_gemma":0.07837426,"teacher_disagreement_score":0.10400265,"about_ca_system_score_codex":0.0020835695,"about_ca_system_score_gemma":0.0011666623,"threshold_uncertainty_score":0.20679456},"labels":[],"label_agreement":null},{"id":"W2901793019","doi":"10.1522/revueot.v11n2.806","title":"Les modes de gestion possibles du transport en commun","year":2002,"lang":"fr","type":"article","venue":"Revue Organisations & territoires","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Political science","score_opus":0.025129768410950753,"score_gpt":0.22321246495171393,"score_spread":0.1980826965407632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901793019","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36522007,0.004322465,0.34849045,0.0059999614,0.0003195449,0.00023298922,0.0010484221,0.00073761103,0.27362847],"genre_scores_gemma":[0.9246671,0.0025745241,0.03107899,0.0001113684,0.000097989236,0.00026137265,0.00026309874,0.000102896236,0.04084268],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970114,0.0009549849,0.000117064395,0.00039343943,0.0009225223,0.00060049305],"domain_scores_gemma":[0.9962192,0.0018071439,0.0004284899,0.0005326381,0.0007184319,0.0002940666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002167995,0.0011938091,0.00044789058,0.0022331593,0.0038968096,0.010273736,0.0011738284,0.0029347201,0.013639067],"category_scores_gemma":[0.007471414,0.00090211956,0.0010664404,0.0016216502,0.003911714,0.006980074,0.004789268,0.0018858694,0.0031622266],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003929466,0.000060966686,0.025004914,0.00041702663,0.00007686791,0.0017806255,0.016204655,0.024927408,0.0076430687,0.833754,0.0059870137,0.08375068],"study_design_scores_gemma":[0.000110649584,0.00029532876,0.023471097,0.0011050822,0.00016726607,0.0064476305,0.04633185,0.11209256,0.012722919,0.6222895,0.17446387,0.0005022581],"about_ca_topic_score_codex":0.008425533,"about_ca_topic_score_gemma":0.0073796134,"teacher_disagreement_score":0.013639067,"about_ca_system_score_codex":0.0019719687,"about_ca_system_score_gemma":0.0015087452,"threshold_uncertainty_score":0.045627236},"labels":[],"label_agreement":null},{"id":"W2901820396","doi":"10.1287/msom.2019.0851","title":"Charging an Electric Vehicle-Sharing Fleet","year":2020,"lang":"en","type":"article","venue":"Manufacturing & Service Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Electric vehicle; Operations research; Queueing theory; Service (business); Renting; Operator (biology); Order (exchange); Business; Computer network; Marketing; Engineering","score_opus":0.018982134301664268,"score_gpt":0.222339311730124,"score_spread":0.20335717742845974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901820396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9178639,0.000046749657,0.039815832,0.00047640287,0.00011313952,0.000100484714,0.00021681302,0.00027326983,0.04109343],"genre_scores_gemma":[0.99357176,0.000011877524,0.0011268308,0.000013757687,0.0000047632884,0.0000061449664,0.00004046549,0.00000868044,0.0052157273],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997147,0.00006684948,0.000008372303,0.000049442235,0.000058087036,0.00010260038],"domain_scores_gemma":[0.9997378,0.00007843311,0.000015046396,0.000048224887,0.00004996817,0.000070564936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002978403,0.00033011936,0.00042464127,0.0003709746,0.0010802138,0.00091362983,0.00083792466,0.000933059,0.010412982],"category_scores_gemma":[0.00094642845,0.00018381787,0.000505385,0.0005291861,0.0004071248,0.0012274074,0.0012100794,0.0004207138,0.00044405094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00095218647,0.00020149304,0.0041699475,0.00006038217,0.000060951937,0.0023186696,0.00016125117,0.9279874,0.00924045,0.019652227,0.004029988,0.031165013],"study_design_scores_gemma":[0.000036515423,0.00022455186,0.0015263687,0.000004999525,0.000015830998,0.0002495543,0.00032143274,0.98589224,0.0017573491,0.007285312,0.0026654676,0.000020371648],"about_ca_topic_score_codex":0.0070561343,"about_ca_topic_score_gemma":0.0060143587,"teacher_disagreement_score":0.010412982,"about_ca_system_score_codex":0.0010065583,"about_ca_system_score_gemma":0.00059749506,"threshold_uncertainty_score":0.03483492},"labels":[],"label_agreement":null},{"id":"W2904242730","doi":"10.5267/j.msl.2018.12.003","title":"Simulation-based optimization approach for vehicle allocation in a private transport service: A case study","year":2018,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Universidad de La Sabana","keywords":"Service (business); Computer science; Operations research; Transport engineering; Business; Operations management; Process management; Marketing; Mathematics; Engineering","score_opus":0.020504309887581933,"score_gpt":0.2630697024034887,"score_spread":0.24256539251590678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904242730","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7350281,0.00075345923,0.22964966,0.0010721829,0.00010122744,0.00033590916,0.0005682072,0.00031519806,0.03217606],"genre_scores_gemma":[0.9727108,0.0002456989,0.023213211,0.000027147034,0.000013641497,0.00013285644,0.00011074231,0.000022485667,0.0035233477],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965346,0.00018301643,0.000012371111,0.000030569805,0.00004105708,0.00007942607],"domain_scores_gemma":[0.9987343,0.00094898284,0.00007842205,0.000038184804,0.00013107208,0.00006902647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067063264,0.0008047294,0.0008226293,0.0006975307,0.0006947258,0.0011926714,0.00081892515,0.0016997246,0.003700227],"category_scores_gemma":[0.0013434663,0.00043627722,0.0008892023,0.0007897019,0.00051200285,0.00048141312,0.00064276176,0.0008550586,0.00016020144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029122444,0.000032543416,0.000407018,0.000016336024,0.000008667414,0.000056774858,0.000014858354,0.9972657,0.00017874078,0.00084243726,0.00008924378,0.0010585128],"study_design_scores_gemma":[0.0000068688296,0.000016827711,0.00011903328,0.000001932989,0.0000044864632,0.000005420359,0.000025090869,0.99941814,0.00008305766,0.00017002212,0.0001464119,0.0000027553133],"about_ca_topic_score_codex":0.041898202,"about_ca_topic_score_gemma":0.027281823,"teacher_disagreement_score":0.041898202,"about_ca_system_score_codex":0.0015581695,"about_ca_system_score_gemma":0.0016107822,"threshold_uncertainty_score":0.08330864},"labels":[],"label_agreement":null},{"id":"W2904680133","doi":"10.1287/trsc.2018.0838","title":"Anticipatory Dynamic Traffic Sensor Location Problems with Connected Vehicle Technologies","year":2018,"lang":"en","type":"article","venue":"Transportation Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Transport engineering; Computer science; Automatic vehicle location; Engineering; Telecommunications; Global Positioning System","score_opus":0.013453210726846345,"score_gpt":0.24518019003698044,"score_spread":0.23172697931013408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904680133","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12331805,0.0011502549,0.8682125,0.0010168117,0.00014024289,0.00012522328,0.00031032588,0.00017838566,0.005548253],"genre_scores_gemma":[0.9590978,0.0005845653,0.03621905,0.00009716015,0.00005125285,0.00016770372,0.00024160603,0.00004610441,0.0034947558],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991954,0.0003257287,0.000028407187,0.00017030664,0.00009210593,0.00018816633],"domain_scores_gemma":[0.996988,0.0023374,0.00030499912,0.00006531942,0.00017610616,0.00012818263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015081692,0.0019774684,0.001478114,0.0007804021,0.0005719308,0.0014035078,0.0014911338,0.0020418689,0.00199065],"category_scores_gemma":[0.004182482,0.0012249238,0.0010393774,0.0010138119,0.0012613072,0.0018370067,0.0012500975,0.0017438857,0.00011146236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003095043,0.000012569273,0.00012770078,0.000019691402,0.000011266443,0.0000226814,0.000009458506,0.9952684,0.00009627272,0.0029869925,0.0001364834,0.001277494],"study_design_scores_gemma":[0.000008551055,0.000022093533,0.000046954887,0.0000033166841,0.0000061063574,0.000005064743,0.000012294124,0.9961125,0.000070269096,0.0035904702,0.00011911108,0.0000032784155],"about_ca_topic_score_codex":0.013967054,"about_ca_topic_score_gemma":0.0075314073,"teacher_disagreement_score":0.013967054,"about_ca_system_score_codex":0.0017346208,"about_ca_system_score_gemma":0.0014027902,"threshold_uncertainty_score":0.027771533},"labels":[],"label_agreement":null},{"id":"W2904792324","doi":"10.1016/j.energy.2018.12.066","title":"Autonomous connected electric vehicle (ACEV)-based car-sharing system modeling and optimal planning: A unified two-stage multi-objective optimization methodology","year":2018,"lang":"en","type":"article","venue":"Energy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":73,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"China Scholarship Council; National Natural Science Foundation of China","keywords":"Flexibility (engineering); Electric vehicle; Service (business); Range (aeronautics); Computer science; Crowds; Transport engineering; Automotive engineering; Operations research; Engineering; Computer security; Business","score_opus":0.0479837353548093,"score_gpt":0.2812157371039533,"score_spread":0.23323200174914402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904792324","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023238234,0.00024285377,0.9665485,0.00012724877,0.000041368945,0.00011470527,0.00012226265,0.00022285238,0.009341873],"genre_scores_gemma":[0.894087,0.00032906866,0.09676463,0.000085609565,0.000045149827,0.00049207546,0.00024208658,0.00010477866,0.00784943],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996388,0.00010782623,0.000014216925,0.0000611997,0.00010949405,0.00006851199],"domain_scores_gemma":[0.99953914,0.00023346781,0.000053869582,0.00002437814,0.00011659456,0.00003258083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009049704,0.0012222176,0.0014317068,0.00070700294,0.00066694064,0.001537778,0.0018686764,0.0016011815,0.0031510498],"category_scores_gemma":[0.0013469389,0.0010869504,0.0012469313,0.00087162806,0.00056198926,0.0012220367,0.001322123,0.0010344101,0.00032888824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008409886,0.000011288961,0.00007210573,0.00001444066,0.000010892007,0.000014721236,0.000010085081,0.99636394,0.00016056214,0.0012555785,0.00008940576,0.001988572],"study_design_scores_gemma":[0.0000017686954,0.0000063388666,0.00002575019,0.0000010864138,0.000003170971,0.0000018901895,0.0000031437537,0.9994962,0.00005264895,0.00032619672,0.00008034684,0.0000014474133],"about_ca_topic_score_codex":0.021127919,"about_ca_topic_score_gemma":0.01730771,"teacher_disagreement_score":0.021127919,"about_ca_system_score_codex":0.0010876122,"about_ca_system_score_gemma":0.002496406,"threshold_uncertainty_score":0.04200989},"labels":[],"label_agreement":null},{"id":"W2904834100","doi":"","title":"Connected and Automated Vehicle Activities in Canada","year":2018,"lang":"en","type":"article","venue":"TR news","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.008222792383164913,"score_gpt":0.2053123247970488,"score_spread":0.19708953241388388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904834100","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5858776,0.010198818,0.0007430952,0.05730468,0.0018578982,0.00012301389,0.03043899,0.0002867311,0.31316924],"genre_scores_gemma":[0.78325003,0.008877179,0.00042673203,0.004656515,0.0002921782,0.00003642339,0.0067914464,0.00009817804,0.19557135],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99877053,0.000038657472,0.000027670492,0.000100722216,0.00057244964,0.00048995786],"domain_scores_gemma":[0.9965553,0.00021969224,0.00018317641,0.000053307474,0.001655824,0.0013327263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003532193,0.00025564592,0.0002534167,0.002451312,0.0056797476,0.004640104,0.0012395486,0.0014048336,0.0137691675],"category_scores_gemma":[0.0019858868,0.00027622268,0.00037704743,0.0060105743,0.0014854904,0.0010286091,0.0014859112,0.002180442,0.00093186816],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048532296,0.0003855666,0.2570443,0.0004879437,0.0001264631,0.0015939099,0.015795937,0.0023939817,0.00088473276,0.04313775,0.4812375,0.19642657],"study_design_scores_gemma":[0.000027371529,0.00005204974,0.57817423,0.00026292272,0.000033686763,0.00016468494,0.018407322,0.0009146133,0.00031256094,0.00097568706,0.40060148,0.000073418145],"about_ca_topic_score_codex":0.99797493,"about_ca_topic_score_gemma":0.99930143,"teacher_disagreement_score":0.9427461,"about_ca_system_score_codex":0.057253912,"about_ca_system_score_gemma":0.09779211,"threshold_uncertainty_score":0.41540813},"labels":[],"label_agreement":null},{"id":"W2905496377","doi":"10.1007/978-3-030-35032-1_9","title":"Distributed Algorithms for Internet-of-Things-Enabled Prosumer Markets: A Control Theoretic Perspective","year":2020,"lang":"en","type":"book-chapter","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Energiteknologisk udviklings- og demonstrationsprogram; Science Foundation Ireland","keywords":"Prosumer; Computer science; Resource (disambiguation); Context (archaeology); Probabilistic logic; Shared resource; Distributed computing; Environmental economics; Computer network; Engineering; Renewable energy; Economics; Artificial intelligence","score_opus":0.011357852429178448,"score_gpt":0.2220512348185765,"score_spread":0.21069338238939805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2905496377","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007312973,0.0029538237,0.95538753,0.002292182,0.0004279414,0.00006245609,0.000065748776,0.000087051914,0.03141044],"genre_scores_gemma":[0.7191138,0.009265946,0.2218003,0.0010652171,0.0013504159,0.00041058334,0.00015866033,0.00019709759,0.046637915],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989988,0.00040443396,0.000040112154,0.0001846701,0.0002610988,0.00011095015],"domain_scores_gemma":[0.9975011,0.0019964701,0.00012568077,0.00013282994,0.00017971067,0.00006424008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019409364,0.001265997,0.0015080574,0.00068779086,0.00074039976,0.0034757277,0.0024228112,0.0026564382,0.005597585],"category_scores_gemma":[0.005267919,0.0005879102,0.0009381728,0.0017301207,0.0029117034,0.004354484,0.0014783815,0.0034777035,0.00068019965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028916213,0.00005334222,0.00008318031,0.000108026914,0.00003159102,0.0000455568,0.000062179155,0.20943472,0.00050549634,0.7683992,0.0031639263,0.018083982],"study_design_scores_gemma":[0.000018651639,0.000028110297,0.00004907495,0.000026037102,0.000011002274,0.00003357234,0.000037689595,0.46923006,0.00020957636,0.52668333,0.0036600751,0.000012769679],"about_ca_topic_score_codex":0.0018354597,"about_ca_topic_score_gemma":0.0012351719,"teacher_disagreement_score":0.005597585,"about_ca_system_score_codex":0.0022130357,"about_ca_system_score_gemma":0.0012934388,"threshold_uncertainty_score":0.018725812},"labels":[],"label_agreement":null},{"id":"W2907074081","doi":"10.1155/2019/2781590","title":"Optimizing Vehicle Scheduling Based on Variable Timetable by Benders-and-Price Approach","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"China Railway","keywords":"Column generation; Scheduling (production processes); Benders' decomposition; Mathematical optimization; Computer science; Variable (mathematics); Fleet management; TRIPS architecture; Integer programming; Operations research; Engineering; Mathematics","score_opus":0.006990760899498868,"score_gpt":0.20761193046122467,"score_spread":0.2006211695617258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2907074081","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029988108,0.0002387256,0.9645912,0.00015402526,0.00006599428,0.00013625609,0.000178583,0.00035317088,0.0042939023],"genre_scores_gemma":[0.62695,0.00058133574,0.3645449,0.00013193012,0.00005176341,0.00040771224,0.0005708011,0.00023257764,0.006528873],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994727,0.00017722671,0.000020283045,0.000093598865,0.00011753214,0.00011875403],"domain_scores_gemma":[0.9996933,0.00015403987,0.00004744823,0.000023369306,0.00004589709,0.000036018442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092525745,0.0011324438,0.0012034074,0.0008317988,0.0005686726,0.0009589293,0.0011819161,0.00085506635,0.0062023797],"category_scores_gemma":[0.0011572861,0.00079601014,0.0010240634,0.0014177631,0.0005882577,0.0013510077,0.00071182434,0.0011014763,0.00041542467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038088983,0.000022529734,0.000099031044,0.00003372194,0.000016519269,0.000022870494,0.000013690579,0.9826481,0.00062317296,0.00683545,0.00051452883,0.009132313],"study_design_scores_gemma":[0.000013881011,0.000035482626,0.000041408613,0.0000021114777,0.0000057720977,0.000007264544,0.0000072546923,0.9947442,0.00021688327,0.0045539485,0.00036749098,0.000004341951],"about_ca_topic_score_codex":0.010847052,"about_ca_topic_score_gemma":0.008695603,"teacher_disagreement_score":0.010847052,"about_ca_system_score_codex":0.0012777974,"about_ca_system_score_gemma":0.0019573495,"threshold_uncertainty_score":0.021567822},"labels":[],"label_agreement":null},{"id":"W2907875385","doi":"","title":"Impacts potentiels du télétravail sur les comportements en transport, la santé et les heures travaillées au Québec","year":2018,"lang":"fr","type":"article","venue":"CIRANO Project Reports","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Telecommuting; Socioeconomic status; Geography; Incentive; Context (archaeology); Welfare economics; Demographic economics; Work (physics); Demography; Sociology; Economics; Population; Engineering","score_opus":0.019202750051212258,"score_gpt":0.2837026595842895,"score_spread":0.2644999095330772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2907875385","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96181035,0.0016865917,0.00057628093,0.004299673,0.000058694553,0.000039612063,0.005206041,0.00006532183,0.02625728],"genre_scores_gemma":[0.9906294,0.0007964239,0.00015114297,0.00020920682,0.000025965302,0.000014925031,0.00067526766,0.0000099608715,0.007487756],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987233,0.00035838922,0.000030211808,0.000101052276,0.00030158425,0.00048534613],"domain_scores_gemma":[0.99633104,0.00071739376,0.00065319013,0.00010117023,0.0011964154,0.0010008387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007509674,0.000331946,0.00026808024,0.0008519479,0.0017639515,0.0022126483,0.0008312794,0.0005024509,0.01450272],"category_scores_gemma":[0.003605122,0.00014517641,0.0006174204,0.0015158289,0.000992148,0.00064942986,0.0012037605,0.00089033705,0.0005855218],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003253948,0.000197544,0.9326409,0.00012117638,0.00024298397,0.0007210818,0.0020267626,0.007797497,0.0008472421,0.004272788,0.00888835,0.04191816],"study_design_scores_gemma":[0.000022103022,0.00008628926,0.9853108,0.000101952566,0.000075741664,0.000078872145,0.0026979225,0.0029696214,0.00011959371,0.00017510269,0.008338014,0.000023995623],"about_ca_topic_score_codex":0.9884419,"about_ca_topic_score_gemma":0.99060947,"teacher_disagreement_score":0.03309888,"about_ca_system_score_codex":0.03309888,"about_ca_system_score_gemma":0.017850202,"threshold_uncertainty_score":0.24015027},"labels":[],"label_agreement":null},{"id":"W2909701316","doi":"10.1177/0361198118822281","title":"Factors That Influence Older Canadians’ Preferences for using Autonomous Vehicle Technology: A Structural Equation Analysis","year":2019,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Structural equation modeling; Affect (linguistics); Perception; Public transport; Quality of life (healthcare); Travel behavior; Business; Psychology; Transport engineering; Demographic economics; Marketing; Gerontology; Engineering; Economics; Computer science; Medicine","score_opus":0.11024453119831541,"score_gpt":0.3661673577577412,"score_spread":0.2559228265594258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909701316","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99513394,0.00017195237,0.00049299304,0.0005907389,0.000015245072,0.00011890047,0.0015944765,0.000015068065,0.0018664729],"genre_scores_gemma":[0.99544746,0.00022835548,0.0012902714,0.00009909764,0.000007888635,0.00010701112,0.0019190878,0.0000059878253,0.0008948647],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986172,0.00020376877,0.000106028856,0.0002064119,0.00046872668,0.000397869],"domain_scores_gemma":[0.9968262,0.000757889,0.00045411845,0.00015744523,0.0013568002,0.0004475707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030793105,0.0007765479,0.00068117667,0.0019271859,0.0035532587,0.0020489069,0.0014916891,0.00081236387,0.0040855175],"category_scores_gemma":[0.0078069014,0.00050789403,0.0019657735,0.0031230056,0.00078790355,0.00062859524,0.0014015877,0.0012009484,0.000266729],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068936286,0.00013134912,0.9867308,0.000059564103,0.00015275292,0.00008233427,0.003860255,0.00081949873,0.00011214826,0.00060437113,0.0013445233,0.0060335123],"study_design_scores_gemma":[0.0000394682,0.00012635897,0.9705702,0.00015990644,0.00024361786,0.00006870391,0.011026392,0.014628298,0.00008294745,0.00038153134,0.0026204954,0.000052048315],"about_ca_topic_score_codex":0.9659263,"about_ca_topic_score_gemma":0.95200044,"teacher_disagreement_score":0.03407371,"about_ca_system_score_codex":0.014022358,"about_ca_system_score_gemma":0.032452874,"threshold_uncertainty_score":0.101739824},"labels":[],"label_agreement":null},{"id":"W2909705168","doi":"10.3386/w24806","title":"A Theory of Multihoming in Rideshare Competition","year":2018,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Multihoming; Duopoly; Monopoly; Competition (biology); Microeconomics; Industrial organization; Economics; Face (sociological concept); Business; Computer science; The Internet; Cournot competition; Ecology","score_opus":0.3344946476654992,"score_gpt":0.490066875791291,"score_spread":0.1555722281257918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909705168","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13894074,0.0022681735,0.38721913,0.008977005,0.00038248207,0.0003292928,0.0005339865,0.00018764829,0.4611616],"genre_scores_gemma":[0.9631207,0.0010025816,0.011168953,0.0007456616,0.00024937716,0.0002119525,0.00008871903,0.000031258583,0.02338084],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986754,0.0004974647,0.000033652308,0.00019340981,0.00022465007,0.0003753111],"domain_scores_gemma":[0.9968059,0.0019125332,0.0004156892,0.00020041617,0.00026074788,0.000404829],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016132524,0.0008154674,0.001213685,0.0011587671,0.002410277,0.004230336,0.0023567842,0.003829419,0.035995547],"category_scores_gemma":[0.004704289,0.00047879448,0.0012863642,0.0015676983,0.0046263486,0.0056371274,0.0025760576,0.0025132117,0.002054156],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019091929,0.00004337,0.00046699372,0.00004914662,0.000013382432,0.00010762337,0.0001398737,0.01725839,0.00018403665,0.97586346,0.002267809,0.0035868897],"study_design_scores_gemma":[0.00005727996,0.00007652161,0.00057991466,0.000039184855,0.00001690985,0.00013445955,0.00027367639,0.08309185,0.00007989084,0.9093471,0.006274919,0.0000283392],"about_ca_topic_score_codex":0.005483215,"about_ca_topic_score_gemma":0.003566038,"teacher_disagreement_score":0.035995547,"about_ca_system_score_codex":0.002646314,"about_ca_system_score_gemma":0.0020019598,"threshold_uncertainty_score":0.12041706},"labels":[],"label_agreement":null},{"id":"W2909765148","doi":"10.1155/2019/7546303","title":"Optimizing Location of Car-Sharing Stations Based on Potential Travel Demand and Present Operation Characteristics: The Case of Chengdu","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Lasso (programming language); Population; Operations research; Data mining; Engineering","score_opus":0.007730756044131535,"score_gpt":0.23325312819110242,"score_spread":0.22552237214697088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909765148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9868804,0.00022244567,0.010458932,0.00039115828,0.000012843222,0.00003963222,0.00031131387,0.00006474038,0.0016185521],"genre_scores_gemma":[0.9961688,0.00006590347,0.0026828945,0.00001772006,0.000004363814,0.000018455054,0.00025607072,0.000008004405,0.0007777556],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9993414,0.00021480526,0.000029034045,0.00015189355,0.00007280041,0.00019002598],"domain_scores_gemma":[0.9983284,0.0007843336,0.00019537148,0.00012405001,0.00038108928,0.00018671941],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014555294,0.0010384228,0.0009824174,0.0012263551,0.00094651815,0.0016099227,0.0020347938,0.0013192659,0.0016506849],"category_scores_gemma":[0.0041261627,0.0005652856,0.00086176116,0.0016008248,0.00081101427,0.0012984056,0.0011557131,0.0006128317,0.00016981395],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023699619,0.0001530034,0.047364235,0.00011547255,0.00008977184,0.0017968225,0.00025137,0.93231595,0.0013264002,0.0022468134,0.0010927389,0.013010339],"study_design_scores_gemma":[0.000015721493,0.0000391986,0.007771822,0.0000054444263,0.000024931145,0.000040998253,0.00030165524,0.9908981,0.00018927413,0.0004885312,0.00020800627,0.000016338381],"about_ca_topic_score_codex":0.21163787,"about_ca_topic_score_gemma":0.117165126,"teacher_disagreement_score":0.21163787,"about_ca_system_score_codex":0.0034930245,"about_ca_system_score_gemma":0.0021141355,"threshold_uncertainty_score":0.42081195},"labels":[],"label_agreement":null},{"id":"W2909817711","doi":"10.4018/978-1-5225-7591-7.ch001","title":"Volunteered Geographic Service","year":2019,"lang":"en","type":"book-chapter","venue":"Advances in public policy and administration (APPA) book series","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Recreation; Service (business); Business; Transport engineering; Marketing; Engineering; Political science","score_opus":0.012572648098910134,"score_gpt":0.2459440278807754,"score_spread":0.23337137978186528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909817711","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0068128915,0.0052839494,0.0038702835,0.0040048724,0.0019687854,0.00023203726,0.0012157825,0.00086227176,0.97574914],"genre_scores_gemma":[0.02772308,0.0042162803,0.0025628833,0.00076762674,0.00030318534,0.000093262024,0.0011130061,0.00018773481,0.9630329],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995116,0.00010447673,0.000023376248,0.00008032311,0.00015284396,0.00012741213],"domain_scores_gemma":[0.9993783,0.00006157882,0.000025906065,0.00011080384,0.00022014129,0.00020321392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050450687,0.000535897,0.0003306974,0.0012041855,0.0016153558,0.003513334,0.0011825947,0.0009872463,0.15214513],"category_scores_gemma":[0.00089152594,0.00019639413,0.00034859512,0.0023209795,0.00080766133,0.0015885403,0.0034056196,0.0006877489,0.037716433],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024165236,0.00004983168,0.0007043912,0.00037971904,0.0000047351537,0.00025978134,0.002198048,0.0002978781,0.0007545942,0.03680483,0.6471606,0.31136155],"study_design_scores_gemma":[0.0000027952265,0.000011468388,0.0004573676,0.000046171568,8.799934e-7,0.00009925162,0.0005783582,0.00006782097,0.000040408708,0.000775054,0.99791783,0.0000024677577],"about_ca_topic_score_codex":0.021251068,"about_ca_topic_score_gemma":0.03914442,"teacher_disagreement_score":0.15214513,"about_ca_system_score_codex":0.00227365,"about_ca_system_score_gemma":0.004245456,"threshold_uncertainty_score":0.50897616},"labels":[],"label_agreement":null},{"id":"W2909893247","doi":"10.1111/cag.12514","title":"Ride‐hailing's impact on Canadian cities: Now let's consider the long game","year":2019,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Taxis; Key (lock); Business; Marketing; Advertising; Transport engineering; Engineering; Computer science; Computer security","score_opus":0.006846992074883867,"score_gpt":0.19616570826522817,"score_spread":0.1893187161903443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909893247","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15716319,0.02353933,0.0015208028,0.49413547,0.003250313,0.00018175546,0.01000754,0.00028845444,0.30991313],"genre_scores_gemma":[0.88395476,0.01994119,0.001732211,0.022359595,0.00046939153,0.00006305811,0.0018106903,0.00010372114,0.06956536],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9970987,0.00019821881,0.000042543918,0.0001423609,0.0012414637,0.0012767895],"domain_scores_gemma":[0.99474734,0.0003284709,0.00017841648,0.0000919645,0.0035623605,0.0010913465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016719445,0.00078397425,0.0006049947,0.0016446757,0.011502434,0.0073055783,0.001889803,0.0021504192,0.023149185],"category_scores_gemma":[0.0069253603,0.00020241777,0.000830295,0.0033681665,0.0040193843,0.002893982,0.002751499,0.0032201954,0.0008938011],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034050693,0.00016399479,0.05273416,0.0011101677,0.0001617718,0.0005871381,0.0061406856,0.0051304437,0.0011254392,0.13999589,0.63523114,0.15727878],"study_design_scores_gemma":[0.000064819855,0.00016024672,0.1580777,0.0010474805,0.00021220921,0.00014219675,0.028633244,0.002097018,0.0009292354,0.012380274,0.7958576,0.00039803193],"about_ca_topic_score_codex":0.99763024,"about_ca_topic_score_gemma":0.9989801,"teacher_disagreement_score":0.12531437,"about_ca_system_score_codex":0.12531437,"about_ca_system_score_gemma":0.18452717,"threshold_uncertainty_score":0.9092237},"labels":[],"label_agreement":null},{"id":"W2911427661","doi":"10.22215/etd/2013-09478","title":"Generative contracts","year":2013,"lang":"en","type":"dissertation","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Generative grammar; Computer science; Humanities; Artificial intelligence; Philosophy","score_opus":0.008711564132643061,"score_gpt":0.22868109532135836,"score_spread":0.2199695311887153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911427661","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009845346,0.0011105975,0.5024401,0.0069971196,0.00039808662,0.00030542942,0.001680709,0.0014840949,0.47573858],"genre_scores_gemma":[0.35988206,0.0026405652,0.23398921,0.0022116234,0.0004945965,0.0011248938,0.004572323,0.0022624552,0.39282224],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9942701,0.0027123874,0.0003227046,0.00096730865,0.0013595704,0.00036789256],"domain_scores_gemma":[0.98771626,0.0054875268,0.00044762326,0.004463264,0.001269861,0.00061541336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052778656,0.00080596114,0.00061267783,0.0016460551,0.002642726,0.006956242,0.0022135149,0.0023045233,0.07456341],"category_scores_gemma":[0.02037305,0.0008511993,0.0014328005,0.0028579892,0.004390085,0.008746397,0.00576561,0.0027835313,0.015131147],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017370909,0.000019771189,0.0002369175,0.000041610125,0.0000092720065,0.000053673037,0.00035671308,0.0011480747,0.00017631316,0.9678799,0.007916355,0.022144103],"study_design_scores_gemma":[0.00002421094,0.000013680578,0.00019251126,0.00009373681,0.000012116391,0.000168328,0.00021009019,0.0069694268,0.00046173317,0.80094594,0.19089375,0.000014511104],"about_ca_topic_score_codex":0.004295364,"about_ca_topic_score_gemma":0.0052403775,"teacher_disagreement_score":0.07456341,"about_ca_system_score_codex":0.0042091915,"about_ca_system_score_gemma":0.0041701216,"threshold_uncertainty_score":0.24943948},"labels":[],"label_agreement":null},{"id":"W2911554803","doi":"10.1287/mksc.2018.1126","title":"Sensor Data and Behavioral Tracking: Does Usage-Based Auto Insurance Benefit Drivers?","year":2019,"lang":"en","type":"article","venue":"Marketing Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Tracking (education); Computer science; Business; Actuarial science; Econometrics; Marketing; Economics; Psychology","score_opus":0.022223301618739404,"score_gpt":0.26866240131494623,"score_spread":0.24643909969620684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911554803","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9950865,0.00039829235,0.0008558969,0.0009969857,0.000018548748,0.000016920168,0.0006471597,0.0000073329165,0.0019723193],"genre_scores_gemma":[0.9989059,0.00019231693,0.00019307238,0.00006185807,0.00002061675,0.0000047526455,0.00022204107,0.000001220799,0.00039816],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99960214,0.00015519063,0.000021513615,0.00008900518,0.000053400843,0.000078718076],"domain_scores_gemma":[0.9954796,0.0025423863,0.0012851985,0.00015729283,0.0002917637,0.00024367752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011078703,0.00027515946,0.0002965497,0.0005935271,0.00022753616,0.0012613252,0.00039344054,0.0010337465,0.002153044],"category_scores_gemma":[0.0073111304,0.0001575193,0.00040694533,0.00083766645,0.00026390827,0.0009217564,0.00036911076,0.0005656675,0.00033257986],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023154635,0.00028527877,0.9832888,0.00003019918,0.00017191464,0.00005966666,0.000055810116,0.0032202934,0.00032925725,0.0005118224,0.0003919282,0.011423445],"study_design_scores_gemma":[0.00003162894,0.00040224844,0.92680615,0.00004712159,0.00040449767,0.00011944836,0.00065435393,0.06660775,0.0008828956,0.0020553041,0.0019677193,0.000020712285],"about_ca_topic_score_codex":0.011824354,"about_ca_topic_score_gemma":0.015770426,"teacher_disagreement_score":0.011824354,"about_ca_system_score_codex":0.00044609673,"about_ca_system_score_gemma":0.0004345002,"threshold_uncertainty_score":0.023511052},"labels":[],"label_agreement":null},{"id":"W2912416526","doi":"10.26411/83-1734-2015-3-39-1-18","title":"Car-sharing development – current state and perspective","year":2018,"lang":"en","type":"article","venue":"Logistics and Transport","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Car sharing; Perspective (graphical); Process (computing); Business; State (computer science); Transport engineering; Engineering; Architectural engineering; Telecommunications; Computer science","score_opus":0.025365729799986348,"score_gpt":0.25909594007590436,"score_spread":0.233730210275918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912416526","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037264656,0.6657389,0.006217387,0.053068597,0.0015270852,0.000037757385,0.00051805703,0.00013022927,0.23549734],"genre_scores_gemma":[0.4043714,0.5764816,0.0029545308,0.003075392,0.0008745357,0.00002960431,0.00040349286,0.000028685658,0.011780786],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99922216,0.00018724945,0.00006052882,0.00016374968,0.00019459872,0.00017172721],"domain_scores_gemma":[0.99789053,0.0007257906,0.00032511723,0.00008149718,0.00068267214,0.00029432742],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016798897,0.00031619475,0.00025419588,0.0014732231,0.00086888915,0.004218876,0.00087315385,0.0015125581,0.008799772],"category_scores_gemma":[0.002023058,0.0001808366,0.00026970074,0.002919541,0.0018519599,0.005498563,0.0015068974,0.0015574552,0.0012458777],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012242865,0.00021254562,0.0070635146,0.0028933769,0.000024375064,0.00032412118,0.0012414008,0.002556388,0.0005880873,0.34655035,0.023115044,0.6153084],"study_design_scores_gemma":[0.0000064065616,0.00032821574,0.011073992,0.004064642,0.0000367444,0.0008910057,0.007189606,0.0013686401,0.0018431983,0.030889072,0.94225407,0.000054379434],"about_ca_topic_score_codex":0.0058770333,"about_ca_topic_score_gemma":0.0058927275,"teacher_disagreement_score":0.008799772,"about_ca_system_score_codex":0.0041268854,"about_ca_system_score_gemma":0.0050917924,"threshold_uncertainty_score":0.02994281},"labels":[],"label_agreement":null},{"id":"W2912502253","doi":"","title":"Louer une voiture au Canada","year":2020,"lang":"fr","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Humanities; Art","score_opus":0.009397677693910426,"score_gpt":0.1862103875435138,"score_spread":0.17681270984960337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912502253","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13744536,0.027411787,0.006755749,0.058628242,0.008212342,0.0003748876,0.007082406,0.0020347638,0.75205445],"genre_scores_gemma":[0.12815617,0.0057301056,0.0031339964,0.0021867263,0.0005586933,0.00012356152,0.0010196947,0.00024365736,0.8588474],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9967483,0.000296475,0.000078458914,0.00039856485,0.001422438,0.0010558089],"domain_scores_gemma":[0.99764353,0.00036722046,0.0000960139,0.0001162082,0.0009824298,0.0007945487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014392883,0.001625997,0.0010840048,0.0019435403,0.010188596,0.008665588,0.0011029977,0.0041713775,0.10577014],"category_scores_gemma":[0.004168773,0.00062445033,0.0019400324,0.0022589045,0.0022128914,0.0017781953,0.0022078813,0.006136077,0.011351606],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016336498,0.0006313951,0.02962709,0.0010498216,0.0004055456,0.0062509878,0.0043125334,0.007137737,0.011735399,0.18838242,0.36944988,0.3793836],"study_design_scores_gemma":[0.00009886766,0.00006546961,0.025161734,0.00026688568,0.00002495693,0.00032652085,0.001353913,0.00081987045,0.0012734589,0.0012714629,0.9692805,0.00005640793],"about_ca_topic_score_codex":0.963074,"about_ca_topic_score_gemma":0.97012275,"teacher_disagreement_score":0.10577014,"about_ca_system_score_codex":0.05478727,"about_ca_system_score_gemma":0.06858978,"threshold_uncertainty_score":0.3975113},"labels":[],"label_agreement":null},{"id":"W2912571273","doi":"","title":"Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems","year":2015,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Track (disk drive); Autonomous agent; Robotics; Operations research; Computer science; Library science; Artificial intelligence; Engineering; Robot","score_opus":0.05825585305266649,"score_gpt":0.2714410652857452,"score_spread":0.21318521223307868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912571273","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01497904,0.1130006,0.23702002,0.027660897,0.10603276,0.00095066155,0.0023440584,0.0052380767,0.4927739],"genre_scores_gemma":[0.14652763,0.0998941,0.12161448,0.008316478,0.02371245,0.001407928,0.013670263,0.0013750943,0.58348155],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99817014,0.0005198787,0.0001919899,0.00032422945,0.0006501943,0.00014362356],"domain_scores_gemma":[0.9976808,0.0006369413,0.00014495195,0.0003315465,0.00083295006,0.00037272938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025264386,0.0012776708,0.0016242709,0.0010706149,0.0010719963,0.006821173,0.0018458755,0.0021885773,0.06472136],"category_scores_gemma":[0.0052615735,0.0003606,0.0008226928,0.0008435718,0.0012296331,0.003500342,0.0026143144,0.0026492681,0.028905796],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021281595,0.00020974784,0.0010384865,0.0009539218,0.00014560732,0.00045992338,0.00056769454,0.003515474,0.0030332606,0.04647408,0.5755404,0.36784858],"study_design_scores_gemma":[0.000014290914,0.000045969537,0.00055019406,0.0002313177,0.00003957572,0.0002161164,0.00017605176,0.004099137,0.000537779,0.011779924,0.98228604,0.000023582505],"about_ca_topic_score_codex":0.00229088,"about_ca_topic_score_gemma":0.0020665172,"teacher_disagreement_score":0.06472136,"about_ca_system_score_codex":0.0010335713,"about_ca_system_score_gemma":0.0028729555,"threshold_uncertainty_score":0.21651453},"labels":[],"label_agreement":null},{"id":"W2912586992","doi":"10.3968/10723","title":"The Implementation and Welfare Effect of Vehicle Quantity Regulation Policy: A Case Study of Beijing Vehicle Quota System","year":2018,"lang":"en","type":"article","venue":"Cross-cultural communication","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Beijing; License; Welfare; Control (management); Business; Traffic congestion; Public transport; Public policy; Government (linguistics); Transport engineering; Intervention (counseling); Public economics; Policy analysis; Economics; Economic growth; Engineering; Public administration; Computer science; Market economy; China; Political science","score_opus":0.017361659908771414,"score_gpt":0.3540928601859925,"score_spread":0.3367312002772211,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912586992","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9864478,0.0001693634,0.0021665068,0.0006646464,0.0000156806,0.0001109952,0.00009046396,0.000021753774,0.010312887],"genre_scores_gemma":[0.9973362,0.0001054786,0.0006156686,0.00004307513,0.000006337951,0.000047041678,0.00004030682,0.000005108671,0.0018008437],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9974734,0.0014163081,0.00006554928,0.00016727329,0.00022792685,0.00064953545],"domain_scores_gemma":[0.9962255,0.0022837154,0.00047805632,0.00019128718,0.00052383484,0.00029768838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003094116,0.00059672166,0.00063971616,0.00092769077,0.0015004212,0.0017064429,0.0012464818,0.0020492326,0.004102272],"category_scores_gemma":[0.0039930004,0.00030443503,0.0009957312,0.001014919,0.0018602349,0.0022054287,0.0016445552,0.0017041261,0.00023432856],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024156047,0.008002303,0.2185439,0.000990743,0.00077493506,0.017422775,0.007488709,0.4702957,0.012811147,0.18289241,0.008427351,0.069934435],"study_design_scores_gemma":[0.0009628208,0.0036741034,0.16773316,0.00017164601,0.00079910975,0.00056926825,0.031375695,0.7296745,0.010253578,0.039869376,0.014623833,0.00029294813],"about_ca_topic_score_codex":0.05397255,"about_ca_topic_score_gemma":0.03951019,"teacher_disagreement_score":0.05397255,"about_ca_system_score_codex":0.0058205365,"about_ca_system_score_gemma":0.002925587,"threshold_uncertainty_score":0.10731679},"labels":[],"label_agreement":null},{"id":"W2913357448","doi":"10.26411/83-1734-2015-4-40-17-18","title":"Electric-Car-Sharing in Urban Logistics – The Analysis of Implementation and Maintenance","year":2018,"lang":"en","type":"article","venue":"Logistics and Transport","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Car sharing; Sustainable transport; Business; Sharing economy; Renting; Transport engineering; Strengths and weaknesses; City logistics; Environmental economics; Sustainable development; Process management; Sustainability; Marketing; Computer science; Engineering; Economics","score_opus":0.01939384407924822,"score_gpt":0.2666142345444116,"score_spread":0.24722039046516336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913357448","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93268675,0.00064211973,0.012681875,0.0024021545,0.000015970452,0.00021085954,0.00018468374,0.000031948355,0.05114365],"genre_scores_gemma":[0.9932532,0.0002853777,0.0018671822,0.00004899513,0.0000070270185,0.00006494968,0.000074959076,0.000008127691,0.0043902732],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9970548,0.00134022,0.00013014564,0.00016477828,0.0006991442,0.00061089924],"domain_scores_gemma":[0.990655,0.004575919,0.0017260931,0.0006103501,0.0021195277,0.00031307072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036764804,0.00018981604,0.00024872454,0.0013476055,0.0006108554,0.0028403588,0.00093070447,0.00068474346,0.0039006264],"category_scores_gemma":[0.00983577,0.00024072203,0.00044982156,0.0026161813,0.00166805,0.0032071613,0.0015644594,0.000752147,0.00034965252],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045153234,0.0011363203,0.26061994,0.0009900205,0.00021091559,0.0010054427,0.01483028,0.07198735,0.002705018,0.35264856,0.004169909,0.2892447],"study_design_scores_gemma":[0.00007932242,0.0018092325,0.6436918,0.0010599951,0.00032964884,0.00063853833,0.068732135,0.1161896,0.0073802923,0.07049276,0.0894238,0.00017290533],"about_ca_topic_score_codex":0.011421994,"about_ca_topic_score_gemma":0.0072486955,"teacher_disagreement_score":0.011421994,"about_ca_system_score_codex":0.004369197,"about_ca_system_score_gemma":0.0037366236,"threshold_uncertainty_score":0.03170091},"labels":[],"label_agreement":null},{"id":"W2913510440","doi":"10.4018/978-1-5225-7949-6.ch008","title":"Who Wants an Automated Vehicle?","year":2019,"lang":"en","type":"book-chapter","venue":"Advances in human and social aspects of technology book series","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Electrification; Software deployment; Emerging technologies; Automation; Business; Computer security; Political science; Internet privacy; Engineering; Computer science; Electricity","score_opus":0.0071705866816448955,"score_gpt":0.2536631626723182,"score_spread":0.2464925759906733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913510440","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005068521,0.011125206,0.001310564,0.049010262,0.0033752234,0.000023278857,0.00010568128,0.0000841422,0.92989707],"genre_scores_gemma":[0.10848394,0.017409598,0.0012429444,0.011916072,0.0014931394,0.00004850531,0.0002546084,0.000098781115,0.8590524],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992205,0.00018151855,0.000016201624,0.00015570842,0.00026522306,0.0001607926],"domain_scores_gemma":[0.99953115,0.00017844244,0.000026018086,0.000023900186,0.00013721091,0.00010327032],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078549,0.00041714136,0.0002866788,0.0005680732,0.0028173644,0.0059178704,0.0006999272,0.0022960487,0.035781335],"category_scores_gemma":[0.0018767258,0.00024337716,0.00022338952,0.0007588707,0.0020733005,0.007857108,0.0010823373,0.0019889532,0.013411209],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002346524,0.00004979933,0.0018039721,0.00019534916,0.0000060656316,0.00032115832,0.005408738,0.00018401232,0.00022816753,0.37632194,0.47814345,0.13731398],"study_design_scores_gemma":[0.0000019299878,0.000009388127,0.0005338176,0.00013714304,0.0000022513827,0.00021208702,0.0048920615,0.00017104961,0.00004541913,0.01800838,0.9759797,0.0000067765463],"about_ca_topic_score_codex":0.008580174,"about_ca_topic_score_gemma":0.0135389045,"teacher_disagreement_score":0.035781335,"about_ca_system_score_codex":0.0024911952,"about_ca_system_score_gemma":0.002487701,"threshold_uncertainty_score":0.11970043},"labels":[],"label_agreement":null},{"id":"W2913564011","doi":"","title":"Proceedings of the 16th international conference on Intelligent user interfaces","year":2011,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; User interface; Presentation (obstetrics); World Wide Web; Relevance (law); Variety (cybernetics); Personalization; Interfacing; Artificial intelligence; Political science","score_opus":0.057764445167113494,"score_gpt":0.24067439166543061,"score_spread":0.18290994649831713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913564011","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018475305,0.17005873,0.23983304,0.013900268,0.096400775,0.002147248,0.0041468567,0.0152939055,0.43974388],"genre_scores_gemma":[0.10125474,0.08493516,0.13115555,0.009457937,0.015040339,0.0026687796,0.017802766,0.0027775036,0.63490725],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966888,0.0010017415,0.00040354766,0.00051250774,0.0011519103,0.00024154912],"domain_scores_gemma":[0.9964742,0.0011535228,0.000119096614,0.000465012,0.0014537704,0.00033439652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003181032,0.0022540854,0.0024945661,0.0015416001,0.0008265604,0.006582621,0.0021551924,0.0030461983,0.1203346],"category_scores_gemma":[0.0080370605,0.00050502794,0.0011573116,0.0011772419,0.0011177548,0.00502482,0.0029218046,0.0034812533,0.07557856],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030077223,0.00021251237,0.0009854833,0.0010628767,0.00015940063,0.00029864683,0.00047389284,0.00039203954,0.005207137,0.0054767462,0.4841271,0.5013034],"study_design_scores_gemma":[0.000033563345,0.00015954071,0.0018472847,0.0005333408,0.000085253676,0.00049423386,0.00026689647,0.0032918537,0.0011432751,0.004219311,0.987877,0.000048506776],"about_ca_topic_score_codex":0.001547167,"about_ca_topic_score_gemma":0.0013127751,"teacher_disagreement_score":0.1203346,"about_ca_system_score_codex":0.0005775446,"about_ca_system_score_gemma":0.0011774629,"threshold_uncertainty_score":0.40255934},"labels":[],"label_agreement":null},{"id":"W2914407935","doi":"10.4018/ijdsst.2019040105","title":"A Decision Support System for On-Demand Goods Delivery Using Shared Autonomous Electric Vehicles","year":2019,"lang":"en","type":"article","venue":"International Journal of Decision Support System Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Sizing; Computer science; Decision support system; Strategic planning; Operations research; Environmental economics; Business; Process management; Marketing; Artificial intelligence; Engineering; Economics","score_opus":0.014872778090957701,"score_gpt":0.27510909307045883,"score_spread":0.2602363149795011,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914407935","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.051503833,0.00012968252,0.93813574,0.00041610282,0.00010798728,0.00026627508,0.00040305787,0.0040592477,0.0049780854],"genre_scores_gemma":[0.8514368,0.0001607825,0.1446666,0.00013121373,0.000040987947,0.00031006717,0.000624794,0.000060991828,0.0025677395],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99950147,0.00014087351,0.000058229212,0.00010264016,0.00014213202,0.000054637207],"domain_scores_gemma":[0.9992028,0.00031634807,0.0000946312,0.00006329429,0.0002420291,0.00008100198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009114497,0.0006546748,0.000594261,0.0007668224,0.00066349463,0.0013140035,0.0009802791,0.00073938834,0.0040731966],"category_scores_gemma":[0.0017116324,0.00023504798,0.00043261645,0.00048808436,0.0002760289,0.0009319267,0.0009612133,0.00069922983,0.00070852635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006183371,0.00041580066,0.0038482554,0.00023374984,0.00010383544,0.0006673628,0.00033077996,0.6887036,0.015309259,0.022260029,0.0074666,0.26004237],"study_design_scores_gemma":[0.00006244613,0.00012199373,0.00031851247,0.00001589543,0.00002361686,0.000057066238,0.00006515578,0.9874844,0.0030840614,0.0033530896,0.0053981594,0.00001571132],"about_ca_topic_score_codex":0.0036532746,"about_ca_topic_score_gemma":0.0025305673,"teacher_disagreement_score":0.0040731966,"about_ca_system_score_codex":0.000703375,"about_ca_system_score_gemma":0.0012867147,"threshold_uncertainty_score":0.013626218},"labels":[],"label_agreement":null},{"id":"W2914539483","doi":"10.11575/prism/32041","title":"Evaluating For-Profit Ridesharing Regulations in Canada","year":2017,"lang":"en","type":"dissertation","venue":"Open MIND","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Profit (economics); Transport engineering; Engineering; Economics; Microeconomics","score_opus":0.10951245036971408,"score_gpt":0.3875878262364174,"score_spread":0.27807537586670333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914539483","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9064877,0.0025808003,0.0019675596,0.0042450535,0.00017221298,0.0026174588,0.010348632,0.00017340931,0.07140713],"genre_scores_gemma":[0.97119427,0.001278157,0.0037485207,0.0017123101,0.000034300116,0.00054780365,0.0063726977,0.0000495368,0.015062497],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.97791004,0.0021657138,0.00083543337,0.0014885437,0.012570372,0.0050299573],"domain_scores_gemma":[0.8984431,0.021250417,0.0061203516,0.0020477397,0.06654778,0.005590553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014504451,0.001046308,0.0010911074,0.005809862,0.009589822,0.008146422,0.0042032595,0.0026278507,0.0057839933],"category_scores_gemma":[0.050223928,0.00078597176,0.0016805569,0.009921236,0.003664636,0.002050568,0.0019810088,0.0028244387,0.0005442695],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034428523,0.006165766,0.62262064,0.0017598334,0.001513297,0.0015068969,0.01112961,0.053525012,0.0025373485,0.071120724,0.10078586,0.12389228],"study_design_scores_gemma":[0.0008979039,0.0018396648,0.77053845,0.00075785426,0.0012880991,0.00013790578,0.03165128,0.06385655,0.0030292657,0.003676592,0.121618174,0.0007082968],"about_ca_topic_score_codex":0.9979231,"about_ca_topic_score_gemma":0.9986203,"teacher_disagreement_score":0.30465975,"about_ca_system_score_codex":0.30465975,"about_ca_system_score_gemma":0.31003916,"threshold_uncertainty_score":0.80649614},"labels":[],"label_agreement":null},{"id":"W2914551013","doi":"","title":"Proceedings of the Agent-Directed Simulation Symposium","year":2013,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Presentation (obstetrics); Honor; Privilege (computing); Computer science; Panel discussion; Work (physics); Operations research; Library science; Engineering; Internet privacy; Medicine; Computer security; Business","score_opus":0.008144127855413463,"score_gpt":0.19967415179429382,"score_spread":0.19153002393888036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914551013","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01815871,0.059995644,0.37237686,0.039741978,0.0682771,0.00031056933,0.002480723,0.0054519437,0.4332065],"genre_scores_gemma":[0.22026356,0.04725174,0.13479225,0.0029294754,0.008629278,0.00058151747,0.00918342,0.0024890357,0.5738798],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925727,0.00025277428,0.000051167714,0.00011194842,0.00026516477,0.00006158111],"domain_scores_gemma":[0.99859685,0.00036004942,0.000041358424,0.00023019924,0.00046232715,0.0003092371],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001932328,0.0010364293,0.0008890523,0.0006208204,0.00082588254,0.0035047086,0.0011948335,0.0012271717,0.04694786],"category_scores_gemma":[0.0027443497,0.0004946702,0.0010109041,0.00048271028,0.00056684704,0.001667279,0.0019294444,0.0020057466,0.014060665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035105986,0.0002078993,0.0016680545,0.00034361865,0.00019093785,0.0002847388,0.0002936568,0.0369219,0.002452419,0.059233338,0.7004245,0.1976279],"study_design_scores_gemma":[0.00004050291,0.00005913186,0.00055322197,0.00020053369,0.000057526016,0.00014757251,0.000118699696,0.036515698,0.0010014075,0.021920834,0.93936116,0.000023700488],"about_ca_topic_score_codex":0.0032578057,"about_ca_topic_score_gemma":0.0039267773,"teacher_disagreement_score":0.04694786,"about_ca_system_score_codex":0.0010881833,"about_ca_system_score_gemma":0.0023726376,"threshold_uncertainty_score":0.15705627},"labels":[],"label_agreement":null},{"id":"W2914986926","doi":"10.1177/0361198118825465","title":"Exploring Service Usage and Activity Space Evolution in a Free-Floating Carsharing Service","year":2019,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"TRIPS architecture; Service (business); Space (punctuation); Business; Computer science; Free space; Living space; Telecommunications; Transport engineering; Marketing; Demographic economics; Engineering; Economics; Physics","score_opus":0.14069116106788931,"score_gpt":0.3406481450921918,"score_spread":0.1999569840243025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914986926","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981681,0.000018106308,0.0012022131,0.000020358691,0.0000018353496,0.000009697275,0.00017655354,0.000011551866,0.00039165816],"genre_scores_gemma":[0.9982942,0.00001834942,0.0011381881,0.0000046980444,0.0000025486179,0.000008617555,0.00030981837,0.000003037309,0.00022049279],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995049,0.00014218553,0.000025515932,0.00012224927,0.000119880526,0.000085273125],"domain_scores_gemma":[0.99845815,0.00066415133,0.00030193405,0.0001458211,0.0002127382,0.00021723987],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006234822,0.00021770273,0.00025893844,0.0009482138,0.00030693,0.00091092923,0.0003963008,0.00037838673,0.0011611184],"category_scores_gemma":[0.0029101395,0.00012152833,0.00026198442,0.0012995884,0.00032928953,0.0011358038,0.00056403974,0.00031754147,0.0003912661],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047341498,0.00041998044,0.93684673,0.000093555194,0.00008417226,0.00021370867,0.0027167213,0.011082262,0.0063541466,0.0006597051,0.0003946145,0.04066109],"study_design_scores_gemma":[0.000006550098,0.0005185781,0.91661507,0.000016671065,0.00004119122,0.00023673142,0.006208243,0.07251507,0.0019542286,0.00054637896,0.0013167302,0.000024686453],"about_ca_topic_score_codex":0.009071109,"about_ca_topic_score_gemma":0.011422861,"teacher_disagreement_score":0.009071109,"about_ca_system_score_codex":0.00052192126,"about_ca_system_score_gemma":0.00030910803,"threshold_uncertainty_score":0.018036604},"labels":[],"label_agreement":null},{"id":"W2916069659","doi":"10.36939/cjur/vol27no2/art132","title":"From Renegade to Regulated: The Digital Platform Economy, Ride-hailing and the Case of Toronto","year":2018,"lang":"en","type":"article","venue":"Canadian journal of urban research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Humanities; Political science; Corporate governance; Art; Economics; Management","score_opus":0.03300819227073659,"score_gpt":0.282215862618264,"score_spread":0.2492076703475274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916069659","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7338138,0.004753662,0.0017576226,0.021851787,0.00011425823,0.00006363541,0.0002507395,0.00003165676,0.23736282],"genre_scores_gemma":[0.9878941,0.00078178843,0.00016216491,0.0003754494,0.000014969387,0.000016233458,0.00003269574,0.000008526388,0.0107139805],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.99659604,0.0010241634,0.00008136755,0.00025021323,0.0004885878,0.0015595367],"domain_scores_gemma":[0.9980647,0.0006474258,0.00029930501,0.00021015742,0.00032374501,0.00045461155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014617314,0.00027760584,0.00024995094,0.0010682096,0.024288027,0.008810472,0.0013867649,0.0023009607,0.004557788],"category_scores_gemma":[0.002950985,0.00031710797,0.0003923665,0.0039897286,0.024620352,0.002677287,0.0051363013,0.00183312,0.00023055616],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047820755,0.000023010167,0.0140883075,0.00016579317,0.000020698006,0.0041072574,0.26055595,0.0016647946,0.0005666718,0.6987364,0.009159733,0.010863629],"study_design_scores_gemma":[0.00003103358,0.000040347008,0.040030885,0.00036692168,0.00007371287,0.0005937319,0.5248991,0.0013443887,0.00071943516,0.020036465,0.41174614,0.000117803065],"about_ca_topic_score_codex":0.9630559,"about_ca_topic_score_gemma":0.98380184,"teacher_disagreement_score":0.11885955,"about_ca_system_score_codex":0.11885955,"about_ca_system_score_gemma":0.0423058,"threshold_uncertainty_score":0.86239046},"labels":[],"label_agreement":null},{"id":"W2916496389","doi":"10.1155/2019/7648735","title":"Efficiency of Semi-Autonomous and Fully Autonomous Bus Services in Trunk-and-Branches Networks","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":70,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"China Scholarship Council","keywords":"Interurban; Automation; Public transport; Operating cost; Computer science; Operational costs; Capital cost; Transport engineering; Operations research; Engineering; Electrical engineering","score_opus":0.003330135711497246,"score_gpt":0.19927717809716308,"score_spread":0.19594704238566585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916496389","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94764215,0.00025089915,0.045133956,0.00015526726,0.000008283783,0.000022442622,0.00018580719,0.00007039041,0.006530943],"genre_scores_gemma":[0.9980367,0.000060265204,0.0012495907,0.0000050763947,0.0000014660899,0.000005783316,0.000041371266,0.000008424503,0.0005913647],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994254,0.00022336171,0.000016486088,0.000051943978,0.00012154092,0.00016132604],"domain_scores_gemma":[0.99864525,0.0008149172,0.00018617723,0.00010789692,0.00017716327,0.00006866225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069260574,0.00036890322,0.00042005375,0.00055317447,0.00027899753,0.0009604691,0.0006763777,0.0005274113,0.0018426601],"category_scores_gemma":[0.002317342,0.00021512063,0.00041981696,0.0007246873,0.0005928012,0.0015442461,0.0004977958,0.00024352243,0.00013752135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007708762,0.000019296182,0.0018231776,0.00001851109,0.000010200911,0.00004331868,0.000022713659,0.98639756,0.000839644,0.0067448863,0.00018835107,0.003815206],"study_design_scores_gemma":[0.0000028462891,0.000028897515,0.0010666966,0.0000027207857,0.0000046184723,0.000016135631,0.00004840083,0.9963129,0.0003297559,0.0020641354,0.0001195395,0.0000034859002],"about_ca_topic_score_codex":0.011632856,"about_ca_topic_score_gemma":0.010170238,"teacher_disagreement_score":0.011632856,"about_ca_system_score_codex":0.0016137002,"about_ca_system_score_gemma":0.0007298225,"threshold_uncertainty_score":0.023130298},"labels":[],"label_agreement":null},{"id":"W2916809502","doi":"10.1109/glocom.2018.8647545","title":"Matching-Game for User-Fog Assignment","year":2018,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Matching (statistics); Human–computer interaction; Mathematics","score_opus":0.013306681863750497,"score_gpt":0.24639657689752778,"score_spread":0.23308989503377728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916809502","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043465164,0.00016272075,0.9442,0.0006206506,0.00013658234,0.0003231919,0.00017623698,0.00018282035,0.010732681],"genre_scores_gemma":[0.931425,0.00017134758,0.057528555,0.00032790314,0.00008065177,0.00034259845,0.00010246552,0.00004827958,0.00997325],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99726677,0.001216082,0.00010731502,0.00047334097,0.00032713675,0.00060931954],"domain_scores_gemma":[0.9970836,0.0017115625,0.00023268115,0.00014201176,0.00032360666,0.00050641823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025085588,0.0015618115,0.0018408193,0.00065306044,0.0010629285,0.0017925721,0.0028919836,0.0025685471,0.008492194],"category_scores_gemma":[0.006482475,0.00055365317,0.0011945104,0.00082533224,0.0015605058,0.0027992013,0.002393642,0.0026587166,0.0007333932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007668067,0.00038682172,0.0015297089,0.00024968336,0.00016736638,0.0006296296,0.000543362,0.7193653,0.0055322796,0.2332717,0.0053937803,0.032163613],"study_design_scores_gemma":[0.00004228795,0.000085067026,0.00013397288,0.000008360777,0.000019946552,0.00006613197,0.000051678642,0.96338177,0.00036953652,0.034773402,0.0010495544,0.000018233355],"about_ca_topic_score_codex":0.005070796,"about_ca_topic_score_gemma":0.00433452,"teacher_disagreement_score":0.008492194,"about_ca_system_score_codex":0.0023086832,"about_ca_system_score_gemma":0.0022779265,"threshold_uncertainty_score":0.028409243},"labels":[],"label_agreement":null},{"id":"W2921339928","doi":"10.1155/2019/2867247","title":"Drivers’ Perceptions of Smartphone Applications for Real-Time Route Planning and Distracted Driving Prevention","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Qatar Foundation","keywords":"Distracted driving; SAFER; Distraction; Smartphone application; Perception; Transport engineering; Computer security; Real-time data; Installation; Internet privacy; Engineering; Computer science; Business; Multimedia; Psychology; World Wide Web","score_opus":0.005648121736415206,"score_gpt":0.24889341093122153,"score_spread":0.2432452891948063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2921339928","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969523,0.00017186685,0.00014931694,0.00027579206,0.0000067459564,0.000014502434,0.000025899184,0.000003586952,0.0023999352],"genre_scores_gemma":[0.9988707,0.00019143053,0.00022142848,0.00009708502,0.0000052394844,0.000007448968,0.000020713831,0.0000017009176,0.0005841496],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992637,0.0002923487,0.00005389286,0.00004243562,0.0002329083,0.000114837516],"domain_scores_gemma":[0.9969903,0.0012245933,0.00070591044,0.00006755385,0.0006930403,0.00031858258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012304187,0.00019600167,0.00011664696,0.00037485402,0.0005077767,0.0016233657,0.00018158875,0.00051801157,0.002525421],"category_scores_gemma":[0.0047765095,0.00015278888,0.00029421342,0.00022667048,0.00037021027,0.0008302725,0.0005136531,0.00041654272,0.0003246676],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052708434,0.00087881624,0.8275111,0.00053489173,0.00013760992,0.0015157686,0.08933148,0.0007193555,0.009908327,0.0019953153,0.0029906933,0.06394966],"study_design_scores_gemma":[0.000036163823,0.0012205176,0.7859158,0.00027182416,0.00015387173,0.0013922919,0.18353894,0.0030775054,0.0018281,0.0003578256,0.022100642,0.000106522144],"about_ca_topic_score_codex":0.009646646,"about_ca_topic_score_gemma":0.012684463,"teacher_disagreement_score":0.009646646,"about_ca_system_score_codex":0.0005344432,"about_ca_system_score_gemma":0.0005520244,"threshold_uncertainty_score":0.019181013},"labels":[],"label_agreement":null},{"id":"W2924854431","doi":"10.1037/cap0000175","title":"Cellphone use and young drivers.","year":2019,"lang":"en","type":"article","venue":"Canadian Psychology/Psychologie canadienne","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Moncton; University of Sudbury; McMaster University; Laurentian University","funders":"Canada Foundation for Innovation","keywords":"Internet privacy; Computer science","score_opus":0.01951104301090927,"score_gpt":0.22559106248864785,"score_spread":0.20608001947773857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2924854431","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9917042,0.0014689362,0.000047272428,0.00037595743,0.00006695439,0.000020629059,0.0006518585,0.0000051114625,0.005659126],"genre_scores_gemma":[0.99456376,0.001177081,0.000033194683,0.0001281779,0.000020431957,0.000010841194,0.00027218225,0.000002832051,0.0037915504],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99961674,0.000050288712,0.000026109452,0.00003623708,0.00016584335,0.000104739236],"domain_scores_gemma":[0.99812,0.00027720685,0.0004712058,0.00004660984,0.0004638518,0.0006211517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040152084,0.0001229811,0.0002067199,0.0007683698,0.00084904506,0.0014146091,0.00037440137,0.0010224155,0.0061475593],"category_scores_gemma":[0.0030640373,0.0002193063,0.0003975338,0.00068930304,0.00024094064,0.00069446565,0.00056634215,0.00067035883,0.001120269],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007842759,0.00015425564,0.9904766,0.00003623639,0.000020840487,0.00023241296,0.0016960824,0.000021520682,0.00013056533,0.000104590414,0.0009744702,0.00607385],"study_design_scores_gemma":[0.0000040413393,0.0001648788,0.98942345,0.00006533803,0.00003536932,0.0003487436,0.0063231667,0.00007417622,0.000081929444,0.000053176263,0.0034143275,0.000011327745],"about_ca_topic_score_codex":0.09504971,"about_ca_topic_score_gemma":0.14813021,"teacher_disagreement_score":0.09504971,"about_ca_system_score_codex":0.0007141131,"about_ca_system_score_gemma":0.0011128039,"threshold_uncertainty_score":0.18899292},"labels":[],"label_agreement":null},{"id":"W2927807022","doi":"10.5772/intechopen.84287","title":"Connected Autonomous Electric Vehicles as Enablers for Low-Carbon Future","year":2019,"lang":"en","type":"book-chapter","venue":"IntechOpen eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Government of Ontario","keywords":"Greenhouse gas; Electrification; Renewable energy; Fossil fuel; Sustainable transport; Climate change; Market penetration; Climate change mitigation; Global warming; Environmental science; Natural resource economics; Environmental economics; Business; Environmental engineering; Engineering; Electricity; Waste management; Sustainability; Ecology","score_opus":0.009726265783071118,"score_gpt":0.20973832203646187,"score_spread":0.20001205625339075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2927807022","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00520526,0.14021139,0.016429288,0.0030359684,0.00519156,0.000113073576,0.0003352014,0.00063629437,0.828842],"genre_scores_gemma":[0.021311903,0.12545845,0.010213541,0.000960807,0.0009196167,0.00009310933,0.00045572457,0.0001900597,0.8403967],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99987745,0.00001186611,0.0000035238434,0.000022478333,0.00007181215,0.000012839051],"domain_scores_gemma":[0.9999614,0.000011789294,0.0000035956964,0.000003696578,0.000013030608,0.000006565587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009831208,0.00053629733,0.0002356109,0.000653062,0.00041787824,0.00213528,0.00053696433,0.00082584633,0.020648029],"category_scores_gemma":[0.00018269556,0.00023246219,0.000296559,0.0010336102,0.00037528813,0.002618062,0.00091649225,0.0015705895,0.01078205],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004320072,0.00008635633,0.00015033489,0.0014139212,0.000016609773,0.00030726398,0.0006914284,0.0019332317,0.005763228,0.302467,0.19986686,0.48726052],"study_design_scores_gemma":[0.0000013842083,0.000013693382,0.00011552828,0.00020247402,0.0000029509085,0.00013449298,0.00006187122,0.00028281807,0.00039110697,0.010487763,0.9883017,0.000004263699],"about_ca_topic_score_codex":0.00046640926,"about_ca_topic_score_gemma":0.001047957,"teacher_disagreement_score":0.020648029,"about_ca_system_score_codex":0.00059891364,"about_ca_system_score_gemma":0.00043272573,"threshold_uncertainty_score":0.06907457},"labels":[],"label_agreement":null},{"id":"W2929932977","doi":"10.1109/mnet.2019.1800228","title":"Demystifying the Crowd Intelligence in Last Mile Parcel Delivery for Smart Cities","year":2019,"lang":"en","type":"article","venue":"IEEE Network","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; National Science Foundation","keywords":"Last mile (transportation); Computer science; The Internet; Mile; Computer security; Cloud computing; Internet of Things; Smart city; Telecommunications; World Wide Web","score_opus":0.021104812438838248,"score_gpt":0.23467176955305333,"score_spread":0.21356695711421508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2929932977","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16528282,0.006006299,0.77437633,0.005236152,0.0007629103,0.0003294448,0.00033210102,0.003999158,0.0436748],"genre_scores_gemma":[0.9368754,0.0017617304,0.05597142,0.00038120264,0.00013789914,0.000062364306,0.00019144687,0.00012490674,0.00449361],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994259,0.00017503955,0.00002333393,0.000080568534,0.00016257157,0.00013259471],"domain_scores_gemma":[0.9994777,0.00013101673,0.000054814762,0.00009690539,0.00016781651,0.00007186057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000942642,0.00060687575,0.00049026887,0.00087515835,0.0009033095,0.0018404373,0.001179388,0.0009046213,0.0016319676],"category_scores_gemma":[0.0014749118,0.00024523103,0.0003247806,0.00077766535,0.00068061764,0.0030498712,0.002679247,0.0008770796,0.0006087689],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042517224,0.00029562984,0.0068531428,0.00057353085,0.00010915422,0.0010001954,0.0023391834,0.24479753,0.037646946,0.104355566,0.029205503,0.5723985],"study_design_scores_gemma":[0.000028325509,0.00021139649,0.0020435564,0.00009876255,0.00006825956,0.00032076598,0.0021525917,0.84689385,0.014263283,0.034160167,0.09968042,0.00007865759],"about_ca_topic_score_codex":0.006517153,"about_ca_topic_score_gemma":0.006059842,"teacher_disagreement_score":0.006517153,"about_ca_system_score_codex":0.00087591284,"about_ca_system_score_gemma":0.0007920627,"threshold_uncertainty_score":0.012958407},"labels":[],"label_agreement":null},{"id":"W2932453505","doi":"10.1080/01634372.2019.1596184","title":"Assisted-Transport Caregiving and Its Impact Towards Carer-Employees","year":2019,"lang":"en","type":"article","venue":"Journal of Gerontological Social Work","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University","funders":"Canadian Institutes of Health Research","keywords":"Psychology; Nursing; Gerontology; Business; Medicine","score_opus":0.024124541478952124,"score_gpt":0.2878397942735516,"score_spread":0.2637152527945995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2932453505","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9937178,0.001550179,0.00006319068,0.0019257674,0.000033823533,0.000009848637,0.00036794302,0.0000028594222,0.0023285295],"genre_scores_gemma":[0.9980021,0.001106722,0.000075744916,0.00021894286,0.000022872558,0.0000116703995,0.00017436796,0.0000021675726,0.00038541717],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985286,0.0005332338,0.00012857725,0.00010410517,0.00028700204,0.00041854556],"domain_scores_gemma":[0.9947491,0.0010202586,0.0020854422,0.00015296422,0.0008834344,0.0011088478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016130742,0.00025280495,0.00031462387,0.0006166703,0.0015046513,0.0015116186,0.00045841033,0.0004484203,0.0036326628],"category_scores_gemma":[0.008001995,0.00015599099,0.0007843852,0.0008765077,0.0006041177,0.0007804876,0.0022691458,0.0010075945,0.0003399265],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010115837,0.00010018381,0.97795343,0.00007704381,0.000078509736,0.00023738091,0.0052499147,0.000056704295,0.00006315725,0.00017595303,0.0012495896,0.014656896],"study_design_scores_gemma":[0.0000031029015,0.00007461032,0.98153347,0.00017870167,0.000041379913,0.00016917163,0.016492281,0.00009484531,0.000035999936,0.00011494422,0.00125055,0.000010886316],"about_ca_topic_score_codex":0.045218054,"about_ca_topic_score_gemma":0.07519074,"teacher_disagreement_score":0.045218054,"about_ca_system_score_codex":0.0016426321,"about_ca_system_score_gemma":0.0021546183,"threshold_uncertainty_score":0.08990973},"labels":[],"label_agreement":null},{"id":"W2934037410","doi":"10.1177/0361198119837218","title":"Quantifying the Potential Impact of Autonomous Vehicle Adoption on Government Finances","year":2019,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Revenue; Government (linguistics); Business; Government revenue; Tax revenue; Finance; Economic impact analysis; Public economics; Total revenue; Economics","score_opus":0.071173462433277,"score_gpt":0.36442405174876774,"score_spread":0.29325058931549075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2934037410","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9846318,0.0002000703,0.0009873679,0.00055859564,0.000008660846,0.000059226568,0.0026228575,0.00002076274,0.010910682],"genre_scores_gemma":[0.9971636,0.00016708457,0.00046647296,0.000025004802,0.0000038753037,0.000014203961,0.0011325855,0.000002504271,0.0010244946],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99750286,0.00038934435,0.000067514426,0.00013776713,0.0011188431,0.00078369473],"domain_scores_gemma":[0.991288,0.003075327,0.0021052144,0.0002562121,0.0027590964,0.00051626033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025098298,0.0003907279,0.00023692715,0.0015234452,0.00069363485,0.0024676989,0.00069964683,0.0005258056,0.0017146588],"category_scores_gemma":[0.013744674,0.00020746984,0.00059616,0.0029412657,0.0008723397,0.0011007357,0.0008093266,0.0011241308,0.00015249648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022357146,0.00015784979,0.7802702,0.000082364386,0.0001555661,0.00041060685,0.00051465124,0.17341366,0.0008480869,0.010955647,0.0024862771,0.03048144],"study_design_scores_gemma":[0.000018008888,0.00030282408,0.87710136,0.000054048905,0.00014451261,0.000084506035,0.0028051864,0.106488734,0.001521417,0.0021974987,0.009213843,0.00006813356],"about_ca_topic_score_codex":0.7770812,"about_ca_topic_score_gemma":0.81153244,"teacher_disagreement_score":0.7770812,"about_ca_system_score_codex":0.02106092,"about_ca_system_score_gemma":0.013645709,"threshold_uncertainty_score":0.4484632},"labels":[],"label_agreement":null},{"id":"W2937707477","doi":"10.5539/res.v11n2p15","title":"Optimal Pricing and Capacity Under Well-Defined and Well-Known Deterministic Demand Fluctuations","year":2019,"lang":"en","type":"article","venue":"Review of European Studies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Economic shortage; Economics; Revenue; Maximization; Microeconomics; Profit (economics); Finance","score_opus":0.027726191003740904,"score_gpt":0.2659333202735586,"score_spread":0.23820712926981769,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2937707477","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4675318,0.015186994,0.4464419,0.0068053366,0.00037288302,0.000108495995,0.00063314644,0.00020244703,0.062717006],"genre_scores_gemma":[0.9916299,0.0024476745,0.0042089033,0.00007557675,0.00006257656,0.000021658016,0.00003704955,0.00001720396,0.0014994618],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99812454,0.0008952015,0.00005520352,0.00030443232,0.00020002057,0.00042056243],"domain_scores_gemma":[0.99802643,0.0012526157,0.00037670074,0.00008998574,0.0001625675,0.00009176273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017395284,0.000569578,0.00094329834,0.00071461825,0.000509825,0.0031368586,0.0013779051,0.002159701,0.0015718408],"category_scores_gemma":[0.005701835,0.00067459734,0.00084067625,0.0014048859,0.0029867538,0.0036332305,0.0008585083,0.0012771398,0.00015485607],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000064663844,0.00004775371,0.00079716835,0.00012127386,0.00006448888,0.00013652595,0.000053453216,0.7901623,0.00046119367,0.20055175,0.00080224226,0.0067371507],"study_design_scores_gemma":[0.000018808778,0.00006262816,0.0014693455,0.00004802825,0.00003041412,0.00008148039,0.00017562795,0.745568,0.0003937,0.2503997,0.0017135906,0.000038721293],"about_ca_topic_score_codex":0.0070537054,"about_ca_topic_score_gemma":0.0031781574,"teacher_disagreement_score":0.0070537054,"about_ca_system_score_codex":0.004637314,"about_ca_system_score_gemma":0.00218887,"threshold_uncertainty_score":0.033646226},"labels":[],"label_agreement":null},{"id":"W2938352754","doi":"10.1016/j.trpro.2020.03.160","title":"A vehicle routing problem with movement synchronization of drones, sidewalk robots, or foot-walkers","year":2020,"lang":"en","type":"article","venue":"Transportation research procedia","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Drone; Robot; Vehicle routing problem; Metaheuristic; Routing (electronic design automation); Computer science; Synchronization (alternating current); Truck; Transport engineering; Set (abstract data type); Operations research; Simulation; Engineering; Computer network; Artificial intelligence; Automotive engineering","score_opus":0.04794890171061727,"score_gpt":0.2922506684648733,"score_spread":0.24430176675425602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2938352754","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19183727,0.0020073687,0.76822513,0.0019083646,0.00036222528,0.00041460636,0.0018993027,0.00037024595,0.0329756],"genre_scores_gemma":[0.7925188,0.0012122367,0.18178095,0.00024790157,0.00015404572,0.00043994916,0.0012263998,0.0001108326,0.02230883],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921215,0.00030779184,0.00003043451,0.0002536053,0.00007543211,0.000120543715],"domain_scores_gemma":[0.9994392,0.00032529153,0.00009767759,0.000029821733,0.000036030106,0.00007201242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065827416,0.0012413734,0.0012719684,0.0006147725,0.000604015,0.0017050221,0.0013001232,0.0025267224,0.0052012764],"category_scores_gemma":[0.0017330594,0.00069664844,0.0010777618,0.0012973753,0.0006449497,0.001794551,0.0011502863,0.0010686615,0.00047007194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011579797,0.00006558998,0.00031584353,0.00013655712,0.000057254987,0.0002583944,0.00003594401,0.9613001,0.0011313813,0.022131596,0.0018416982,0.012609999],"study_design_scores_gemma":[0.000086727785,0.00013188827,0.00026990502,0.00002048964,0.00002723795,0.00015562496,0.00007493084,0.98031723,0.0004683678,0.013844477,0.0045847027,0.000018383898],"about_ca_topic_score_codex":0.0055037304,"about_ca_topic_score_gemma":0.0033216355,"teacher_disagreement_score":0.0055037304,"about_ca_system_score_codex":0.001124315,"about_ca_system_score_gemma":0.0010786641,"threshold_uncertainty_score":0.017400026},"labels":[],"label_agreement":null},{"id":"W2938847926","doi":"10.1109/vtcfall.2018.8690905","title":"Automated Reservation Mechanism for Charging Connected and Autonomous EVs in Smart Cities","year":2018,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Reservation; Computer science; Wireless; Order (exchange); Transport engineering; Computer network; Business; Telecommunications; Engineering","score_opus":0.021127950633990866,"score_gpt":0.24886754563271046,"score_spread":0.2277395949987196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2938847926","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51131874,0.000329346,0.46888453,0.0002688483,0.00020330424,0.00020194917,0.00017436089,0.006970323,0.011648664],"genre_scores_gemma":[0.9833323,0.00003377884,0.014908409,0.000026135094,0.000009137502,0.000030945164,0.00005289715,0.000027279673,0.0015791367],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997538,0.00007028077,0.000025877567,0.000048280188,0.000048208734,0.000053543477],"domain_scores_gemma":[0.99961686,0.000105591236,0.000044384124,0.00009863063,0.00009733478,0.000037253478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044962845,0.0002261377,0.0002506165,0.00032342138,0.00045042485,0.0006342343,0.0010365507,0.00031537376,0.0020290106],"category_scores_gemma":[0.000646013,0.00021532993,0.00020664993,0.00020249942,0.0003010477,0.0007831066,0.00046017783,0.0002678074,0.00057905266],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026504959,0.0007170069,0.011866421,0.00041502086,0.00015691639,0.0017936347,0.0018162453,0.3829848,0.23013888,0.049465198,0.011745066,0.30625027],"study_design_scores_gemma":[0.00012105795,0.00016612643,0.0012130949,0.000013787429,0.000047198286,0.00018201882,0.00017417953,0.9438098,0.03821586,0.003807489,0.012197008,0.000052318035],"about_ca_topic_score_codex":0.002207335,"about_ca_topic_score_gemma":0.0018218256,"teacher_disagreement_score":0.002207335,"about_ca_system_score_codex":0.00033164676,"about_ca_system_score_gemma":0.0005264688,"threshold_uncertainty_score":0.0067876577},"labels":[],"label_agreement":null},{"id":"W2939263671","doi":"10.1155/2019/3867874","title":"Research on Taxi Pricing Model and Optimization for Carpooling Detour Problem","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Lanzhou Jiaotong University; National Natural Science Foundation of China; Youth Science Foundation of Lanzhou Jiaotong University; Lanzhou University","keywords":"Payment; Computer science; Genetic algorithm; Scheme (mathematics); Value (mathematics); Operations research; Transport engineering; Mathematics; Engineering; Machine learning","score_opus":0.026097371598332267,"score_gpt":0.30376612446747736,"score_spread":0.2776687528691451,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2939263671","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03135469,0.002300122,0.93628836,0.0015441398,0.00020255847,0.00013442428,0.00018822042,0.00013501965,0.027852522],"genre_scores_gemma":[0.8734606,0.005032051,0.096108265,0.0003155171,0.00022730915,0.00040729652,0.00037223988,0.00011340041,0.023963345],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993789,0.0002009586,0.000020460357,0.0001398425,0.00013683565,0.0001228986],"domain_scores_gemma":[0.9996393,0.00016928029,0.000052159332,0.000014726773,0.00008507931,0.000039404797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087383634,0.0011158373,0.001434943,0.00087166415,0.000980769,0.0030454379,0.002176901,0.0021370365,0.00452229],"category_scores_gemma":[0.0015087683,0.0006151478,0.0014586139,0.0016037363,0.0008812258,0.0027090374,0.00090728165,0.002431602,0.00036247514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018325425,0.00003415924,0.0003900438,0.00008695159,0.000016762204,0.0000810321,0.000038592338,0.96173626,0.00030548841,0.029498845,0.0012433659,0.006550279],"study_design_scores_gemma":[0.00000363205,0.000009741465,0.00008235749,0.000008368112,0.000005542643,0.000015599304,0.00002329924,0.99276006,0.00006306864,0.006375849,0.0006459944,0.0000064661103],"about_ca_topic_score_codex":0.023273295,"about_ca_topic_score_gemma":0.008955907,"teacher_disagreement_score":0.023273295,"about_ca_system_score_codex":0.0027275211,"about_ca_system_score_gemma":0.0027039677,"threshold_uncertainty_score":0.046275675},"labels":[],"label_agreement":null},{"id":"W2941926664","doi":"10.1287/trsc.2019.0969","title":"The Commute Trip-Sharing Problem","year":2020,"lang":"en","type":"preprint","venue":"Transportation Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"TRIPS architecture; Pooling; Vehicle routing problem; Computer science; Routing (electronic design automation); Duration (music); Locality; Generalization; Operations research; Set (abstract data type); Transport engineering; Mathematical optimization; Engineering; Computer network; Mathematics; Artificial intelligence","score_opus":0.039509205333722625,"score_gpt":0.280293889707339,"score_spread":0.24078468437361636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2941926664","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34582144,0.0013794041,0.5891397,0.0032237824,0.0003055674,0.0011167421,0.0068327184,0.000926271,0.051254336],"genre_scores_gemma":[0.8697042,0.00070775824,0.108787335,0.00031203806,0.00012504225,0.00052044226,0.004318049,0.00021401278,0.01531117],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989158,0.000351387,0.000055842942,0.00036356604,0.00012935438,0.00018412652],"domain_scores_gemma":[0.9991223,0.00046869306,0.00009363997,0.00010289097,0.00008017904,0.00013228557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000947281,0.0011030461,0.0014925885,0.00060200976,0.0008831628,0.0015620362,0.0017946792,0.0017515537,0.011655983],"category_scores_gemma":[0.0026372995,0.00048969325,0.0010388122,0.0014425472,0.000705535,0.0024994547,0.0015484175,0.0011541129,0.0008627299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003382842,0.00034981442,0.0022311592,0.00040652874,0.00018330869,0.00048611383,0.0002135496,0.85371935,0.0013166622,0.04648821,0.014776873,0.07949009],"study_design_scores_gemma":[0.00013139161,0.0002139429,0.0013479957,0.000041906704,0.00006530244,0.00048224366,0.00056892954,0.87251765,0.0014279309,0.10596148,0.017200567,0.000040685874],"about_ca_topic_score_codex":0.0055922237,"about_ca_topic_score_gemma":0.0033885255,"teacher_disagreement_score":0.011655983,"about_ca_system_score_codex":0.0010697427,"about_ca_system_score_gemma":0.0017109402,"threshold_uncertainty_score":0.03899318},"labels":[],"label_agreement":null},{"id":"W2943524896","doi":"10.1155/2019/9348496","title":"The Impact of Car-Sharing on the Willingness to Postpone a Car Purchase: A Case Study in Hangzhou, China","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Car sharing; Renting; Business; Sharing economy; Car ownership; Work (physics); China; Transport engineering; Advertising; Marketing; Public transport; Computer science; Engineering; Geography","score_opus":0.011643116106243278,"score_gpt":0.2836370056776622,"score_spread":0.2719938895714189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2943524896","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996263,0.0000143217885,0.00006355349,0.000037249494,8.433758e-7,0.000011573652,0.000016477328,9.3693365e-7,0.00022865656],"genre_scores_gemma":[0.9995454,0.000035100587,0.0001160724,0.000008856286,0.0000011047201,0.00000868017,0.000022122469,6.442805e-7,0.0002620221],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991042,0.00033856774,0.000039363207,0.00009373539,0.00010682247,0.00031729753],"domain_scores_gemma":[0.99782264,0.0012288452,0.0002545571,0.000112519716,0.00020312527,0.00037827605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001421841,0.00040954247,0.0003615597,0.00076062564,0.0017220089,0.0008982594,0.0010434923,0.0009461305,0.00231662],"category_scores_gemma":[0.0023774721,0.00027685493,0.00077370775,0.0010354636,0.0010140298,0.00084282097,0.0008852219,0.00070468796,0.00012201218],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006237392,0.0028226655,0.9193139,0.00022437294,0.00021344576,0.01899886,0.017035194,0.01623104,0.003041572,0.0029423244,0.00082912325,0.017723683],"study_design_scores_gemma":[0.00012829727,0.0021881852,0.82888544,0.00007970179,0.00027826006,0.0016824175,0.08954795,0.070643015,0.0028427143,0.0011428525,0.002436837,0.00014434099],"about_ca_topic_score_codex":0.15517531,"about_ca_topic_score_gemma":0.17098439,"teacher_disagreement_score":0.15517531,"about_ca_system_score_codex":0.0052235536,"about_ca_system_score_gemma":0.0029708403,"threshold_uncertainty_score":0.30854422},"labels":[],"label_agreement":null},{"id":"W2945764562","doi":"10.1177/0361198119846094","title":"Who’s Driving Change? Potential to Commute Further using Automated Vehicles among Existing Drivers in Southern Ontario, Canada","year":2019,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"TRIPS architecture; Human multitasking; Work (physics); Transport engineering; Business; Public transport; Demographic economics; Public economics; Engineering; Economics; Psychology","score_opus":0.06997803295397584,"score_gpt":0.32748399960873265,"score_spread":0.2575059666547568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2945764562","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98707694,0.00072308147,0.00015354683,0.0014317662,0.00002965769,0.00006768331,0.004057472,0.000008994977,0.00645099],"genre_scores_gemma":[0.99346465,0.000809681,0.00019375276,0.00027010238,0.000009487884,0.000041272604,0.0015883915,0.000006424828,0.0036162275],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992275,0.000046474946,0.00004852474,0.00013362114,0.00026232927,0.0002815765],"domain_scores_gemma":[0.9974698,0.00014550985,0.00039428234,0.00006982492,0.0012233125,0.0006972461],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068626757,0.00027750502,0.00035581086,0.0010253008,0.0045602983,0.0019031435,0.0012710486,0.00052520575,0.0027980173],"category_scores_gemma":[0.0019434098,0.00032820826,0.00068293134,0.0030506642,0.0009880131,0.0007830521,0.001100081,0.0009414456,0.00029538234],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033116703,0.000034109955,0.9833891,0.000063315194,0.000029985775,0.000111629226,0.00753335,0.000085190884,0.00015404128,0.00026203928,0.0028625987,0.005441464],"study_design_scores_gemma":[0.0000047622593,0.000017424372,0.9700444,0.00012701072,0.000024176241,0.00004505273,0.024312867,0.0003077207,0.000057193323,0.00006251989,0.00497274,0.000024166211],"about_ca_topic_score_codex":0.99772185,"about_ca_topic_score_gemma":0.9992974,"teacher_disagreement_score":0.033960074,"about_ca_system_score_codex":0.033960074,"about_ca_system_score_gemma":0.047303513,"threshold_uncertainty_score":0.24639875},"labels":[],"label_agreement":null},{"id":"W2947691164","doi":"10.1016/j.tra.2019.09.027","title":"Assessing the welfare impacts of Shared Mobility and Mobility as a Service (MaaS)","year":2019,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":234,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Public transport; Environmental economics; Transport engineering; Energy consumption; Business; Sharing economy; Private transport; Consumption (sociology); Service (business); Efficient energy use; Investment (military); Mode choice; Computer science; Marketing; Economics; Engineering","score_opus":0.08451333171178946,"score_gpt":0.43520963896940396,"score_spread":0.35069630725761447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2947691164","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95756745,0.0011318745,0.008022446,0.0058091083,0.00018637338,0.00024527608,0.0023143624,0.000053820284,0.024669323],"genre_scores_gemma":[0.9966454,0.00027029045,0.0010569409,0.00010530165,0.000028559809,0.00009995646,0.0002356672,0.000005818724,0.0015520453],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9865296,0.009011093,0.00030057406,0.0006607823,0.0015541563,0.0019437907],"domain_scores_gemma":[0.9865029,0.0074327984,0.0021865563,0.0007411107,0.0019993815,0.0011373798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008751008,0.00089072186,0.0007637721,0.0015794324,0.0008532534,0.0036713332,0.001487268,0.0019928727,0.007502953],"category_scores_gemma":[0.03036369,0.00044082306,0.0017853541,0.0030302352,0.0018533284,0.0048755496,0.0054695057,0.0022374983,0.0004065603],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004941039,0.0024197635,0.29640314,0.0008685988,0.0033361877,0.00061457395,0.0017877654,0.23236503,0.0017115758,0.29241166,0.009684773,0.15345594],"study_design_scores_gemma":[0.0005897635,0.00946161,0.31570315,0.0010754459,0.0034904198,0.00037119625,0.02000169,0.36097714,0.0039575654,0.25256974,0.03159394,0.00020830645],"about_ca_topic_score_codex":0.036046356,"about_ca_topic_score_gemma":0.0418613,"teacher_disagreement_score":0.036046356,"about_ca_system_score_codex":0.008593867,"about_ca_system_score_gemma":0.008005861,"threshold_uncertainty_score":0.071673095},"labels":[],"label_agreement":null},{"id":"W2949405227","doi":"10.48550/arxiv.1010.1438","title":"Coalition Formation Games for Distributed Cooperation Among Roadside Units in Vehicular Networks","year":2010,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Norges Forskningsråd; National Science Foundation","keywords":"Computer science; Partition (number theory); Scheme (mathematics); Stochastic game; Computer network; Vehicular ad hoc network; Work (physics); Operations research; Wireless ad hoc network; Telecommunications; Wireless; Engineering; Microeconomics","score_opus":0.04053859063522432,"score_gpt":0.17112444092009407,"score_spread":0.13058585028486974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949405227","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.056701127,0.00040113644,0.9286932,0.00064548134,0.00007809297,0.0002144177,0.00015974294,0.00012092438,0.012985875],"genre_scores_gemma":[0.8986693,0.00054939964,0.08995553,0.00018947221,0.000058020385,0.000639045,0.00024510737,0.00006684421,0.009627219],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847025,0.0008650471,0.000058469694,0.00019161329,0.00021148962,0.00020309782],"domain_scores_gemma":[0.9968868,0.002166937,0.00030480768,0.00012700095,0.00024253112,0.000271849],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017642934,0.0011880164,0.0013461233,0.0006282491,0.00089213013,0.0014285384,0.0019622385,0.0012794884,0.0029651623],"category_scores_gemma":[0.00683863,0.00045761795,0.00085871445,0.0007420456,0.001721159,0.0018892401,0.002036178,0.0017130726,0.0003754939],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015392575,0.00005747755,0.00047825635,0.00008565862,0.00006900839,0.00021335612,0.00034568654,0.77782637,0.0009200903,0.20854537,0.0018613929,0.00944335],"study_design_scores_gemma":[0.000045808993,0.000034109882,0.00009803071,0.000011837584,0.000010353883,0.00003104621,0.00006127886,0.9176093,0.00019934912,0.080544524,0.001343646,0.000010733897],"about_ca_topic_score_codex":0.0056269797,"about_ca_topic_score_gemma":0.004839387,"teacher_disagreement_score":0.0056269797,"about_ca_system_score_codex":0.0026045153,"about_ca_system_score_gemma":0.0017563091,"threshold_uncertainty_score":0.018897176},"labels":[],"label_agreement":null},{"id":"W2949989052","doi":"10.2139/ssrn.3250557","title":"Introducing Autonomous Vehicles: Formulation and Analysis of Public Policies","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; University of Toronto","funders":"","keywords":"Computer science; Political science","score_opus":0.009800723956280455,"score_gpt":0.2384277614582015,"score_spread":0.22862703750192104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949989052","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17968789,0.0020420258,0.6958018,0.017327638,0.00044611492,0.0002809697,0.00069591944,0.00022827995,0.103489354],"genre_scores_gemma":[0.9475352,0.0015381625,0.028339801,0.0003581458,0.0003084008,0.00025321683,0.00013694746,0.00007561543,0.021454593],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99840087,0.0008618694,0.00003961181,0.00018283732,0.00017283717,0.00034199154],"domain_scores_gemma":[0.9918516,0.0063378955,0.0007465017,0.00020596571,0.0004983608,0.00035953478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031796515,0.0009718515,0.0016994042,0.0012945628,0.00089872256,0.0043988135,0.0022423568,0.0041887686,0.009621658],"category_scores_gemma":[0.011417069,0.0011106102,0.0012787379,0.001242985,0.0034761308,0.004351958,0.0018347079,0.0030546219,0.00027588577],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031399522,0.00006670438,0.00031155391,0.00005917751,0.000022880984,0.000056901234,0.000084698375,0.26194623,0.00012786512,0.7332608,0.0014656713,0.0025661793],"study_design_scores_gemma":[0.000045185083,0.00004206719,0.00021648832,0.000029036371,0.000024741608,0.000014136131,0.00021313952,0.580838,0.00014946038,0.41536814,0.003044186,0.000015435608],"about_ca_topic_score_codex":0.013100719,"about_ca_topic_score_gemma":0.010994858,"teacher_disagreement_score":0.013100719,"about_ca_system_score_codex":0.0058353255,"about_ca_system_score_gemma":0.0060137995,"threshold_uncertainty_score":0.04233843},"labels":[],"label_agreement":null},{"id":"W2950344037","doi":"10.1145/3292500.3330793","title":"Two-Sided Fairness for Repeated Matchings in Two-Sided Markets","year":2019,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":116,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Microsoft (Canada)","funders":"Horizon 2020 Framework Programme; European Commission","keywords":"Worry; Sharing economy; Boosting (machine learning); Computer science; Range (aeronautics); Business; Internet privacy; Marketing; World Wide Web; Engineering; Artificial intelligence","score_opus":0.007627534998150848,"score_gpt":0.2529023876426246,"score_spread":0.24527485264447377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950344037","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10353713,0.0013079203,0.8483958,0.0054848366,0.0006345821,0.00043762036,0.0008344841,0.0005634504,0.038804196],"genre_scores_gemma":[0.8460111,0.00147914,0.10361872,0.0013786844,0.0012523918,0.00076827797,0.00046654663,0.0004025544,0.044622507],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98707306,0.005583931,0.0006993753,0.00262918,0.0017490045,0.0022653926],"domain_scores_gemma":[0.93750465,0.04298031,0.0053527956,0.0069459183,0.0040097316,0.003206589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024571761,0.0019534207,0.00517689,0.002299318,0.0042602066,0.0065344684,0.0062296586,0.0069502625,0.030512558],"category_scores_gemma":[0.07536937,0.001369658,0.0036163155,0.0020767397,0.008389798,0.016269773,0.005495583,0.0065636155,0.003911435],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019301995,0.00009191583,0.0007450285,0.00008903249,0.00004787563,0.00024380238,0.0002609297,0.018664762,0.00037177265,0.96866804,0.0026030152,0.008020818],"study_design_scores_gemma":[0.00007383739,0.000041516385,0.0001755908,0.000028788487,0.000020956617,0.00010307509,0.000066302586,0.13748969,0.00012157798,0.8603989,0.0014394751,0.000040306466],"about_ca_topic_score_codex":0.0048171785,"about_ca_topic_score_gemma":0.003821482,"teacher_disagreement_score":0.030512558,"about_ca_system_score_codex":0.004240671,"about_ca_system_score_gemma":0.0047140294,"threshold_uncertainty_score":0.12994945},"labels":[],"label_agreement":null},{"id":"W2951977839","doi":"10.5539/nct.v4n1p26","title":"An Intelligent Dispatch System Operating in a Partially Closed Environment","year":2019,"lang":"en","type":"article","venue":"Network and Communication Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Covenant University","keywords":"Microcontroller; Android (operating system); GSM; Embedded system; Computer science; Operating system; Software","score_opus":0.008086336446389996,"score_gpt":0.2071061860885422,"score_spread":0.1990198496421522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951977839","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19578025,0.0009106855,0.6224891,0.0007318946,0.00091609184,0.0016054233,0.0018697568,0.1225461,0.05315077],"genre_scores_gemma":[0.78002137,0.00051811896,0.13876124,0.0004928445,0.00029081307,0.00062622305,0.0020967266,0.00096231536,0.07623033],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960166,0.000040395524,0.000046795405,0.000121034165,0.00015015788,0.000039954644],"domain_scores_gemma":[0.999551,0.00009005283,0.00005038645,0.00008080032,0.00014376479,0.00008385894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002982634,0.0005677663,0.0006339707,0.0006190664,0.0006387843,0.0011702006,0.0011008547,0.0006098982,0.009717346],"category_scores_gemma":[0.000742672,0.0003136691,0.00023495025,0.000298882,0.0002600949,0.0012372944,0.0007902864,0.00046223728,0.004297276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022061812,0.00072567473,0.008292944,0.0008586734,0.00014274256,0.002550501,0.0014773589,0.014644045,0.2859691,0.012254851,0.08250427,0.5883737],"study_design_scores_gemma":[0.0007233983,0.0020668616,0.018703261,0.00018269723,0.00037716795,0.004029925,0.00062226184,0.40458566,0.16576393,0.005693817,0.39683008,0.00042088763],"about_ca_topic_score_codex":0.0011681152,"about_ca_topic_score_gemma":0.0008371701,"teacher_disagreement_score":0.009717346,"about_ca_system_score_codex":0.00027201115,"about_ca_system_score_gemma":0.000607246,"threshold_uncertainty_score":0.032507777},"labels":[],"label_agreement":null},{"id":"W2952378113","doi":"10.1287/trsc.2018.0869","title":"A Branch-and-Cut Algorithm for the Alternative Fuel Refueling Station Location Problem with Routing","year":2019,"lang":"en","type":"article","venue":"Transportation Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Range (aeronautics); Alternative fuel vehicle; Bounded function; Vehicle routing problem; Routing (electronic design automation); Mathematical optimization; Flow network; Driving range; Engineering; Computer science; Algorithm; Mathematics; Computer network; Automotive engineering; Alternative fuels; Electric vehicle","score_opus":0.013158606151967886,"score_gpt":0.2513267268759522,"score_spread":0.2381681207239843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952378113","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01760161,0.00038636426,0.97477424,0.00045476083,0.0000616639,0.0003093415,0.00033159213,0.0005517265,0.0055285604],"genre_scores_gemma":[0.10576738,0.00029939698,0.88901633,0.0001400637,0.000056118653,0.00056748843,0.0008350583,0.00015989324,0.0031583488],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913424,0.0003138237,0.000040541043,0.00021737018,0.00015175086,0.0001422927],"domain_scores_gemma":[0.99847406,0.001133905,0.0001079794,0.00006073604,0.00013558396,0.000087748216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015601454,0.0016325434,0.001746856,0.0009653226,0.000895079,0.0015491763,0.0018191759,0.0020149183,0.0068125436],"category_scores_gemma":[0.0032037531,0.0008975998,0.0010678509,0.0019254468,0.0005845354,0.0017438353,0.0013808156,0.0021568686,0.00084719236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001212059,0.00019976293,0.00046350693,0.00014694448,0.000041674073,0.00010281463,0.00008544932,0.8987525,0.0006604589,0.015912326,0.0049280077,0.07858525],"study_design_scores_gemma":[0.00004601531,0.00003834218,0.000053199197,0.000008871091,0.000008234801,0.000018466895,0.000022695334,0.99112153,0.00016483432,0.00761906,0.00089436537,0.000004394877],"about_ca_topic_score_codex":0.010201251,"about_ca_topic_score_gemma":0.010130168,"teacher_disagreement_score":0.010201251,"about_ca_system_score_codex":0.0016638396,"about_ca_system_score_gemma":0.0029131435,"threshold_uncertainty_score":0.022790253},"labels":[],"label_agreement":null},{"id":"W2953609581","doi":"10.1155/2019/3689389","title":"Analyses of the Imbalance of Urban Taxis’ High-Quality Customers Based on Didi Trajectory Data","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Social Science Fund of China; National Natural Science Foundation of China","keywords":"Taxis; Distribution (mathematics); Revenue; Order (exchange); Business; Transport engineering; Quality (philosophy); Dimension (graph theory); Computer science; Operations research; Engineering; Mathematics","score_opus":0.029306938749643924,"score_gpt":0.3056825048508582,"score_spread":0.2763755661012143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953609581","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9926024,0.00006917318,0.0011305488,0.00007578171,0.0000068257286,0.000018158717,0.0053043975,0.000054241136,0.0007383255],"genre_scores_gemma":[0.98967135,0.000045304918,0.000597182,0.0000068783847,0.00000576758,0.000015710955,0.009332994,0.000010748953,0.00031398248],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992465,0.00012878435,0.000060611335,0.00017220798,0.00020287518,0.00018904905],"domain_scores_gemma":[0.9978969,0.00047062,0.00046166175,0.00020400644,0.00077067333,0.00019607268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001066638,0.00046843503,0.000492279,0.0029998075,0.00037677938,0.000770726,0.0005507623,0.00041301677,0.0012889795],"category_scores_gemma":[0.0029652216,0.000218429,0.0005615237,0.004862673,0.00025967616,0.0006499704,0.0007156442,0.000519784,0.00050548645],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022528181,0.00012073541,0.9661718,0.00005167659,0.00015570638,0.00025712364,0.00041366965,0.019612558,0.0009803132,0.00066659006,0.0015175586,0.009826996],"study_design_scores_gemma":[0.000009707771,0.00003774511,0.90285254,0.000014583295,0.00004532524,0.00009015342,0.0013161637,0.092926346,0.0005744694,0.0002571308,0.0018511359,0.000024719217],"about_ca_topic_score_codex":0.046303533,"about_ca_topic_score_gemma":0.033796147,"teacher_disagreement_score":0.046303533,"about_ca_system_score_codex":0.0011178486,"about_ca_system_score_gemma":0.000537574,"threshold_uncertainty_score":0.092068076},"labels":[],"label_agreement":null},{"id":"W2953974006","doi":"10.1155/2019/8607942","title":"A Study of Taxi Service Mode Choice Based on Evolutionary Game Theory","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Evolutionary game theory; Service (business); Mode (computer interface); Game theory; Stochastic game; Evolutionarily stable strategy; Mode choice; Computer science; Operations research; Convergence (economics); Process (computing); Business; Transport engineering; Microeconomics; Economics; Engineering; Marketing; Public transport; Human–computer interaction","score_opus":0.008606629112499299,"score_gpt":0.2495789030602851,"score_spread":0.2409722739477858,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953974006","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6220661,0.0003763054,0.3494642,0.0008903324,0.000045608296,0.00018545352,0.00009788515,0.000025816873,0.026848383],"genre_scores_gemma":[0.9854081,0.0001843975,0.012098563,0.000033080014,0.00000866313,0.000055474095,0.00001778827,0.0000043975933,0.0021895175],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994867,0.00030067994,0.000012799052,0.00006737455,0.000055361474,0.00007713054],"domain_scores_gemma":[0.9988838,0.00076580775,0.000118097065,0.000031493735,0.00009828779,0.0001025247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092356204,0.00039498525,0.00053156033,0.00050815963,0.0005572495,0.0010310359,0.0008625084,0.00080754247,0.0025053439],"category_scores_gemma":[0.00404463,0.00023332576,0.0006034292,0.0005460316,0.0009809209,0.0018333636,0.00048884936,0.00087568717,0.000085439984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000679011,0.00015850888,0.009912308,0.00010619742,0.00011670536,0.000560014,0.00083425484,0.5112006,0.0024943664,0.45624802,0.0008363659,0.017464833],"study_design_scores_gemma":[0.000014988492,0.000059915263,0.0016798807,0.00001178078,0.000021820277,0.00007119213,0.0002574886,0.95283437,0.00016078686,0.043896675,0.000974444,0.000016664151],"about_ca_topic_score_codex":0.008244188,"about_ca_topic_score_gemma":0.004526682,"teacher_disagreement_score":0.008244188,"about_ca_system_score_codex":0.0015101403,"about_ca_system_score_gemma":0.001064816,"threshold_uncertainty_score":0.01639241},"labels":[],"label_agreement":null},{"id":"W2954558387","doi":"10.1061/9780784482292.489","title":"Scenario-Based Infrastructure Requirements for Automated Driving","year":2019,"lang":"en","type":"article","venue":"CICTP 2019","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Computer science; Key (lock); Wireless; Critical infrastructure; Systems engineering; Transport engineering; Risk analysis (engineering); Engineering; Computer security; Telecommunications; Business","score_opus":0.007438479955866551,"score_gpt":0.24229016552876595,"score_spread":0.2348516855728994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2954558387","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43796256,0.00037963176,0.41426507,0.0023160868,0.000060889673,0.0016130758,0.0025603664,0.0005129334,0.14032936],"genre_scores_gemma":[0.95721334,0.00014614477,0.03969845,0.000039551862,0.00000921491,0.0004105515,0.0011260065,0.00002589369,0.001330813],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9948243,0.0024084116,0.00040294798,0.00025860337,0.0015879265,0.0005178199],"domain_scores_gemma":[0.9916524,0.0046672532,0.0007946499,0.0005777715,0.0019299554,0.00037800192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003216226,0.00058207806,0.00020659556,0.0012961779,0.0009739557,0.0027966124,0.001172408,0.001680397,0.0045731063],"category_scores_gemma":[0.011032534,0.00041498235,0.00068417296,0.0008877081,0.0008197559,0.0028978593,0.0016421371,0.0009066517,0.00059962785],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018094711,0.0002030185,0.010607304,0.0005151942,0.00007297668,0.0031742088,0.0054630907,0.5461305,0.009787477,0.392371,0.0035907782,0.027903534],"study_design_scores_gemma":[0.00005266103,0.0003940492,0.012119358,0.00045364947,0.00009514434,0.0025155768,0.014178241,0.6906753,0.007238007,0.18257374,0.0895234,0.0001808921],"about_ca_topic_score_codex":0.0051844865,"about_ca_topic_score_gemma":0.006252422,"teacher_disagreement_score":0.0051844865,"about_ca_system_score_codex":0.002038175,"about_ca_system_score_gemma":0.0018297788,"threshold_uncertainty_score":0.017009199},"labels":[],"label_agreement":null},{"id":"W2955361553","doi":"10.5383/jttm.01.01.004","title":"Modeling framework for supporting taxi policy making","year":2019,"lang":"en","type":"article","venue":"International Journal of Traffic and Transportation Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Policy making; Computer science; Process management; Business; Political science; Public administration","score_opus":0.011268370391382027,"score_gpt":0.2926964490448884,"score_spread":0.2814280786535064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955361553","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005629613,0.000104665065,0.9754612,0.00131499,0.00010564845,0.00010323004,0.0009584028,0.0007558074,0.015566431],"genre_scores_gemma":[0.42411524,0.00061747554,0.55352455,0.00039910487,0.00016936442,0.0005492087,0.0018240475,0.0003687547,0.018432243],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919456,0.00031130319,0.000060876282,0.0001379434,0.00019298181,0.00010239563],"domain_scores_gemma":[0.9984403,0.0007175214,0.00013225518,0.00016121991,0.00043531827,0.00011348637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020846922,0.00088275055,0.00094947766,0.0012945542,0.0012141232,0.0033538884,0.002990586,0.0020756994,0.012323808],"category_scores_gemma":[0.0051158983,0.00066529424,0.0013459328,0.001270254,0.00079816265,0.0031210184,0.0019242868,0.0021098002,0.0016511745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019153918,0.000061212864,0.00049122283,0.00004043917,0.00003948274,0.00011702611,0.00011863809,0.6440506,0.00035270062,0.34236974,0.0030468623,0.009292861],"study_design_scores_gemma":[0.000007171056,0.0000059295903,0.00003579805,0.000011140365,0.000012236303,0.00001182191,0.000033525437,0.9277167,0.00014863117,0.06724084,0.0047677713,0.000008527307],"about_ca_topic_score_codex":0.042804264,"about_ca_topic_score_gemma":0.032599855,"teacher_disagreement_score":0.042804264,"about_ca_system_score_codex":0.0020514054,"about_ca_system_score_gemma":0.0050294874,"threshold_uncertainty_score":0.08511025},"labels":[],"label_agreement":null},{"id":"W2959543353","doi":"10.1007/s11116-019-10030-w","title":"Incorporating features of autonomous vehicles in activity-based travel demand model for Columbus, OH","year":2019,"lang":"en","type":"article","venue":"Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Inro Consultants (Canada)","funders":"","keywords":"TRIPS architecture; Metropolitan area; Transport engineering; Relocation; Population; Computer science; Travel behavior; Mode choice; Operations research; Public transport; Geography; Engineering","score_opus":0.01290585492906691,"score_gpt":0.22967023071334128,"score_spread":0.21676437578427438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2959543353","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82371384,0.00030823244,0.15312283,0.0007930614,0.0001510543,0.000077748526,0.003111209,0.00029772564,0.018424315],"genre_scores_gemma":[0.9929508,0.000053166506,0.0025045532,0.000020125013,0.000013006183,0.000031545027,0.0005020819,0.000014579854,0.003910044],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998927,0.000024191722,0.0000048322486,0.00002974824,0.000016866365,0.000031525367],"domain_scores_gemma":[0.99985313,0.00004808807,0.00001707209,0.00000968752,0.00005150774,0.000020554924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021462276,0.00038837918,0.00043213522,0.00029175088,0.00042216445,0.0007658748,0.001029388,0.00084860297,0.003104563],"category_scores_gemma":[0.00049864996,0.0003984244,0.0005251584,0.0005623866,0.0001897679,0.00081430224,0.0002992281,0.00048391204,0.0003141443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015847228,0.00002529054,0.0018870512,0.000010347856,0.000008672209,0.00004210335,0.000017032395,0.99392176,0.00028745868,0.001070583,0.00053190516,0.0021819489],"study_design_scores_gemma":[0.0000012574576,0.0000034035972,0.0004567668,6.401375e-7,0.0000020125337,0.000002495876,0.00000902541,0.9991817,0.000022051596,0.00016409445,0.00015466317,0.0000018024758],"about_ca_topic_score_codex":0.126786,"about_ca_topic_score_gemma":0.12299863,"teacher_disagreement_score":0.126786,"about_ca_system_score_codex":0.00096992386,"about_ca_system_score_gemma":0.001023685,"threshold_uncertainty_score":0.25209606},"labels":[],"label_agreement":null},{"id":"W2963395683","doi":"10.1109/uv.2018.8642141","title":"Autonomous Mobility and Energy Service Management in Future Smart Cities: An Overview","year":2018,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Electrification; Computer science; Flexibility (engineering); Key (lock); Service (business); Systems engineering; Transport engineering; Computer security; Electricity; Business; Engineering","score_opus":0.018794130612083505,"score_gpt":0.24731785577298881,"score_spread":0.2285237251609053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963395683","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014370621,0.7014675,0.16023326,0.017817643,0.0019563232,0.00017942824,0.00016023095,0.0004399121,0.10337503],"genre_scores_gemma":[0.14546393,0.7776458,0.058834665,0.0020771886,0.003419894,0.00016595169,0.00027946415,0.000065278815,0.012047836],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996457,0.00008970135,0.00003578269,0.000050808878,0.00011746474,0.000060583243],"domain_scores_gemma":[0.99972004,0.00011717797,0.0000277832,0.000019813273,0.00008101067,0.00003410971],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054688053,0.00061731064,0.00035438262,0.001679251,0.0006267868,0.0030308461,0.0006958337,0.0021076018,0.0014376411],"category_scores_gemma":[0.0004979399,0.0004122975,0.00042781432,0.002534341,0.0008639095,0.0049928003,0.0014055176,0.001777762,0.00057496043],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042348565,0.0001232802,0.0023291623,0.0033869243,0.00005542416,0.00032387397,0.0009646116,0.020995203,0.0017493909,0.5646043,0.023359327,0.38206613],"study_design_scores_gemma":[0.0000062220565,0.00012790163,0.0021382286,0.0013332792,0.00004836723,0.0007410194,0.0012178945,0.030476049,0.0009669822,0.09513033,0.8677515,0.00006231496],"about_ca_topic_score_codex":0.003304165,"about_ca_topic_score_gemma":0.002692065,"teacher_disagreement_score":0.003304165,"about_ca_system_score_codex":0.0016153528,"about_ca_system_score_gemma":0.0013842975,"threshold_uncertainty_score":0.0117201805},"labels":[],"label_agreement":null},{"id":"W2963428364","doi":"10.1109/iwcmc.2019.8766676","title":"Mobility Traffic Model Based on Combination of Multiple Transportation Forms in the Smart City","year":2019,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Transport engineering; Road traffic; Computer network; Engineering","score_opus":0.014502150868250933,"score_gpt":0.22120339286386806,"score_spread":0.20670124199561712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963428364","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35223964,0.000498895,0.61498046,0.00078516285,0.00024263865,0.00014094732,0.0010212396,0.00050731405,0.029583763],"genre_scores_gemma":[0.97747266,0.00032133612,0.013674756,0.000030362724,0.00003724442,0.000102175385,0.00029839255,0.000028827755,0.008034095],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997584,0.000052664665,0.000010306793,0.00007584233,0.000044028962,0.000058872607],"domain_scores_gemma":[0.9998809,0.000025740455,0.000019805673,0.000008125,0.00004553552,0.000019901972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016626218,0.00062136055,0.00046552136,0.00044813083,0.00058731146,0.0009567573,0.0008222606,0.000675782,0.002746927],"category_scores_gemma":[0.0003944156,0.00027363712,0.0008016839,0.00067319855,0.00041585873,0.0014337889,0.0005512625,0.0004584772,0.00029875437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015699088,0.000013195485,0.0009465479,0.000013586002,0.00001131925,0.00006345749,0.000024753288,0.9884062,0.00068480126,0.0070902356,0.00029775265,0.0024325373],"study_design_scores_gemma":[0.0000030430708,0.000009830144,0.0002725256,0.0000015954035,0.0000063314988,0.000012691053,0.000016794003,0.9981736,0.00006681553,0.0009651001,0.00046752763,0.000004065932],"about_ca_topic_score_codex":0.038159106,"about_ca_topic_score_gemma":0.022535846,"teacher_disagreement_score":0.038159106,"about_ca_system_score_codex":0.0010348157,"about_ca_system_score_gemma":0.0010185078,"threshold_uncertainty_score":0.07587397},"labels":[],"label_agreement":null},{"id":"W2964571806","doi":"10.1287/opre.2018.1822","title":"Empty-Car Routing in Ridesharing Systems","year":2019,"lang":"en","type":"article","venue":"Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":226,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Chinese University of Hong Kong; University of Hong Kong; University of Toronto","keywords":"Computer science; Vehicle routing problem; Routing (electronic design automation); Operations research; Transport engineering; Mathematical optimization; Computer network; Mathematics; Engineering","score_opus":0.05969899393229509,"score_gpt":0.34784404873476843,"score_spread":0.2881450548024733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2964571806","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04167682,0.0045765587,0.8970648,0.0022198043,0.0002996513,0.00008620949,0.00023948406,0.00012397674,0.053712863],"genre_scores_gemma":[0.9008183,0.0070922133,0.06711799,0.00038113858,0.0004677777,0.00007188718,0.00026879332,0.000065706256,0.02371623],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929273,0.00018769858,0.00004348052,0.00019058913,0.00015365367,0.00013180917],"domain_scores_gemma":[0.9987111,0.0006889985,0.00015450468,0.00011835489,0.0002636138,0.00006342819],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071007194,0.0006410797,0.001049941,0.00082795287,0.0012052733,0.003847548,0.0016366941,0.0015979694,0.008082273],"category_scores_gemma":[0.0027702898,0.000613307,0.0008335627,0.0012957946,0.001825392,0.006369015,0.001515103,0.0021667567,0.00075190194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016434708,0.000039587194,0.00045660694,0.00012348656,0.000013306922,0.00013478972,0.00022416553,0.22940066,0.000763315,0.7529287,0.0020299875,0.013868971],"study_design_scores_gemma":[0.0000060245775,0.000028807786,0.00042108295,0.000056936264,0.000013632163,0.00012458234,0.00027720645,0.5031648,0.0004227109,0.4862669,0.009186941,0.000030313058],"about_ca_topic_score_codex":0.008975354,"about_ca_topic_score_gemma":0.004989177,"teacher_disagreement_score":0.008975354,"about_ca_system_score_codex":0.0022166565,"about_ca_system_score_gemma":0.0013913991,"threshold_uncertainty_score":0.027037919},"labels":[],"label_agreement":null},{"id":"W2965591468","doi":"10.11159/icert19.107","title":"Spatial Information Systems as Sources of Data for Electromobility Planning","year":2019,"lang":"en","type":"article","venue":"Proceedings of the World Congress on New Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Narodowe Centrum Badań i Rozwoju","keywords":"Computer science; Spatial analysis; Data science; Remote sensing; Geography","score_opus":0.01888588868906522,"score_gpt":0.2540102232382302,"score_spread":0.23512433454916498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965591468","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014350455,0.0039789486,0.890962,0.008204936,0.0004986676,0.0004373218,0.012142332,0.004059536,0.06536569],"genre_scores_gemma":[0.35803497,0.00798913,0.59408814,0.00089562417,0.00056063593,0.0007067876,0.022835312,0.00083153317,0.014057906],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99506927,0.0019142631,0.0006136163,0.0005777934,0.0016491447,0.00017586935],"domain_scores_gemma":[0.99345994,0.0028160913,0.00044857364,0.0018262686,0.0012791049,0.00016986346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044301045,0.00055488094,0.0006243748,0.0076627517,0.0011495803,0.00963342,0.0019597737,0.0012374694,0.005217046],"category_scores_gemma":[0.010808783,0.00059918285,0.0006165765,0.01113006,0.0022534442,0.009505823,0.0049127475,0.0015020873,0.0023695899],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055479166,0.00003550951,0.0030806318,0.0004778142,0.0000823562,0.0003327293,0.0010442554,0.015189605,0.0010961146,0.8256147,0.019884951,0.1331058],"study_design_scores_gemma":[0.000027235868,0.00004934404,0.0027204216,0.0008198783,0.0000802198,0.00032937698,0.0021608127,0.07062026,0.0053328783,0.39175454,0.52602214,0.00008293138],"about_ca_topic_score_codex":0.005676891,"about_ca_topic_score_gemma":0.003552607,"teacher_disagreement_score":0.00963342,"about_ca_system_score_codex":0.0028434463,"about_ca_system_score_gemma":0.0028942549,"threshold_uncertainty_score":0.023428917},"labels":[],"label_agreement":null},{"id":"W2966418027","doi":"10.5539/ijbm.v14n9p65","title":"Ride-sharing Service in Bangladesh: Contemporary States and Prospects","year":2019,"lang":"en","type":"article","venue":"International Journal of Business and Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Marketing; Flexibility (engineering); Business; Service (business); Descriptive statistics; Service quality; Sample (material); Quarter (Canadian coin); Quality (philosophy); Economics; Geography; Management","score_opus":0.012220632759474489,"score_gpt":0.22580394270454893,"score_spread":0.21358330994507443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2966418027","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9417779,0.00756652,0.00023052034,0.009625478,0.00004940827,0.00003471413,0.0009096178,0.000016786977,0.039789096],"genre_scores_gemma":[0.9895195,0.007484122,0.00010286674,0.00033188917,0.000018297878,0.000014508341,0.00021752107,0.0000028678708,0.002308443],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996246,0.00007778107,0.000045255685,0.000040098486,0.00008073448,0.00013139476],"domain_scores_gemma":[0.99906427,0.00017481226,0.0002543215,0.000023911656,0.00023247174,0.00025027234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004739363,0.00017436451,0.00014363602,0.0008049814,0.0010307953,0.0015015118,0.0003676514,0.00052089844,0.008762365],"category_scores_gemma":[0.0010216872,0.00013558258,0.00010370024,0.0029880365,0.00092496973,0.0014947705,0.0008371179,0.00043600824,0.0009803015],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027951162,0.00026914792,0.7257054,0.0016481428,0.000036534453,0.0034244454,0.03428849,0.00048082403,0.004051654,0.018812796,0.010959176,0.2000439],"study_design_scores_gemma":[0.000014966752,0.0003389556,0.66718626,0.0008402308,0.00003974482,0.0027918941,0.20513548,0.0006017425,0.0005641844,0.0020629806,0.12033547,0.00008822493],"about_ca_topic_score_codex":0.03708816,"about_ca_topic_score_gemma":0.048781242,"teacher_disagreement_score":0.03708816,"about_ca_system_score_codex":0.0019266815,"about_ca_system_score_gemma":0.0018526677,"threshold_uncertainty_score":0.073744535},"labels":[],"label_agreement":null},{"id":"W2969466554","doi":"10.5038/cutr-nctr-rr-2004-17","title":"Rideshare/511 Signage in the U.S. and Canada","year":2004,"lang":"en","type":"report","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Signage; Engineering; Art history; Geography; History; Art; Visual arts","score_opus":0.017616187083119652,"score_gpt":0.2212809325735139,"score_spread":0.20366474549039423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969466554","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3787511,0.002327635,0.0009836118,0.012269952,0.00042288564,0.0008302344,0.08466018,0.0007766249,0.51897776],"genre_scores_gemma":[0.28530514,0.0021495637,0.0011397547,0.0013867143,0.00003061761,0.00016356878,0.021129023,0.00013084292,0.6885647],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99650526,0.0000797935,0.00005793243,0.00016407136,0.0018290207,0.0013639256],"domain_scores_gemma":[0.995552,0.00008745237,0.00015246571,0.000075171556,0.0030711808,0.0010616789],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073814084,0.00043053637,0.0004257693,0.0029371155,0.0062125013,0.0030584768,0.0013526621,0.0010210493,0.02008057],"category_scores_gemma":[0.0026579506,0.00038511943,0.00041161044,0.00496071,0.0009626761,0.00070276455,0.0016778455,0.0015956016,0.0036774848],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015936178,0.00030954726,0.22729693,0.00019311174,0.000046450758,0.0006225789,0.0038353358,0.0011551178,0.0009483146,0.010077106,0.64751065,0.10784543],"study_design_scores_gemma":[0.000027807935,0.00008870291,0.62979263,0.00014476769,0.000043710817,0.00014978104,0.0154455835,0.0010889474,0.00090546923,0.00024712225,0.3520064,0.000059006317],"about_ca_topic_score_codex":0.9976163,"about_ca_topic_score_gemma":0.9993911,"teacher_disagreement_score":0.054347843,"about_ca_system_score_codex":0.054347843,"about_ca_system_score_gemma":0.14644706,"threshold_uncertainty_score":0.39432305},"labels":[],"label_agreement":null},{"id":"W2969963949","doi":"10.1007/s12597-019-00405-z","title":"Airplane boarding optimization considering reserved seats and passengers’ carry-on bags","year":2019,"lang":"en","type":"article","venue":"OPSEARCH","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Airplane; Carry (investment); Computer science; Integer programming; Operations research; Transport engineering; Business; Engineering; Algorithm; Finance","score_opus":0.01450194598291363,"score_gpt":0.22864210442323665,"score_spread":0.21414015844032303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969963949","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.66328484,0.0026604906,0.2746338,0.0011379259,0.00061614654,0.0002450461,0.0014026058,0.00062583515,0.055393334],"genre_scores_gemma":[0.96966124,0.00046361654,0.016181452,0.00010005902,0.000073677926,0.00007908047,0.0004844423,0.00013415604,0.01282233],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999605,0.00010716895,0.000008003265,0.000072922885,0.00004016893,0.00016677765],"domain_scores_gemma":[0.9993963,0.00030933245,0.000050176746,0.000025078312,0.00010130666,0.00011784651],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000595097,0.0025346302,0.0024013047,0.0010305184,0.0007088191,0.0022573166,0.0010328862,0.0022597513,0.010299042],"category_scores_gemma":[0.0013880864,0.0009969847,0.0014162948,0.0010536496,0.0005410611,0.0014705572,0.0007507292,0.0013180721,0.00079493376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019766156,0.000075449854,0.00049629644,0.00008363756,0.000040375,0.00009435055,0.00001642338,0.9898913,0.001063174,0.00089916325,0.0011125278,0.0060295737],"study_design_scores_gemma":[0.000023161618,0.00011531755,0.0006896638,0.000013211674,0.000037629987,0.000017274098,0.000054716966,0.9976497,0.0003230249,0.0006400766,0.00042858702,0.000007546265],"about_ca_topic_score_codex":0.020039152,"about_ca_topic_score_gemma":0.009956103,"teacher_disagreement_score":0.020039152,"about_ca_system_score_codex":0.00084554026,"about_ca_system_score_gemma":0.0012169395,"threshold_uncertainty_score":0.03984499},"labels":[],"label_agreement":null},{"id":"W2972292487","doi":"","title":"Autonomous Vehicles: Understanding Adoption Potential in the Greater Toronto and Hamilton Area","year":2019,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"University of Waterloo","keywords":"Transport engineering; Engineering; Geography","score_opus":0.015219486642858987,"score_gpt":0.1873374349330384,"score_spread":0.1721179482901794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2972292487","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99012005,0.0004868635,0.00019206681,0.0010463545,0.000008733823,0.000038921175,0.00046582703,0.000005028339,0.0076361103],"genre_scores_gemma":[0.99812204,0.0006059593,0.0001687494,0.00005561417,0.0000035292223,0.000019621728,0.00017479419,0.0000021403305,0.000847493],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992906,0.00015776254,0.000032804845,0.00008103605,0.00023935545,0.00019854584],"domain_scores_gemma":[0.99790645,0.0005552662,0.00043110517,0.00005727144,0.0005851896,0.00046471323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067460124,0.00018201586,0.00017960914,0.0018302012,0.0021563454,0.00220309,0.0006204288,0.00026623203,0.0020471683],"category_scores_gemma":[0.0028291836,0.00017995934,0.00022686679,0.0047841934,0.0018202533,0.0011575061,0.0015672947,0.00047331984,0.00010451378],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044594974,0.0000502456,0.7574852,0.00025045127,0.000057083384,0.0009434056,0.19949387,0.00064684753,0.0007315842,0.007325662,0.004716205,0.028254744],"study_design_scores_gemma":[0.0000042839606,0.000029611669,0.7806073,0.0001206127,0.00002111068,0.00008555169,0.20604101,0.0006340535,0.000078945995,0.00030399338,0.01205544,0.00001812075],"about_ca_topic_score_codex":0.97080505,"about_ca_topic_score_gemma":0.98559016,"teacher_disagreement_score":0.029194951,"about_ca_system_score_codex":0.026346495,"about_ca_system_score_gemma":0.01651218,"threshold_uncertainty_score":0.19115812},"labels":[],"label_agreement":null},{"id":"W2972375079","doi":"10.1109/cdc40024.2019.9030043","title":"On Re-Balancing Self-Interested Agents in Ride-Sourcing Transportation Networks","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Control (management); Operations research; Profit (economics); Set (abstract data type); Business; Microeconomics; Engineering; Economics; Artificial intelligence","score_opus":0.02020311611858147,"score_gpt":0.25160009507520736,"score_spread":0.2313969789566259,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2972375079","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13149945,0.0013278511,0.8591816,0.0010668978,0.00016794303,0.00023048474,0.00011005742,0.0003951198,0.006020587],"genre_scores_gemma":[0.9382778,0.000501149,0.05672302,0.0002995781,0.00011194213,0.00016198568,0.000099546305,0.000114934075,0.0037100345],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99895513,0.00046731238,0.000043886183,0.00022636274,0.00013219749,0.00017500766],"domain_scores_gemma":[0.9935408,0.0046690293,0.0006652525,0.00033441282,0.0005070293,0.0002834142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033962992,0.0018191272,0.0016698741,0.0008440249,0.0009308046,0.0015987904,0.0021456673,0.001911875,0.003262947],"category_scores_gemma":[0.0082430765,0.0005342636,0.0006465048,0.00081758725,0.0017093607,0.0027902897,0.0017257828,0.00135503,0.00041743912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009676268,0.000086804364,0.00051376526,0.00006091239,0.000031316493,0.000038031325,0.00010069137,0.97605544,0.0011195872,0.0060906727,0.00076869543,0.015037349],"study_design_scores_gemma":[0.000016670647,0.00004166829,0.000104770355,0.0000047387484,0.000006090061,0.000009689032,0.00004312452,0.9942768,0.00023060858,0.00485175,0.00040846982,0.0000055634014],"about_ca_topic_score_codex":0.007643895,"about_ca_topic_score_gemma":0.00493163,"teacher_disagreement_score":0.007643895,"about_ca_system_score_codex":0.0015203658,"about_ca_system_score_gemma":0.001129451,"threshold_uncertainty_score":0.017961562},"labels":[],"label_agreement":null},{"id":"W297314987","doi":"10.17226/22195","title":"Open Data: Challenges and Opportunities for Transit Agencies","year":2015,"lang":"en","type":"book","venue":"Transportation Research Board eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Computer science; Internet privacy; Business; Data science; Transport engineering; Engineering; Public transport","score_opus":0.5432801677344464,"score_gpt":0.4019768985033521,"score_spread":0.14130326923109432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W297314987","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011176686,0.08390903,0.041469563,0.5284377,0.0066170236,0.00018227054,0.00071426487,0.0011144243,0.326379],"genre_scores_gemma":[0.21105808,0.23717889,0.08355005,0.04920774,0.00778784,0.0006570598,0.0021661024,0.0020014297,0.40639284],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9890448,0.005188469,0.0007849521,0.0006354772,0.0034618848,0.00088441494],"domain_scores_gemma":[0.96849537,0.019456197,0.0010263177,0.0028730298,0.0059774844,0.002171649],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.017266257,0.00039061706,0.0004582978,0.0032353972,0.005499872,0.026731445,0.0020364171,0.0049971538,0.012594788],"category_scores_gemma":[0.021482822,0.00055510044,0.0006947261,0.009985577,0.008771038,0.033326108,0.009899976,0.0068303375,0.0043435637],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000149554835,0.000049057908,0.00049655035,0.0006072654,0.0000061269457,0.00025806515,0.009063204,0.00039791194,0.00019086107,0.49886864,0.26692334,0.22312395],"study_design_scores_gemma":[0.0000018075025,0.000007522683,0.000108484346,0.0005039134,0.000002103124,0.0001103229,0.0058233636,0.0001290396,0.00007240136,0.03007608,0.9631543,0.000010590366],"about_ca_topic_score_codex":0.012242497,"about_ca_topic_score_gemma":0.01787714,"teacher_disagreement_score":0.9979636,"about_ca_system_score_codex":0.0074398075,"about_ca_system_score_gemma":0.016267492,"threshold_uncertainty_score":0.09131378},"labels":[],"label_agreement":null},{"id":"W2975410001","doi":"10.22215/timreview/1265","title":"Smart Mobility: Services, Platforms and Ecosystems","year":2019,"lang":"en","type":"article","venue":"Technology Innovation Management Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Niche market; Niche; Business; Ecosystem services; Telecommunications; Transport engineering; Ecosystem; Computer science; Engineering; Marketing; Ecology","score_opus":0.007665171175118804,"score_gpt":0.22482855938600732,"score_spread":0.2171633882108885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2975410001","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036383166,0.8361816,0.008507802,0.020388503,0.0049064443,0.00006808163,0.00023620165,0.0001713607,0.12590173],"genre_scores_gemma":[0.057132628,0.89249134,0.0041651386,0.0044140667,0.0048482507,0.00006790297,0.0003195646,0.000055157685,0.036505997],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992459,0.00016644163,0.000057704307,0.000109881184,0.0003038877,0.000116276344],"domain_scores_gemma":[0.9992348,0.00026885534,0.000087410335,0.000049081686,0.00026661254,0.000093272414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069729105,0.0009117533,0.0005304534,0.0025657816,0.0008114676,0.004755202,0.00066554185,0.0022443475,0.009910053],"category_scores_gemma":[0.001149363,0.00020136786,0.00041320224,0.003566628,0.0022326016,0.0063662003,0.0020766696,0.0017088929,0.0024337603],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027230773,0.000046116413,0.00058553723,0.0043982794,0.000038476697,0.00024038604,0.0006570482,0.0015270456,0.0010101696,0.39555734,0.079745054,0.5161672],"study_design_scores_gemma":[0.0000014618971,0.0000207692,0.00044980503,0.0016619527,0.000010864151,0.0003879102,0.0003619704,0.00023951948,0.00017221613,0.028675674,0.96800673,0.000011137633],"about_ca_topic_score_codex":0.003971391,"about_ca_topic_score_gemma":0.0035010325,"teacher_disagreement_score":0.009910053,"about_ca_system_score_codex":0.0021922668,"about_ca_system_score_gemma":0.0025860232,"threshold_uncertainty_score":0.0331524},"labels":[],"label_agreement":null},{"id":"W2975866074","doi":"10.1287/mksc.2019.1187","title":"Mobile Hailing Technology and Taxi Driving Behaviors","year":2019,"lang":"en","type":"article","venue":"Marketing Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Business; Productivity; Marketing; Advertising; Mobile technology; Industrial organization; Information technology; Mobile device; Computer science; Economics; World Wide Web","score_opus":0.003114607355565924,"score_gpt":0.2153157878350974,"score_spread":0.21220118047953146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2975866074","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9968309,0.00018883034,0.00010167105,0.000099094264,0.000009812213,0.000014630769,0.00012208195,0.0000039320544,0.0026289793],"genre_scores_gemma":[0.99764144,0.00019784537,0.00015329124,0.000028256256,0.000011388743,0.000012755761,0.00013784067,0.0000026530213,0.0018144337],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99944514,0.00021105066,0.00003176737,0.000068771275,0.00012678791,0.000116497344],"domain_scores_gemma":[0.99389124,0.002243797,0.0021046763,0.00017108816,0.0005762503,0.0010128662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004870781,0.00027123347,0.00021800041,0.0007511628,0.0005342904,0.0015854585,0.00028592,0.00060717395,0.004292581],"category_scores_gemma":[0.0050207833,0.00016768616,0.00062136824,0.00083104067,0.00034144183,0.00061350025,0.0005386437,0.0009435401,0.0007064827],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029489005,0.0008564514,0.98948354,0.00004212489,0.00014961812,0.00007926737,0.00071170204,0.00021566018,0.00052096683,0.00015893143,0.00015341693,0.00733331],"study_design_scores_gemma":[0.0000050275776,0.00038269232,0.9968605,0.000015763402,0.00008709035,0.000067207206,0.0013052739,0.00042551916,0.00018708073,0.000062727995,0.0005936074,0.00000758703],"about_ca_topic_score_codex":0.019153746,"about_ca_topic_score_gemma":0.020578751,"teacher_disagreement_score":0.019153746,"about_ca_system_score_codex":0.0007178287,"about_ca_system_score_gemma":0.0005511955,"threshold_uncertainty_score":0.038084507},"labels":[],"label_agreement":null},{"id":"W2978716933","doi":"10.48550/arxiv.1910.00053","title":"A Price-Based Iterative Double Auction for Charger Sharing Markets","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Double auction; Computer science; Scheduling (production processes); Clearance; Microeconomics; Business; Economics; Operations management","score_opus":0.06941339855230898,"score_gpt":0.1915654675800541,"score_spread":0.12215206902774513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978716933","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027843341,0.00012716898,0.96543604,0.00020933455,0.00005895977,0.00019044247,0.00007575185,0.00024134413,0.0058176364],"genre_scores_gemma":[0.6765958,0.00020833181,0.31691512,0.00014385956,0.00006995493,0.00031871424,0.00018898101,0.00012092004,0.005438315],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966186,0.0013873463,0.00014508473,0.0004996149,0.0009112697,0.00043807592],"domain_scores_gemma":[0.99587363,0.0022621057,0.00042808562,0.00053515227,0.00057794375,0.0003230861],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035236932,0.0011022845,0.0018298834,0.00068267045,0.0008117874,0.0028491442,0.0033613641,0.0015893157,0.004594204],"category_scores_gemma":[0.011619104,0.00088128995,0.0014112104,0.0011571154,0.0014072673,0.0036567282,0.0023212612,0.0020802845,0.00075507275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031691443,0.00024621747,0.0008383646,0.0001566753,0.00009526275,0.00039389648,0.00019799458,0.8447931,0.004392526,0.100660235,0.002786291,0.045122456],"study_design_scores_gemma":[0.000048627106,0.00006340857,0.00007342929,0.0000064002106,0.000012541861,0.00007002263,0.000022474365,0.97370005,0.00054134073,0.024581071,0.0008644274,0.000016259126],"about_ca_topic_score_codex":0.0024889826,"about_ca_topic_score_gemma":0.0018744502,"teacher_disagreement_score":0.004594204,"about_ca_system_score_codex":0.0016328107,"about_ca_system_score_gemma":0.0032124538,"threshold_uncertainty_score":0.018635273},"labels":[],"label_agreement":null},{"id":"W2979419542","doi":"10.1109/tits.2019.2944134","title":"Car4Pac: Last Mile Parcel Delivery Through Intelligent Car Trip Sharing","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"TRIPS architecture; Leverage (statistics); Transport engineering; Last mile (transportation); Computer science; Mile; Operations research; Engineering; Geography; Artificial intelligence","score_opus":0.026905489490453117,"score_gpt":0.24128856573728738,"score_spread":0.21438307624683425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2979419542","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12127849,0.0005439261,0.8150102,0.00045612507,0.00023153439,0.00044152446,0.0022780453,0.049015466,0.010744758],"genre_scores_gemma":[0.74961525,0.0002309706,0.23711774,0.00019467952,0.00005324659,0.00021442113,0.0041550254,0.0008280688,0.00759057],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995701,0.000049593225,0.000014002425,0.00015116752,0.00011912417,0.00009595147],"domain_scores_gemma":[0.99928707,0.00009726389,0.00006898503,0.00029888953,0.00013653762,0.000111300884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000473233,0.0009778556,0.0008118067,0.00067544717,0.00061621965,0.00079788856,0.002796272,0.0007041449,0.0034368853],"category_scores_gemma":[0.0012868525,0.00031126713,0.00043699043,0.0009279171,0.0003272578,0.0014600792,0.0023092786,0.0008124192,0.0015045188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085873983,0.0004533854,0.0062376335,0.00028064987,0.00019834275,0.00045464997,0.00041946518,0.4515675,0.020176973,0.0102383355,0.05028405,0.4588303],"study_design_scores_gemma":[0.000035237164,0.000120099605,0.00075279723,0.000004952618,0.000019564686,0.00010084017,0.00008551993,0.9802106,0.004632664,0.0031231276,0.01089159,0.000023139044],"about_ca_topic_score_codex":0.011824141,"about_ca_topic_score_gemma":0.011646674,"teacher_disagreement_score":0.011824141,"about_ca_system_score_codex":0.0007102438,"about_ca_system_score_gemma":0.0013467734,"threshold_uncertainty_score":0.023510635},"labels":[],"label_agreement":null},{"id":"W2980423739","doi":"10.1093/ccc/tcz026","title":"A Desirable Future: Uber as Image-Making in Winnipeg","year":2019,"lang":"en","type":"article","venue":"Communication Culture and Critique","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Wilfrid Laurier University","funders":"Wilfrid Laurier University","keywords":"Vision; The Imaginary; Reputation; White (mutation); Indigenous; Sociology; Sociotechnical system; The Symbolic; Power (physics); Media studies; Political science; Management; Social science","score_opus":0.006945854866525326,"score_gpt":0.2636035830570885,"score_spread":0.25665772819056315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980423739","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7265185,0.0012028397,0.005341418,0.012716464,0.00022632415,0.00006221261,0.000041485957,0.00003929801,0.2538514],"genre_scores_gemma":[0.9883378,0.0002363422,0.000622845,0.00025647043,0.0000063394587,0.0000075252997,0.000006864866,0.000020234233,0.010505569],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9980475,0.0009713513,0.00003932581,0.0002384161,0.00030324058,0.000400094],"domain_scores_gemma":[0.9988759,0.00046130118,0.0001340799,0.0001003384,0.00020096915,0.00022738501],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00264643,0.00042918432,0.00022318133,0.0014054225,0.012786432,0.0098789595,0.000886252,0.001241779,0.0053516156],"category_scores_gemma":[0.003708875,0.00027321847,0.00017086676,0.0008780851,0.018539378,0.0042764395,0.0073482953,0.00172434,0.00022011323],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005178199,0.000018354276,0.0030190723,0.00006874388,0.00000668739,0.0013789503,0.71409297,0.00020069732,0.0012536611,0.258368,0.0025156296,0.019025508],"study_design_scores_gemma":[0.0000061389105,0.000024840903,0.0040873764,0.00013934477,0.000011379971,0.00042576433,0.7444491,0.0005131576,0.0010289475,0.01229283,0.23699091,0.000030136283],"about_ca_topic_score_codex":0.22386234,"about_ca_topic_score_gemma":0.28777578,"teacher_disagreement_score":0.77613765,"about_ca_system_score_codex":0.013933052,"about_ca_system_score_gemma":0.0065224064,"threshold_uncertainty_score":0.44511867},"labels":[],"label_agreement":null},{"id":"W2981066294","doi":"10.1109/tcomm.2019.2947509","title":"A Game-Theoretic Analysis for Complementary and Substitutable IoT Services Delivery With Externalities","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Research Foundation of Korea; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; National Science Foundation","keywords":"Stackelberg competition; Computer science; Service provider; Internet of Things; Service (business); Computer network; Backward induction; Game theory; Computer security; Business; Marketing","score_opus":0.016440721435037043,"score_gpt":0.23686351490469432,"score_spread":0.22042279346965726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2981066294","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.039856017,0.0007479217,0.908197,0.0017645785,0.00016596825,0.00026129704,0.0003255993,0.00010000097,0.048581615],"genre_scores_gemma":[0.91125965,0.001587846,0.06341584,0.00046133832,0.00020138068,0.00051705644,0.000188594,0.00007492271,0.02229335],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998123,0.0008108241,0.000062062325,0.0002536105,0.0003521594,0.00039824707],"domain_scores_gemma":[0.99694437,0.0020594522,0.00029142745,0.000083425875,0.0003537057,0.00026767992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024146251,0.0022818358,0.0016659375,0.0014449292,0.0014476465,0.0031746093,0.0021327608,0.0024798457,0.006584733],"category_scores_gemma":[0.0055551934,0.0009447585,0.0018873124,0.0012862073,0.0028623613,0.004629575,0.002138833,0.0028655205,0.00059784314],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068844594,0.00010279409,0.00037994894,0.00014513041,0.00007624888,0.00039046028,0.00020697547,0.39973244,0.0016923362,0.58943504,0.002548012,0.0052217455],"study_design_scores_gemma":[0.000027446205,0.00005406038,0.00017103845,0.00002688641,0.000034199336,0.000079463156,0.0000931006,0.8505542,0.00019809857,0.14700294,0.001727414,0.000031219253],"about_ca_topic_score_codex":0.010177783,"about_ca_topic_score_gemma":0.005980775,"teacher_disagreement_score":0.010177783,"about_ca_system_score_codex":0.0055307546,"about_ca_system_score_gemma":0.0034926778,"threshold_uncertainty_score":0.04012865},"labels":[],"label_agreement":null},{"id":"W29816525","doi":"","title":"Evaluating car sharing fleet management strategies using Discrete Event Simulation","year":2013,"lang":"en","type":"dissertation","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Discrete event simulation; Event (particle physics); Operations research; Service (business); Fleet management; Transport engineering; Incident management; Quality (philosophy); Order (exchange); Engineering; Computer science; Operations management; Simulation; Computer security; Business","score_opus":0.05479712188233327,"score_gpt":0.37564282660614434,"score_spread":0.3208457047238111,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W29816525","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9497312,0.00008935836,0.041570168,0.00011767438,0.000022910508,0.00036766482,0.00026541107,0.00012544246,0.0077102687],"genre_scores_gemma":[0.9870629,0.0000662239,0.011944394,0.000009743297,0.000002559889,0.00013008679,0.00013251431,0.000006724506,0.0006449056],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99888843,0.0006173696,0.000050338793,0.00008743922,0.0001983664,0.00015806824],"domain_scores_gemma":[0.9932153,0.0054348055,0.00037942483,0.00020576226,0.0005389766,0.00022571898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025307813,0.0008240069,0.0006602115,0.0010153077,0.0004149515,0.0013255286,0.00092826015,0.00078966503,0.0016651375],"category_scores_gemma":[0.0050377143,0.0003278511,0.0006947804,0.0006814149,0.00034042235,0.00082465576,0.00053335546,0.00064433255,0.00013632461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008747865,0.00013666518,0.0019375836,0.000017939468,0.000022319045,0.000016866154,0.000023265684,0.9935782,0.00046956626,0.0006155693,0.00005607215,0.0030385212],"study_design_scores_gemma":[0.000012209745,0.00013308313,0.0003274087,0.0000030330204,0.000008595571,0.0000019763156,0.00004400959,0.9987936,0.000464038,0.00013570719,0.00007206619,0.000004192475],"about_ca_topic_score_codex":0.026332716,"about_ca_topic_score_gemma":0.015056618,"teacher_disagreement_score":0.026332716,"about_ca_system_score_codex":0.0027105582,"about_ca_system_score_gemma":0.0015375782,"threshold_uncertainty_score":0.052358866},"labels":[],"label_agreement":null},{"id":"W2982141760","doi":"10.1109/mits.2019.2939037","title":"Special Section on Modeling &amp; Simulation of Application Scenarios for Autonomous Vehicles [Guest Editorial]","year":2019,"lang":"en","type":"article","venue":"IEEE Intelligent Transportation Systems Magazine","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Special section; Section (typography); Aeronautics; Computer science; Systems engineering; Engineering; Operations research; Telecommunications; Simulation; Engineering physics; Operating system","score_opus":0.02451721191787113,"score_gpt":0.2620340447631555,"score_spread":0.23751683284528438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982141760","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007753114,0.004539407,0.0009467962,0.0070974887,0.9832322,0.00002544092,0.00006377921,0.000108769214,0.0039086123],"genre_scores_gemma":[0.000838743,0.005754114,0.00029626943,0.0033461945,0.9745894,0.000028314327,0.000080222584,0.00014134176,0.014925328],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979576,0.0002570838,0.000230625,0.0004375794,0.00094968604,0.00016740987],"domain_scores_gemma":[0.9884343,0.0038150183,0.0007184489,0.00037619573,0.004891683,0.0017643032],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026555702,0.0026995223,0.0025675576,0.0028770072,0.0013850136,0.0045306077,0.0020446144,0.0055986363,0.033944808],"category_scores_gemma":[0.0076499744,0.0007418522,0.0016405736,0.0011557885,0.0011538892,0.0027939528,0.0014172656,0.0065479595,0.020533016],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042508535,0.000017590632,0.000036802146,0.00016783632,0.000013626654,0.00009297611,0.000008308069,0.00014709645,0.00028171352,0.0005803951,0.9864352,0.012175957],"study_design_scores_gemma":[0.000030057266,0.00008738713,0.0002363344,0.00023398323,0.000035093217,0.00032552093,0.00001303955,0.0007789699,0.00039405975,0.0013817808,0.9964652,0.000018496741],"about_ca_topic_score_codex":0.0006608315,"about_ca_topic_score_gemma":0.0014653604,"teacher_disagreement_score":0.033944808,"about_ca_system_score_codex":0.001272907,"about_ca_system_score_gemma":0.0012291676,"threshold_uncertainty_score":0.11355674},"labels":[],"label_agreement":null},{"id":"W2982579321","doi":"10.29173/mlj1139","title":"Bill 30: Redefining the Ride-Sharing Economy in Winnipeg","year":2019,"lang":"en","type":"article","venue":"Manitoba Law Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Okanagan University College; University of Manitoba; Okanagan Science Centre; Okanagan College","funders":"","keywords":"Sharing economy; Business; Economy; Economics; Political science; Law","score_opus":0.015548332537064218,"score_gpt":0.20720152057874858,"score_spread":0.19165318804168435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982579321","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.103957556,0.0027294697,0.008836855,0.21401757,0.005155898,0.001368194,0.0012284686,0.00043609412,0.66226983],"genre_scores_gemma":[0.24431829,0.001238471,0.004730041,0.090263404,0.00037666486,0.0006172627,0.00024773294,0.00019554714,0.6580125],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99453,0.0005409091,0.00015815356,0.00061063835,0.0016756615,0.002484573],"domain_scores_gemma":[0.9975883,0.00030741593,0.00011009066,0.00013459318,0.0008309402,0.0010286666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032098955,0.00095459475,0.00047327313,0.0011547551,0.011608086,0.0095043825,0.004026714,0.014337266,0.018121356],"category_scores_gemma":[0.010290966,0.0013639287,0.0009152501,0.00073347776,0.0037094373,0.0042536943,0.007425034,0.008062907,0.001581442],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010656192,0.00007225567,0.003488484,0.00010593755,0.000038285943,0.001636213,0.005026731,0.0015892762,0.0016160221,0.6573725,0.30669117,0.022256603],"study_design_scores_gemma":[0.00007857971,0.00006528225,0.0061409497,0.00018235655,0.00004945903,0.00026251457,0.003250806,0.0013186509,0.0011505701,0.012282713,0.97508335,0.00013472789],"about_ca_topic_score_codex":0.9127929,"about_ca_topic_score_gemma":0.9521114,"teacher_disagreement_score":0.08720708,"about_ca_system_score_codex":0.0326278,"about_ca_system_score_gemma":0.074717246,"threshold_uncertainty_score":0.23673236},"labels":[],"label_agreement":null},{"id":"W2982665629","doi":"10.1016/j.energy.2019.116321","title":"A sharing economy market system for private EV parking with consideration of demand side management","year":2019,"lang":"en","type":"article","venue":"Energy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ministry of Education of the People's Republic of China; National Natural Science Foundation of China; Diagnostic Services Manitoba","keywords":"Demand side; Sharing economy; Business; Industrial organization; Management system; Demand management; Commerce; Environmental economics; Market economy; Economics; Operations management; Computer science","score_opus":0.006229270379278574,"score_gpt":0.18140263055409353,"score_spread":0.17517336017481497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982665629","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24358094,0.0002027204,0.66935915,0.0011556556,0.00041119359,0.0009338755,0.00045095402,0.0019716728,0.08193384],"genre_scores_gemma":[0.9760711,0.000034748722,0.015867315,0.0000653846,0.000042206535,0.000099539815,0.000058007594,0.000050813785,0.007710809],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882704,0.00033707643,0.000047221303,0.00026340963,0.00026876587,0.0002564538],"domain_scores_gemma":[0.99918777,0.00016860334,0.000049351653,0.00013864979,0.00032276232,0.00013287904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001346424,0.0004926217,0.0010053148,0.00065577944,0.001591463,0.0026650692,0.0023306466,0.001360772,0.017077312],"category_scores_gemma":[0.0013982014,0.0003364365,0.0007666905,0.0006402242,0.00084104796,0.002762137,0.002243645,0.00073877245,0.001488683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011607584,0.0013362811,0.0026900538,0.00019907452,0.00015568992,0.0008721299,0.0003923288,0.5126722,0.026947739,0.2900234,0.017547233,0.14600313],"study_design_scores_gemma":[0.000055737433,0.00023609349,0.0005113528,0.000008879984,0.000035822435,0.00013387212,0.00011460336,0.9691079,0.0023086104,0.0219651,0.005473564,0.0000484306],"about_ca_topic_score_codex":0.003327393,"about_ca_topic_score_gemma":0.0042841034,"teacher_disagreement_score":0.017077312,"about_ca_system_score_codex":0.0016678927,"about_ca_system_score_gemma":0.0026884149,"threshold_uncertainty_score":0.057129264},"labels":[],"label_agreement":null},{"id":"W2983193830","doi":"10.1007/s13369-019-04216-8","title":"IoT Applications and Services for Connected and Autonomous Electric Vehicles","year":2019,"lang":"en","type":"article","venue":"Arabian Journal for Science and Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Automotive industry; The Internet; Computer science; Electric vehicle; Vehicular ad hoc network; Wireless ad hoc network; Telecommunications; Wireless; Engineering; World Wide Web","score_opus":0.006616435894791064,"score_gpt":0.21825185920008003,"score_spread":0.21163542330528898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2983193830","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2371283,0.017911071,0.2874393,0.007960025,0.0030512349,0.0005462605,0.0026510651,0.0061051827,0.43720752],"genre_scores_gemma":[0.8939608,0.00872408,0.027435584,0.0010305145,0.0005781178,0.00013883524,0.0027224235,0.0002702791,0.065139286],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999775,0.000033149663,0.000018244902,0.000028079314,0.00008617898,0.000059372127],"domain_scores_gemma":[0.9997458,0.0000370089,0.000022996623,0.000045141896,0.0001090331,0.00004006474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023045024,0.0004310417,0.00017078125,0.00070586725,0.00047218648,0.0012410117,0.0005797698,0.000801713,0.0072494675],"category_scores_gemma":[0.00043908594,0.00017066779,0.00034093228,0.0009559869,0.0002725823,0.0019276738,0.0012872675,0.00053964084,0.002346376],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005487238,0.000281052,0.016322592,0.0008777152,0.00009410705,0.0026878328,0.0012852825,0.008973753,0.08424984,0.10510594,0.08500706,0.69456613],"study_design_scores_gemma":[0.000033035773,0.00033877668,0.018173179,0.0004537892,0.00014247296,0.0032478224,0.0027435066,0.07681493,0.036484573,0.051474493,0.8100126,0.00008087418],"about_ca_topic_score_codex":0.0011914184,"about_ca_topic_score_gemma":0.0016202381,"teacher_disagreement_score":0.0072494675,"about_ca_system_score_codex":0.0003096171,"about_ca_system_score_gemma":0.0003887535,"threshold_uncertainty_score":0.024251938},"labels":[],"label_agreement":null},{"id":"W2984667781","doi":"10.1016/j.jth.2019.100701","title":"Turning the Tide from Cars to Active Transport: Policy Recommendations for New Zealand","year":2019,"lang":"en","type":"article","venue":"Journal of Transport & Health","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Transport policy; Oceanography; Environmental science; Geography; Business; Political science; Transport engineering; Geology; Engineering; Public transport","score_opus":0.021762383368979166,"score_gpt":0.30385899945335704,"score_spread":0.28209661608437786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2984667781","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0064328965,0.0069116247,0.0010889451,0.9519736,0.004242298,0.00031637988,0.00081360625,0.00015811007,0.02806253],"genre_scores_gemma":[0.15347724,0.041503802,0.02536606,0.6683528,0.0042882906,0.0022791685,0.0018078984,0.00026168264,0.10266318],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9929877,0.0014958251,0.0007642412,0.00051308924,0.0016962169,0.002543046],"domain_scores_gemma":[0.9650329,0.007925367,0.0024182855,0.00050771725,0.009590644,0.014525157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013271996,0.0013532599,0.0015684927,0.0021226157,0.0042397087,0.01406206,0.0038604708,0.03000067,0.05556669],"category_scores_gemma":[0.041354887,0.0010904211,0.0023721377,0.0022979851,0.0051370054,0.013720571,0.0062897946,0.016717248,0.003801322],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048729498,0.0005635948,0.0063082646,0.00436345,0.000119375894,0.0013438893,0.0066758366,0.002852732,0.001972364,0.068414845,0.8293395,0.07755895],"study_design_scores_gemma":[0.00088320236,0.00041156478,0.032468837,0.01156763,0.00029392907,0.00033691773,0.035014164,0.0023787566,0.00077293935,0.032599397,0.8827634,0.00050926796],"about_ca_topic_score_codex":0.64452565,"about_ca_topic_score_gemma":0.7373562,"teacher_disagreement_score":0.64452565,"about_ca_system_score_codex":0.019672858,"about_ca_system_score_gemma":0.15949535,"threshold_uncertainty_score":0.7151356},"labels":[],"label_agreement":null},{"id":"W2986051603","doi":"10.3390/electronics9010072","title":"On Car-Sharing Usage Prediction with Open Socio-Demographic Data","year":2020,"lang":"en","type":"article","venue":"Electronics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Provisioning; Computer science; Open data; Service provider; Service (business); Predictive modelling; Data science; Work (physics); Data mining; Machine learning; World Wide Web; Engineering; Business; Telecommunications; Marketing","score_opus":0.032334822929831766,"score_gpt":0.25136932260119715,"score_spread":0.2190344996713654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2986051603","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9577636,0.0012735444,0.021096881,0.0008155458,0.00013718464,0.00009536819,0.015657425,0.001240949,0.0019193689],"genre_scores_gemma":[0.9492395,0.00047811773,0.018374395,0.000115746436,0.00011626286,0.00007998971,0.030519553,0.000056012224,0.0010204378],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991248,0.00031624766,0.000057729572,0.00025242093,0.00014561738,0.00010306004],"domain_scores_gemma":[0.994389,0.0037116478,0.00040157692,0.00060051674,0.0006236899,0.00027359845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017836841,0.0013938181,0.0008242269,0.0032732484,0.00040846458,0.00091375265,0.0013246919,0.0014099516,0.0012699341],"category_scores_gemma":[0.006462562,0.00037053475,0.0008391564,0.0030330718,0.0003704484,0.0015060818,0.0010228135,0.0013002142,0.001402147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005430758,0.0012841737,0.41675583,0.00039317008,0.0003631351,0.0005531924,0.00028751843,0.40502727,0.0010547381,0.0010016189,0.014374042,0.1583622],"study_design_scores_gemma":[0.000010290096,0.000049714614,0.030541565,0.000040595394,0.000020364969,0.00007325074,0.00014964842,0.9667413,0.00038184554,0.0007493436,0.0012265344,0.00001555352],"about_ca_topic_score_codex":0.057404984,"about_ca_topic_score_gemma":0.061060082,"teacher_disagreement_score":0.057404984,"about_ca_system_score_codex":0.00084145647,"about_ca_system_score_gemma":0.000767303,"threshold_uncertainty_score":0.1141417},"labels":[],"label_agreement":null},{"id":"W2986111414","doi":"10.4018/978-1-5225-9570-0.ch018","title":"Operations Planning in Carsharing Systems","year":2019,"lang":"en","type":"book-chapter","venue":"Advances in logistics, operations, and management science book series","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Point (geometry); Computer science; Operations research; Network planning and design; Strategic planning; Transport engineering; Business; Engineering; Marketing; Telecommunications","score_opus":0.018063305883240136,"score_gpt":0.260240194422668,"score_spread":0.24217688853942787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2986111414","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020738993,0.020560589,0.6425254,0.003804967,0.0006072088,0.0003503764,0.0008109204,0.0004114097,0.31019014],"genre_scores_gemma":[0.5603179,0.045765802,0.24756238,0.00046165113,0.00054103485,0.0006893288,0.0018953389,0.0002680123,0.14249858],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947494,0.00017781576,0.000023961373,0.00010505648,0.00014577777,0.00007243545],"domain_scores_gemma":[0.9995641,0.00026637633,0.000039116618,0.0000183918,0.00007120137,0.000040717612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057532877,0.0012120203,0.00066867593,0.00092425395,0.0008629168,0.0033181312,0.0009878145,0.00088302733,0.01404345],"category_scores_gemma":[0.001266445,0.00063300895,0.0006165589,0.0037841268,0.0010508883,0.0021480047,0.0010402605,0.0014252947,0.0013693013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003094878,0.000079408834,0.00039711196,0.00034192635,0.000023382941,0.00017605862,0.00025720845,0.43505922,0.00048300964,0.44945526,0.018309908,0.09538665],"study_design_scores_gemma":[0.000020025958,0.000075334385,0.0006864493,0.00031757762,0.000021249647,0.000105500265,0.0008888818,0.50737613,0.0007947895,0.37289533,0.11676716,0.00005161338],"about_ca_topic_score_codex":0.015053761,"about_ca_topic_score_gemma":0.0126330955,"teacher_disagreement_score":0.015053761,"about_ca_system_score_codex":0.003140472,"about_ca_system_score_gemma":0.0029198313,"threshold_uncertainty_score":0.046980023},"labels":[],"label_agreement":null},{"id":"W2987361325","doi":"10.4018/978-1-5225-9570-0.ch029","title":"Location Planning of Electric Vehicles Charging Stations","year":2019,"lang":"en","type":"book-chapter","venue":"Advances in logistics, operations, and management science book series","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Charging station; Computer science; Genetic algorithm; Operations research; Electric vehicle; Real-time computing; Mathematical optimization; Simulation; Transport engineering; Engineering; Mathematics","score_opus":0.013679651289179024,"score_gpt":0.25476569657549464,"score_spread":0.2410860452863156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2987361325","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.059957154,0.0035586737,0.8546901,0.00057380757,0.00022974277,0.00012812723,0.0006258196,0.00076799974,0.079468615],"genre_scores_gemma":[0.69796777,0.0061188787,0.20801295,0.00009269958,0.00008936478,0.0001878962,0.00096355315,0.00017453378,0.086392395],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988174,0.000025607329,0.0000037242867,0.000033485863,0.00003360836,0.000021847865],"domain_scores_gemma":[0.9999442,0.000023171335,0.000006838181,0.0000039228394,0.000016000155,0.000005884074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014193714,0.00057610386,0.0004797612,0.0003833932,0.00035852275,0.0008643232,0.0008161211,0.0005627622,0.009037901],"category_scores_gemma":[0.0004114423,0.0003985319,0.00041645422,0.00098862,0.00021421022,0.00073874847,0.00046853392,0.00043807627,0.0012174492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006556004,0.000031693813,0.00052318064,0.00012215797,0.000014113354,0.00015126748,0.00007240866,0.8523482,0.0024731497,0.029338727,0.0051263836,0.10973321],"study_design_scores_gemma":[0.000019509167,0.00007105483,0.0004666763,0.000058460202,0.000020841864,0.00011677905,0.000166938,0.9449097,0.0034638161,0.020420926,0.03026022,0.000024954892],"about_ca_topic_score_codex":0.0047235694,"about_ca_topic_score_gemma":0.005649476,"teacher_disagreement_score":0.009037901,"about_ca_system_score_codex":0.00071668887,"about_ca_system_score_gemma":0.00080009125,"threshold_uncertainty_score":0.030234814},"labels":[],"label_agreement":null},{"id":"W2988421839","doi":"10.1145/3347146.3359064","title":"An Efficient Electric Vehicle Path-Planner That Considers the Waiting Time","year":2019,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Occupancy; Electric vehicle; Charging station; Probabilistic logic; Planner; Real-time computing; Range (aeronautics); Travel time; Operations research; Mathematical optimization; Simulation; Transport engineering; Engineering; Mathematics; Artificial intelligence","score_opus":0.006778573134705901,"score_gpt":0.1933727125470902,"score_spread":0.1865941394123843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2988421839","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043862622,0.0005591952,0.9448299,0.0003755749,0.00011312165,0.00027846865,0.0010271348,0.0020371017,0.0069169006],"genre_scores_gemma":[0.42924714,0.00042604163,0.56206167,0.000118927856,0.00004232156,0.00030827892,0.001931324,0.00037340476,0.005490938],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971694,0.000070457485,0.000014279512,0.00009050674,0.000054144333,0.00005363493],"domain_scores_gemma":[0.9994537,0.00033670236,0.00004344677,0.000045223922,0.000076633536,0.000044284043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005069683,0.0011075863,0.00074494944,0.0005602468,0.0004548008,0.0005661322,0.0010259183,0.00077571726,0.0044242195],"category_scores_gemma":[0.0015333724,0.00045724487,0.0006883033,0.0009468005,0.0003550935,0.00089227676,0.0007022755,0.0008957249,0.0005306514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000110704954,0.00007251552,0.0004889486,0.00011772013,0.000025573767,0.000055896875,0.000040747793,0.93055147,0.0011913533,0.0044655455,0.00326534,0.05961418],"study_design_scores_gemma":[0.000019387331,0.000038053262,0.00007964679,0.0000056080085,0.00001171682,0.00002298676,0.000022163314,0.99460864,0.00046366165,0.003161453,0.0015620386,0.0000045564575],"about_ca_topic_score_codex":0.008872671,"about_ca_topic_score_gemma":0.012272136,"teacher_disagreement_score":0.008872671,"about_ca_system_score_codex":0.0008332875,"about_ca_system_score_gemma":0.0029322668,"threshold_uncertainty_score":0.017642021},"labels":[],"label_agreement":null},{"id":"W2989825574","doi":"10.1155/2019/6125798","title":"Modeling and Prediction of Ride-Sharing Utilization Dynamics","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Israel Science Foundation","keywords":"TRIPS architecture; Traffic congestion; Computer science; Order (exchange); Transport engineering; Service (business); Sharing economy; Car sharing; Operations research; Engineering; Business; Marketing; Finance","score_opus":0.014578145931436639,"score_gpt":0.2353788146533024,"score_spread":0.22080066872186577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989825574","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9776953,0.00026028467,0.015316853,0.0004786425,0.00003457499,0.000029239722,0.004742723,0.00024889983,0.0011934921],"genre_scores_gemma":[0.9933658,0.00013946183,0.0030358268,0.000015588144,0.000010974566,0.000021442573,0.0028443348,0.000010895092,0.00055556226],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997876,0.000032852982,0.000014696155,0.00008946153,0.00002312658,0.000052335054],"domain_scores_gemma":[0.99933344,0.0002862694,0.0001425433,0.00008047193,0.00010189714,0.00005533736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000649858,0.0006503629,0.00042677033,0.0010083863,0.0002762593,0.00088735163,0.0010943807,0.00095958274,0.0009261219],"category_scores_gemma":[0.0020429378,0.00041029704,0.0006371138,0.0013351821,0.0004036918,0.001114873,0.00048330767,0.0010056079,0.00022232709],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004672347,0.000057834503,0.047162965,0.000029000226,0.000050889168,0.00007723421,0.00005463486,0.9459868,0.000578555,0.00076668814,0.00075481256,0.0044339364],"study_design_scores_gemma":[0.0000014571934,0.000005784832,0.0055444716,0.000002512513,0.000004324774,0.0000068503973,0.000024231704,0.9939805,0.000075149306,0.00018800705,0.00016367472,0.000003042502],"about_ca_topic_score_codex":0.12195711,"about_ca_topic_score_gemma":0.07878228,"teacher_disagreement_score":0.12195711,"about_ca_system_score_codex":0.0013144065,"about_ca_system_score_gemma":0.00078316784,"threshold_uncertainty_score":0.24249452},"labels":[],"label_agreement":null},{"id":"W2989872627","doi":"10.32866/10937","title":"Modeling the Purpose for Renting Passenger Vehicles","year":2019,"lang":"en","type":"article","venue":"Findings","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Renting; Multinomial logistic regression; Sample (material); Business; Econometrics; Term (time); Transport engineering; Statistics; Economics; Engineering; Mathematics","score_opus":0.015580958055202421,"score_gpt":0.22350098858590492,"score_spread":0.2079200305307025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989872627","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8625252,0.00075329456,0.105719894,0.0022511557,0.00008592902,0.00034250732,0.006379929,0.00033801055,0.021604002],"genre_scores_gemma":[0.9784465,0.00030756294,0.0091536315,0.000055004286,0.000018161441,0.00012851993,0.0013316772,0.00002811869,0.010530782],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894553,0.00040965856,0.00004152604,0.00018153542,0.00015608135,0.00026557167],"domain_scores_gemma":[0.99744415,0.0014332775,0.0004152336,0.00014455729,0.0004069053,0.00015588659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018310569,0.00061178533,0.0004985112,0.0017780546,0.00086062425,0.0024585228,0.0018839443,0.0012544744,0.004559956],"category_scores_gemma":[0.0058752396,0.0005834728,0.0010278715,0.0012990698,0.0008971714,0.0015793361,0.0011841304,0.0009874363,0.001115664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003264534,0.00052868726,0.37010464,0.00017706442,0.00020866889,0.00073124736,0.0017063501,0.45087945,0.00096426706,0.12925458,0.00611892,0.03899964],"study_design_scores_gemma":[0.000049134433,0.000103542916,0.04390718,0.00007292995,0.000116725045,0.00024539398,0.0009891496,0.9250936,0.00037276963,0.01991056,0.009069868,0.00006916852],"about_ca_topic_score_codex":0.26367137,"about_ca_topic_score_gemma":0.31142816,"teacher_disagreement_score":0.26367137,"about_ca_system_score_codex":0.004444985,"about_ca_system_score_gemma":0.0032442096,"threshold_uncertainty_score":0.5242733},"labels":[],"label_agreement":null},{"id":"W2990511679","doi":"10.1108/fs-05-2019-0044","title":"A foresight study on urban mobility: Singapore in 2040","year":2019,"lang":"en","type":"article","venue":"foresight","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Futures studies; Vision; Scenario planning; Originality; Government (linguistics); Urban planning; Transportation planning; Politics; Business; Environmental planning; Transport engineering; Computer science; Political science; Marketing; Engineering; Sociology; Geography; Civil engineering","score_opus":0.010306376656367258,"score_gpt":0.22086634554391607,"score_spread":0.2105599688875488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990511679","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95450073,0.00051779073,0.0012338621,0.011519609,0.00013184108,0.00022371982,0.00064858113,0.000019972704,0.031203862],"genre_scores_gemma":[0.9906034,0.0012831461,0.0010284629,0.0008685049,0.000022461785,0.000186266,0.00038767597,0.000012466578,0.0056076474],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99835014,0.0009579074,0.000078389785,0.00012027891,0.00018161452,0.00031166928],"domain_scores_gemma":[0.998058,0.0007215266,0.0002820955,0.0001326057,0.00036793647,0.00043778832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004455783,0.00043074778,0.0002110148,0.0009147802,0.004625591,0.0024615652,0.0005164795,0.0010431922,0.004673165],"category_scores_gemma":[0.0029547769,0.00035191383,0.0005174436,0.0016733236,0.001868253,0.0050711925,0.0031653664,0.0015345359,0.00043022848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018874159,0.00040098678,0.09704334,0.00071145874,0.000056497924,0.012814657,0.7670182,0.0033384266,0.0011652559,0.035877585,0.02479779,0.056586985],"study_design_scores_gemma":[0.000006116617,0.00020977404,0.02310158,0.00026449127,0.000013480892,0.0005289232,0.89982283,0.00068418705,0.0003494794,0.0024215442,0.07255465,0.000042963995],"about_ca_topic_score_codex":0.035792377,"about_ca_topic_score_gemma":0.09151365,"teacher_disagreement_score":0.035792377,"about_ca_system_score_codex":0.0061279684,"about_ca_system_score_gemma":0.005361312,"threshold_uncertainty_score":0.071168065},"labels":[],"label_agreement":null},{"id":"W2991582200","doi":"10.1016/j.dss.2019.113224","title":"A decision support system for home dialysis visit scheduling and nurse routing","year":2019,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ottawa Hospital; Wilfrid Laurier University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Telfer School of Management, University of Ottawa","keywords":"Workload; Medicine; Dialysis; Nursing; Overtime; Decision support system; Workflow; Operations management; Medical emergency; Computer science; Internal medicine; Database; Engineering","score_opus":0.012005630893697375,"score_gpt":0.25548859207335467,"score_spread":0.2434829611796573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991582200","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13280113,0.000602792,0.731,0.0019053564,0.00083846087,0.0011641303,0.006223554,0.1147519,0.010712655],"genre_scores_gemma":[0.6787746,0.00040906417,0.30225345,0.00083264185,0.00027120777,0.00073322776,0.005317283,0.00079790584,0.010610637],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993136,0.00012239734,0.00012780608,0.00017338034,0.00020945558,0.00005336568],"domain_scores_gemma":[0.99733186,0.00140628,0.00016755958,0.00023831765,0.0005460082,0.00030998143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013124745,0.00081352744,0.0010131139,0.0011341663,0.000810847,0.002143955,0.0012738154,0.0010477399,0.013325097],"category_scores_gemma":[0.004083632,0.00038470572,0.0005033205,0.00076555525,0.00024410221,0.0010640662,0.0008814726,0.00077600376,0.0026023423],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003915291,0.0015312135,0.014158262,0.00058535417,0.00036519693,0.0018176339,0.0005437859,0.13734399,0.03115085,0.008933476,0.07276626,0.72688866],"study_design_scores_gemma":[0.00038608848,0.00020457931,0.0024249188,0.00005017526,0.00012551754,0.00024919852,0.00008459661,0.95873255,0.01129957,0.004061728,0.022306444,0.00007460821],"about_ca_topic_score_codex":0.0067935926,"about_ca_topic_score_gemma":0.004488638,"teacher_disagreement_score":0.013325097,"about_ca_system_score_codex":0.00096545037,"about_ca_system_score_gemma":0.0019821508,"threshold_uncertainty_score":0.044576883},"labels":[],"label_agreement":null},{"id":"W2994665394","doi":"","title":"A pool-based approach to manage transportation and urgent request by EMS organizations","year":2018,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Engineering management; Business; Engineering","score_opus":0.008881526769674299,"score_gpt":0.20206153581361092,"score_spread":0.19318000904393662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2994665394","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06113258,0.00024805128,0.8963234,0.003425183,0.00024480766,0.0016348029,0.0009240892,0.0024502068,0.033616886],"genre_scores_gemma":[0.60984904,0.00023383115,0.36639777,0.0005801111,0.00018741829,0.001028472,0.0009446962,0.00023711355,0.020541478],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99677914,0.0013111931,0.00026539862,0.00063524727,0.0005082978,0.0005006974],"domain_scores_gemma":[0.9945979,0.0018061128,0.00048279518,0.00073757104,0.00135704,0.0010184646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005095393,0.00083828525,0.0013056359,0.0026818004,0.0030323262,0.0059806616,0.0036520704,0.0024168151,0.020920748],"category_scores_gemma":[0.008456547,0.00074462796,0.0013005424,0.002549339,0.0009733262,0.00681447,0.006031912,0.0011155455,0.0032435716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013399968,0.0020141187,0.017626848,0.0008327306,0.00059479236,0.0021843037,0.006303697,0.37095326,0.01569846,0.21112251,0.060313772,0.31101546],"study_design_scores_gemma":[0.00011792061,0.000514676,0.0022807561,0.000117696465,0.0001880239,0.00027594029,0.0048180274,0.8955764,0.003166323,0.05719135,0.0356351,0.000117729476],"about_ca_topic_score_codex":0.010030574,"about_ca_topic_score_gemma":0.011277898,"teacher_disagreement_score":0.020920748,"about_ca_system_score_codex":0.002222894,"about_ca_system_score_gemma":0.0062541696,"threshold_uncertainty_score":0.06998688},"labels":[],"label_agreement":null},{"id":"W2994771130","doi":"10.1155/2019/7878042","title":"Exploring the Performance of Different On-Demand Transit Services Provided by a Fleet of Shared Automated Vehicles: An Agent-Based Model","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Public transport; Service (business); Transport engineering; Transit (satellite); TRIPS architecture; Kilometer; Computer science; Intelligent transportation system; Operations research; Travel time; Service system; Level of service; Fleet management; Simulation; Engineering; Business","score_opus":0.018669507459118943,"score_gpt":0.234221779963214,"score_spread":0.21555227250409506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2994771130","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8480218,0.0003320161,0.129279,0.0007948926,0.00008461184,0.000185885,0.000755956,0.00027488795,0.02027096],"genre_scores_gemma":[0.9915764,0.00011116666,0.0036431672,0.000023347866,0.000008493351,0.000075887554,0.00013239746,0.000011911545,0.0044172574],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99976355,0.00006336014,0.000009564381,0.000043390955,0.000034224002,0.00008596754],"domain_scores_gemma":[0.99947244,0.0002153606,0.000102277205,0.00002460287,0.00010397923,0.00008132133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038233472,0.0009265507,0.0007059197,0.0005711973,0.00061418617,0.0013242844,0.0015715655,0.0018059526,0.0028173365],"category_scores_gemma":[0.0009388376,0.00049340696,0.0010436286,0.00048389588,0.0006600035,0.00096972473,0.0007794185,0.0008726614,0.00033253894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033017976,0.00002484648,0.00052691327,0.000007736231,0.000011492222,0.000041717783,0.000013588351,0.9975866,0.0002452033,0.0009181918,0.000080729944,0.00050987845],"study_design_scores_gemma":[0.000005285128,0.000015055786,0.00011302657,9.035651e-7,0.0000046265377,0.0000025776899,0.000010145139,0.9996093,0.00003124276,0.00015648085,0.0000495589,0.0000018052534],"about_ca_topic_score_codex":0.052528724,"about_ca_topic_score_gemma":0.020303508,"teacher_disagreement_score":0.052528724,"about_ca_system_score_codex":0.0016116035,"about_ca_system_score_gemma":0.00136521,"threshold_uncertainty_score":0.104445994},"labels":[],"label_agreement":null},{"id":"W2995723352","doi":"10.1155/2019/4603548","title":"Fully Autonomous Buses: A Literature Review and Future Research Directions","year":2019,"lang":"en","type":"review","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":123,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Office of Research and Engagement, University of Tennessee, Knoxville; University of Tennessee, Knoxville","keywords":"Software deployment; Autonomy; Business; Risk analysis (engineering); Transport engineering; Computer security; Engineering; Computer science; Political science","score_opus":0.033586869523180594,"score_gpt":0.3531966268559354,"score_spread":0.3196097573327548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995723352","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012783571,0.99870384,0.00008119983,0.0004535289,0.00012820712,0.000008988298,0.00003389257,0.000003724592,0.00045880207],"genre_scores_gemma":[0.00080144964,0.99859864,0.00017104505,0.00019109446,0.00008491215,0.000010797521,0.00003171223,0.0000013448018,0.000108950466],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985868,0.00034789604,0.0003664092,0.00020613967,0.0003934059,0.00009943198],"domain_scores_gemma":[0.9908585,0.0062320265,0.00085259153,0.00012620636,0.0017413845,0.00018920287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031409962,0.0011289944,0.002098796,0.0098081315,0.00074632163,0.0027942013,0.001413616,0.0017625114,0.0067627337],"category_scores_gemma":[0.008420877,0.0006481237,0.0020363533,0.009384953,0.000753365,0.0035977333,0.0010414376,0.0017741448,0.0012064651],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009428537,0.000085276784,0.0006222336,0.26456702,0.0003829385,0.00029405777,0.00060219556,0.00050882064,0.00063374045,0.0063365526,0.02794426,0.69792855],"study_design_scores_gemma":[0.00002449125,0.00015841593,0.0030037519,0.242183,0.0019417449,0.001196967,0.0010703437,0.0002111283,0.00038686744,0.00350866,0.74626154,0.000053036885],"about_ca_topic_score_codex":0.0052541564,"about_ca_topic_score_gemma":0.010521494,"teacher_disagreement_score":0.0098081315,"about_ca_system_score_codex":0.0018874884,"about_ca_system_score_gemma":0.008848262,"threshold_uncertainty_score":0.022623658},"labels":[],"label_agreement":null},{"id":"W2995882312","doi":"10.1155/2019/6895239","title":"Urban Arterial Road Optimization and Design Combined with HOV Carpooling under Connected Vehicle Environment","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Huaiyin Institute of Technology; Government of Jiangsu Province; National Natural Science Foundation of China","keywords":"VisSim; Traffic volume; Traffic congestion; Traffic flow (computer networking); Transport engineering; Scheme (mathematics); Road traffic; Computer science; Environmental science; Engineering; Computer network; Mathematics; Microsimulation","score_opus":0.006378563564565969,"score_gpt":0.18578791168297382,"score_spread":0.17940934811840784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995882312","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5745325,0.00016503895,0.41129088,0.0001029388,0.000055256824,0.00018529284,0.00010336101,0.00066880696,0.012895926],"genre_scores_gemma":[0.99169123,0.00003591444,0.007320114,0.000005098412,0.000003027163,0.00003512259,0.000028018518,0.00001164431,0.0008697307],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997348,0.000052823685,0.000009007647,0.00005492773,0.00006492951,0.000083458166],"domain_scores_gemma":[0.99976116,0.000050366445,0.000035787776,0.000029859346,0.00008731678,0.00003547996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024202414,0.0005037051,0.00039465725,0.0006274374,0.0004814606,0.0007614045,0.00087332434,0.0005597056,0.0013648948],"category_scores_gemma":[0.000540909,0.00027410843,0.0005727357,0.00043241892,0.00039112606,0.00055587845,0.00065922,0.00032246168,0.00016309695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000063717474,0.000051278228,0.0023050285,0.000051551142,0.000021115386,0.00014984558,0.000039904535,0.9693868,0.008057956,0.0012235658,0.00024042527,0.018408837],"study_design_scores_gemma":[0.00000873333,0.000099119854,0.0010684648,0.000002812109,0.000020119262,0.0000263844,0.000064815584,0.9954399,0.002296326,0.00051476853,0.00044910685,0.000009379116],"about_ca_topic_score_codex":0.0107068205,"about_ca_topic_score_gemma":0.009746762,"teacher_disagreement_score":0.0107068205,"about_ca_system_score_codex":0.0005229503,"about_ca_system_score_gemma":0.0010179019,"threshold_uncertainty_score":0.021288991},"labels":[],"label_agreement":null},{"id":"W2997916132","doi":"10.1504/ijsom.2020.10026105","title":"Carsharing customer demand forecasting using causal, time series and neural network methods: a case study","year":2020,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Exponential smoothing; Demand forecasting; Computer science; Autoregressive integrated moving average; Time series; Artificial neural network; Operations research; Service quality; Customer satisfaction; Service (business); Business; Marketing; Artificial intelligence; Machine learning","score_opus":0.036478361910206696,"score_gpt":0.30528396017292664,"score_spread":0.26880559826271994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2997916132","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9801276,0.00027666084,0.016017346,0.0004243875,0.000026549475,0.00008513123,0.00037707415,0.000101813945,0.0025634868],"genre_scores_gemma":[0.99047416,0.00021301502,0.008105857,0.000016685422,0.000012299622,0.000036825128,0.0001988319,0.000008604775,0.0009337554],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946445,0.00022357248,0.000038812184,0.00006327779,0.00013058604,0.00007922989],"domain_scores_gemma":[0.9967204,0.002473474,0.00015721773,0.00014415763,0.00041184816,0.00009292031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015095185,0.0006395644,0.00045303084,0.0010440765,0.0006358281,0.0008342381,0.0008997683,0.0016371188,0.0016066043],"category_scores_gemma":[0.0030687645,0.00033327844,0.0006657179,0.0015931291,0.00042437518,0.0009154698,0.000481683,0.0008802385,0.0001582576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058335945,0.0013926639,0.042009134,0.00029368085,0.000129764,0.0027764447,0.00042211916,0.8912948,0.00236235,0.0040074764,0.0021492646,0.052579015],"study_design_scores_gemma":[0.000019462826,0.00014149782,0.0054189954,0.000006084674,0.000017576056,0.000077501434,0.00026424005,0.9920493,0.0010963158,0.00044727675,0.00044395155,0.000017762814],"about_ca_topic_score_codex":0.04089427,"about_ca_topic_score_gemma":0.034139574,"teacher_disagreement_score":0.04089427,"about_ca_system_score_codex":0.0014689406,"about_ca_system_score_gemma":0.0006565452,"threshold_uncertainty_score":0.08131248},"labels":[],"label_agreement":null},{"id":"W2998221938","doi":"10.1061/(asce)cp.1943-5487.0000875","title":"Bilevel Decision-Support Model for Bus-Route Optimization and Accessibility Improvement for Seniors","year":2019,"lang":"en","type":"article","venue":"Journal of Computing in Civil Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Bilevel optimization; Public transport; Scheme (mathematics); Transit (satellite); Computer science; Genetic algorithm; Transport engineering; Disadvantaged; Operations research; Order (exchange); Decision support system; Service (business); Routing (electronic design automation); Optimization problem; Engineering; Computer network; Business; Economics","score_opus":0.011400763523986298,"score_gpt":0.2514294177485885,"score_spread":0.2400286542246022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2998221938","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04469118,0.0005740661,0.9391334,0.00067683076,0.0001346345,0.0001403153,0.0003245228,0.0002550843,0.014069927],"genre_scores_gemma":[0.90524805,0.00063532684,0.08124157,0.00014795047,0.00006526159,0.0005650035,0.0004434258,0.00004858278,0.0116048725],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905616,0.0003676694,0.000050381204,0.00018149597,0.00015018975,0.00019413639],"domain_scores_gemma":[0.998703,0.00073190936,0.00014416418,0.00004212721,0.00027738596,0.00010132292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001563956,0.0010426323,0.0019375752,0.0007825404,0.00080397975,0.0025923229,0.0016493967,0.0023023733,0.006550349],"category_scores_gemma":[0.003211286,0.0006785771,0.0013655482,0.0012973122,0.0008052307,0.0010297676,0.0018123966,0.0023804894,0.0005676286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039851042,0.00003519902,0.00032399208,0.00006648745,0.000017758288,0.000094377574,0.000049990696,0.985817,0.00025886684,0.009106254,0.00031124929,0.003878948],"study_design_scores_gemma":[0.000008482321,0.000019689442,0.000039573424,0.0000050601834,0.0000054332177,0.000005425544,0.00001544415,0.9977816,0.00005402833,0.0017161772,0.00034554512,0.0000036489632],"about_ca_topic_score_codex":0.013085611,"about_ca_topic_score_gemma":0.0081754085,"teacher_disagreement_score":0.013085611,"about_ca_system_score_codex":0.0015438403,"about_ca_system_score_gemma":0.0023197907,"threshold_uncertainty_score":0.026018858},"labels":[],"label_agreement":null},{"id":"W2999032258","doi":"10.1287/trsc.2019.0928","title":"Strategic Network Design for Parcel Delivery with Drones Under Competition","year":2020,"lang":"en","type":"article","venue":"Transportation Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Competition (biology); Drone; Service (business); Government (linguistics); Multinomial logistic regression; Service delivery framework; Business; Operations research; Computer science; Industrial organization; Marketing; Engineering","score_opus":0.0682763272352669,"score_gpt":0.24798068673100684,"score_spread":0.17970435949573993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2999032258","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10317261,0.00036007626,0.86894417,0.0006030654,0.00007574186,0.00021241054,0.00022754015,0.00014095209,0.026263416],"genre_scores_gemma":[0.91083753,0.00059158605,0.074776135,0.00015173365,0.000027650858,0.00018731994,0.00016155813,0.00007804874,0.013188399],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992754,0.00033838136,0.000014961485,0.00012819204,0.00010914487,0.00013392887],"domain_scores_gemma":[0.99867415,0.00078829756,0.00018239755,0.000034274788,0.00021249586,0.00010837403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012391442,0.00091852085,0.0007482283,0.0007222064,0.0005995787,0.0016861206,0.0010224511,0.0010790521,0.007936815],"category_scores_gemma":[0.0027629805,0.0006108834,0.0007110755,0.0007389981,0.0009583932,0.0017659949,0.0011716662,0.0011810501,0.0005126677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003915112,0.00002497984,0.0003136228,0.000037750968,0.000011269641,0.000090566245,0.000041675554,0.9692964,0.0009935419,0.024545986,0.0004795503,0.004125528],"study_design_scores_gemma":[0.000009403265,0.00004573248,0.00007859461,0.000005338885,0.000006348668,0.000019684943,0.000054934528,0.99207956,0.00019875685,0.00669959,0.0007961606,0.000005904013],"about_ca_topic_score_codex":0.010186462,"about_ca_topic_score_gemma":0.010587648,"teacher_disagreement_score":0.010186462,"about_ca_system_score_codex":0.002961291,"about_ca_system_score_gemma":0.0014950858,"threshold_uncertainty_score":0.026551247},"labels":[],"label_agreement":null},{"id":"W2999524808","doi":"10.1155/2020/7081628","title":"Quantifying the Impact of Rainfall on Taxi Hailing and Operation","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China","keywords":"Taxis; Global Positioning System; Transport engineering; Environmental science; Significant difference; Statistical analysis; Computer science; Statistics; Mathematics; Engineering","score_opus":0.02950323863203709,"score_gpt":0.29146549788678633,"score_spread":0.26196225925474925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2999524808","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99066305,0.00020184481,0.005437491,0.000052935615,0.00001638793,0.0000256406,0.0012622619,0.00006718154,0.0022732534],"genre_scores_gemma":[0.99817085,0.00012291943,0.0008900854,0.000005036227,0.000007648902,0.000006574639,0.00056040776,0.000006021134,0.00023048624],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995117,0.00013617892,0.000038428763,0.000076849494,0.00014429606,0.00009251819],"domain_scores_gemma":[0.9980804,0.0011002922,0.00044883272,0.00010252541,0.00020127463,0.000066645815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048762577,0.00037933284,0.00023225861,0.000853671,0.00015824779,0.00056450494,0.00021110817,0.00026581963,0.0010630535],"category_scores_gemma":[0.0023393624,0.00012254037,0.00030826754,0.0010559482,0.00021094519,0.00057970645,0.00032051545,0.00028492976,0.00018507092],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002768477,0.00015296959,0.79254013,0.00018013053,0.0002678953,0.00037214,0.00024104635,0.14144287,0.013788279,0.0007593042,0.00064602314,0.049332432],"study_design_scores_gemma":[0.000007199213,0.0003111659,0.8964648,0.000016995782,0.000094298586,0.00016444521,0.00082638586,0.09324001,0.007144691,0.0005028805,0.0011866746,0.000040429106],"about_ca_topic_score_codex":0.0065897685,"about_ca_topic_score_gemma":0.0075566904,"teacher_disagreement_score":0.0065897685,"about_ca_system_score_codex":0.00034335666,"about_ca_system_score_gemma":0.0002966956,"threshold_uncertainty_score":0.013102829},"labels":[],"label_agreement":null},{"id":"W3001414348","doi":"10.1155/2020/1275851","title":"Maximum Closeness Centrality <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\"><mml:mi>k</mml:mi></mml:math>-Clubs: A Study of Dock-Less Bike Sharing","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Closeness; Computer science; Algorithm; Centrality; Metric (unit); DOCK; Machine learning; Artificial intelligence; Mathematics; Combinatorics; Engineering","score_opus":0.021219970727138826,"score_gpt":0.2486240189252886,"score_spread":0.22740404819814977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3001414348","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10170794,0.0032726643,0.87403077,0.0020092018,0.00014564933,0.00013673592,0.00050256425,0.00022098944,0.017973473],"genre_scores_gemma":[0.84431916,0.0024675936,0.14374651,0.00024057778,0.0004480252,0.00015921418,0.0006027987,0.00027632876,0.007739861],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99598783,0.0018735144,0.00010623963,0.0010259361,0.00066883455,0.0003376551],"domain_scores_gemma":[0.9828037,0.011901102,0.0016622132,0.0012001875,0.0014099138,0.0010228817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030990664,0.0011179929,0.0015887098,0.00347493,0.0021474957,0.003911673,0.0032824418,0.0023054224,0.0036721618],"category_scores_gemma":[0.018212708,0.00074737496,0.0011870187,0.0049091335,0.002631987,0.0066482634,0.002569956,0.0019421957,0.0006298928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022670029,0.00013055153,0.008373142,0.00039325593,0.00022024658,0.00048821967,0.0011441917,0.2777193,0.0027353792,0.64651996,0.009378641,0.052670456],"study_design_scores_gemma":[0.000034117085,0.00009053411,0.0027132623,0.00009941331,0.00009758386,0.00046620503,0.00060163124,0.7497209,0.0011420425,0.2323927,0.012575652,0.0000660339],"about_ca_topic_score_codex":0.009222763,"about_ca_topic_score_gemma":0.008380116,"teacher_disagreement_score":0.009222763,"about_ca_system_score_codex":0.0040356354,"about_ca_system_score_gemma":0.0015166649,"threshold_uncertainty_score":0.029280722},"labels":[],"label_agreement":null},{"id":"W3003403390","doi":"10.1007/s12469-019-00222-z","title":"Analytical models for comparing operational costs of regular bus and semi-flexible transit services","year":2020,"lang":"en","type":"article","venue":"Public Transport","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Public transport; Transport engineering; Transit (satellite); Service (business); Schedule; Flexibility (engineering); Bus rapid transit; Level of service; Engineering; Computer science; Operations research; Business; Operating system","score_opus":0.043453394547196926,"score_gpt":0.23870747925041402,"score_spread":0.1952540847032171,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003403390","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5096662,0.0041555273,0.37604588,0.0030138085,0.00042929876,0.0008774657,0.004979319,0.0005101186,0.10032231],"genre_scores_gemma":[0.96172106,0.001425282,0.022158843,0.00011946322,0.00007206805,0.00037370675,0.0009824297,0.00009676973,0.013050329],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99854916,0.0005816655,0.000051300794,0.00014574124,0.00026822745,0.0004038816],"domain_scores_gemma":[0.99134046,0.006945962,0.00056249066,0.00021429926,0.0007166002,0.00022017623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030939216,0.0013114999,0.0011497025,0.0030334927,0.0008362883,0.003578821,0.004242584,0.0019544882,0.012552188],"category_scores_gemma":[0.015336554,0.0009796385,0.0020162151,0.0038984003,0.0011870204,0.002785344,0.00095283746,0.0017883809,0.00063850614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010327319,0.0001019144,0.0009204564,0.00008456973,0.000034322362,0.000064701206,0.00007623679,0.94598615,0.00020437545,0.044505995,0.0015471852,0.0063707223],"study_design_scores_gemma":[0.000028685745,0.00005315069,0.0011148978,0.00004043757,0.000062956955,0.000033273474,0.0002580344,0.97883075,0.00014403624,0.017974572,0.0014388083,0.000020509853],"about_ca_topic_score_codex":0.04416131,"about_ca_topic_score_gemma":0.03318747,"teacher_disagreement_score":0.04416131,"about_ca_system_score_codex":0.0093478495,"about_ca_system_score_gemma":0.0044884463,"threshold_uncertainty_score":0.08780855},"labels":[],"label_agreement":null},{"id":"W3004281979","doi":"10.1155/2020/8935857","title":"Demand Management of Station-Based Car Sharing System Based on Deep Learning Forecasting","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China; National Science Foundation","keywords":"Computer science; Service (business); Car sharing; Metropolitan area; Term (time); Real-time computing; Perspective (graphical); Deep learning; Artificial intelligence; Operations research; Transport engineering; Engineering","score_opus":0.015420806734694995,"score_gpt":0.2228853990369586,"score_spread":0.2074645923022636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3004281979","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7710541,0.00016928837,0.22348906,0.0003816981,0.00004205899,0.000039662038,0.0003301062,0.00079673587,0.0036972875],"genre_scores_gemma":[0.9968143,0.000015589985,0.0026180556,0.0000130207045,0.000004408169,0.000007684164,0.00008785552,0.000006553043,0.00043255428],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998411,0.000021376703,0.000010790704,0.00004633924,0.00003071776,0.00004961717],"domain_scores_gemma":[0.99968517,0.000120098186,0.000051147512,0.000025188596,0.00008938739,0.000029111365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003595556,0.0005892411,0.00048188184,0.0003877348,0.000252262,0.0004954672,0.00073743664,0.00051205506,0.001018713],"category_scores_gemma":[0.0008854158,0.00022898997,0.0003010592,0.00036525473,0.00020871586,0.00075657264,0.0004486191,0.000626313,0.00016871291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000081573824,0.00008868564,0.0066820844,0.000018461731,0.000026916872,0.00006088414,0.000044961787,0.9642118,0.0023877488,0.0005889587,0.0005675212,0.02524042],"study_design_scores_gemma":[4.2273254e-7,0.0000039748666,0.00027122168,2.7182122e-7,0.0000010433696,0.000001224326,0.000003443788,0.9994537,0.00014410917,0.00010447945,0.000015018083,0.0000010765974],"about_ca_topic_score_codex":0.018591644,"about_ca_topic_score_gemma":0.015035248,"teacher_disagreement_score":0.018591644,"about_ca_system_score_codex":0.00084332586,"about_ca_system_score_gemma":0.00050686346,"threshold_uncertainty_score":0.03696686},"labels":[],"label_agreement":null},{"id":"W3005708921","doi":"10.1155/2020/3271608","title":"An Efficient Solving Method to Vehicle and Passenger Matching Problem for Sharing Autonomous Vehicle System","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China; National Science Foundation","keywords":"Matching (statistics); Computer science; Key (lock); Perspective (graphical); Cluster (spacecraft); Similarity (geometry); Travel time; Sensitivity (control systems); Transport engineering; Operations research; Mathematical optimization; Simulation; Engineering; Computer network; Artificial intelligence; Computer security; Mathematics; Statistics","score_opus":0.012266708352804518,"score_gpt":0.26577666459003096,"score_spread":0.25350995623722644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3005708921","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016704129,0.00028291,0.9781382,0.00016365458,0.000059476395,0.00013422527,0.000080694736,0.00019129181,0.004245433],"genre_scores_gemma":[0.5904407,0.0005230178,0.3987053,0.00015870281,0.00012858937,0.0005183907,0.0004569072,0.00012038578,0.008947997],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994881,0.000119748474,0.000029350076,0.00013847485,0.00009932394,0.00012496911],"domain_scores_gemma":[0.9995492,0.00022685793,0.000034987763,0.000023815432,0.00012910932,0.00003587189],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091221725,0.0010115346,0.001332159,0.00067706546,0.00092226453,0.0011500606,0.0014044452,0.00108904,0.0064277095],"category_scores_gemma":[0.0014577273,0.00043487354,0.0010978162,0.0008575382,0.00037988054,0.0010607303,0.0012393567,0.0010756821,0.0005053915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009540821,0.000075793716,0.0008778791,0.00019156683,0.000042002703,0.00010698051,0.00010811198,0.90767914,0.0015175719,0.0131846415,0.0029086045,0.073212355],"study_design_scores_gemma":[0.000010172232,0.00002104624,0.000067791705,0.0000036429153,0.0000065033837,0.000015608292,0.000028669712,0.99604803,0.00016521582,0.003016324,0.00061340886,0.000003567263],"about_ca_topic_score_codex":0.013197287,"about_ca_topic_score_gemma":0.007527915,"teacher_disagreement_score":0.013197287,"about_ca_system_score_codex":0.000932122,"about_ca_system_score_gemma":0.0021949627,"threshold_uncertainty_score":0.026240885},"labels":[],"label_agreement":null},{"id":"W3005815104","doi":"10.1016/j.jterra.2019.12.001","title":"Erratum to ‘A review of mobility metrics for next generation vehicle mobility models’ [Terramechanics 87 (2020) 11–20]","year":2019,"lang":"en","type":"erratum","venue":"Journal of Terramechanics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Mobility model; Computer science; Computer network","score_opus":0.06060858183929889,"score_gpt":0.28307118685941757,"score_spread":0.22246260502011866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3005815104","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00059059705,0.04647792,0.010693491,0.13003007,0.77785534,0.00012274501,0.008589478,0.00070753467,0.02493284],"genre_scores_gemma":[0.02135578,0.16317275,0.049917243,0.14323936,0.22822846,0.00072253606,0.034945477,0.0033682282,0.3550502],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.994719,0.0010143345,0.0010317288,0.00047029,0.0025475891,0.00021699406],"domain_scores_gemma":[0.9664101,0.00687953,0.001603187,0.0010171189,0.023552664,0.00053738354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005735718,0.0021391313,0.0017153061,0.005780293,0.0016168854,0.0038624257,0.002961912,0.0040341443,0.034688283],"category_scores_gemma":[0.04641164,0.00074336666,0.0013857062,0.005108778,0.0017255298,0.004345352,0.0018569052,0.006277605,0.024630608],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014708055,0.000004339391,0.0000707802,0.00025467644,0.0000075535045,0.000037002745,0.000017289136,0.00014769346,0.00003721395,0.0031265288,0.983452,0.012830178],"study_design_scores_gemma":[0.000012922465,0.000023588665,0.0005465852,0.00093462487,0.00002485702,0.00013676187,0.00006288547,0.0004065259,0.00014790134,0.0031173616,0.9945475,0.000038643906],"about_ca_topic_score_codex":0.036453456,"about_ca_topic_score_gemma":0.036707234,"teacher_disagreement_score":0.036453456,"about_ca_system_score_codex":0.0038189758,"about_ca_system_score_gemma":0.006955827,"threshold_uncertainty_score":0.116043925},"labels":[],"label_agreement":null},{"id":"W3006594710","doi":"10.1109/tits.2020.2976568","title":"Modeling, Relocation, and Real-Time Inventory Control of One-Way Electric Cars Sharing Systems in a Stochastic Petri Nets Framework","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Relocation; TRIPS architecture; Petri net; Computer science; Process (computing); Discrete event simulation; Stochastic Petri net; Operations research; Simulation; Engineering; Real-time computing; Distributed computing; Transport engineering","score_opus":0.026627809873143293,"score_gpt":0.23418288802397255,"score_spread":0.20755507815082927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006594710","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07415031,0.00035258208,0.9165266,0.00021082872,0.00009514111,0.000108776905,0.0002447952,0.00039249248,0.007918316],"genre_scores_gemma":[0.9750123,0.00031039797,0.019318497,0.000035335568,0.000024746245,0.00016101944,0.0001279031,0.000031828975,0.0049778735],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994222,0.00014321602,0.000035107445,0.00014300313,0.00013273972,0.00012372277],"domain_scores_gemma":[0.99938524,0.00028008086,0.00014138121,0.000020314856,0.0001266358,0.000046277313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008921076,0.0010058087,0.0009135115,0.00053951977,0.0004834344,0.001444689,0.0013901283,0.0008285559,0.0015168302],"category_scores_gemma":[0.0010081648,0.0004890013,0.0009437573,0.0005607137,0.0009696554,0.00071377185,0.000683717,0.0008433147,0.00017803094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011274011,0.0000065754393,0.00015701324,0.000010114472,0.000007377709,0.00003070817,0.000011337917,0.995427,0.00031334878,0.0032455237,0.000048912098,0.0007307148],"study_design_scores_gemma":[0.0000024894525,0.0000062678537,0.00004993789,0.000001330646,0.0000037381799,0.0000031528234,0.000003977504,0.999151,0.00007457994,0.0006251003,0.00007623702,0.000002197766],"about_ca_topic_score_codex":0.044265404,"about_ca_topic_score_gemma":0.023350546,"teacher_disagreement_score":0.044265404,"about_ca_system_score_codex":0.0017483417,"about_ca_system_score_gemma":0.0022288829,"threshold_uncertainty_score":0.0880155},"labels":[],"label_agreement":null},{"id":"W3006892492","doi":"","title":"Comparison Of Self-Declared Mobile Use While Driving In Canada, The United States, And Europe","year":2018,"lang":"en","type":"article","venue":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Political science","score_opus":0.0233693453016581,"score_gpt":0.25545885451672423,"score_spread":0.23208950921506613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006892492","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9873197,0.0021113094,0.00009203452,0.000182857,0.000022434242,0.00003554516,0.0058043124,0.000012410284,0.0044194604],"genre_scores_gemma":[0.991488,0.002102643,0.000135691,0.000103799866,0.000008424825,0.000025072562,0.00497787,0.000012783239,0.0011457828],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99785393,0.00016625701,0.0002567604,0.00026368562,0.00095410895,0.0005052974],"domain_scores_gemma":[0.99357295,0.00050592603,0.00075473613,0.00014135745,0.0040330426,0.000992031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001326676,0.0003309882,0.0006414632,0.004513789,0.0015379662,0.0023044464,0.0010527922,0.00044993006,0.0018137159],"category_scores_gemma":[0.004388164,0.00025303932,0.0009902583,0.007594081,0.0008462201,0.00060016505,0.0014611551,0.0005444348,0.000282083],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002070196,0.0000314386,0.98770475,0.00012690532,0.00023711343,0.00013625786,0.0024850685,0.00013206729,0.00015665813,0.00020411896,0.0009402429,0.0076382076],"study_design_scores_gemma":[0.0000027977308,0.000014713684,0.9964561,0.00004681907,0.00002653183,0.000048875,0.0025676226,0.00006011281,0.00004311497,0.000010323582,0.00071085186,0.000012216165],"about_ca_topic_score_codex":0.977767,"about_ca_topic_score_gemma":0.98194,"teacher_disagreement_score":0.02223301,"about_ca_system_score_codex":0.011450706,"about_ca_system_score_gemma":0.0137480935,"threshold_uncertainty_score":0.08308107},"labels":[],"label_agreement":null},{"id":"W3007054387","doi":"10.1155/2020/8674512","title":"Multiagent Reinforcement Learning-Based Taxi Predispatching Model to Balance Taxi Supply and Demand","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Changchun Science and Technology Bureau; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Taxis; Reinforcement learning; Computer science; Scheduling (production processes); Operations research; Profit (economics); Public transport; Transport engineering; Engineering; Artificial intelligence; Operations management; Economics","score_opus":0.010932843815160865,"score_gpt":0.2308156951688306,"score_spread":0.21988285135366975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007054387","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16267172,0.0005676623,0.8229471,0.00077481166,0.00018096832,0.0001616531,0.00036994932,0.0008179537,0.01150822],"genre_scores_gemma":[0.9808889,0.00012662014,0.013059472,0.00007916224,0.00002574938,0.00011788156,0.00010377376,0.000020864678,0.005577618],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996044,0.00009039891,0.000022342547,0.00013075535,0.0000696848,0.00008246597],"domain_scores_gemma":[0.99925095,0.00030091795,0.00016107653,0.000029143599,0.0001820921,0.00007579573],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007436486,0.0007453471,0.001175971,0.0003667967,0.00043978967,0.00085808587,0.0013550739,0.0008506221,0.0032393408],"category_scores_gemma":[0.0014042344,0.00038481006,0.0006201031,0.00038259925,0.00050764915,0.0007772134,0.0006105341,0.0010995001,0.0003672134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003594023,0.000032960645,0.00078767305,0.000022486274,0.000023414426,0.00007173114,0.000022758735,0.9918933,0.0003724146,0.001852147,0.00036567377,0.004519591],"study_design_scores_gemma":[0.0000058276605,0.000008081622,0.0001019718,9.976704e-7,0.0000046146292,0.000004258024,0.0000026143018,0.9994487,0.000043014283,0.0003014118,0.000076458025,0.0000020984878],"about_ca_topic_score_codex":0.025322158,"about_ca_topic_score_gemma":0.013324997,"teacher_disagreement_score":0.025322158,"about_ca_system_score_codex":0.0012360087,"about_ca_system_score_gemma":0.001214003,"threshold_uncertainty_score":0.050349534},"labels":[],"label_agreement":null},{"id":"W3007181818","doi":"10.1016/j.retrec.2020.100828","title":"Analysis of consumer attitudes towards autonomous, connected, and electric vehicles: A survey in China","year":2020,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":121,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; University of Toronto","funders":"National Key Research and Development Program of China; Beijing Municipal Commission of Education; National Natural Science Foundation of China","keywords":"Business; China; Service (business); Liability; Transport engineering; Marketing; Electric vehicle; Environmental economics; Engineering; Finance; Economics","score_opus":0.07464968264254536,"score_gpt":0.3192091382952694,"score_spread":0.24455945565272408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007181818","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99961734,0.000022273525,0.000014357791,0.000030692612,0.0000011675412,0.000002552137,0.00005483921,5.345847e-7,0.00025623335],"genre_scores_gemma":[0.99934024,0.000058265698,0.000021633256,0.000034324185,0.0000018247987,0.0000034011161,0.00010990099,5.6799604e-7,0.00042979626],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996338,0.000055528682,0.000038046164,0.00006529414,0.000106076994,0.00010131315],"domain_scores_gemma":[0.9990497,0.00014610036,0.00026209303,0.00004051995,0.00019053061,0.00031092932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051347347,0.00023582418,0.00021293486,0.0009208509,0.0007284599,0.00052515464,0.00027442328,0.0004771984,0.002097067],"category_scores_gemma":[0.00071917207,0.00030163093,0.0005003218,0.0015535894,0.00039943733,0.00054558285,0.00034795052,0.00042951197,0.00021590762],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029891906,0.00009389366,0.9957141,0.000013978424,0.00003295289,0.00010561098,0.0016386647,0.000054442735,0.00033724812,0.00006268921,0.000121004865,0.0017955621],"study_design_scores_gemma":[0.0000019395561,0.00004548318,0.99749315,0.0000036924507,0.000009153609,0.000043205226,0.0020115734,0.00016654977,0.000039039143,0.000014006725,0.00016792008,0.000004215837],"about_ca_topic_score_codex":0.07240764,"about_ca_topic_score_gemma":0.087248586,"teacher_disagreement_score":0.07240764,"about_ca_system_score_codex":0.0010728483,"about_ca_system_score_gemma":0.00094055705,"threshold_uncertainty_score":0.14397234},"labels":[],"label_agreement":null},{"id":"W3009095099","doi":"10.1177/0361198120909842","title":"Spatial Characteristics of Transit-Integrated Ridesourcing Trips and Their Competitiveness with Transit and Walking Alternatives","year":2020,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"TRIPS architecture; Transit (satellite); Transport engineering; Public transport; Engineering","score_opus":0.050645393234185834,"score_gpt":0.29880060149120297,"score_spread":0.24815520825701715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3009095099","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988789,0.00003273618,0.00007149374,0.000008315789,5.801916e-7,0.000009768211,0.00024134295,0.0000018381513,0.00075510645],"genre_scores_gemma":[0.9990393,0.00004745881,0.00012698045,0.0000018153979,0.0000010089055,0.00000708719,0.00036225442,0.0000018697126,0.00041232142],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996308,0.000062759886,0.000050314175,0.00006378384,0.000113474525,0.00007889597],"domain_scores_gemma":[0.9978483,0.00037041545,0.00082353095,0.00013448288,0.00056981255,0.00025350298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003969625,0.00016692234,0.00019796324,0.0015897297,0.00043493556,0.00096801977,0.00042397768,0.00020112035,0.0030947516],"category_scores_gemma":[0.0028054416,0.00011928616,0.0003587811,0.0030183455,0.00050113176,0.0005583019,0.00075309735,0.00018401323,0.0003280503],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000069686575,0.00002338818,0.9924204,0.000022162267,0.000031589512,0.00017107824,0.0018012634,0.0002100665,0.0006117343,0.0000981092,0.000082021004,0.004458554],"study_design_scores_gemma":[6.8228303e-7,0.00002860151,0.99536586,0.000004317288,0.0000051540023,0.00007620134,0.0040240157,0.00016898524,0.000036792582,0.000014106776,0.00027202247,0.0000031877864],"about_ca_topic_score_codex":0.1176349,"about_ca_topic_score_gemma":0.20929596,"teacher_disagreement_score":0.1176349,"about_ca_system_score_codex":0.00082469155,"about_ca_system_score_gemma":0.00059470406,"threshold_uncertainty_score":0.23390037},"labels":[],"label_agreement":null},{"id":"W3009252341","doi":"10.1155/2020/4680959","title":"Capturing the Characteristics of Car-Sharing Users: Data-Driven Analysis and Prediction Based on Classification","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Renting; Computer science; Lease; Scrolling; Cluster analysis; Categorization; Business; Engineering; Artificial intelligence","score_opus":0.03160745834784723,"score_gpt":0.25121119981681134,"score_spread":0.2196037414689641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3009252341","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98431814,0.000070133014,0.013618519,0.00016240099,0.000016604346,0.00006336207,0.0011829835,0.00016138604,0.00040644166],"genre_scores_gemma":[0.9914547,0.000040946983,0.006480049,0.000017928858,0.000011263547,0.000041565163,0.0017213607,0.0000068527893,0.00022537581],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916375,0.00022503638,0.000087921944,0.00020629025,0.00017959833,0.00013737359],"domain_scores_gemma":[0.9956801,0.002434993,0.00054424035,0.00036769416,0.0007246845,0.0002483953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014460166,0.00080316426,0.0006958058,0.0021607894,0.0003688524,0.00086263206,0.0007568135,0.0008332212,0.0005188101],"category_scores_gemma":[0.0042468854,0.00027799993,0.00084993173,0.0016664641,0.0002932881,0.0008859044,0.0004723496,0.0008088112,0.0003135734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003503385,0.0009293108,0.8062826,0.00009617514,0.00018203676,0.0002795262,0.0005211933,0.12248658,0.0030809038,0.00046269855,0.0014216036,0.063907094],"study_design_scores_gemma":[0.000004502088,0.00007051221,0.11531294,0.000007952834,0.000020505493,0.000056820263,0.00021358982,0.8829441,0.0008562831,0.00027217137,0.00022118178,0.000019459234],"about_ca_topic_score_codex":0.026541205,"about_ca_topic_score_gemma":0.018473964,"teacher_disagreement_score":0.026541205,"about_ca_system_score_codex":0.0007886231,"about_ca_system_score_gemma":0.00058188115,"threshold_uncertainty_score":0.052773416},"labels":[],"label_agreement":null},{"id":"W3010220509","doi":"10.1287/trsc.2021.1042","title":"Dynamic Ride-Hailing with Electric Vehicles","year":2021,"lang":"en","type":"preprint","venue":"Transportation Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada; HEC Montréal","funders":"HEC Montréal; Institut de Valorisation des Données; Agence Nationale de la Recherche","keywords":"Automotive engineering; Computer science; Aeronautics; Engineering","score_opus":0.010824230880328961,"score_gpt":0.24561652637769224,"score_spread":0.23479229549736327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010220509","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8639297,0.00064792525,0.116457224,0.0021446228,0.00018682316,0.00017241151,0.0011565876,0.0006398895,0.014664806],"genre_scores_gemma":[0.9855055,0.000112980226,0.010765474,0.00008334844,0.000016694934,0.000044784054,0.00047446665,0.000033945696,0.0029628286],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99967027,0.00009700506,0.000009978531,0.00008463547,0.000035601122,0.00010244136],"domain_scores_gemma":[0.99851555,0.0009499008,0.00013858147,0.00009550288,0.00010861691,0.00019192595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000828659,0.0009777639,0.0008398492,0.0004373484,0.0005725924,0.0007603397,0.0015189811,0.0014661254,0.005606239],"category_scores_gemma":[0.0035910797,0.00041047295,0.0005687331,0.0005522207,0.001267938,0.0016485191,0.0008001026,0.0016702597,0.00035212206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000111690664,0.00006273871,0.0009806604,0.000024047922,0.000015093692,0.00009439939,0.000013715769,0.9929041,0.00016823728,0.0017127715,0.0008409258,0.0030716138],"study_design_scores_gemma":[0.000021651495,0.00002447306,0.00027405325,0.000004146412,0.000003794623,0.000010105425,0.00002821666,0.99707794,0.00021027126,0.0019112251,0.00042984917,0.000004351482],"about_ca_topic_score_codex":0.035016164,"about_ca_topic_score_gemma":0.032644436,"teacher_disagreement_score":0.035016164,"about_ca_system_score_codex":0.001802237,"about_ca_system_score_gemma":0.0011218874,"threshold_uncertainty_score":0.06962472},"labels":[],"label_agreement":null},{"id":"W3010547523","doi":"10.29173/mlj1140","title":"Bill 30: The Local Vehicles for Hire Act: Manitoba’s Controversial Approach to Ride Sharing Services","year":2019,"lang":"en","type":"article","venue":"Manitoba Law Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Car sharing; Transport engineering; Telecommunications; Public administration; Engineering; Political science","score_opus":0.012986261872811336,"score_gpt":0.20704169829797137,"score_spread":0.19405543642516004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010547523","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.035169173,0.0018552821,0.002047919,0.28133816,0.0055343374,0.0014609933,0.0026148704,0.00044267563,0.66953653],"genre_scores_gemma":[0.05074924,0.0006658661,0.0012327919,0.28427076,0.0007641939,0.0007316666,0.00035673546,0.00012802857,0.6611007],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.98734355,0.0012312526,0.00054506655,0.0012607299,0.0046363804,0.004983024],"domain_scores_gemma":[0.99030226,0.0028059094,0.000451909,0.00050164794,0.003883597,0.0020546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069796513,0.0019184037,0.001378633,0.002146889,0.031791095,0.016018404,0.008456763,0.06710557,0.033689152],"category_scores_gemma":[0.016230464,0.0038068497,0.002013908,0.002178581,0.0066246027,0.0034932103,0.005557304,0.028390383,0.011477656],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001303456,0.0003641405,0.004739659,0.00011120144,0.00007966004,0.001666903,0.0046093413,0.0006300835,0.0018516835,0.22030418,0.75856394,0.0069487854],"study_design_scores_gemma":[0.0002837039,0.00014355313,0.01701613,0.0005304327,0.00014855758,0.00034473836,0.008369213,0.00110367,0.0009809707,0.0089253,0.9618513,0.00030240844],"about_ca_topic_score_codex":0.85805094,"about_ca_topic_score_gemma":0.9448614,"teacher_disagreement_score":0.14194906,"about_ca_system_score_codex":0.0395405,"about_ca_system_score_gemma":0.1408828,"threshold_uncertainty_score":0.28688776},"labels":[],"label_agreement":null},{"id":"W3011164954","doi":"","title":"Land For Sale - Maple Ridge, British Columbia, Canada - Price $1,999,000","year":2020,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Ridge; Maple; Geology; Archaeology; Forestry; Geography; History; Cartography","score_opus":0.008834376600157994,"score_gpt":0.17949522871405962,"score_spread":0.17066085211390164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3011164954","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030493531,0.0022639774,0.00041732774,0.0012074834,0.0015341337,0.00020075937,0.011281763,0.00087794947,0.9791672],"genre_scores_gemma":[0.0013244383,0.0004097989,0.00006693714,0.00008423435,0.00001687781,0.000009039392,0.00119951,0.00007422874,0.9968149],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997147,0.000009716673,0.0000066540965,0.0000523987,0.00013634823,0.00008023668],"domain_scores_gemma":[0.9994789,0.000026021638,0.000008225279,0.000025628131,0.00027257405,0.00018871362],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00020420179,0.0015826607,0.0009901348,0.0014443169,0.0030861848,0.003097941,0.001282419,0.0013784834,0.77791923],"category_scores_gemma":[0.000604957,0.0006472687,0.0007198368,0.0019177664,0.00063670985,0.0010342671,0.0013231478,0.0013723609,0.6093841],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000120538556,0.000041922758,0.00058941904,0.00010944432,0.0000063167868,0.00006064888,0.000035042107,0.00017658828,0.00070516317,0.0004397775,0.928008,0.069707006],"study_design_scores_gemma":[0.000038145026,0.000042330426,0.0063199084,0.00015482321,0.000014828814,0.00006577552,0.00035086015,0.00026036738,0.0003072076,0.00022110183,0.99220675,0.000017970367],"about_ca_topic_score_codex":0.6028681,"about_ca_topic_score_gemma":0.8593584,"teacher_disagreement_score":0.39713192,"about_ca_system_score_codex":0.0046575456,"about_ca_system_score_gemma":0.0069779265,"threshold_uncertainty_score":0.7989414},"labels":[],"label_agreement":null},{"id":"W3011446745","doi":"10.31219/osf.io/x7ryj","title":"The Who, Why, and When of Uber and other Ride-hailing Trips: An Examination of a Large Sample Household Travel Survey","year":2020,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Taxis; TRIPS architecture; Public transport; Sample (material); Business; Mode choice; Mode (computer interface); Position (finance); Travel behavior; Marketing; Advertising; Demographic economics; Economics; Transport engineering; Finance; Engineering","score_opus":0.05605465555450336,"score_gpt":0.24789352799409378,"score_spread":0.1918388724395904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3011446745","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977295,0.00014920735,0.00010144507,0.000104103834,0.00000285805,0.000020616579,0.0013389289,0.0000030536016,0.00055036193],"genre_scores_gemma":[0.99818665,0.00025210695,0.00012858509,0.00006949026,0.000005704723,0.000029668947,0.00093617203,0.0000036448541,0.00038785845],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995148,0.00017094161,0.000076828626,0.00008144756,0.00008432834,0.00007160498],"domain_scores_gemma":[0.9980623,0.00039260724,0.0009752931,0.00013332462,0.0002347927,0.00020175929],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088656606,0.00011816853,0.00019543026,0.00089658133,0.00034657115,0.00061373535,0.00032990135,0.00037917338,0.001893152],"category_scores_gemma":[0.0023057591,0.00021856443,0.00035061722,0.0014824909,0.00029508624,0.0009363979,0.0006378739,0.00038584688,0.00062860455],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038159214,0.000027123191,0.99454004,0.000038546743,0.000039887716,0.000043068936,0.0014343434,0.000030080011,0.00019030289,0.00004344715,0.00041757402,0.0031574867],"study_design_scores_gemma":[5.3357934e-7,0.000021817465,0.9974215,0.0000069823504,0.0000065590107,0.000043958902,0.0020666646,0.000058918165,0.000024146575,0.000007841443,0.00033845476,0.0000025473007],"about_ca_topic_score_codex":0.015059254,"about_ca_topic_score_gemma":0.027219357,"teacher_disagreement_score":0.015059254,"about_ca_system_score_codex":0.00029089485,"about_ca_system_score_gemma":0.0002330263,"threshold_uncertainty_score":0.029943228},"labels":[],"label_agreement":null},{"id":"W3012667494","doi":"10.1111/deci.12433","title":"Data‐Driven Driver Dispatching System with Allocation Constraints and Operational Risk Management for a Ride‐Sharing Platform","year":2020,"lang":"en","type":"article","venue":"Decision Sciences","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Marcus och Amalia Wallenbergs minnesfond; National Natural Science Foundation of China","keywords":"Computer science; Time horizon; Operations research; Heuristic; Control (management); Mathematical optimization; Mode (computer interface); Time allocation; Real-time computing; Engineering; Economics","score_opus":0.05863694938468269,"score_gpt":0.2925452800284088,"score_spread":0.2339083306437261,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3012667494","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5030571,0.00016638947,0.4918363,0.00043495058,0.000054844204,0.00016333793,0.00014537638,0.00057259825,0.0035691056],"genre_scores_gemma":[0.9883422,0.000020988482,0.010624538,0.000014225523,0.0000064731275,0.000037413334,0.000034610166,0.000009313306,0.00091032666],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999539,0.000095688156,0.000022394926,0.000118307595,0.000094907016,0.00012960935],"domain_scores_gemma":[0.9992384,0.0003276588,0.000110380715,0.000053203832,0.00017269734,0.00009767576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009055501,0.0007414586,0.00082297745,0.00039937923,0.0008906289,0.0014297052,0.0010367833,0.0008969321,0.0018204135],"category_scores_gemma":[0.0013833928,0.00045974154,0.0005443261,0.00030223167,0.00049496687,0.0007756685,0.00074444636,0.00077692576,0.0001750662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005423251,0.0000469052,0.0006129335,0.00001634864,0.00001599361,0.00008998754,0.000035403235,0.9912253,0.0016213281,0.0014154739,0.0001953597,0.0046708747],"study_design_scores_gemma":[0.000004646184,0.000016612512,0.00009060169,6.462616e-7,0.0000034023537,0.0000053127824,0.000008688282,0.9992836,0.00023179437,0.00028094265,0.000070960974,0.0000027793897],"about_ca_topic_score_codex":0.016199253,"about_ca_topic_score_gemma":0.0069750887,"teacher_disagreement_score":0.016199253,"about_ca_system_score_codex":0.0015833209,"about_ca_system_score_gemma":0.0022596559,"threshold_uncertainty_score":0.032209933},"labels":[],"label_agreement":null},{"id":"W3016857857","doi":"10.1016/j.procs.2020.03.084","title":"Planning for Connected, Autonomous and Shared Mobility: A Synopsis of Practitioners’ Perspectives","year":2020,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Standardization; Equity (law); Citizen journalism; Plan (archaeology); Service (business); Set (abstract data type); Knowledge management; Process management; Engineering management; Business; Marketing; Political science; World Wide Web","score_opus":0.025353460659327434,"score_gpt":0.25345690209277605,"score_spread":0.22810344143344863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016857857","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10191179,0.21571888,0.073266186,0.49261343,0.0065489262,0.00037104986,0.0002114609,0.00013650832,0.109221734],"genre_scores_gemma":[0.7261279,0.18797839,0.028035698,0.044589303,0.0017914723,0.0006026994,0.00013864135,0.00020289134,0.010532909],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9738724,0.01864265,0.0011970057,0.0014648645,0.002950807,0.0018722614],"domain_scores_gemma":[0.9659422,0.02711507,0.00087721716,0.0005929093,0.0036415753,0.0018310205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0343037,0.0010265406,0.00092620484,0.0043810927,0.009317229,0.0112813115,0.003170304,0.009351388,0.0030290931],"category_scores_gemma":[0.022385033,0.00093453645,0.000676436,0.0066571464,0.018433731,0.017465448,0.010932429,0.012766121,0.0005339058],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005148947,0.00008552652,0.0011108852,0.0024992712,0.000017780189,0.0018065148,0.7088898,0.0009940405,0.00069049187,0.19409445,0.019254584,0.07050519],"study_design_scores_gemma":[0.000009944894,0.00008288666,0.00059459906,0.004658879,0.000009995899,0.0010390384,0.55511683,0.0005142034,0.00023899865,0.031076437,0.40660903,0.000049145026],"about_ca_topic_score_codex":0.0081300745,"about_ca_topic_score_gemma":0.011133016,"teacher_disagreement_score":0.0343037,"about_ca_system_score_codex":0.010741658,"about_ca_system_score_gemma":0.0141212465,"threshold_uncertainty_score":0.18141747},"labels":[],"label_agreement":null},{"id":"W3017048345","doi":"10.1002/itl2.164","title":"Towards smart transportation: A <scp>learning‐based data‐driven</scp> optimization approach for electric taxi dispatch problem","year":2020,"lang":"en","type":"article","venue":"Internet Technology Letters","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Artificial Intelligence in Medicine (Canada); Ericsson (Canada)","funders":"National Natural Science Foundation of China","keywords":"Computer science; Mathematical optimization; Context (archaeology); Kernel density estimation; Stochastic programming; Stochastic optimization; Monte Carlo method; Parametric statistics; Optimization problem; Economic dispatch; Key (lock); Electric power system; Algorithm; Mathematics; Power (physics)","score_opus":0.01731625667329766,"score_gpt":0.2174608578534743,"score_spread":0.20014460118017663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3017048345","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00871675,0.00022358513,0.98861796,0.00035555448,0.000036281985,0.000026138068,0.000063354615,0.00017466664,0.0017857265],"genre_scores_gemma":[0.78146505,0.0007105463,0.21274605,0.0003466865,0.00014281193,0.0002156371,0.0004808519,0.0001355809,0.0037566791],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999577,0.00012261831,0.000021891652,0.00011740101,0.00009969692,0.00006135363],"domain_scores_gemma":[0.9991955,0.00040204317,0.00009543458,0.00006184025,0.00018829004,0.000056881632],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009950901,0.00076899247,0.001132233,0.00043647416,0.00038820872,0.00114503,0.0011616112,0.0013235492,0.0020641938],"category_scores_gemma":[0.0018799827,0.00051876955,0.0008155315,0.00092065654,0.0006031121,0.0015208386,0.0010574688,0.0017416303,0.00031859736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018275445,0.000028073502,0.00030351031,0.00003696416,0.000017395962,0.000024693752,0.00001833069,0.973643,0.000381745,0.0067428635,0.0009776833,0.01780751],"study_design_scores_gemma":[0.0000012353847,0.00000451969,0.000021281578,0.0000013107381,0.0000012540065,0.0000024086285,0.0000025323031,0.9984256,0.000055674765,0.001330678,0.00015237882,0.0000011343437],"about_ca_topic_score_codex":0.010505515,"about_ca_topic_score_gemma":0.005717598,"teacher_disagreement_score":0.010505515,"about_ca_system_score_codex":0.00088763324,"about_ca_system_score_gemma":0.0017669778,"threshold_uncertainty_score":0.020888746},"labels":[],"label_agreement":null},{"id":"W3021274929","doi":"10.2298/yjor0501025s","title":"The operational flight and multi-crew scheduling problem","year":2005,"lang":"en","type":"article","venue":"Yugoslav journal of operations research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Crew; Crew scheduling; Operations research; Computer science; Column generation; Scheduling (production processes); Schedule; Set cover problem; Set (abstract data type); Mathematical optimization; Aeronautics; Engineering; Mathematics","score_opus":0.060539457765180424,"score_gpt":0.36647221311571265,"score_spread":0.3059327553505322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3021274929","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05324058,0.0011177675,0.91811657,0.0008042248,0.00041150203,0.00029744586,0.0007668798,0.00035878975,0.024886178],"genre_scores_gemma":[0.56328547,0.0017246783,0.41422722,0.00035007004,0.0006052383,0.0004945878,0.0019377142,0.00025600096,0.017119],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871814,0.00044742788,0.00006170411,0.00027596956,0.00024885611,0.0002479718],"domain_scores_gemma":[0.99936944,0.00033184906,0.00007476512,0.00006864484,0.00006703397,0.00008823617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000992634,0.0014129686,0.0010262991,0.0006043792,0.00061258674,0.001309658,0.0013519935,0.0014828638,0.0062284274],"category_scores_gemma":[0.0014937302,0.00040992466,0.0010024628,0.0011550757,0.0006641317,0.0017739335,0.0012471486,0.0013074315,0.00071327103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003707445,0.00036481355,0.0013501071,0.00063910533,0.00015249025,0.00085088785,0.00023954832,0.73290014,0.00704771,0.08230184,0.013284083,0.16049848],"study_design_scores_gemma":[0.00010042323,0.00027251645,0.00087502284,0.000032601813,0.000055397184,0.00052797963,0.00017406655,0.93601465,0.0020394672,0.033161603,0.026710836,0.000035505625],"about_ca_topic_score_codex":0.003694369,"about_ca_topic_score_gemma":0.0024844254,"teacher_disagreement_score":0.0062284274,"about_ca_system_score_codex":0.00068361574,"about_ca_system_score_gemma":0.0016477791,"threshold_uncertainty_score":0.020836115},"labels":[],"label_agreement":null},{"id":"W3023892645","doi":"","title":"ROVs with Semi-Autonomous Capabilities for use on Renewable Energy Platforms","year":2015,"lang":"en","type":"article","venue":"The Twenty-fifth International Ocean and Polar Engineering Conference","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Remotely operated underwater vehicle; Renewable energy; Wind power; Computer science; Business; Engineering; Artificial intelligence; Mobile robot; Robot; Electrical engineering","score_opus":0.024457378515669537,"score_gpt":0.21351616191252196,"score_spread":0.18905878339685242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3023892645","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6213794,0.0004246492,0.30395475,0.0006890453,0.00026567685,0.0002443233,0.00094173645,0.0033474546,0.06875296],"genre_scores_gemma":[0.95242804,0.00011504195,0.035480134,0.000090788264,0.00003215304,0.00014999462,0.0006769216,0.00007200123,0.010954931],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981457,0.000019338138,0.000006142534,0.000025706513,0.000087086926,0.00004706104],"domain_scores_gemma":[0.9997079,0.0000377866,0.000024192905,0.00009500311,0.000095004565,0.000040185972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021790377,0.0002714482,0.00026986506,0.000263212,0.00043702312,0.0004683669,0.0005615446,0.00044838505,0.0038390553],"category_scores_gemma":[0.00045469633,0.00015378131,0.00023774338,0.00022889963,0.0002961335,0.0010360783,0.0014138785,0.0005003633,0.0016332499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066384854,0.0002840565,0.012160739,0.0004001891,0.00010286276,0.00080213184,0.00078129815,0.048504204,0.5296927,0.018362205,0.0135287,0.37471712],"study_design_scores_gemma":[0.00022907092,0.0022120788,0.041363057,0.00015075193,0.00012728773,0.0019420901,0.001233472,0.4257332,0.25307775,0.019749861,0.2540195,0.00016184509],"about_ca_topic_score_codex":0.0012103982,"about_ca_topic_score_gemma":0.0028801346,"teacher_disagreement_score":0.0038390553,"about_ca_system_score_codex":0.00013207825,"about_ca_system_score_gemma":0.00042924573,"threshold_uncertainty_score":0.012842894},"labels":[],"label_agreement":null},{"id":"W3024193273","doi":"10.1038/d41586-020-01370-0","title":"Mapping emissions from cars and lorries","year":2020,"lang":"en","type":"article","venue":"Nature","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"CARE Canada","funders":"","keywords":"Truck; Green vehicle; Energy (signal processing); Computer science; Environmental economics; Transport engineering; Business; Environmental science; Engineering; Automotive engineering; Fuel efficiency; Economics","score_opus":0.00945440536793154,"score_gpt":0.21270614809497587,"score_spread":0.20325174272704433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3024193273","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9874079,0.00016885395,0.0026445452,0.00007114317,0.000013478982,0.000014245048,0.0020407687,0.000083424,0.0075555746],"genre_scores_gemma":[0.99410266,0.00018795916,0.0020984726,0.000013007071,0.000007579762,0.00001268944,0.0013436987,0.000032277963,0.0022017763],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99984956,0.000020272684,0.0000042825995,0.000044284177,0.00004842754,0.000033239317],"domain_scores_gemma":[0.9998752,0.00003992444,0.0000146310695,0.000011980565,0.000044322238,0.00001384885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013119433,0.00032001076,0.00018794055,0.0011587683,0.00035678744,0.00077440514,0.00021691478,0.0005503847,0.0017400311],"category_scores_gemma":[0.00044166934,0.00014256338,0.00056570524,0.0015420882,0.00017092998,0.00060735276,0.00035763776,0.0002851254,0.00051156525],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00094763184,0.00044825306,0.6467813,0.00043747903,0.00073427556,0.0008350883,0.001301284,0.1398959,0.046207815,0.004108638,0.005027088,0.15327518],"study_design_scores_gemma":[0.000049048173,0.00022343111,0.8229244,0.000093551214,0.00026391825,0.00039672817,0.0034118402,0.11736084,0.023448883,0.0028881216,0.028861385,0.00007791275],"about_ca_topic_score_codex":0.030103322,"about_ca_topic_score_gemma":0.03654817,"teacher_disagreement_score":0.030103322,"about_ca_system_score_codex":0.00046764754,"about_ca_system_score_gemma":0.00036323827,"threshold_uncertainty_score":0.059856236},"labels":[],"label_agreement":null},{"id":"W3025815279","doi":"10.3390/su12103977","title":"Costs and Benefits of Electrifying and Automating Bus Transit Fleets","year":2020,"lang":"en","type":"article","venue":"Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":110,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Battery (electricity); Gallon (US); Diesel fuel; Total cost of ownership; Public transport; Metropolitan area; Transport engineering; Battery electric vehicle; Capital cost; Fleet management; Business; Environmental economics; Engineering; Automotive engineering; Power (physics); Economics; Waste management; Electrical engineering","score_opus":0.009944862717799784,"score_gpt":0.21969908535508195,"score_spread":0.20975422263728216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3025815279","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97197986,0.00028257546,0.0014955786,0.00047310098,0.000017422963,0.00014994523,0.0008395994,0.000022828935,0.024739066],"genre_scores_gemma":[0.9962011,0.0002121033,0.0011504259,0.000027842523,0.000009858571,0.000026599162,0.00034188788,0.0000052162604,0.0020250683],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859744,0.0005469673,0.00007719093,0.00007520287,0.00048418102,0.00021912048],"domain_scores_gemma":[0.9962992,0.0017471141,0.00087118556,0.00018659134,0.00070170127,0.00019422648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011300623,0.00039440807,0.00012897907,0.0011948791,0.00048105596,0.001428188,0.00055415416,0.00045791836,0.003915209],"category_scores_gemma":[0.007464065,0.00027430765,0.000651815,0.0011540256,0.0005468211,0.0013883705,0.0006305937,0.000410828,0.00029856784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008159307,0.00053835736,0.46250588,0.00043208592,0.00027829138,0.0010794403,0.0008895465,0.33079568,0.005364143,0.02289892,0.0036333562,0.17076845],"study_design_scores_gemma":[0.000064984815,0.0017022581,0.7970662,0.0002527284,0.0004611149,0.00063039525,0.012162757,0.15106507,0.0050490666,0.009457724,0.021937707,0.0001500314],"about_ca_topic_score_codex":0.024611285,"about_ca_topic_score_gemma":0.052352004,"teacher_disagreement_score":0.024611285,"about_ca_system_score_codex":0.003324023,"about_ca_system_score_gemma":0.0013963132,"threshold_uncertainty_score":0.04893607},"labels":[],"label_agreement":null},{"id":"W3027102885","doi":"10.1016/j.trc.2020.102661","title":"Dynamic holding control to avoid bus bunching: A multi-agent deep reinforcement learning framework","year":2020,"lang":"en","type":"article","venue":"Transportation Research Part C Emerging Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":120,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Foundation for Innovation","keywords":"Reinforcement learning; Headway; Schedule; Public transport; Computer science; Control (management); Reliability (semiconductor); Operations research; Engineering; Simulation; Artificial intelligence; Transport engineering; Power (physics)","score_opus":0.056885668138254526,"score_gpt":0.3386778136150954,"score_spread":0.2817921454768409,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3027102885","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.065752566,0.0005445943,0.926354,0.0006469854,0.00013907226,0.000054579195,0.000111846,0.00064288086,0.0057534883],"genre_scores_gemma":[0.9646103,0.000113609,0.030711036,0.00018607466,0.000042508487,0.000058845213,0.000074569725,0.000045351007,0.00415767],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997651,0.000045454755,0.000009482727,0.00006936352,0.0000388212,0.000071675735],"domain_scores_gemma":[0.9993943,0.0002961022,0.00008007705,0.000031707095,0.00011766266,0.00008005704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007793152,0.0007594031,0.0013311609,0.00035374367,0.00040751815,0.0007717939,0.0018574639,0.001651206,0.0034158148],"category_scores_gemma":[0.0015525793,0.000529923,0.00045122244,0.000275532,0.000794174,0.000884673,0.0011584117,0.0016278512,0.00032571642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006215191,0.000060453265,0.0003297476,0.000026990156,0.000021903452,0.00003838069,0.00002345066,0.9789001,0.00058637396,0.0035439022,0.0007092913,0.015697263],"study_design_scores_gemma":[0.000004050108,0.0000083125105,0.000021116757,0.0000015680097,0.0000025463446,0.0000018696022,0.0000012821494,0.9993291,0.000041469782,0.00054515764,0.000042215535,0.0000012644933],"about_ca_topic_score_codex":0.013705531,"about_ca_topic_score_gemma":0.012018063,"teacher_disagreement_score":0.013705531,"about_ca_system_score_codex":0.00087880617,"about_ca_system_score_gemma":0.001374684,"threshold_uncertainty_score":0.027251482},"labels":[],"label_agreement":null},{"id":"W3028428492","doi":"10.1287/trsc.2019.0950","title":"Integrating Resource Management in Service Network Design for Bike-Sharing Systems","year":2020,"lang":"en","type":"article","venue":"Transportation Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Computer science; Service (business); Operations research; Network planning and design; Redistribution (election); Resource allocation; Heuristic; Level of service; Transport engineering; Computer network; Engineering","score_opus":0.05980128379169978,"score_gpt":0.267698934900163,"score_spread":0.20789765110846323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028428492","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021677779,0.00021283035,0.9735893,0.00025341279,0.000037109086,0.00010774306,0.00003698631,0.000085329535,0.0039994884],"genre_scores_gemma":[0.7206046,0.00062859163,0.27343622,0.00011291942,0.000049394013,0.00034603875,0.00010390152,0.000097114156,0.0046211006],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992042,0.00036795574,0.000035511024,0.00011815298,0.00015009787,0.00012412143],"domain_scores_gemma":[0.9993956,0.00035529025,0.00005843738,0.000039049126,0.000103735416,0.000047805126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012745758,0.0009380906,0.00078027195,0.0005003118,0.00077313103,0.0016756568,0.0011815003,0.001111522,0.0026580011],"category_scores_gemma":[0.0025853147,0.00050045294,0.00055220386,0.0006372001,0.00088785193,0.0017560015,0.0012854628,0.00088050764,0.00029336388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027014334,0.000021233218,0.00021131516,0.00005143099,0.000010661358,0.00003550751,0.00004698304,0.9746755,0.0012284684,0.013435854,0.00023711695,0.0100189205],"study_design_scores_gemma":[0.0000051311354,0.000021866748,0.000037543676,0.0000048053016,0.0000043351797,0.000010025286,0.00002709423,0.99357563,0.00034755905,0.0052461857,0.00071627373,0.000003557024],"about_ca_topic_score_codex":0.0071409666,"about_ca_topic_score_gemma":0.007859045,"teacher_disagreement_score":0.0071409666,"about_ca_system_score_codex":0.0019292305,"about_ca_system_score_gemma":0.00231433,"threshold_uncertainty_score":0.01419878},"labels":[],"label_agreement":null},{"id":"W3028576205","doi":"10.1016/j.tre.2020.101958","title":"Optimal investment strategy of a free-floating sharing platform","year":2020,"lang":"en","type":"article","venue":"Transportation Research Part E Logistics and Transportation Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Investment (military); Product (mathematics); Quality (philosophy); Dual (grammatical number); Service (business); Control (management); Optimal control; Investment strategy; Computer science; Business; Operations research; Industrial organization; Mathematical optimization; Marketing; Engineering; Finance; Mathematics","score_opus":0.18491880783516798,"score_gpt":0.3595042101989439,"score_spread":0.17458540236377593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028576205","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5336987,0.0031457182,0.37366158,0.0032672258,0.00033673193,0.00030293665,0.00044343356,0.0002316631,0.084911965],"genre_scores_gemma":[0.9777999,0.0009925517,0.009726292,0.000054735152,0.000039121034,0.0000662677,0.000050904753,0.000017612307,0.011252672],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958414,0.00011849586,0.000013221179,0.00008323926,0.00006344526,0.00013750231],"domain_scores_gemma":[0.999556,0.00021683819,0.000054042765,0.00003146931,0.00006124339,0.00008034644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007836034,0.001210269,0.0010157765,0.0005808574,0.0005385279,0.002144903,0.0017614932,0.0020419494,0.0075393273],"category_scores_gemma":[0.0016676578,0.0005887698,0.0008276102,0.00066790526,0.0009335704,0.0038378378,0.0013229387,0.001249747,0.00038450753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039641754,0.0001365237,0.0005931241,0.0003845178,0.00010060435,0.00037784045,0.00012958053,0.61204505,0.004979726,0.33969107,0.0036784492,0.03748714],"study_design_scores_gemma":[0.00010579453,0.0003615463,0.0007200737,0.00007156156,0.000097118995,0.0001256293,0.0001891348,0.83340406,0.0015596957,0.15933031,0.003979698,0.000055353732],"about_ca_topic_score_codex":0.0032610216,"about_ca_topic_score_gemma":0.0015100604,"teacher_disagreement_score":0.0075393273,"about_ca_system_score_codex":0.0019459669,"about_ca_system_score_gemma":0.0015333702,"threshold_uncertainty_score":0.025221586},"labels":[],"label_agreement":null},{"id":"W3029148486","doi":"10.1016/j.enbenv.2020.05.002","title":"Future cities and autonomous vehicles: analysis of the barriers to full adoption","year":2020,"lang":"en","type":"article","venue":"Energy and Built Environment","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":107,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Trent University; Nottingham Trent University","keywords":"Information and Communications Technology; Key (lock); Government (linguistics); Architecture; Legislation; Computer science; Business; Knowledge management; Computer security; Political science; World Wide Web; Geography","score_opus":0.005771527607306818,"score_gpt":0.16963836164748414,"score_spread":0.16386683404017732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3029148486","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8164012,0.045598947,0.010453267,0.022372259,0.00014516909,0.00023415826,0.00055978884,0.000035482277,0.1041997],"genre_scores_gemma":[0.98617285,0.010696001,0.0012983414,0.0002906356,0.000021093083,0.00008717812,0.000107236345,0.00001622079,0.0013105833],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99125564,0.0036169463,0.0006132086,0.00057257985,0.0030850878,0.0008565305],"domain_scores_gemma":[0.95662475,0.030517077,0.004746437,0.0007716058,0.00664,0.0007001078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008096372,0.00024091903,0.00044694528,0.0033143975,0.0015711009,0.007727446,0.0009666129,0.0011595096,0.0036004882],"category_scores_gemma":[0.03027068,0.00034229603,0.0005535996,0.005477656,0.0029589732,0.007294631,0.0033072743,0.0016860001,0.00026735407],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018954724,0.00018297535,0.15577464,0.0066278633,0.0002387936,0.001163133,0.17530684,0.003333025,0.0012635771,0.4261793,0.0055539026,0.22418642],"study_design_scores_gemma":[0.000023846467,0.00033891405,0.23684038,0.008121078,0.0003679721,0.00097206584,0.41943204,0.0050624767,0.0016709567,0.044699118,0.2823358,0.00013536538],"about_ca_topic_score_codex":0.014314602,"about_ca_topic_score_gemma":0.0135365985,"teacher_disagreement_score":0.014314602,"about_ca_system_score_codex":0.0050271903,"about_ca_system_score_gemma":0.006295355,"threshold_uncertainty_score":0.04281819},"labels":[],"label_agreement":null},{"id":"W3029453425","doi":"10.1155/2020/4380610","title":"Analysis of Perceived Value and Travelers’ Behavioral Intention to Adopt Ride-Hailing Services: Case of Nanjing, China","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology; National Natural Science Foundation of China; Nanjing University of Information Science and Technology; Natural Science Research of Jiangsu Higher Education Institutions of China; China Scholarship Council; Government of Jiangsu Province","keywords":"China; Value (mathematics); Psychology; Sacrifice; Empirical research; Social psychology; Test (biology); Questionnaire; Norm (philosophy); Marketing; Applied psychology; Business; Geography; Political science; Statistics; Mathematics","score_opus":0.01265075112676979,"score_gpt":0.2624725583658158,"score_spread":0.249821807239046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3029453425","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995727,0.000015223378,0.00003730601,0.00002603741,5.048904e-7,0.000004042528,0.000014090834,5.468077e-7,0.00032958583],"genre_scores_gemma":[0.9996592,0.000028062703,0.000056218,0.0000054392076,8.993108e-7,0.000005394903,0.000030333815,4.505296e-7,0.00021407809],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99961096,0.00011898723,0.000028555762,0.000042574953,0.00008759381,0.00011136595],"domain_scores_gemma":[0.99828404,0.00076013367,0.0003125255,0.00009000312,0.00033525634,0.0002180365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011288368,0.00024329408,0.00024046467,0.0013340851,0.00074861024,0.0008693513,0.00041054943,0.0003349814,0.0017552016],"category_scores_gemma":[0.0019389319,0.00014616331,0.0006812948,0.0013538058,0.00056214916,0.0006137067,0.00047130574,0.00046459795,0.000121003344],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004843747,0.00016999381,0.9873285,0.000032305383,0.000036947567,0.00071211776,0.0059861992,0.0003588426,0.00036351822,0.00042449503,0.00009160461,0.0044471044],"study_design_scores_gemma":[0.0000054490665,0.00010816748,0.9771523,0.000018344339,0.000047696765,0.00012301128,0.01901845,0.0028951578,0.0001699412,0.00009650277,0.00035276008,0.000012253819],"about_ca_topic_score_codex":0.12063792,"about_ca_topic_score_gemma":0.11541467,"teacher_disagreement_score":0.12063792,"about_ca_system_score_codex":0.002039408,"about_ca_system_score_gemma":0.0017912358,"threshold_uncertainty_score":0.23987144},"labels":[],"label_agreement":null},{"id":"W3033407562","doi":"10.3386/w28133","title":"Consumer Surplus of Alternative Payment Methods: Paying Uber with Cash","year":2020,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Payment; Economic surplus; Cash; Economics; Business; Commerce; Microeconomics; Finance; Welfare","score_opus":0.38753107489664057,"score_gpt":0.5320207839769061,"score_spread":0.14448970908026554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3033407562","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9801256,0.00042577265,0.0051576896,0.00026559562,0.000024639163,0.00035905113,0.0018623341,0.000037369336,0.011741971],"genre_scores_gemma":[0.9913106,0.00014495505,0.0032414729,0.00005523607,0.000016849775,0.0002197094,0.0010958087,0.0000053628382,0.003909923],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99726593,0.0012919339,0.00012315011,0.0003603897,0.00070418563,0.00025448785],"domain_scores_gemma":[0.98184973,0.010728255,0.004179025,0.0016845593,0.0012718632,0.00028665006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043034297,0.0005127794,0.00068021915,0.0012378979,0.00055153004,0.0018721189,0.0009869396,0.0009779,0.009499119],"category_scores_gemma":[0.016188748,0.0003213011,0.001037052,0.0012649382,0.0009857251,0.0019961959,0.000931513,0.0011258374,0.0006366622],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008985823,0.0036307531,0.7340037,0.0009319024,0.0016966609,0.00037712543,0.0008377513,0.07816549,0.0024976977,0.026471753,0.005532883,0.1368684],"study_design_scores_gemma":[0.0008908856,0.0050661094,0.82261366,0.00026390844,0.0009793949,0.00034010352,0.0014835921,0.14024119,0.0031772277,0.011114729,0.013680676,0.00014846011],"about_ca_topic_score_codex":0.018929895,"about_ca_topic_score_gemma":0.014710398,"teacher_disagreement_score":0.018929895,"about_ca_system_score_codex":0.0020483832,"about_ca_system_score_gemma":0.000755276,"threshold_uncertainty_score":0.03763944},"labels":[],"label_agreement":null},{"id":"W3035271144","doi":"10.24963/ijcai.2020/581","title":"A Unified Model for the Two-stage Offline-then-Online Resource Allocation","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Key Research and Development Program of China; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; Heuristics; Resource allocation; Parameterized complexity; The Internet; Crowdsourcing; Robustness (evolution); Online algorithm; Matching (statistics); Distributed computing; Mathematical optimization; Algorithm; Computer network; World Wide Web","score_opus":0.07081426285499279,"score_gpt":0.2975434412272082,"score_spread":0.22672917837221543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035271144","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0042673955,0.00030753273,0.99046737,0.00044459605,0.000062844185,0.00011381924,0.00031405437,0.00038187753,0.0036405055],"genre_scores_gemma":[0.5617446,0.0013723233,0.4029192,0.0007133067,0.00041584836,0.0014348875,0.0012775871,0.0004883179,0.029634004],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973206,0.0008044975,0.00012525698,0.0008390875,0.0003729544,0.00053758244],"domain_scores_gemma":[0.9977126,0.0013116102,0.00022924341,0.00020590442,0.0003534291,0.00018725029],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030518451,0.0022788502,0.0026842465,0.0009936014,0.0010761356,0.0037961884,0.006402835,0.0036749416,0.013578752],"category_scores_gemma":[0.005063478,0.0017164742,0.0017200469,0.0020714654,0.0018636564,0.0040624808,0.0024796652,0.0035609538,0.002634613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000074907744,0.00007024165,0.00023084435,0.000077146906,0.000025892956,0.000070648704,0.000046708057,0.95576596,0.00049469445,0.028037475,0.0027469986,0.012358382],"study_design_scores_gemma":[0.000011784096,0.000012919373,0.00003220298,0.0000041617095,0.0000062027807,0.000013553649,0.000006220143,0.9920581,0.00007587853,0.0072095464,0.0005639448,0.00000557012],"about_ca_topic_score_codex":0.013127861,"about_ca_topic_score_gemma":0.011676094,"teacher_disagreement_score":0.013578752,"about_ca_system_score_codex":0.0030172018,"about_ca_system_score_gemma":0.004158595,"threshold_uncertainty_score":0.045425415},"labels":[],"label_agreement":null},{"id":"W3036189015","doi":"10.5539/jas.v12n7p53","title":"A Method of Location Selection for Rural Highway Transportation Service Facilities Based on GIS","year":2020,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Analytic hierarchy process; Transport engineering; Site selection; Selection (genetic algorithm); Service (business); Process (computing); Computer science; Geographic information system; Operations research; Engineering; Geography; Business","score_opus":0.01752816698016807,"score_gpt":0.24629677664065802,"score_spread":0.22876860966048995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3036189015","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0066136243,0.000075902586,0.98738444,0.00010114647,0.000037905407,0.00031946736,0.000427151,0.0010868236,0.003953496],"genre_scores_gemma":[0.07565002,0.00017189345,0.9201743,0.000025752279,0.000017817374,0.000474594,0.0006451906,0.00011515292,0.0027252901],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975535,0.00072431494,0.00016755816,0.00043324116,0.0010012069,0.00012016666],"domain_scores_gemma":[0.9987488,0.00032720668,0.00010641848,0.00015348877,0.0006082502,0.000055764696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001440178,0.0010473556,0.00074261473,0.005839665,0.001507122,0.0019418435,0.001261673,0.000538021,0.005940388],"category_scores_gemma":[0.0032818879,0.00056439947,0.0012579096,0.0057244007,0.0006061173,0.0016212033,0.001442708,0.00063715025,0.0014779761],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001542217,0.00016798613,0.013189269,0.0008040509,0.00014735865,0.00041023744,0.0021966125,0.04616642,0.012864084,0.035947703,0.015486645,0.8724654],"study_design_scores_gemma":[0.0002687585,0.0004886469,0.023850506,0.00034882073,0.00036130456,0.0019110055,0.009272875,0.7054426,0.034760103,0.0414307,0.18129547,0.0005691484],"about_ca_topic_score_codex":0.009681059,"about_ca_topic_score_gemma":0.011438864,"teacher_disagreement_score":0.009681059,"about_ca_system_score_codex":0.001131773,"about_ca_system_score_gemma":0.0028255144,"threshold_uncertainty_score":0.019872546},"labels":[],"label_agreement":null},{"id":"W3037809107","doi":"10.22215/etd/2020-14044","title":"Passenger Assignment for Ridesharing Through Supervised Learning","year":2020,"lang":"en","type":"dissertation","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Artificial neural network; Computer science; Intelligent transportation system; Architecture; Work (physics); Transportation theory; Transport engineering; Artificial intelligence; Operations research; Engineering; Mathematical optimization; Mathematics; Geography","score_opus":0.024985066219904067,"score_gpt":0.2586910708207604,"score_spread":0.23370600460085636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037809107","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10935246,0.000661209,0.87736136,0.00075572374,0.00018788538,0.00015066852,0.000569221,0.002384823,0.008576638],"genre_scores_gemma":[0.8510788,0.00026856657,0.13095833,0.00024234361,0.0001518865,0.00016992986,0.0015127393,0.0001576984,0.015459746],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997137,0.00006411145,0.0000130266835,0.00011466615,0.00004015847,0.0000543625],"domain_scores_gemma":[0.9994273,0.000246676,0.000057358673,0.00006453881,0.00016153342,0.000042611446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075092015,0.00073134823,0.00079877634,0.00059206487,0.0006237101,0.0008513968,0.001430917,0.0011904049,0.0062752077],"category_scores_gemma":[0.0024303982,0.0004225091,0.0007511285,0.0006138623,0.000509349,0.0011792212,0.0008803995,0.0016372271,0.0011173285],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014019693,0.00021909343,0.0017345187,0.000078989564,0.000047998637,0.00003986774,0.00007170699,0.782465,0.0009990094,0.004566491,0.0058694156,0.20376782],"study_design_scores_gemma":[0.0000041920257,0.00001239998,0.00010222368,0.000004084543,0.0000040533714,0.0000029079938,0.000006655613,0.99756515,0.0001759334,0.0017984285,0.00032194852,0.0000020251468],"about_ca_topic_score_codex":0.016266279,"about_ca_topic_score_gemma":0.017821867,"teacher_disagreement_score":0.016266279,"about_ca_system_score_codex":0.0010019123,"about_ca_system_score_gemma":0.0013474053,"threshold_uncertainty_score":0.03234321},"labels":[],"label_agreement":null},{"id":"W3038874001","doi":"10.1007/978-3-030-51566-9_26","title":"Smart Mobility in Urban Development","year":2020,"lang":"en","type":"book-chapter","venue":"Advances in intelligent systems and computing","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Geography; Regional science; Euros; Capital region; Capital city; Center (category theory); Economic growth; Capital (architecture); Urban planning; Environmental planning; Economic geography; Business; Civil engineering; Engineering; Economics; Archaeology; Humanities","score_opus":0.018096975199745718,"score_gpt":0.23645459903430563,"score_spread":0.21835762383455992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3038874001","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017498024,0.046273347,0.0027165178,0.006780593,0.0014499511,0.000021525932,0.000076886805,0.000051527048,0.9408798],"genre_scores_gemma":[0.052639414,0.054179087,0.0019056204,0.0017315628,0.0010026564,0.000053639393,0.00013376225,0.00006787947,0.8882863],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99990153,0.000031621697,0.000002662447,0.0000135686605,0.000030799936,0.000019901148],"domain_scores_gemma":[0.9999573,0.000013756775,0.0000034031902,0.0000058726646,0.00001001222,0.000009584096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015085554,0.0006361876,0.00023065598,0.0006554677,0.0010842326,0.0024670204,0.00038315955,0.00091809867,0.017524222],"category_scores_gemma":[0.00028567476,0.00017308374,0.00013723249,0.0013907208,0.001700168,0.0023877886,0.00132387,0.0012574142,0.0032974398],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005995891,0.00001361943,0.00013393158,0.00010398293,0.0000026746811,0.000049220846,0.0010107999,0.00065008394,0.00012843593,0.77851486,0.1431997,0.076186754],"study_design_scores_gemma":[9.0822437e-7,0.000005277176,0.00025794856,0.000100846526,0.0000015136849,0.00003698272,0.0005902725,0.00018170179,0.000044397002,0.06453612,0.93424135,0.0000027723395],"about_ca_topic_score_codex":0.006595256,"about_ca_topic_score_gemma":0.019098265,"teacher_disagreement_score":0.017524222,"about_ca_system_score_codex":0.0019626804,"about_ca_system_score_gemma":0.0013061528,"threshold_uncertainty_score":0.058624327},"labels":[],"label_agreement":null},{"id":"W3041426509","doi":"10.1016/j.tbs.2020.06.008","title":"Free-floating carsharing users’ willingness-to-pay/accept for logistics management mechanisms","year":2020,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"EcoMetrix","funders":"","keywords":"Unavailability; Relocation; Willingness to accept; Incentive; Business; Willingness to pay; Drop out; Stock (firearms); Demographic economics; Computer science; Economics; Statistics; Engineering; Microeconomics; Mathematics","score_opus":0.0328376180328471,"score_gpt":0.24889594172035887,"score_spread":0.21605832368751177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3041426509","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9954326,0.00003467844,0.0003566377,0.00011741516,0.000008127215,0.0000128068805,0.000110751,0.0000108983495,0.003916186],"genre_scores_gemma":[0.9980767,0.000014017887,0.00014314194,0.00002517504,0.000003008709,0.0000071455775,0.00006136329,0.000004184459,0.0016652688],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993831,0.00019009535,0.000057440655,0.00008442199,0.00012107373,0.00016392213],"domain_scores_gemma":[0.9924642,0.0040671313,0.0011329642,0.0006511727,0.00090241164,0.00078221393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010885841,0.00018763563,0.00020502564,0.00045941517,0.00045200833,0.0019690702,0.00038478387,0.0007857793,0.021129454],"category_scores_gemma":[0.011300059,0.0002423137,0.00044594196,0.0003471258,0.000327475,0.0015692418,0.0007101565,0.0009813822,0.0019249052],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002488958,0.0013746386,0.8834198,0.00015354922,0.00029179535,0.00033783648,0.012062933,0.0025303073,0.0065363557,0.0045836503,0.0027412751,0.08347888],"study_design_scores_gemma":[0.000047443697,0.00051447446,0.9655754,0.000043239732,0.0001328825,0.00032083053,0.016360508,0.00855899,0.0016849794,0.0019318654,0.004731127,0.00009818701],"about_ca_topic_score_codex":0.0039855833,"about_ca_topic_score_gemma":0.004455303,"teacher_disagreement_score":0.021129454,"about_ca_system_score_codex":0.00039865653,"about_ca_system_score_gemma":0.00029643095,"threshold_uncertainty_score":0.07068509},"labels":[],"label_agreement":null},{"id":"W3041822776","doi":"10.24963/ijcai.2020/774","title":"A Testbed for Studying COVID-19 Spreading in Ride-Sharing Systems","year":2020,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Testbed; Computer science; Order (exchange); Coronavirus disease 2019 (COVID-19); Computer security; Infectious disease (medical specialty); Distributed computing; Computer network; Disease; Business","score_opus":0.11283971328532671,"score_gpt":0.30004784157847536,"score_spread":0.18720812829314865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3041822776","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.950711,0.00017135953,0.040724616,0.00030213757,0.00015934733,0.00048433567,0.0013238854,0.0010184437,0.0051048654],"genre_scores_gemma":[0.9718746,0.000085581814,0.02607691,0.00004991072,0.00001271689,0.00025848424,0.00061420305,0.000028990677,0.0009985649],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993327,0.00031597578,0.000043793378,0.000093031194,0.00010646598,0.00010788659],"domain_scores_gemma":[0.9977303,0.0010092274,0.0002594236,0.00041815193,0.00022170554,0.0003612669],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008268389,0.0004416131,0.0004746619,0.0005682349,0.00068526017,0.00052947947,0.0009926476,0.00085845013,0.0019886135],"category_scores_gemma":[0.0020125303,0.00017437516,0.00031708498,0.00038877554,0.0006451187,0.0007775857,0.0008277707,0.0006802635,0.00029456202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021275703,0.005944529,0.035102766,0.0006262226,0.00027979125,0.0018079045,0.0012964698,0.71794015,0.15035497,0.039063834,0.006915011,0.038540777],"study_design_scores_gemma":[0.0003384024,0.0025700843,0.01003753,0.00004314013,0.000057987872,0.00018095972,0.000636663,0.943672,0.027768508,0.006308728,0.008321778,0.00006433663],"about_ca_topic_score_codex":0.0038452498,"about_ca_topic_score_gemma":0.0028301536,"teacher_disagreement_score":0.0038452498,"about_ca_system_score_codex":0.00067988306,"about_ca_system_score_gemma":0.00055077614,"threshold_uncertainty_score":0.007645726},"labels":[],"label_agreement":null},{"id":"W3042755183","doi":"10.1111/cag.12638","title":"Who uses ride‐hailing? Policy implications and evidence from the Greater Toronto and Hamilton Area","year":2020,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Context (archaeology); Public transport; Public policy; Business; Social mobility; Marketing; Economics; Demographic economics; Economic growth; Sociology; Geography; Political science; Social science; Law","score_opus":0.01869915683098658,"score_gpt":0.20731181748726518,"score_spread":0.1886126606562786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042755183","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9628775,0.005835793,0.00019113487,0.011141917,0.0000489912,0.0001259553,0.0049296166,0.00001114654,0.014837907],"genre_scores_gemma":[0.9915929,0.0041964944,0.0001729276,0.0006204841,0.0000208937,0.00005720636,0.00095186726,0.0000047571393,0.0023825215],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986633,0.00023977664,0.000063318665,0.00011672537,0.00026169006,0.00065517507],"domain_scores_gemma":[0.9952923,0.0010010245,0.00094318,0.00014122712,0.0012412774,0.0013810615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009386404,0.00024136047,0.00029080946,0.0011092653,0.0025476944,0.0015086419,0.0010769115,0.0006247247,0.0040645283],"category_scores_gemma":[0.0043702363,0.0002746722,0.00037183642,0.0041245464,0.0014390614,0.0009463383,0.0013806026,0.001001624,0.00021199569],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033194953,0.0001531172,0.90033233,0.0015088407,0.00019188209,0.00079917023,0.024754629,0.0007858733,0.00044425367,0.007181689,0.023174897,0.0403413],"study_design_scores_gemma":[0.000021356385,0.00003731442,0.9506445,0.00053452887,0.00008866829,0.0000556673,0.036221452,0.0004045038,0.000114249226,0.00024280323,0.011604076,0.000030822666],"about_ca_topic_score_codex":0.9957689,"about_ca_topic_score_gemma":0.9983354,"teacher_disagreement_score":0.04254132,"about_ca_system_score_codex":0.04254132,"about_ca_system_score_gemma":0.04627889,"threshold_uncertainty_score":0.3086604},"labels":[],"label_agreement":null},{"id":"W3044306824","doi":"10.1155/2020/8365194","title":"Designing High-Freedom Responsive Feeder Transit System with Multitype Vehicles","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Changsha University of Science and Technology; National Natural Science Foundation of China; Natural Science Foundation of Hunan Province; Education Department of Hunan Province","keywords":"Reservation; Scheduling (production processes); Computer science; Public transport; Mathematical optimization; Last mile (transportation); Metaheuristic; Mode (computer interface); Integer programming; Heuristic; Service level; Service (business); Transport engineering; Engineering; Simulation; Mile; Algorithm; Computer network; Mathematics","score_opus":0.010668816934638324,"score_gpt":0.20880156524977816,"score_spread":0.19813274831513983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3044306824","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2261724,0.00030343235,0.75946414,0.00019144831,0.000054524586,0.0001776165,0.00011341997,0.00048526473,0.013037764],"genre_scores_gemma":[0.9724501,0.0001197878,0.024430037,0.000020843054,0.0000128364545,0.000073314535,0.00007140697,0.000018150133,0.0028035722],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968493,0.000085732434,0.000011215766,0.000066553104,0.00006188387,0.00008970059],"domain_scores_gemma":[0.9998472,0.000036059322,0.000038985483,0.000012247151,0.000034579498,0.000030920157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029770858,0.0007101843,0.00049173826,0.00039189888,0.00065819913,0.00079100823,0.00087830727,0.00063806935,0.0022663309],"category_scores_gemma":[0.0003707975,0.00028938177,0.0007559936,0.00045256468,0.0002691592,0.0006431754,0.00057993387,0.00040563138,0.00027622216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010526688,0.000068144276,0.0012991395,0.00013100525,0.000039749757,0.00025338453,0.00008196137,0.95399666,0.01457681,0.003995234,0.0005555187,0.024897087],"study_design_scores_gemma":[0.000012879488,0.0001684394,0.0003070224,0.000005119824,0.00002059833,0.000056450703,0.00006641908,0.99602145,0.0014277275,0.0007382471,0.0011672727,0.0000082634615],"about_ca_topic_score_codex":0.0074135535,"about_ca_topic_score_gemma":0.0075849006,"teacher_disagreement_score":0.0074135535,"about_ca_system_score_codex":0.0007965512,"about_ca_system_score_gemma":0.0010707618,"threshold_uncertainty_score":0.014740825},"labels":[],"label_agreement":null},{"id":"W3044403913","doi":"","title":"Real-Time Spatial-Intertemporal Dynamic Pricing for Balancing Supply and Demand in a Ride-Hailing Network","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Dynamic pricing; Heuristics; Computer science; TRIPS architecture; Time horizon; Operations research; Heuristic; Flexibility (engineering); Mathematical optimization; Economics; Microeconomics; Mathematics","score_opus":0.004362460598252109,"score_gpt":0.20982958887070924,"score_spread":0.20546712827245714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3044403913","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.67913854,0.0006324434,0.31195405,0.0008802515,0.000091174596,0.0001827595,0.00035842916,0.00027060622,0.006491757],"genre_scores_gemma":[0.98692,0.000113282105,0.01214561,0.000026530863,0.0000114375725,0.00003220633,0.000072384544,0.000020763451,0.0006578223],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894184,0.00056557986,0.000031342035,0.00013593887,0.00009863644,0.0002266857],"domain_scores_gemma":[0.9956703,0.0030078823,0.0004793314,0.0001935543,0.00028643143,0.00036260538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020196212,0.0009818779,0.0014089617,0.00090179377,0.00093130226,0.001869461,0.002000087,0.0017858061,0.002383034],"category_scores_gemma":[0.007960609,0.00070308876,0.00072166114,0.0015958225,0.0014061274,0.0029789235,0.0011057373,0.0014960435,0.00014750614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031352116,0.000025008103,0.00042150015,0.000010792285,0.000009248165,0.000036951544,0.0000168712,0.99520123,0.00018700781,0.0025833535,0.0001289481,0.001347867],"study_design_scores_gemma":[0.0000048166207,0.000012561701,0.000105592604,0.0000010521222,0.0000027585604,0.000007842072,0.000023056476,0.99818283,0.000045227927,0.001548386,0.00006184867,0.0000039399824],"about_ca_topic_score_codex":0.019013654,"about_ca_topic_score_gemma":0.012814438,"teacher_disagreement_score":0.019013654,"about_ca_system_score_codex":0.0026805676,"about_ca_system_score_gemma":0.0010800816,"threshold_uncertainty_score":0.037805915},"labels":[],"label_agreement":null},{"id":"W3045214016","doi":"10.1155/2020/9635853","title":"Influence of Mobile Payment on Bus Boarding Service Time","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Payment; Computer science; Service (business); Cash; Code (set theory); Process (computing); Payment system; Mobile payment; Set (abstract data type); Business; Finance; Marketing; Operating system; World Wide Web","score_opus":0.007274320359856431,"score_gpt":0.22443546062357525,"score_spread":0.21716114026371883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3045214016","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.993632,0.00023395052,0.0015238593,0.00036972214,0.00003631143,0.000040415176,0.00017676209,0.000026490568,0.0039605103],"genre_scores_gemma":[0.99812347,0.00011896879,0.0003426468,0.000024941302,0.000013052732,0.000013439795,0.000100817975,0.000008245597,0.0012543781],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972721,0.001251185,0.00012258772,0.00030775432,0.00048387656,0.000562559],"domain_scores_gemma":[0.976061,0.01547954,0.004210021,0.0006687522,0.002148231,0.0014323957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020568252,0.0004017839,0.0003691482,0.0007948133,0.0005385782,0.001702917,0.0004432256,0.00062342425,0.0074983602],"category_scores_gemma":[0.026463145,0.00019590618,0.00090950564,0.0010234353,0.0005270088,0.0011886825,0.0009317678,0.0012290674,0.0010310286],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010016228,0.0008293828,0.906033,0.00016389434,0.00024581968,0.0008630042,0.0019045767,0.028917935,0.002532154,0.003808581,0.0021857163,0.051514253],"study_design_scores_gemma":[0.000057243935,0.0011370705,0.862228,0.00009464537,0.00034690896,0.00037332077,0.0051382403,0.12136518,0.0015801406,0.0019273591,0.005663755,0.000088160654],"about_ca_topic_score_codex":0.019871071,"about_ca_topic_score_gemma":0.011989335,"teacher_disagreement_score":0.019871071,"about_ca_system_score_codex":0.001523991,"about_ca_system_score_gemma":0.0016459306,"threshold_uncertainty_score":0.039510787},"labels":[],"label_agreement":null},{"id":"W3045258774","doi":"10.1021/cen-09621-buscon9","title":"Enerkem picks Spain for waste-to-methanol","year":2018,"lang":"en","type":"article","venue":"C&EN Global Enterprise","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Methanol; Waste management; Environmental science; Chemistry; Engineering; Organic chemistry","score_opus":0.007260028284869964,"score_gpt":0.2563838582201244,"score_spread":0.24912382993525442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3045258774","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07730567,0.013100705,0.013052177,0.008688366,0.005167242,0.0005539958,0.005973594,0.006878594,0.8692797],"genre_scores_gemma":[0.09210681,0.0030649025,0.013281709,0.0013600099,0.00029814002,0.00008540983,0.0050849644,0.0013586577,0.88335943],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.999374,0.000048534166,0.000018249882,0.00012586717,0.00031959685,0.000113778],"domain_scores_gemma":[0.9994885,0.000041677904,0.000034513698,0.0000793555,0.00019113199,0.00016482767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011889961,0.00104101,0.00065292884,0.00212522,0.001850848,0.0029346545,0.0011699973,0.0017829541,0.1386711],"category_scores_gemma":[0.001118573,0.00046832784,0.00076915877,0.0011558166,0.0005496853,0.0012174712,0.0020790494,0.0017340594,0.041110724],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030122886,0.0010714323,0.006767984,0.0013125786,0.000063137,0.0037283422,0.0006617114,0.0017720436,0.03638398,0.035719983,0.51178205,0.39772457],"study_design_scores_gemma":[0.00008699375,0.00010350378,0.0017134318,0.00011406162,0.000008585515,0.00030092476,0.00024747165,0.00033488515,0.003834424,0.0009657642,0.9922747,0.000015297515],"about_ca_topic_score_codex":0.0062338845,"about_ca_topic_score_gemma":0.015511145,"teacher_disagreement_score":0.1386711,"about_ca_system_score_codex":0.0014811264,"about_ca_system_score_gemma":0.0018140103,"threshold_uncertainty_score":0.46390104},"labels":[],"label_agreement":null},{"id":"W3046041180","doi":"10.5465/ambpp.2020.12471abstract","title":"Nonmarket Strategies of New Entrants and Incumbents: Evidence from Ridesharing and Taxi Firms","year":2020,"lang":"en","type":"article","venue":"Academy of Management Proceedings","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Western University","funders":"","keywords":"Nonmarket forces; Competition (biology); Politics; Leverage (statistics); Legitimacy; Barriers to entry; Industrial organization; Business; Economics; Market economy; Marketing; Market structure; Political science; Factor market","score_opus":0.03579480984754621,"score_gpt":0.2517642425728604,"score_spread":0.2159694327253142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046041180","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9929669,0.00043685827,0.0000996089,0.00041988777,0.0000069851903,0.000022192156,0.00087134424,0.000005942751,0.005170336],"genre_scores_gemma":[0.99637586,0.00032431493,0.00004046013,0.00013461383,0.000017682734,0.000012689161,0.0010942926,0.000005079701,0.001995001],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99842024,0.0002781606,0.000097836026,0.00028240224,0.00037230694,0.0005490601],"domain_scores_gemma":[0.97480834,0.005109093,0.012804933,0.0012455074,0.0021286276,0.003903476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018257491,0.00017134806,0.00047702694,0.0021289971,0.002212802,0.0026471636,0.0007185394,0.00090251974,0.0061896574],"category_scores_gemma":[0.0084747635,0.00027843975,0.00032903661,0.0032395597,0.0016976027,0.0016744807,0.0021431851,0.0012408486,0.0012155882],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021834126,0.00022932213,0.9734943,0.00008984547,0.000087604145,0.0003635724,0.009676757,0.00017886695,0.0003027722,0.0012595685,0.0040341783,0.010064817],"study_design_scores_gemma":[0.000013862081,0.0000573955,0.9823659,0.00003072596,0.00003113423,0.00006295347,0.012483301,0.00028958765,0.0001657098,0.00012722677,0.0043541156,0.000018116187],"about_ca_topic_score_codex":0.3097615,"about_ca_topic_score_gemma":0.49221087,"teacher_disagreement_score":0.3097615,"about_ca_system_score_codex":0.0032849652,"about_ca_system_score_gemma":0.0022606493,"threshold_uncertainty_score":0.61591697},"labels":[],"label_agreement":null},{"id":"W3046515879","doi":"","title":"The Pakistan Competition Authority approves an acquisition between two application-based ride-sharing service companies despite extremely high market concentration levels and efficiencies failing to outweigh the adverse effects of lessening of competition (Careem / Uber Technologies)","year":2020,"lang":"en","type":"article","venue":"e-Competitions Bulletin","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Business; Competition (biology); Service (business); Marketing; Industrial organization; Finance","score_opus":0.0150021713978137,"score_gpt":0.241876891570744,"score_spread":0.22687472017293028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046515879","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.051106013,0.00074397074,0.005885178,0.025411123,0.0041156304,0.0014126044,0.0026845152,0.0014187493,0.9072224],"genre_scores_gemma":[0.26351225,0.0005090262,0.0048464024,0.012211285,0.0008182849,0.0002998307,0.0014187967,0.00016631324,0.7162178],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9927489,0.0004253285,0.0002597976,0.0005802734,0.0045524486,0.0014332931],"domain_scores_gemma":[0.9842382,0.0017600727,0.00064669043,0.00079920935,0.011025177,0.0015306548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00428661,0.00056205166,0.0005420393,0.0014524728,0.0073631555,0.005175579,0.00094010826,0.007367063,0.048882734],"category_scores_gemma":[0.0107519785,0.0007065692,0.0006590936,0.0009557724,0.0022359756,0.0015536575,0.0017122991,0.004792983,0.018425168],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006453967,0.00048565454,0.010469451,0.00025786672,0.00004649617,0.0026455002,0.0009767297,0.00029305858,0.007818123,0.15034509,0.7146191,0.11139761],"study_design_scores_gemma":[0.0001438102,0.00043577605,0.0105412565,0.000067912864,0.000033384855,0.00093169074,0.00045613854,0.00065213547,0.004719247,0.0022382648,0.9797079,0.00007238407],"about_ca_topic_score_codex":0.08999339,"about_ca_topic_score_gemma":0.103508055,"teacher_disagreement_score":0.08999339,"about_ca_system_score_codex":0.004848114,"about_ca_system_score_gemma":0.030352917,"threshold_uncertainty_score":0.17893916},"labels":[],"label_agreement":null},{"id":"W3049002765","doi":"10.1155/2020/8935692","title":"Model Contrast of Autonomous Vehicle Impacts on Traffic","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Wisconsin Department of Transportation; Florida Department of Transportation; U.S. Department of Transportation","keywords":"Software deployment; Geospatial analysis; Transport engineering; Range (aeronautics); Traffic congestion; Work (physics); Computer science; Transit (satellite); Vehicle miles of travel; Contrast (vision); Operations research; Engineering; Public transport; Geography","score_opus":0.015344722509921114,"score_gpt":0.2382145148313942,"score_spread":0.22286979232147308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3049002765","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92103183,0.00026588913,0.024605745,0.00067184656,0.00008985735,0.00009383101,0.0028508892,0.00027156368,0.05011843],"genre_scores_gemma":[0.99237424,0.00010791336,0.001700857,0.000040894774,0.000008868895,0.000046860696,0.00041732303,0.000020725687,0.005282302],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982184,0.000047209767,0.0000058661094,0.000053365737,0.00002331223,0.000048434977],"domain_scores_gemma":[0.99956185,0.00019858629,0.000051926352,0.000028803357,0.0001260292,0.000032734864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034599507,0.000621431,0.0003449837,0.00051310187,0.0003798322,0.0011409394,0.0010464804,0.000885092,0.0045090388],"category_scores_gemma":[0.0010559855,0.00027799068,0.0007214487,0.00046724005,0.00034578895,0.00078504585,0.00052612164,0.0005236102,0.00027969744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003535093,0.000038195052,0.0019479672,0.00001209251,0.00001599663,0.000035803474,0.000019119292,0.992683,0.0003528884,0.0031521216,0.0005006948,0.001206796],"study_design_scores_gemma":[0.000015936195,0.000032701726,0.0008982595,0.0000043893974,0.000016454615,0.0000076272468,0.00003334744,0.9968611,0.00021079468,0.0009827613,0.0009295359,0.0000070837195],"about_ca_topic_score_codex":0.101582065,"about_ca_topic_score_gemma":0.052165348,"teacher_disagreement_score":0.101582065,"about_ca_system_score_codex":0.0018724852,"about_ca_system_score_gemma":0.0013675941,"threshold_uncertainty_score":0.20198154},"labels":[],"label_agreement":null},{"id":"W3051511610","doi":"10.3390/su12176727","title":"Dynamic Pricing on Round-Trip Carsharing Services: Travel Behavior and Equity Impact Analysis through an Agent-Based Simulation","year":2020,"lang":"en","type":"article","venue":"Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Fonds National de la Recherche Luxembourg","keywords":"Equity (law); Mode choice; Dynamic pricing; Service (business); Mode (computer interface); Business; Microeconomics; Environmental economics; Operations research; Transport engineering; Computer science; Economics; Marketing; Public transport; Engineering","score_opus":0.028317383672146743,"score_gpt":0.34582745311646007,"score_spread":0.3175100694443133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3051511610","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9838786,0.000041067226,0.011116252,0.00011205062,0.000014703479,0.00006740085,0.00022419711,0.00004587952,0.0045000003],"genre_scores_gemma":[0.9955504,0.00003618869,0.0035033862,0.000011172065,0.0000023999335,0.00004776251,0.00008572396,0.000005194551,0.0007578436],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999742,0.000117897944,0.000009361609,0.00003395914,0.000033456792,0.000063314066],"domain_scores_gemma":[0.9982414,0.0012814121,0.00013978046,0.0000838213,0.00014428099,0.00010925292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005993256,0.0003786637,0.000426098,0.0005128811,0.0003147448,0.0007934278,0.0007168271,0.0007188239,0.0029984273],"category_scores_gemma":[0.0022077186,0.00020510113,0.00050144666,0.0004536194,0.00043169878,0.0006216685,0.0005688046,0.00071938493,0.00013988942],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001730015,0.00028429242,0.00536576,0.000028685805,0.000035631285,0.000053888056,0.00006866754,0.98683167,0.00065160077,0.0037218663,0.00023692234,0.0025479256],"study_design_scores_gemma":[0.000019472756,0.00006819749,0.0010714445,0.0000026985517,0.000011648914,0.000004792262,0.00004806449,0.99792945,0.00020565379,0.00047075943,0.0001631347,0.0000046567598],"about_ca_topic_score_codex":0.022049583,"about_ca_topic_score_gemma":0.012024055,"teacher_disagreement_score":0.022049583,"about_ca_system_score_codex":0.0009642618,"about_ca_system_score_gemma":0.00075092266,"threshold_uncertainty_score":0.043842494},"labels":[],"label_agreement":null},{"id":"W3067494023","doi":"10.32866/001c.14547","title":"Using Wait-time Thresholds to Improve Mobility: The Case of UberWAV Services in Toronto","year":2020,"lang":"en","type":"article","venue":"Findings","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Downtown; TRIPS architecture; Service (business); Travel time; Rush hour; Transport engineering; Business; Geography; Engineering; Marketing","score_opus":0.017601173557306775,"score_gpt":0.25925661461982646,"score_spread":0.24165544106251968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3067494023","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98490506,0.0008498427,0.0011190659,0.001324887,0.000031966945,0.000028861448,0.007956903,0.00007048282,0.0037128383],"genre_scores_gemma":[0.99512404,0.00017811573,0.0007255629,0.000054227712,0.000010805979,0.000013729519,0.0033454765,0.000014084329,0.00053390785],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999132,0.00016827315,0.00005768931,0.00015659016,0.00019265804,0.0002928697],"domain_scores_gemma":[0.99575907,0.0016283953,0.0007603913,0.00027976197,0.0009857656,0.00058660004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010994362,0.00040268307,0.00036043796,0.0012456748,0.0011042246,0.0014892401,0.00089374965,0.00051386905,0.0017876424],"category_scores_gemma":[0.009801196,0.00017145264,0.00046817854,0.0037107542,0.0005781113,0.0012829828,0.00094909547,0.00078291335,0.0003608672],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004400879,0.00009831486,0.94349974,0.00021578906,0.00018475573,0.0004955819,0.0043702866,0.015572786,0.0007940117,0.0028252103,0.01205834,0.019445086],"study_design_scores_gemma":[0.000022571048,0.00009797761,0.9560362,0.00009879297,0.00012449121,0.00013802307,0.008393275,0.025587572,0.0004844583,0.0008140396,0.008150278,0.000052374064],"about_ca_topic_score_codex":0.8957742,"about_ca_topic_score_gemma":0.9401006,"teacher_disagreement_score":0.104225814,"about_ca_system_score_codex":0.009557142,"about_ca_system_score_gemma":0.0049133934,"threshold_uncertainty_score":0.20967919},"labels":[],"label_agreement":null},{"id":"W3081872153","doi":"10.1155/2020/9853164","title":"A Green Demand-Responsive Airport Shuttle Service Problem with Time-Varying Speeds","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Civil Aviation University of China; Ministry of Education of the People's Republic of China","keywords":"Genetic algorithm; Fuel efficiency; Integer programming; Mathematical optimization; Sorting; Duration (music); Operations research; Alternative fuel vehicle; Heuristic; Set (abstract data type); Service (business); Computer science; Path (computing); Sensitivity (control systems); Multi-objective optimization; Engineering; Automotive engineering; Alternative fuels; Mathematics","score_opus":0.009955579887802725,"score_gpt":0.21922706925864577,"score_spread":0.20927148937084306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081872153","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15386404,0.00070236303,0.82229185,0.000845402,0.00021684135,0.0002655722,0.0010439222,0.000483307,0.020286603],"genre_scores_gemma":[0.9481981,0.00034890653,0.038805712,0.00011530266,0.00004329912,0.00024205576,0.00042652572,0.00008977357,0.011730432],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991829,0.0002905876,0.000020836225,0.00015681767,0.0001079266,0.00024097267],"domain_scores_gemma":[0.9995484,0.00020842349,0.00007537966,0.000019758476,0.0000642739,0.000083823375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084478693,0.001873588,0.0016205512,0.00072682963,0.0006242846,0.0018374387,0.0018225271,0.0023392353,0.0038897272],"category_scores_gemma":[0.0010659716,0.00089342095,0.001348772,0.001064743,0.0007571865,0.0013124732,0.00093963457,0.0013844036,0.00033732917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042347685,0.000026739752,0.00014515729,0.00004127367,0.0000174983,0.0001091359,0.0000189368,0.99344,0.0007303054,0.003066633,0.00035311875,0.0020089617],"study_design_scores_gemma":[0.000009713248,0.00003090758,0.00008134673,0.000003855783,0.0000080726795,0.000015584304,0.000025090068,0.9982212,0.00015560462,0.0010483168,0.00039521846,0.000005091075],"about_ca_topic_score_codex":0.011510797,"about_ca_topic_score_gemma":0.008548322,"teacher_disagreement_score":0.011510797,"about_ca_system_score_codex":0.0018164649,"about_ca_system_score_gemma":0.0014973447,"threshold_uncertainty_score":0.022887588},"labels":[],"label_agreement":null},{"id":"W3082930779","doi":"10.1155/2020/8838994","title":"Customized Bus Route Optimization with the Real-Time Data","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Southeast University; Ministry of Education, India; Ministry of Education of the People's Republic of China","keywords":"Computer science; Computation; Schedule; Nonlinear programming; Scheduling (production processes); Real-time data; Real-time computing; Optimization problem; Mathematical optimization; Nonlinear system; Algorithm","score_opus":0.013837583466756587,"score_gpt":0.22841197402303443,"score_spread":0.21457439055627783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082930779","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.123939954,0.00032551872,0.8703674,0.0002081062,0.00005891075,0.00006691436,0.00013786617,0.00042308684,0.0044721775],"genre_scores_gemma":[0.89089227,0.00013517358,0.10617158,0.000036272002,0.000021978189,0.000077479446,0.00022508175,0.00007277993,0.0023673363],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996018,0.00011523418,0.000014381082,0.00009730528,0.00009891003,0.00007239532],"domain_scores_gemma":[0.99953985,0.0001923674,0.00008445415,0.000051935214,0.000098412485,0.000032946424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000653015,0.0009429834,0.00097107544,0.00048680237,0.0003396583,0.0009205776,0.0008516857,0.00069926324,0.0016216894],"category_scores_gemma":[0.0014417815,0.0004903881,0.0006141561,0.0007394422,0.0004016753,0.0013006125,0.00061278907,0.00076515373,0.00017829426],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020714131,0.0000137458255,0.00021714547,0.000011858652,0.000008145142,0.000017792847,0.000008375485,0.9923441,0.00039556014,0.00082648377,0.00014115166,0.005995053],"study_design_scores_gemma":[0.0000023433995,0.000009950755,0.00006353581,5.2278233e-7,0.000001921426,0.0000041916405,0.00000639072,0.9993549,0.00013014355,0.00031284968,0.00011156691,0.000001570292],"about_ca_topic_score_codex":0.013299099,"about_ca_topic_score_gemma":0.0112595055,"teacher_disagreement_score":0.013299099,"about_ca_system_score_codex":0.0010728023,"about_ca_system_score_gemma":0.0013738105,"threshold_uncertainty_score":0.026443422},"labels":[],"label_agreement":null},{"id":"W3083901868","doi":"10.1016/j.tranpol.2020.09.004","title":"Assessment of delivery models for semi-flexible transit operation in low-demand conditions","year":2020,"lang":"en","type":"article","venue":"Transport Policy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Public transport; Operating cost; Transit (satellite); Transport engineering; Service (business); Marginal cost; Total cost; Operations research; Scheduling (production processes); Operating budget; Computer science; Budget constraint; Operations management; Business; Engineering; Economics; Finance; Microeconomics","score_opus":0.028107132873573977,"score_gpt":0.29438202355794624,"score_spread":0.26627489068437227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083901868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88970816,0.0006459237,0.08552984,0.0015052934,0.00010194912,0.0005272122,0.0026404844,0.00044303344,0.018898094],"genre_scores_gemma":[0.9910124,0.00017437233,0.0053276345,0.000036206926,0.000015198128,0.00011223686,0.0005142115,0.00004702607,0.0027606634],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985347,0.00082009897,0.00004443004,0.00016922619,0.00015934059,0.00027218126],"domain_scores_gemma":[0.9882504,0.009371573,0.0006729737,0.00027662265,0.0010080959,0.00042040044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0054087318,0.0010520628,0.0011484601,0.0014684679,0.00067756994,0.002730228,0.0020529414,0.0018750902,0.004806606],"category_scores_gemma":[0.011865347,0.00060909335,0.0014864844,0.0012395787,0.0006840843,0.0022008135,0.0009210066,0.0013704395,0.00042149896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020836237,0.00006804281,0.0011126096,0.000038315826,0.000019519708,0.000023254313,0.000029236564,0.9927043,0.00012831767,0.003187809,0.0003527383,0.002127529],"study_design_scores_gemma":[0.000028406257,0.00012314264,0.00081347657,0.0000117663485,0.000022695463,0.0000065152703,0.000078412675,0.9971551,0.00012754169,0.0013766664,0.00024635188,0.000009983666],"about_ca_topic_score_codex":0.050338056,"about_ca_topic_score_gemma":0.018503552,"teacher_disagreement_score":0.050338056,"about_ca_system_score_codex":0.0076990747,"about_ca_system_score_gemma":0.0039373403,"threshold_uncertainty_score":0.100090146},"labels":[],"label_agreement":null},{"id":"W3083938007","doi":"10.13140/rg.2.2.18963.84007","title":"Estimation of Car Trips Generated by the Arrival of Autonomous Vehicles in the Montreal Metropolitan Area","year":2019,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Occupancy; TRIPS architecture; Metropolitan area; Estimation; Transport engineering; Business; Econometrics; Geography; Engineering; Economics; Civil engineering","score_opus":0.026216490212181618,"score_gpt":0.28364528625586677,"score_spread":0.2574287960436851,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083938007","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9898836,0.00010102633,0.0041261627,0.000121424695,0.000007733427,0.000061680985,0.0035660996,0.00009194552,0.0020402847],"genre_scores_gemma":[0.99452376,0.000088116205,0.002113574,0.0000146791035,0.000004771246,0.00002827882,0.002285539,0.000008786174,0.00093248324],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972314,0.00006443048,0.000010008728,0.00006761948,0.00007571102,0.000059087302],"domain_scores_gemma":[0.9991499,0.00024381095,0.00014705736,0.000054653734,0.00031056456,0.00009398755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041366692,0.00047009185,0.00017739144,0.0010234129,0.00028461128,0.00068910175,0.00064902764,0.00039315465,0.001453044],"category_scores_gemma":[0.002364247,0.00023186718,0.0005014801,0.00086515094,0.00021427251,0.00041228035,0.00036687186,0.00035920664,0.00016995454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000114097646,0.000064766995,0.3134907,0.00003307041,0.00021604796,0.00015316575,0.000094813084,0.67476,0.001051396,0.0007390725,0.0012170925,0.008065848],"study_design_scores_gemma":[0.000016469834,0.00007850278,0.23634355,0.000011838839,0.00003745964,0.00003489119,0.00027134817,0.7606546,0.0008182093,0.00018206998,0.0015145631,0.000036529924],"about_ca_topic_score_codex":0.84046876,"about_ca_topic_score_gemma":0.7924016,"teacher_disagreement_score":0.15953124,"about_ca_system_score_codex":0.0048531042,"about_ca_system_score_gemma":0.0022946694,"threshold_uncertainty_score":0.32094145},"labels":[],"label_agreement":null},{"id":"W3084293858","doi":"10.32393/csme.2020.1203","title":"A Review of Essential Technologies for Autonomous and Semi-autonomous Articulated Heavy Vehicles","year":2020,"lang":"en","type":"review","venue":"Progress in Canadian Mechanical Engineering. Volume 3","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Computer science; Systems engineering; Control engineering; Engineering","score_opus":0.013549347056441119,"score_gpt":0.26119749332131087,"score_spread":0.24764814626486975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084293858","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00040535344,0.99195284,0.0017121899,0.00033750277,0.0004499552,0.000019183866,0.00007085326,0.000029261417,0.005022788],"genre_scores_gemma":[0.0018286543,0.99397767,0.0018621861,0.00015858439,0.00020419537,0.000018709834,0.0001078368,0.000006163873,0.0018360706],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99953556,0.00005321336,0.00008126878,0.000075366755,0.00021839542,0.000036153953],"domain_scores_gemma":[0.9993623,0.00028251912,0.00009007954,0.000020345024,0.00021348592,0.000031333017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005666726,0.00090774166,0.00085391756,0.0029292975,0.0003910681,0.0010681567,0.0009290937,0.00097293966,0.0052273483],"category_scores_gemma":[0.0008305067,0.00044352573,0.000623492,0.0030324042,0.00041240855,0.0021900733,0.00057087885,0.0010591456,0.0026696674],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056994668,0.00008690617,0.000263552,0.036414344,0.0000496162,0.00023916128,0.00014909716,0.00090981513,0.0055504036,0.010386868,0.030791115,0.9151022],"study_design_scores_gemma":[0.000002835386,0.00007567995,0.0005824163,0.004333774,0.00006293102,0.00047074424,0.000083328014,0.00020777056,0.0010570121,0.0015680675,0.9915343,0.000021236498],"about_ca_topic_score_codex":0.0021242495,"about_ca_topic_score_gemma":0.0025508602,"teacher_disagreement_score":0.0052273483,"about_ca_system_score_codex":0.00068561384,"about_ca_system_score_gemma":0.0017533379,"threshold_uncertainty_score":0.017487228},"labels":[],"label_agreement":null},{"id":"W3086056573","doi":"","title":"7.2 Travel Services in Canada and BC","year":2015,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Geography","score_opus":0.010895274392780704,"score_gpt":0.18647832275791523,"score_spread":0.17558304836513453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3086056573","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5310391,0.0070526805,0.0007311267,0.02389797,0.0010392119,0.00034901514,0.024663102,0.00026261163,0.41096517],"genre_scores_gemma":[0.7182234,0.0031584785,0.0012875615,0.005210387,0.00010604462,0.00011212706,0.006343475,0.00011187489,0.26544657],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976714,0.00010376989,0.00004709224,0.00011748368,0.0006878645,0.001372284],"domain_scores_gemma":[0.9974057,0.000058377118,0.0000725464,0.000019728308,0.0011154662,0.0013280901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039189475,0.00026414037,0.0003073405,0.0016810073,0.00748102,0.0038462947,0.00087381294,0.0011817338,0.026006695],"category_scores_gemma":[0.0013243336,0.00026005003,0.00052212825,0.0038713692,0.0006111291,0.0006844293,0.001411203,0.0015210044,0.002268822],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037860393,0.00035948236,0.3883084,0.00084170717,0.00013509301,0.0014135399,0.0073935213,0.0018199404,0.002182119,0.031019887,0.3453484,0.22079936],"study_design_scores_gemma":[0.00003504847,0.000056234712,0.5404921,0.0004913116,0.000044037464,0.0003051438,0.026627721,0.001039473,0.00046978178,0.0004669232,0.4299215,0.00005066115],"about_ca_topic_score_codex":0.99647945,"about_ca_topic_score_gemma":0.9991873,"teacher_disagreement_score":0.06507833,"about_ca_system_score_codex":0.06507833,"about_ca_system_score_gemma":0.10459056,"threshold_uncertainty_score":0.47217858},"labels":[],"label_agreement":null},{"id":"W3087247166","doi":"10.1016/j.trpro.2020.08.192","title":"Predicting Carsharing Station-Based Trip Generation Using a Growth Model","year":2020,"lang":"en","type":"article","venue":"Transportation research procedia","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Transport engineering; Service (business); Level of service; Computer science; Operations research; Engineering; Business","score_opus":0.1991005540041871,"score_gpt":0.35051720836699035,"score_spread":0.15141665436280324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3087247166","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9037528,0.0002047583,0.08835663,0.0003769822,0.000043787102,0.000100506775,0.002252709,0.00031185994,0.004600053],"genre_scores_gemma":[0.99235415,0.00008370559,0.0050371005,0.000011441521,0.0000062749987,0.000055957476,0.00085162173,0.000013584459,0.0015861886],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980336,0.000051515348,0.000009114773,0.00006039054,0.000024827306,0.00005087693],"domain_scores_gemma":[0.9990534,0.00062688027,0.00008551526,0.00003651032,0.00015344775,0.000044264023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006849823,0.00075264135,0.00049804215,0.00062302157,0.00029562405,0.0009405579,0.0010741306,0.0009869965,0.0017871769],"category_scores_gemma":[0.0017046323,0.00035046332,0.0008334419,0.00084703293,0.00041117633,0.00063113245,0.00048739763,0.001021257,0.00031697287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016790364,0.000019055371,0.0041116024,0.000010274173,0.000008804231,0.000030246441,0.000016781125,0.99311334,0.00017223232,0.00048534633,0.00015632044,0.0018591514],"study_design_scores_gemma":[0.0000011947874,0.0000063454895,0.0007302228,0.0000011544571,0.0000025116494,0.0000024838869,0.000010775723,0.9990397,0.00004606545,0.000104288374,0.00005291962,0.000002241049],"about_ca_topic_score_codex":0.111981735,"about_ca_topic_score_gemma":0.060733076,"teacher_disagreement_score":0.111981735,"about_ca_system_score_codex":0.001861316,"about_ca_system_score_gemma":0.001111637,"threshold_uncertainty_score":0.22265989},"labels":[],"label_agreement":null},{"id":"W3088814282","doi":"10.1016/b978-0-12-816816-5.00027-9","title":"Future of connected autonomous vehicles in smart cities","year":2020,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Smart city; Internet of Things; Computer science; Architectural engineering; Engineering; Telecommunications; Computer security","score_opus":0.011801399184485884,"score_gpt":0.20270929248760922,"score_spread":0.19090789330312333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3088814282","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0064787474,0.10669493,0.055712983,0.012431788,0.005684221,0.00008227771,0.00032274527,0.0005299959,0.81206244],"genre_scores_gemma":[0.10550696,0.17210682,0.031202426,0.002214148,0.0021736221,0.00013286508,0.0009395892,0.00024371124,0.6854799],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9998116,0.000045420125,0.0000065290023,0.000024234232,0.00008708642,0.000025151954],"domain_scores_gemma":[0.9998385,0.000059394526,0.000008114116,0.000018401814,0.00004831445,0.000027363947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030800723,0.000570896,0.00027383651,0.0006186571,0.00044667098,0.0025945986,0.0008396755,0.0018416457,0.029850395],"category_scores_gemma":[0.00045314617,0.00024449607,0.0003487018,0.0013715064,0.00076625444,0.004207231,0.0014538399,0.0011683756,0.0063904095],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020852289,0.000043574284,0.00018600072,0.0004633513,0.000015341328,0.00011031597,0.00028721147,0.008479093,0.0009917214,0.5567425,0.11914878,0.31351122],"study_design_scores_gemma":[0.0000033279487,0.000020477895,0.00010975887,0.00015971008,0.0000045330075,0.0000794408,0.00017481102,0.0033930172,0.00016252464,0.07223215,0.9236545,0.000005790561],"about_ca_topic_score_codex":0.002151125,"about_ca_topic_score_gemma":0.0033478658,"teacher_disagreement_score":0.029850395,"about_ca_system_score_codex":0.0011307488,"about_ca_system_score_gemma":0.0009258708,"threshold_uncertainty_score":0.099859536},"labels":[],"label_agreement":null},{"id":"W3092209517","doi":"10.1155/2020/8877499","title":"A Study on Public Adoption of Robo-Taxis in China","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China; China Association for Science and Technology","keywords":"Taxis; Public transport; Business; Construct (python library); China; Transport engineering; Usability; Marketing; Traffic congestion; Computer science; Engineering; Political science","score_opus":0.021589064225588022,"score_gpt":0.2551414491344825,"score_spread":0.2335523849088945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092209517","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99952984,0.000017641854,0.00002096301,0.000050332943,0.0000011267127,0.0000100998295,0.000024835124,8.9780895e-7,0.00034440504],"genre_scores_gemma":[0.9994241,0.000062719744,0.0000332795,0.000033812277,0.0000022092745,0.000016862368,0.00006221819,9.825761e-7,0.00036369904],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990139,0.00018162317,0.00009756956,0.00012703984,0.00026853327,0.00031136267],"domain_scores_gemma":[0.9969181,0.0007718332,0.0007401385,0.00019171614,0.0007925438,0.0005857072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018688898,0.00038896612,0.00039099655,0.001610263,0.001877569,0.0010042044,0.00046625655,0.0005838989,0.0024062446],"category_scores_gemma":[0.0028252096,0.00036876043,0.0007175253,0.002253515,0.0007754291,0.0009729188,0.0007108434,0.0007127193,0.00026531832],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004943638,0.0006659921,0.96512836,0.00006474573,0.00003934472,0.00042445926,0.024590358,0.00010751022,0.00068782957,0.00029846613,0.0003231355,0.0076203267],"study_design_scores_gemma":[0.0000079493775,0.00019701647,0.9783972,0.000021068467,0.000024363473,0.00007338793,0.019801103,0.0005688811,0.00014669937,0.00003542901,0.00071227696,0.000014651363],"about_ca_topic_score_codex":0.13655676,"about_ca_topic_score_gemma":0.12133631,"teacher_disagreement_score":0.13655676,"about_ca_system_score_codex":0.0027855253,"about_ca_system_score_gemma":0.0033298435,"threshold_uncertainty_score":0.27152377},"labels":[],"label_agreement":null},{"id":"W3092266739","doi":"10.1177/0361198120953797","title":"Finding the Subway Disruption Regimes of Switching Subway to Uber in Toronto","year":2020,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"TRIPS architecture; Public transport; Service (business); Transport engineering; Transit (satellite); Government (linguistics); Commission; Business; Engineering; Marketing; Finance","score_opus":0.09085504978165909,"score_gpt":0.38280445988627015,"score_spread":0.29194941010461106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092266739","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963676,0.00009649611,0.00016386919,0.000108287175,0.0000022058562,0.0000076125884,0.0018628881,0.0000057437683,0.0013852215],"genre_scores_gemma":[0.998128,0.000087724075,0.000065902546,0.000011535362,0.000001392789,0.000004838145,0.0010024626,0.0000024439034,0.0006956817],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997391,0.000026298434,0.000014930733,0.00005750563,0.00005493676,0.00010723587],"domain_scores_gemma":[0.9989826,0.00015416602,0.0003143427,0.000049509134,0.00028595066,0.00021341011],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020992232,0.00017820892,0.00023531972,0.0008933512,0.00069739384,0.0010074443,0.000387837,0.0003178065,0.00279435],"category_scores_gemma":[0.0017055959,0.00017248964,0.0002308329,0.002081237,0.00046148666,0.0005444947,0.0008113064,0.00037575295,0.0003372189],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014244046,0.00003193763,0.97896796,0.000063134015,0.000059347167,0.000320632,0.009016945,0.0013921311,0.0010343486,0.00085681846,0.0022774083,0.005836915],"study_design_scores_gemma":[0.0000012871932,0.000012089334,0.9864277,0.00001802933,0.000014484874,0.00002954187,0.010992955,0.0013043495,0.000118086034,0.000054592096,0.001018447,0.0000084370595],"about_ca_topic_score_codex":0.90373117,"about_ca_topic_score_gemma":0.9576043,"teacher_disagreement_score":0.09626883,"about_ca_system_score_codex":0.0069962023,"about_ca_system_score_gemma":0.0031583526,"threshold_uncertainty_score":0.19367152},"labels":[],"label_agreement":null},{"id":"W3092783261","doi":"10.1080/09687599.2020.1828044","title":"Governance models for rural accessible transportation: insights from Atlantic Canada","year":2020,"lang":"en","type":"article","venue":"Disability & Society","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Mount Allison University","funders":"","keywords":"Corporate governance; Regional science; Political science; Public administration; Economic geography; Business; Geography; Finance","score_opus":0.017339692332652458,"score_gpt":0.21672349101741828,"score_spread":0.19938379868476583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092783261","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5400371,0.0026149969,0.0038678548,0.040984783,0.00011975487,0.00021870923,0.00096314383,0.00003739371,0.41115624],"genre_scores_gemma":[0.976498,0.001896024,0.0012226711,0.0012673081,0.000009958653,0.00003950498,0.00019880888,0.000020640731,0.01884707],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.99803287,0.00036465318,0.000043001877,0.00012865395,0.0004572441,0.0009736334],"domain_scores_gemma":[0.99720913,0.00059489533,0.00019706154,0.00009995645,0.0010414767,0.0008573852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013790249,0.0002400395,0.0002478127,0.0012814404,0.01682792,0.006736545,0.0011932884,0.0008076448,0.0046855994],"category_scores_gemma":[0.0028138757,0.00021886262,0.00030116827,0.0035255153,0.005802315,0.0017154678,0.0026367565,0.0018982838,0.00020013211],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006301832,0.0001050893,0.058554593,0.00019602808,0.000032376713,0.0022221906,0.1610198,0.0038801907,0.0006201638,0.7009557,0.03543769,0.036913116],"study_design_scores_gemma":[0.000039934355,0.000031264673,0.07219003,0.0007220487,0.000050376628,0.00032350828,0.5037241,0.0052945595,0.00028016645,0.035184324,0.3820614,0.00009830266],"about_ca_topic_score_codex":0.99641573,"about_ca_topic_score_gemma":0.9985958,"teacher_disagreement_score":0.1580648,"about_ca_system_score_codex":0.1580648,"about_ca_system_score_gemma":0.16365169,"threshold_uncertainty_score":0.9765255},"labels":[],"label_agreement":null},{"id":"W3094199731","doi":"10.1049/iet-smc.2020.0046","title":"Decentralised game‐theoretic management for a community‐based transportation system","year":2020,"lang":"en","type":"article","venue":"IET Smart Cities","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Game theory; Management system; Computer science; Business; Mathematical economics; Operations management; Economics","score_opus":0.025247340411612057,"score_gpt":0.22307673330756103,"score_spread":0.19782939289594897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094199731","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06420234,0.00013084627,0.9242941,0.0005018491,0.000054861815,0.00014425698,0.00009513678,0.00012434722,0.010452219],"genre_scores_gemma":[0.9627343,0.00011525419,0.031989567,0.00004956997,0.000018263725,0.00014648895,0.000054314492,0.000016578402,0.0048757526],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992625,0.00028276796,0.000025839063,0.00014703046,0.0001451059,0.00013676075],"domain_scores_gemma":[0.999433,0.00020335667,0.000081088736,0.000057689525,0.00010892945,0.00011586515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007770508,0.00073218445,0.00089767337,0.00039918837,0.0008464314,0.0015523909,0.0015413704,0.0011622675,0.0036181184],"category_scores_gemma":[0.001318823,0.0003820633,0.00076671643,0.00054932234,0.0014929852,0.0017570424,0.0019535257,0.0016234268,0.00030121708],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000447714,0.000035628043,0.00017832004,0.000029130526,0.000017264369,0.00007404887,0.000056602774,0.9590326,0.00097016833,0.036552615,0.00032372252,0.0026852365],"study_design_scores_gemma":[0.000010467178,0.000022917733,0.000052278774,0.0000023744885,0.0000043840364,0.000013034131,0.000021496742,0.99020165,0.00008481063,0.009161744,0.00042044267,0.000004474479],"about_ca_topic_score_codex":0.009083806,"about_ca_topic_score_gemma":0.0081521105,"teacher_disagreement_score":0.009083806,"about_ca_system_score_codex":0.0020370386,"about_ca_system_score_gemma":0.0017168182,"threshold_uncertainty_score":0.018061876},"labels":[],"label_agreement":null},{"id":"W3094687104","doi":"","title":"Machine Learning Based Demand Modelling for On-Demand Transit Services: A Case Study of Belleville, Ontario.","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Public transport; Service (business); TRIPS architecture; Schedule; Transport engineering; Trip generation; Computer science; Supply and demand; Population; Demand forecasting; Operations research; Business; Engineering; Marketing; Economics","score_opus":0.08502253351029912,"score_gpt":0.18890998066761916,"score_spread":0.10388744715732004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094687104","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97223884,0.0006493616,0.0071782316,0.0013424847,0.000036710295,0.00027257693,0.003214625,0.00015490968,0.014912237],"genre_scores_gemma":[0.9829266,0.0004659279,0.0039444147,0.00007251821,0.000008774749,0.00007861409,0.0024072607,0.00003607105,0.010059879],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994728,0.000119327466,0.00002400226,0.00008023378,0.00014773812,0.00015592696],"domain_scores_gemma":[0.9989716,0.0004036417,0.000072887444,0.000059586262,0.00036552182,0.00012686242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007551206,0.00083509623,0.00038175602,0.00061751873,0.0023093468,0.0011502687,0.001564289,0.0010237104,0.002720592],"category_scores_gemma":[0.0018153612,0.00039832338,0.0007896733,0.0019930871,0.00079558813,0.0006752705,0.00058216794,0.00066570326,0.0003716399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083930837,0.0013744867,0.2946576,0.0009939746,0.00034206206,0.013749075,0.007884861,0.5382427,0.007556981,0.0156086655,0.03275389,0.08599641],"study_design_scores_gemma":[0.000105348576,0.00028762777,0.15526551,0.00011663715,0.00011297876,0.00044874602,0.013492851,0.8002599,0.001362257,0.0015294433,0.026896121,0.0001225877],"about_ca_topic_score_codex":0.9807298,"about_ca_topic_score_gemma":0.98571026,"teacher_disagreement_score":0.026189543,"about_ca_system_score_codex":0.026189543,"about_ca_system_score_gemma":0.013270397,"threshold_uncertainty_score":0.19001931},"labels":[],"label_agreement":null},{"id":"W3096081032","doi":"10.1109/isc251055.2020.9239059","title":"Learning-based open driver guidance and rebalancing for reducing riders’ wait time in ride-hailing platforms","year":2020,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Matching (statistics); Parametric statistics; Real-time computing; Simulation","score_opus":0.01932233946978846,"score_gpt":0.2388863125293627,"score_spread":0.21956397305957426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3096081032","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10205963,0.00025271252,0.89456284,0.00016056078,0.00005982954,0.00008490851,0.000070874,0.0011409025,0.0016077247],"genre_scores_gemma":[0.9383299,0.00007239808,0.059545632,0.00006318324,0.000034264114,0.00006106095,0.00009911209,0.00005077535,0.0017437257],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999418,0.00009545665,0.000022857177,0.00018135198,0.00011647041,0.00016581276],"domain_scores_gemma":[0.9990783,0.00038152485,0.00014895025,0.000081285456,0.000190902,0.00011898951],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077134505,0.00077312003,0.0010939378,0.0005961765,0.00049073156,0.0006609182,0.002150149,0.0007964286,0.0018450174],"category_scores_gemma":[0.002336804,0.00051299646,0.0006050357,0.00059935387,0.0005418037,0.0011534947,0.0010077112,0.0011221664,0.00035255236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020045838,0.00026939507,0.002377521,0.00006032868,0.00004138338,0.00007837847,0.000113533024,0.8685758,0.0048431936,0.0024939815,0.0013575838,0.11958848],"study_design_scores_gemma":[0.000010952558,0.00006335745,0.0003748644,0.0000023082043,0.000010296544,0.000010823728,0.000023730852,0.9977895,0.00064176624,0.00082641386,0.00023852388,0.0000075682387],"about_ca_topic_score_codex":0.017310914,"about_ca_topic_score_gemma":0.01441693,"teacher_disagreement_score":0.017310914,"about_ca_system_score_codex":0.0008010185,"about_ca_system_score_gemma":0.0022038806,"threshold_uncertainty_score":0.03442031},"labels":[],"label_agreement":null},{"id":"W3096546741","doi":"10.2139/ssrn.3675063","title":"Courier Dispatch in On-Demand Delivery","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Business; Demand forecasting; On demand; Computer science; Operations management; Operations research; Economics; Engineering; Marketing; Commerce","score_opus":0.0073788065253199645,"score_gpt":0.20147670361114128,"score_spread":0.1940978970858213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3096546741","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13485646,0.0035407536,0.7577281,0.0059347665,0.0024887784,0.00032005543,0.00075012847,0.00048763267,0.09389332],"genre_scores_gemma":[0.897916,0.001579461,0.020929798,0.00033195145,0.0007398642,0.00013143629,0.0002590254,0.00038219133,0.077730305],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99714655,0.0015605671,0.000093182294,0.00039901488,0.0003006269,0.000500117],"domain_scores_gemma":[0.9886135,0.009027139,0.0006162221,0.00023333744,0.0006309882,0.00087879796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041365307,0.0018253095,0.004254268,0.0012805626,0.001518686,0.005182512,0.0033175114,0.0038358346,0.022071825],"category_scores_gemma":[0.018344127,0.0018426838,0.0016267007,0.0017376613,0.002813726,0.0053540096,0.002973535,0.0044857245,0.0015258691],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041147476,0.00012863916,0.00050334353,0.00024290965,0.000072370225,0.0004644006,0.0003408711,0.65026313,0.00046512525,0.32977667,0.008687829,0.008643111],"study_design_scores_gemma":[0.00003539671,0.00006797442,0.00017606725,0.000020643076,0.000022278593,0.000043305394,0.00012369509,0.9336748,0.00007757875,0.06398333,0.0017460099,0.000028960267],"about_ca_topic_score_codex":0.019764714,"about_ca_topic_score_gemma":0.009620364,"teacher_disagreement_score":0.022071825,"about_ca_system_score_codex":0.003937243,"about_ca_system_score_gemma":0.0020902327,"threshold_uncertainty_score":0.07383764},"labels":[],"label_agreement":null},{"id":"W3097533361","doi":"","title":"Calepin / ASTAQ, Alliance des services de transport adapté du Québec","year":2005,"lang":"fr","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Alliance; Political science; Business","score_opus":0.011042616366039705,"score_gpt":0.2161708121062321,"score_spread":0.2051281957401924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3097533361","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07039982,0.011391771,0.018254265,0.037024472,0.005444317,0.0011983302,0.059580967,0.0038406437,0.7928654],"genre_scores_gemma":[0.072364144,0.0012475016,0.00413395,0.0009338593,0.000119921475,0.00011703528,0.0054247426,0.00024344929,0.91541547],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99850804,0.000114695635,0.000040958363,0.00024322969,0.00071275973,0.00038033287],"domain_scores_gemma":[0.9957339,0.000352421,0.0001421277,0.00019464514,0.0029520418,0.00062488375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011815547,0.0012891067,0.00065977365,0.0018367114,0.0047827247,0.0038765233,0.001413375,0.0020838482,0.12078907],"category_scores_gemma":[0.0024430754,0.00046446093,0.0005755356,0.0022554637,0.00079035235,0.001295994,0.0009781598,0.0024054,0.012456713],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008239409,0.00042867003,0.026128015,0.00027852,0.00011923592,0.00079620956,0.00052451243,0.007950487,0.0046931817,0.06334167,0.682043,0.21287248],"study_design_scores_gemma":[0.0001737691,0.000084913525,0.046011962,0.0001137343,0.00002627417,0.0001680496,0.00045966465,0.012739594,0.0014052136,0.001709516,0.937046,0.00006125507],"about_ca_topic_score_codex":0.9756572,"about_ca_topic_score_gemma":0.97468513,"teacher_disagreement_score":0.12078907,"about_ca_system_score_codex":0.03548515,"about_ca_system_score_gemma":0.054299448,"threshold_uncertainty_score":0.40407974},"labels":[],"label_agreement":null},{"id":"W3100463562","doi":"","title":"Spatial or Temporal Pooling Solves Wild Goose Chase","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Goose; Pooling; Computer science; Geography; Artificial intelligence; Ecology; Biology","score_opus":0.014377084040044086,"score_gpt":0.22895963623343848,"score_spread":0.2145825521933944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3100463562","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2750182,0.00076871214,0.71107113,0.0007785141,0.00014924322,0.000084396845,0.00019524405,0.00049242965,0.011442156],"genre_scores_gemma":[0.9678761,0.00020470166,0.026021225,0.0001673552,0.00006726375,0.00005209461,0.00014616414,0.00008062817,0.0053845965],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993524,0.0001128741,0.000025888081,0.00014051456,0.000070102156,0.00029835603],"domain_scores_gemma":[0.9978314,0.0012378789,0.00025363726,0.00023596159,0.00016851326,0.00027260242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011649694,0.0009961269,0.0019151232,0.00042769648,0.00072687917,0.0009435908,0.0013071259,0.0013589355,0.0041299323],"category_scores_gemma":[0.004027494,0.00045725793,0.00088703464,0.0006448759,0.0013119301,0.0021651676,0.0031909733,0.0013784753,0.00028500092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00095221604,0.00033555695,0.0043889354,0.0003329215,0.00022546542,0.0010740394,0.0003098784,0.7495434,0.010136622,0.15045704,0.009695173,0.07254869],"study_design_scores_gemma":[0.00003193183,0.000083445186,0.00034157003,0.000007524771,0.000025449684,0.00007711172,0.00004937843,0.9483531,0.0007866082,0.0495747,0.0006572862,0.0000117950785],"about_ca_topic_score_codex":0.006380378,"about_ca_topic_score_gemma":0.0029385416,"teacher_disagreement_score":0.006380378,"about_ca_system_score_codex":0.0006017539,"about_ca_system_score_gemma":0.0014668355,"threshold_uncertainty_score":0.013816059},"labels":[],"label_agreement":null},{"id":"W3102391164","doi":"","title":"Courier Sharing in Food Delivery","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Business; Queue; Sharing economy; Market share; Queueing theory; Food delivery; Space (punctuation); Taste; Variety (cybernetics); Marketing; Computer science; Computer network","score_opus":0.01146356992676084,"score_gpt":0.20017623494356548,"score_spread":0.18871266501680464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3102391164","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.362693,0.0019227634,0.591685,0.0023016941,0.00038577363,0.00014005628,0.0002629757,0.00043139714,0.040177394],"genre_scores_gemma":[0.977015,0.0005055919,0.012287314,0.00014631999,0.000105804225,0.00005952135,0.000044851287,0.000053324176,0.009782394],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99831355,0.0005910331,0.000053164527,0.00037656125,0.00023065267,0.00043504118],"domain_scores_gemma":[0.9962631,0.0019002481,0.00071374245,0.0002696151,0.00031209542,0.0005411112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013319731,0.0009804117,0.0010017691,0.0006504175,0.0013290694,0.0024176247,0.001675297,0.0012636087,0.007968095],"category_scores_gemma":[0.0060145324,0.000654351,0.0011067068,0.0006902806,0.0019966832,0.003856807,0.0025140247,0.0014261092,0.0006170751],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034436758,0.00019831647,0.0025644412,0.00015909922,0.000114321985,0.0005208863,0.00060339243,0.57432,0.0038454772,0.39513844,0.0031343424,0.019056832],"study_design_scores_gemma":[0.000050694704,0.00023962645,0.0011569094,0.000021734264,0.000057463032,0.00010381977,0.00021236368,0.85145783,0.00060985924,0.14178358,0.0042434116,0.00006268144],"about_ca_topic_score_codex":0.010636798,"about_ca_topic_score_gemma":0.005527815,"teacher_disagreement_score":0.010636798,"about_ca_system_score_codex":0.0028930507,"about_ca_system_score_gemma":0.0013555166,"threshold_uncertainty_score":0.026655972},"labels":[],"label_agreement":null},{"id":"W3103247660","doi":"10.3390/su12229587","title":"Sustainable Commuting: Results from a Social Approach and International Evidence on Carpooling","year":2020,"lang":"en","type":"article","venue":"Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Ministerio de Ciencia e Innovación","keywords":"Occupancy; Public transport; Business; Multinational corporation; Sustainable transport; Ordinary least squares; Empirical evidence; Work (physics); Transport engineering; Geography; Sustainability; Economic growth; Engineering; Economics; Econometrics; Civil engineering","score_opus":0.043067881989830796,"score_gpt":0.2786521418691271,"score_spread":0.23558425987929632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3103247660","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9517254,0.0032693478,0.0004686794,0.0010726814,0.000039588016,0.00003127906,0.00065245054,0.000007489705,0.04273297],"genre_scores_gemma":[0.998228,0.00084526546,0.000066161934,0.00005170117,0.000026607922,0.000011167414,0.00022532212,0.000004944247,0.00054086314],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998409,0.00071755255,0.00014407033,0.00021452011,0.0002119291,0.00030296706],"domain_scores_gemma":[0.9906598,0.0033343248,0.0035920793,0.0005793185,0.0012233554,0.00061112706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002049806,0.0003342005,0.00027913746,0.0022744192,0.0007034983,0.0013919584,0.0003818381,0.00040677277,0.0059725456],"category_scores_gemma":[0.0064310175,0.000091031885,0.0006904589,0.0041125766,0.0019641342,0.0013019664,0.002154684,0.00053858664,0.0004812353],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024487686,0.00015276317,0.9575188,0.0005734667,0.00031556425,0.00021890661,0.010780086,0.0004388623,0.00023066418,0.004406638,0.0007888756,0.024330394],"study_design_scores_gemma":[0.0000065932536,0.000107371096,0.96591216,0.00027468082,0.00016483199,0.00008117142,0.028855816,0.00021141929,0.000109828376,0.0007092105,0.0035548306,0.000012026375],"about_ca_topic_score_codex":0.014670257,"about_ca_topic_score_gemma":0.017874286,"teacher_disagreement_score":0.014670257,"about_ca_system_score_codex":0.0006420445,"about_ca_system_score_gemma":0.0006159457,"threshold_uncertainty_score":0.029169738},"labels":[],"label_agreement":null},{"id":"W3106857189","doi":"10.2139/ssrn.3675050","title":"Share or Solo? Individual and Social Choices in Ride-Hailing","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Social psychology; Psychology; Business; Economics; Marketing; Sociology","score_opus":0.02270731970242855,"score_gpt":0.24474738528142906,"score_spread":0.22204006557900052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3106857189","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97389096,0.0002465757,0.0008014725,0.0018716089,0.000021199055,0.000010674529,0.000053810447,0.000004839948,0.023098769],"genre_scores_gemma":[0.9987174,0.000039011466,0.00008129516,0.000042468517,0.0000054933325,0.0000026839775,0.000008215399,0.0000021446629,0.0011012271],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985985,0.00079591025,0.000039862287,0.00010745884,0.000118201686,0.00034005273],"domain_scores_gemma":[0.99494886,0.0020921144,0.0009815816,0.0003116733,0.00027675892,0.001388998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022818812,0.00014780265,0.0002872375,0.0006565624,0.001991499,0.0041084853,0.0005024516,0.0019398615,0.011165784],"category_scores_gemma":[0.007287718,0.0002052502,0.00026842934,0.0006776262,0.002969749,0.002954749,0.0014281594,0.0010031015,0.0008508442],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00259044,0.0016140409,0.64878094,0.0001636023,0.0004867411,0.0011558154,0.07563881,0.0060122446,0.0018793748,0.13181259,0.006008579,0.123856746],"study_design_scores_gemma":[0.00010042283,0.0005396993,0.47062218,0.00009266493,0.00012891978,0.0005546291,0.33441013,0.009315259,0.00066053047,0.15898734,0.024435965,0.00015219158],"about_ca_topic_score_codex":0.005206554,"about_ca_topic_score_gemma":0.0132572735,"teacher_disagreement_score":0.011165784,"about_ca_system_score_codex":0.0006927731,"about_ca_system_score_gemma":0.00042714213,"threshold_uncertainty_score":0.037353337},"labels":[],"label_agreement":null},{"id":"W3107004460","doi":"10.1177/0361198120966601","title":"On the Influence of Land Use and Transit Network Attributes on the Generation of, and Relationship between, the Demand for Public Transit and Ride-Hailing Services in Toronto","year":2020,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Public transport; Transit (satellite); Context (archaeology); Recreation; Business; Transport engineering; Trip generation; TRIPS architecture; Geography; Engineering","score_opus":0.1923933875364037,"score_gpt":0.35124854362432323,"score_spread":0.15885515608791953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3107004460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999188,0.00005506589,0.000056086465,0.000060430546,0.0000010398294,0.0000041303515,0.00020508553,0.000002010958,0.00042809112],"genre_scores_gemma":[0.99938214,0.000041526127,0.000027378417,0.0000049776513,8.5417855e-7,0.0000020045163,0.00018228455,0.0000011225577,0.0003576244],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996853,0.000097628064,0.000020898498,0.00004934078,0.000053397034,0.000093554074],"domain_scores_gemma":[0.9970783,0.0015347658,0.00046629919,0.00009946847,0.00030762615,0.00051361293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004542622,0.0002559386,0.00021878816,0.00046690082,0.0005908898,0.0011092948,0.0004355876,0.00030203522,0.002638376],"category_scores_gemma":[0.0029423928,0.00023665153,0.00053895125,0.00070907857,0.0006199476,0.00033558777,0.0006307266,0.00043813203,0.00024182946],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000090034875,0.00004473065,0.99439573,0.00001149861,0.000075746066,0.00018475084,0.0007243256,0.0020395317,0.0005324854,0.00019683137,0.00021532904,0.00148916],"study_design_scores_gemma":[0.0000027187643,0.000021055046,0.9938226,0.000004870756,0.000025517287,0.000027718968,0.0012282173,0.004524184,0.00009422405,0.00003890955,0.00020417481,0.0000058551727],"about_ca_topic_score_codex":0.77799225,"about_ca_topic_score_gemma":0.84142756,"teacher_disagreement_score":0.22200775,"about_ca_system_score_codex":0.0059637194,"about_ca_system_score_gemma":0.0019428604,"threshold_uncertainty_score":0.44663036},"labels":[],"label_agreement":null},{"id":"W3107052621","doi":"10.1155/2020/8831674","title":"The Impact of Ride-Hailing Services on Private Car Use in Urban Areas: An Examination in Chinese Cities","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"China; Business; Private transport; Difference in differences; Public transport; Transport engineering; Marketing; Finance; Economics; Geography; Engineering","score_opus":0.01136981498076854,"score_gpt":0.2566161056950771,"score_spread":0.24524629071430856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3107052621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99905485,0.00012051404,0.000037927977,0.00008445907,0.000003832248,0.000006068794,0.00030485998,0.000002296363,0.00038527953],"genre_scores_gemma":[0.9992625,0.00010546827,0.000029293571,0.000026377957,0.0000047979593,0.000007052698,0.0003716667,0.0000017037088,0.00019123078],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990646,0.00014933622,0.00012383028,0.0001939563,0.00020267486,0.00026554737],"domain_scores_gemma":[0.99786144,0.00030297422,0.00064694806,0.00023492191,0.0004437964,0.0005098691],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010664241,0.00044157208,0.00044541518,0.0019790903,0.0009461079,0.0009332809,0.0007006654,0.00039867134,0.0015167703],"category_scores_gemma":[0.0015924536,0.000374506,0.0016522692,0.0036165272,0.000869369,0.00063853926,0.0014571949,0.00058837456,0.00020170414],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015833562,0.00002476702,0.9971474,0.000018927372,0.000080446895,0.000115813484,0.0007110784,0.00019251756,0.000120466946,0.000076325414,0.00013734723,0.0013592483],"study_design_scores_gemma":[7.072206e-7,0.000009347415,0.99890316,0.000003926787,0.00001765162,0.000013907963,0.00063378556,0.000260815,0.000023084074,0.000009565486,0.000120468525,0.0000036454535],"about_ca_topic_score_codex":0.24505131,"about_ca_topic_score_gemma":0.31447008,"teacher_disagreement_score":0.24505131,"about_ca_system_score_codex":0.002475868,"about_ca_system_score_gemma":0.0021374708,"threshold_uncertainty_score":0.4872499},"labels":[],"label_agreement":null},{"id":"W3107135784","doi":"10.1007/978-3-030-62807-9_31","title":"Methodology for Designing a Collaborative Business Model – Case Study Aerospace Cluster","year":2020,"lang":"en","type":"book-chapter","venue":"IFIP advances in information and communication technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Business model; Aerospace; Product (mathematics); Key (lock); Knowledge management; Process management; Business; Cluster (spacecraft); New business development; Collaborative model; Business Model Canvas; Marketing; Computer science; Engineering","score_opus":0.03703981921268388,"score_gpt":0.30343999892505047,"score_spread":0.26640017971236657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3107135784","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.038733535,0.0000655417,0.9211633,0.00045662766,0.000019640285,0.0035664462,0.0005351646,0.00020674213,0.035252996],"genre_scores_gemma":[0.1806686,0.00009255251,0.80838454,0.00007157942,0.0000060351003,0.0037577255,0.00055606914,0.000055747914,0.0064070956],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9968124,0.0020840727,0.00018114327,0.00029557364,0.00046498358,0.00016191235],"domain_scores_gemma":[0.9968514,0.0020174612,0.00015718726,0.00036035432,0.0005019053,0.00011164683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030171245,0.0006028679,0.00029875975,0.0019336481,0.0015686862,0.00255608,0.0019432867,0.0014175969,0.013396291],"category_scores_gemma":[0.005300339,0.00053183147,0.0008711232,0.0016651693,0.000995018,0.0019800796,0.0018473609,0.00096688926,0.0017104188],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024157205,0.001470561,0.008822727,0.0014534201,0.000112388705,0.0023028017,0.013296129,0.089383826,0.014832911,0.55274075,0.008383101,0.30695975],"study_design_scores_gemma":[0.0003286339,0.0006610802,0.0046979757,0.00091536704,0.00016306242,0.0016363367,0.030413024,0.57121205,0.022802517,0.21123073,0.15580317,0.00013604795],"about_ca_topic_score_codex":0.0042244927,"about_ca_topic_score_gemma":0.005794283,"teacher_disagreement_score":0.013396291,"about_ca_system_score_codex":0.0018506268,"about_ca_system_score_gemma":0.0031927652,"threshold_uncertainty_score":0.044815063},"labels":[],"label_agreement":null},{"id":"W3108306469","doi":"10.1016/j.retrec.2020.101005","title":"2020 editorial statement, Journal of the Transportation Research Forum (JTRF)","year":2020,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Statement (logic); Transport engineering; Engineering; Library science; Business; Political science; Computer science; Law","score_opus":0.0941366642615359,"score_gpt":0.3523132654698264,"score_spread":0.2581766012082905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108306469","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000073011615,0.0018742293,0.00009175726,0.06039604,0.93554986,0.000028478336,0.0001508416,0.00004397782,0.0017918266],"genre_scores_gemma":[0.00114159,0.003202584,0.0002472247,0.040864542,0.92415506,0.00006214336,0.00018913987,0.000086780965,0.030050913],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9921808,0.0008037805,0.00094078307,0.0010574659,0.004284753,0.00073240453],"domain_scores_gemma":[0.9604772,0.008618233,0.0033668906,0.0010084267,0.020529041,0.006000237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011422571,0.0024356432,0.0025352596,0.004240842,0.0043651024,0.010460934,0.00297255,0.020247623,0.035831966],"category_scores_gemma":[0.050279845,0.0009823889,0.0021054407,0.0015008971,0.001865916,0.003920207,0.001901938,0.012612509,0.023532368],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033595894,0.000010952374,0.000043349963,0.00008231667,0.0000072441944,0.000042981734,0.000009185352,0.0000111264935,0.000077277226,0.00017024281,0.99686915,0.0026425915],"study_design_scores_gemma":[0.000065740736,0.000038624512,0.0008685929,0.00036727436,0.00004132747,0.00010916743,0.000082225706,0.00021900877,0.00024760352,0.00062381674,0.99731004,0.000026519996],"about_ca_topic_score_codex":0.0036043837,"about_ca_topic_score_gemma":0.0059516924,"teacher_disagreement_score":0.035831966,"about_ca_system_score_codex":0.0027877355,"about_ca_system_score_gemma":0.008168324,"threshold_uncertainty_score":0.11986983},"labels":[],"label_agreement":null},{"id":"W3108335167","doi":"10.23977/jaip.2020.030109","title":"Research on Airport Taxi Dispatching based on Probability Model","year":2020,"lang":"en","type":"article","venue":"Journal of Artificial Intelligence Practice","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Taxis; Computer science; Operations research; Revenue; Scheduling (production processes); Order (exchange); Transport engineering; Engineering; Operations management","score_opus":0.2441847588478845,"score_gpt":0.41276744050097663,"score_spread":0.16858268165309215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108335167","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022097256,0.0016558467,0.96685386,0.0007556448,0.00015590253,0.000053940115,0.00012104379,0.00022589085,0.008080646],"genre_scores_gemma":[0.9065251,0.0067657204,0.07608549,0.0001563232,0.0003765315,0.000176379,0.000377327,0.000102868304,0.0094343005],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99861073,0.00030907925,0.00008650088,0.00040884598,0.00038806396,0.00019673909],"domain_scores_gemma":[0.99899524,0.0005665086,0.00010624444,0.000052339474,0.00021423299,0.00006542965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011739961,0.0008311571,0.0011761199,0.0011144207,0.00082185795,0.002572161,0.001607436,0.00092456397,0.002962333],"category_scores_gemma":[0.003565896,0.00069888047,0.0014856367,0.0021773684,0.0005846574,0.0043788403,0.0007465446,0.0012809541,0.00039456415],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042842647,0.00005050245,0.0025479181,0.00016634964,0.000060965296,0.00013685609,0.000120314784,0.894822,0.0007852044,0.062269498,0.0018786974,0.037118856],"study_design_scores_gemma":[0.000003523944,0.000013437462,0.00032830396,0.000007638116,0.000013162587,0.00003290564,0.000030510302,0.9884878,0.00017761072,0.010009406,0.0008843056,0.000011453622],"about_ca_topic_score_codex":0.021252347,"about_ca_topic_score_gemma":0.0060026767,"teacher_disagreement_score":0.021252347,"about_ca_system_score_codex":0.0022943518,"about_ca_system_score_gemma":0.002661429,"threshold_uncertainty_score":0.04225725},"labels":[],"label_agreement":null},{"id":"W3110711310","doi":"10.1177/0361198120969368","title":"Mobility-as-a-Service and Demand-Responsive Transport: Practical Implementation in Traditional Forecasting Models","year":2020,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Occupancy; Transport engineering; Service (business); Urban transit; Transit (satellite); Computer science; Transit system; Aside; Demand forecasting; Level of service; Public transport; Operations research; Business; Engineering; Marketing","score_opus":0.22890352221305788,"score_gpt":0.4022165797902091,"score_spread":0.1733130575771512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110711310","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02599466,0.0001145126,0.9706325,0.00042280968,0.000038090955,0.000070811315,0.00006539826,0.00034447692,0.0023167417],"genre_scores_gemma":[0.5348306,0.0003654579,0.46109384,0.00011350189,0.000109954,0.00031549553,0.0001927689,0.000104000144,0.0028743995],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995433,0.00022705074,0.000028296412,0.00007761336,0.000073564894,0.0000503221],"domain_scores_gemma":[0.9979292,0.0015465339,0.00009819218,0.000094058756,0.00026760064,0.00006452141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019581488,0.0007695719,0.0008801881,0.00040909473,0.0008292351,0.00125403,0.0015341919,0.001979146,0.0027305384],"category_scores_gemma":[0.0070719635,0.00062774244,0.0005704177,0.0009680336,0.0006211737,0.0019844568,0.0014345906,0.0019900922,0.0005079599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000150181795,0.000023775801,0.00058540783,0.000012089217,0.000008225658,0.000027163278,0.000039587147,0.97944677,0.00015895303,0.0063960133,0.0002469694,0.01303998],"study_design_scores_gemma":[0.0000016876778,0.0000025443132,0.000016207401,0.0000010624518,8.1868245e-7,0.0000017139932,0.000005086135,0.9987393,0.000024568813,0.0011159494,0.00008995629,0.0000010976872],"about_ca_topic_score_codex":0.05446568,"about_ca_topic_score_gemma":0.0376,"teacher_disagreement_score":0.05446568,"about_ca_system_score_codex":0.0010405183,"about_ca_system_score_gemma":0.0016733373,"threshold_uncertainty_score":0.10829729},"labels":[],"label_agreement":null},{"id":"W3111131827","doi":"10.1007/978-3-030-60865-1_21","title":"Urban Design and Shared Transport","year":2020,"lang":"en","type":"book-chapter","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Carpool; Transport engineering; Traffic congestion; Business; Engineering; Environmental planning; Geography","score_opus":0.027774850874305642,"score_gpt":0.19446449601525223,"score_spread":0.16668964514094659,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111131827","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011966461,0.0028045552,0.011978622,0.001004042,0.000425977,0.000016203296,0.000038707953,0.00007573483,0.98245966],"genre_scores_gemma":[0.043604586,0.002790298,0.0036326847,0.00036265215,0.00013634337,0.000058845984,0.00006626271,0.00015689508,0.9491915],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996424,0.0001426725,0.000007064051,0.000043148026,0.00010258837,0.00006212818],"domain_scores_gemma":[0.9999163,0.000019627536,0.0000044241774,0.000024069588,0.000022366768,0.000013150639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026023854,0.0011260026,0.00039547394,0.0006280276,0.0020821225,0.0041633607,0.000769591,0.0011989989,0.044745613],"category_scores_gemma":[0.00044836669,0.0003823624,0.00038946499,0.0012607229,0.0025078095,0.0024905354,0.0024379047,0.001467224,0.008384564],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000071804857,0.000012785947,0.000048585436,0.000046163117,0.0000032011542,0.000029930934,0.00057329837,0.001794479,0.00009978158,0.8877367,0.06685447,0.0427935],"study_design_scores_gemma":[0.0000019458832,0.000011669211,0.0001050232,0.000056037698,0.0000035509006,0.000042767486,0.0005997574,0.00082244386,0.000099399935,0.15633029,0.84192234,0.0000047621775],"about_ca_topic_score_codex":0.009262455,"about_ca_topic_score_gemma":0.028250817,"teacher_disagreement_score":0.044745613,"about_ca_system_score_codex":0.0033700939,"about_ca_system_score_gemma":0.0019273381,"threshold_uncertainty_score":0.14968902},"labels":[],"label_agreement":null},{"id":"W3113288164","doi":"10.1016/j.trb.2020.11.002","title":"The impact of autonomous vehicles on commute ridesharing with uncertain work end time","year":2020,"lang":"en","type":"article","venue":"Transportation Research Part B Methodological","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"U.S. Department of Energy","keywords":"Bottleneck; Work (physics); Evening; Rush hour; Transport engineering; Computer science; Travel time; Service (business); Journey to work; Modal shift; Business; Engineering; Public transport; Marketing","score_opus":0.3796719486545043,"score_gpt":0.4432009021116626,"score_spread":0.06352895345715825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113288164","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98228365,0.0003985501,0.0086573195,0.00063878123,0.00006879006,0.000036693178,0.00031159763,0.000022703794,0.0075819143],"genre_scores_gemma":[0.99858725,0.00007247236,0.0003309562,0.000012281676,0.0000084133535,0.0000059946024,0.00004349186,0.0000046983837,0.00093435316],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987355,0.0004929948,0.000040089573,0.00017563722,0.00017234082,0.0003834132],"domain_scores_gemma":[0.9764974,0.020134127,0.0010379058,0.00045803856,0.0011179982,0.00075452065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019879076,0.00044399928,0.0005270241,0.00054343423,0.00070144737,0.002138196,0.0011629249,0.0010704609,0.005242001],"category_scores_gemma":[0.018467398,0.00038658563,0.0005517611,0.00072618545,0.0009791921,0.0019791827,0.0013660945,0.0010879231,0.00023975453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015587226,0.00041849315,0.05643761,0.00014823503,0.00017137645,0.0006357675,0.00046415854,0.9022495,0.0012853073,0.017554563,0.0010849349,0.017991342],"study_design_scores_gemma":[0.000050387614,0.00076291733,0.06931153,0.00003278509,0.00023732643,0.00014003355,0.0031096037,0.9022935,0.0011286973,0.021699833,0.0011626036,0.000070834445],"about_ca_topic_score_codex":0.038406625,"about_ca_topic_score_gemma":0.025683157,"teacher_disagreement_score":0.038406625,"about_ca_system_score_codex":0.0016713168,"about_ca_system_score_gemma":0.0011515405,"threshold_uncertainty_score":0.07636613},"labels":[],"label_agreement":null},{"id":"W3114826675","doi":"10.1109/isncc49221.2020.9297295","title":"Game Theoretic Approach for a Multi-Mode Transportation in Smart Cities","year":2020,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"MATLAB; Computer science; Mode (computer interface); Game theory; Software; Work (physics); Transport engineering; Simulation; Real-time computing; Engineering; Human–computer interaction; Operating system","score_opus":0.036437985909866605,"score_gpt":0.2540244304151114,"score_spread":0.2175864445052448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3114826675","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008691576,0.0003462041,0.9764905,0.0004890313,0.000093296505,0.0000694647,0.00011530781,0.000078155215,0.013626503],"genre_scores_gemma":[0.7776471,0.0012133486,0.20546256,0.0003688595,0.00012028567,0.0003943404,0.0002000278,0.00008439498,0.014509081],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936324,0.00032064208,0.000019983829,0.00008533995,0.00013887716,0.00007184015],"domain_scores_gemma":[0.99969053,0.00015904215,0.000029937615,0.00001781691,0.00007083229,0.000031918706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007156272,0.00086791615,0.000734924,0.00059345353,0.00060908316,0.0014988062,0.001437333,0.0010806976,0.00431703],"category_scores_gemma":[0.0010687042,0.0003823776,0.0010308803,0.0006691422,0.00093496835,0.001922749,0.0010999297,0.0012912393,0.00049938506],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017909613,0.000034840785,0.00023324337,0.00006656146,0.000029265724,0.00013659295,0.00007824501,0.7368358,0.00070691743,0.25428456,0.0013586659,0.0062174695],"study_design_scores_gemma":[0.0000060164625,0.00001406414,0.000049063812,0.000007369978,0.0000074073873,0.000027394648,0.00003131337,0.9557808,0.00009936375,0.041692775,0.0022766585,0.000007785703],"about_ca_topic_score_codex":0.011814791,"about_ca_topic_score_gemma":0.0089231115,"teacher_disagreement_score":0.011814791,"about_ca_system_score_codex":0.0019160158,"about_ca_system_score_gemma":0.001558694,"threshold_uncertainty_score":0.023492038},"labels":[],"label_agreement":null},{"id":"W3115356730","doi":"10.1109/itsc45102.2020.9294282","title":"Impact of Charging Infrastructure and Policies on Electric Car Sharing Systems","year":2020,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Relocation; TRIPS architecture; Software deployment; Scope (computer science); Work (physics); Computer science; Transport engineering; Electric vehicle; Task (project management); Environmental economics; Engineering; Systems engineering; Power (physics)","score_opus":0.011754577298643615,"score_gpt":0.23720457540265286,"score_spread":0.22544999810400923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3115356730","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98183113,0.0003508803,0.0065206867,0.0004105523,0.000041382318,0.00006400501,0.00029786376,0.0001577787,0.010325656],"genre_scores_gemma":[0.99919635,0.00005132034,0.00032843434,0.000017253064,0.0000026100947,0.0000056395634,0.000042657295,0.000008590782,0.00034721833],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9984291,0.0005220917,0.000044514403,0.00016687118,0.00019407818,0.0006432533],"domain_scores_gemma":[0.99459356,0.0030135212,0.0006365176,0.00048018305,0.00077057787,0.0005055555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001470201,0.0007077101,0.000613139,0.0007115971,0.00071162026,0.0021636372,0.0010688483,0.0008750736,0.004355468],"category_scores_gemma":[0.008799547,0.0003771567,0.00035434632,0.001149664,0.00095832377,0.0018842788,0.0012886144,0.0008497314,0.00024691556],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045195196,0.00012454207,0.0062610796,0.000046527945,0.000035665333,0.0001262601,0.00003470941,0.97844404,0.0015827718,0.004407739,0.00054920727,0.007935523],"study_design_scores_gemma":[0.00011783949,0.00085832196,0.020864576,0.00003424321,0.000116220086,0.00018588733,0.0009408231,0.9651631,0.004523002,0.004524098,0.002613986,0.000057866408],"about_ca_topic_score_codex":0.024285734,"about_ca_topic_score_gemma":0.016250797,"teacher_disagreement_score":0.024285734,"about_ca_system_score_codex":0.003964478,"about_ca_system_score_gemma":0.0015916676,"threshold_uncertainty_score":0.048288763},"labels":[],"label_agreement":null},{"id":"W3117821862","doi":"10.1109/itsc45102.2020.9294268","title":"Cap-and-trade scheme for ridesharing","year":2020,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Mitsubishi Electric Research Laboratories","keywords":"Scheme (mathematics); Limiting; Marginal cost; Social cost; Service (business); Limit (mathematics); Computer science; Business; Balance (ability); Set (abstract data type); Microeconomics; Economics; Marketing","score_opus":0.028150684098350844,"score_gpt":0.21451944062356793,"score_spread":0.1863687565252171,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3117821862","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043775875,0.0002994041,0.8940147,0.0014876162,0.00053353584,0.00077964435,0.00060805044,0.00248839,0.05601276],"genre_scores_gemma":[0.8579705,0.0001242913,0.12777859,0.0004502486,0.00012352616,0.00042704013,0.00016395721,0.00019704345,0.012764813],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9963433,0.0011179683,0.00016077425,0.00069260545,0.001131507,0.00055367156],"domain_scores_gemma":[0.99478877,0.0012999763,0.0005360459,0.0021354984,0.0007948691,0.00044482635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031062518,0.0009153098,0.0009814566,0.0009030303,0.0016400113,0.0029486963,0.0051499764,0.0034727263,0.018486355],"category_scores_gemma":[0.009778643,0.00052537996,0.0012118125,0.0011092157,0.0026134977,0.004208502,0.0032617827,0.0038166111,0.0022163705],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056518614,0.00064885174,0.0014815794,0.0002133693,0.000092099355,0.00035835663,0.00034870903,0.2961844,0.0138098765,0.59224826,0.017492997,0.07655638],"study_design_scores_gemma":[0.00015188799,0.00035443058,0.0005361755,0.000040478302,0.00004448013,0.00029013015,0.000070433554,0.8692011,0.0048423414,0.08771247,0.036621727,0.00013433104],"about_ca_topic_score_codex":0.0023789292,"about_ca_topic_score_gemma":0.0022398108,"teacher_disagreement_score":0.018486355,"about_ca_system_score_codex":0.002172455,"about_ca_system_score_gemma":0.0018503264,"threshold_uncertainty_score":0.061842978},"labels":[],"label_agreement":null},{"id":"W3118691141","doi":"10.5539/cis.v14n1p8","title":"An O(nlogn/logw) Time Algorithm for Ridesharing","year":2021,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Vertex (graph theory); Carry (investment); Algorithm; Time complexity; Graph; Theoretical computer science","score_opus":0.008269374183623461,"score_gpt":0.23288465599548655,"score_spread":0.22461528181186308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3118691141","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019379543,0.0010407906,0.94733363,0.0011897231,0.00026953607,0.0007189459,0.0010082365,0.012718033,0.016341567],"genre_scores_gemma":[0.09658754,0.0006311352,0.8795445,0.00043366093,0.00009793702,0.00064645434,0.0036602325,0.0011075236,0.01729104],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975127,0.00026971163,0.00018574965,0.0008819138,0.00058205065,0.00056780234],"domain_scores_gemma":[0.9985519,0.00049606274,0.000120241275,0.0005273002,0.00021520472,0.000089265275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008382569,0.0022469843,0.0017454554,0.0014305981,0.0019350556,0.0027913395,0.0033933388,0.0020823425,0.030406425],"category_scores_gemma":[0.003221446,0.00090534135,0.0018901583,0.0035928292,0.0010919939,0.005474439,0.0039222683,0.0024206063,0.011762252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006101266,0.0006241422,0.0008862288,0.0010013412,0.00014115633,0.0002545565,0.00038524598,0.037819985,0.025995458,0.023805378,0.04491574,0.86356056],"study_design_scores_gemma":[0.0010497761,0.0007252251,0.0026356645,0.00020598876,0.00026049753,0.0021156732,0.0009288995,0.68402326,0.032390945,0.18198244,0.09338841,0.00029327712],"about_ca_topic_score_codex":0.0052483855,"about_ca_topic_score_gemma":0.008065127,"teacher_disagreement_score":0.030406425,"about_ca_system_score_codex":0.0018498183,"about_ca_system_score_gemma":0.0030075826,"threshold_uncertainty_score":0.10171962},"labels":[],"label_agreement":null},{"id":"W3120440647","doi":"10.1016/j.omega.2021.102413","title":"Optimal pricing of customized bus services and ride-sharing based on a competitive game model","year":2021,"lang":"en","type":"article","venue":"Omega","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; Fonds de Recherche du Québec-Société et Culture; National Natural Science Foundation of China","keywords":"Mode (computer interface); Public transport; Value of time; Computer science; Service (business); Measure (data warehouse); Value (mathematics); Operations research; Simulation; Transport engineering; Travel time; Business; Marketing; Engineering","score_opus":0.01068363782439253,"score_gpt":0.22020836922906956,"score_spread":0.20952473140467703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120440647","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32144377,0.0010731601,0.60086477,0.003295407,0.00033437813,0.0006263719,0.0011096355,0.0003740346,0.070878476],"genre_scores_gemma":[0.97438496,0.0002975025,0.012441036,0.0001357734,0.00007017447,0.00014067396,0.00012858248,0.000043607863,0.012357631],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979571,0.0008823538,0.000059464925,0.00032366352,0.00022811982,0.00054924603],"domain_scores_gemma":[0.99626356,0.0025038214,0.00026561803,0.000106037114,0.00032291186,0.0005380292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020582646,0.0016161981,0.0047096643,0.0014529693,0.0014176901,0.004321123,0.0039336635,0.00445599,0.012115968],"category_scores_gemma":[0.0068707145,0.0014981598,0.0019927078,0.0017167511,0.0025906307,0.004591862,0.0018461444,0.0026917243,0.0006661018],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002995946,0.00023275313,0.00052808237,0.00011497143,0.00008597292,0.00022436545,0.000103207174,0.8410417,0.000926962,0.14833817,0.0030682802,0.005035999],"study_design_scores_gemma":[0.000054317712,0.000040978328,0.00018489266,0.0000065161016,0.00003216052,0.000029725014,0.000043959557,0.98075783,0.000071769915,0.018380612,0.00037149573,0.00002580759],"about_ca_topic_score_codex":0.026045864,"about_ca_topic_score_gemma":0.018973425,"teacher_disagreement_score":0.026045864,"about_ca_system_score_codex":0.005250253,"about_ca_system_score_gemma":0.0040869787,"threshold_uncertainty_score":0.05178851},"labels":[],"label_agreement":null},{"id":"W3121179778","doi":"","title":"One-Way Carsharing's Evolution and Operator Perspectives from the Americas","year":2015,"lang":"en","type":"preprint","venue":"eScholarship (California Digital Library)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Federal Highway Administration; California Department of Transportation; U.S. Department of Transportation","keywords":"Reservation; Kilometer; Public transport; Car ownership; Transport engineering; Globe; Operator (biology); Business; Geography; Vehicle miles of travel; Telecommunications; Computer science; Engineering","score_opus":0.02234859996250116,"score_gpt":0.22444252152569757,"score_spread":0.20209392156319642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121179778","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86496973,0.005107637,0.0016538537,0.05238818,0.000469946,0.000021737982,0.00012729297,0.000036518664,0.075225085],"genre_scores_gemma":[0.98400754,0.0039638462,0.0005845709,0.005981994,0.00012847873,0.000015767933,0.000050812792,0.000028838007,0.0052381465],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9974826,0.0010100709,0.00006768189,0.00026838898,0.00056720176,0.0006041336],"domain_scores_gemma":[0.9932481,0.002038025,0.00067614065,0.00013311612,0.0016950872,0.002209565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0050289077,0.00030047598,0.00017137305,0.0014758068,0.0060785594,0.005563176,0.0008835761,0.0016571175,0.0046319338],"category_scores_gemma":[0.004045848,0.00023714955,0.00027286782,0.0019397894,0.0056531043,0.0052134837,0.0027042723,0.0029599455,0.00031333015],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012018093,0.00024802005,0.055802222,0.00024723954,0.000020474712,0.0014054669,0.79087204,0.00016398127,0.0024387205,0.047472324,0.027336158,0.07387315],"study_design_scores_gemma":[0.0000075220287,0.000108533175,0.030783048,0.00035389955,0.0000111797035,0.00059223233,0.7851438,0.00032251838,0.00032480326,0.002723379,0.17957586,0.000053250562],"about_ca_topic_score_codex":0.07625682,"about_ca_topic_score_gemma":0.11759584,"teacher_disagreement_score":0.07625682,"about_ca_system_score_codex":0.005596672,"about_ca_system_score_gemma":0.0056430725,"threshold_uncertainty_score":0.15162587},"labels":[],"label_agreement":null},{"id":"W3121475253","doi":"","title":"Is Uber a substitute or complement for public transit","year":2017,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Public transport; Metropolitan area; Transit (satellite); Complement (music); Transport engineering; Flexibility (engineering); Rail transit; Business; Geography; Engineering; Statistics; Mathematics","score_opus":0.14241458219353476,"score_gpt":0.36794989711555776,"score_spread":0.225535314922023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121475253","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78806794,0.0031450705,0.009252087,0.008375768,0.00064450176,0.0001344883,0.0021238956,0.00047351167,0.1877828],"genre_scores_gemma":[0.9706315,0.00084895035,0.0040965443,0.00081080914,0.00013289548,0.000037773843,0.0006532486,0.00011429352,0.022673821],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99782336,0.0006118433,0.00007224846,0.00046926748,0.00053483836,0.00048859126],"domain_scores_gemma":[0.99374914,0.0017507655,0.0017903618,0.0009747275,0.0008487572,0.00088619534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018305107,0.00039600342,0.0012589103,0.0010603878,0.001130774,0.004019354,0.0011623722,0.001969834,0.053780742],"category_scores_gemma":[0.009054212,0.000521344,0.00092757004,0.0018595249,0.0018351462,0.0076001813,0.0021265512,0.0012900438,0.0041958834],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005826086,0.0014057707,0.12814422,0.002343569,0.00062558235,0.0017707926,0.0030940687,0.0054839416,0.012248827,0.5174391,0.05784124,0.2637768],"study_design_scores_gemma":[0.00046423543,0.002921126,0.16480535,0.001964278,0.000995753,0.0023901456,0.014675957,0.01472155,0.011722777,0.06899406,0.71607715,0.0002676311],"about_ca_topic_score_codex":0.008336433,"about_ca_topic_score_gemma":0.019066919,"teacher_disagreement_score":0.053780742,"about_ca_system_score_codex":0.0015578244,"about_ca_system_score_gemma":0.001685793,"threshold_uncertainty_score":0.17991447},"labels":[],"label_agreement":null},{"id":"W3121705972","doi":"","title":"Impact of Carsharing on Household Vehicle Holdings: Resultsvfrom a North American Shared-Use Vehicle Survey","year":2010,"lang":"en","type":"preprint","venue":"eScholarship (California Digital Library)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"San José State University; Arizona State University; California Department of Transportation; University of California, Davis; U.S. Department of Transportation","keywords":"Metropolitan area; Geography; Sample (material); Population; Business; Agricultural economics; Transport engineering; Economics; Engineering; Demography","score_opus":0.03294949527096459,"score_gpt":0.2395879345015998,"score_spread":0.20663843923063518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121705972","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99762505,0.00004343048,0.000057772355,0.00003334904,0.0000027338685,0.00001604129,0.0012308758,0.000004091596,0.0009866114],"genre_scores_gemma":[0.9954774,0.00011902457,0.00011229101,0.00004323267,0.0000054126945,0.00003375371,0.0025396496,0.000003843706,0.0016653873],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99903166,0.00033722745,0.000059665817,0.00013180489,0.0002829384,0.0001566881],"domain_scores_gemma":[0.99762315,0.00061199,0.0006656673,0.00018313134,0.0006628408,0.0002531873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001229355,0.000251816,0.00020236605,0.0010351519,0.00053085224,0.00066460023,0.00036190974,0.00029967405,0.0024482824],"category_scores_gemma":[0.00143816,0.00025874568,0.0006577232,0.0015033288,0.00034390716,0.0005675902,0.0008350871,0.0004068251,0.0005966497],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042292682,0.00014483719,0.995445,0.000015118037,0.00005423336,0.000032216154,0.0004948177,0.00009451225,0.00012882616,0.000015472877,0.00043784184,0.0030947954],"study_design_scores_gemma":[9.140582e-7,0.000051347422,0.9981451,0.000003714143,0.000013097657,0.000014872308,0.0012929447,0.00010088768,0.00008507562,0.000004435224,0.0002849577,0.000002577439],"about_ca_topic_score_codex":0.08241052,"about_ca_topic_score_gemma":0.17239915,"teacher_disagreement_score":0.08241052,"about_ca_system_score_codex":0.0006606788,"about_ca_system_score_gemma":0.0005382549,"threshold_uncertainty_score":0.16386169},"labels":[],"label_agreement":null},{"id":"W3122366227","doi":"10.1155/2021/8885671","title":"Recurrent Neural-Based Vehicle Demand Forecasting and Relocation Optimization for Car-Sharing System: A Real Use Case in Thailand","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Chulalongkorn University","keywords":"Relocation; Computer science; Preprocessor; TRIPS architecture; Data pre-processing; Real-time computing; Operations research; Transport engineering; Simulation; Engineering; Artificial intelligence","score_opus":0.025833968166330986,"score_gpt":0.2505480079395333,"score_spread":0.2247140397732023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122366227","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9864683,0.00008001441,0.011125972,0.00019649418,0.000012327,0.000018619838,0.00025031908,0.0002861887,0.001561834],"genre_scores_gemma":[0.9980623,0.000022070397,0.0012193688,0.0000075380403,0.0000022665508,0.0000067060255,0.00016889015,0.000008138005,0.0005026328],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997844,0.000049252114,0.000014288989,0.000051950698,0.000039395112,0.000060607428],"domain_scores_gemma":[0.99964714,0.00013722997,0.000036471167,0.000031777152,0.00010358593,0.00004377667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036419593,0.00065291644,0.00040505393,0.0003567543,0.00032189715,0.00046838165,0.0007489917,0.0005733253,0.0011328734],"category_scores_gemma":[0.0008820998,0.00024951546,0.00038146952,0.00046149013,0.0003128636,0.0006994965,0.00042016685,0.00048703334,0.00015797612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001915067,0.00013279825,0.010759666,0.00005531348,0.000030134712,0.00061410613,0.000095024814,0.97155535,0.0017589119,0.0004271383,0.0010016775,0.013378302],"study_design_scores_gemma":[0.000004869379,0.000034057066,0.0013868561,9.581747e-7,0.000004086425,0.000018361392,0.00007020313,0.997686,0.0005732513,0.00010425588,0.00011266084,0.0000044526364],"about_ca_topic_score_codex":0.0675055,"about_ca_topic_score_gemma":0.038016148,"teacher_disagreement_score":0.0675055,"about_ca_system_score_codex":0.0012174051,"about_ca_system_score_gemma":0.00062229193,"threshold_uncertainty_score":0.13422519},"labels":[],"label_agreement":null},{"id":"W3122383907","doi":"","title":"A Three-Stage Model for a Decentralized Distribution System of Retailers","year":2006,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Residual; Profit (economics); Stage (stratigraphy); Third stage; Supply chain; Transshipment (information security); Supply and demand; Microeconomics; Business; Operations research; Economics; Computer science; Mathematics; Marketing","score_opus":0.016489638585536665,"score_gpt":0.2195021018730267,"score_spread":0.20301246328749004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122383907","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13308735,0.00066753983,0.8225118,0.002245174,0.00018196985,0.00048560847,0.0017115718,0.00036222796,0.03874673],"genre_scores_gemma":[0.9069225,0.00052890804,0.045963272,0.00021151025,0.000108061526,0.000605173,0.00041524446,0.00006111115,0.045184143],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986028,0.00047053897,0.000054497934,0.00036801936,0.0001737269,0.00033048415],"domain_scores_gemma":[0.9980095,0.00087129936,0.00033946152,0.00012230326,0.00034398813,0.00031357264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016729007,0.001170442,0.0017087278,0.0006285506,0.0012592059,0.0024516224,0.0036715565,0.0032267359,0.018467579],"category_scores_gemma":[0.0027803022,0.0009786438,0.0013868879,0.0010777654,0.0017587995,0.0026942142,0.0018012329,0.002030611,0.0017773364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034426592,0.00015108408,0.0010221901,0.00013601244,0.00007027456,0.0005504091,0.00020140846,0.8331444,0.0021152757,0.15547375,0.0021640921,0.0046267635],"study_design_scores_gemma":[0.00020533103,0.000117366675,0.00030056585,0.000013741098,0.000038333255,0.00008000866,0.00006517883,0.96290624,0.0002461107,0.033860393,0.0021300132,0.000036754926],"about_ca_topic_score_codex":0.011532759,"about_ca_topic_score_gemma":0.009325643,"teacher_disagreement_score":0.018467579,"about_ca_system_score_codex":0.0028109015,"about_ca_system_score_gemma":0.001993905,"threshold_uncertainty_score":0.061780214},"labels":[],"label_agreement":null},{"id":"W3122964408","doi":"10.2139/ssrn.3274628","title":"The Impact of Behavioral and Economic Drivers on Gig Economy Workers","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":69,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Gig economy; Business; Labour economics; Economics; Labour law","score_opus":0.007069438444998051,"score_gpt":0.25397450558959467,"score_spread":0.24690506714459662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122964408","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9967579,0.000101244375,0.000047639187,0.0005069226,0.000021414973,0.0000083009245,0.00022227492,0.0000024061421,0.0023318774],"genre_scores_gemma":[0.99729496,0.000118721626,0.000021562006,0.00007026755,0.000018006971,0.0000058603587,0.0001579281,0.000003064221,0.0023096462],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991242,0.0002507169,0.000045763565,0.00006384741,0.00011217716,0.00040325397],"domain_scores_gemma":[0.99535024,0.0011906063,0.00093800697,0.00018432496,0.0006677581,0.0016690523],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010263856,0.0001902273,0.00024500597,0.0009485919,0.0012108842,0.0019839478,0.0005290247,0.0010968163,0.009867501],"category_scores_gemma":[0.004686749,0.00025157747,0.0006933728,0.0009676979,0.0005633571,0.000827151,0.0013506261,0.0014566899,0.0015024344],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022455321,0.0003354416,0.9936022,0.000012010363,0.000047607802,0.00009656439,0.000781036,0.000121179415,0.00011279814,0.0003325969,0.00031341516,0.0040206034],"study_design_scores_gemma":[0.000008890354,0.00014521704,0.9890598,0.000016384003,0.000043249336,0.00004223313,0.009006603,0.0002524258,0.00008603907,0.00028458997,0.0010427411,0.000011774459],"about_ca_topic_score_codex":0.035398006,"about_ca_topic_score_gemma":0.057557136,"teacher_disagreement_score":0.035398006,"about_ca_system_score_codex":0.00077111495,"about_ca_system_score_gemma":0.0015846104,"threshold_uncertainty_score":0.07038391},"labels":[],"label_agreement":null},{"id":"W3123047120","doi":"10.2139/ssrn.3191793","title":"Adoption of Electric Vehicles in Car Sharing Market","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Waterloo","funders":"","keywords":"Car sharing; Business; Electric cars; Electric vehicle; Industrial organization; Transport engineering; Marketing; Advertising; Automotive engineering; Engineering","score_opus":0.007007291991153369,"score_gpt":0.21973491780701648,"score_spread":0.2127276258158631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123047120","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9837272,0.0001523289,0.0003726349,0.00048417877,0.000011424254,0.000016295997,0.00006816755,0.0000069538855,0.015160826],"genre_scores_gemma":[0.9983847,0.000041158863,0.000036359444,0.000025989928,0.000007089866,0.0000019252973,0.000023732578,0.0000011931231,0.0014777854],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990896,0.00020760193,0.000037230668,0.00015097256,0.0001862963,0.0003283025],"domain_scores_gemma":[0.9954882,0.0018593492,0.0012212221,0.00019516265,0.00064429635,0.00059174496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011345914,0.0001566289,0.00022732627,0.00083077064,0.0006087837,0.0023885146,0.00055713614,0.0013215774,0.01419322],"category_scores_gemma":[0.005080225,0.00013486153,0.00038583385,0.0007466908,0.0006603197,0.003004106,0.0011337564,0.0012084414,0.0006450929],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018229589,0.0024508731,0.76115155,0.00021950352,0.00016709589,0.0021376254,0.006896717,0.008001903,0.0071374965,0.124131024,0.0046408335,0.0812425],"study_design_scores_gemma":[0.000112113776,0.0009275458,0.89098275,0.00009682719,0.00016972321,0.00060363585,0.03784322,0.023438022,0.0033305734,0.02074125,0.021680208,0.0000741159],"about_ca_topic_score_codex":0.0056834514,"about_ca_topic_score_gemma":0.0083687315,"teacher_disagreement_score":0.01419322,"about_ca_system_score_codex":0.0011211043,"about_ca_system_score_gemma":0.0008821742,"threshold_uncertainty_score":0.047481},"labels":[],"label_agreement":null},{"id":"W3123290426","doi":"10.1287/msom.2017.0683","title":"Shared Mobility for Last-Mile Delivery: Design, Operational Prescriptions, and Environmental Impact","year":2018,"lang":"en","type":"article","venue":"Manufacturing & Service Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":216,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Truck; Boom; Business; Service (business); Service provider; Last mile (transportation); Environmental economics; Incentive; Crowds; Transport engineering; Industrial organization; Mile; Computer science; Economics; Microeconomics; Marketing","score_opus":0.015300065151319419,"score_gpt":0.22772917610194332,"score_spread":0.2124291109506239,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123290426","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11704249,0.00091175624,0.847031,0.0022801636,0.00018693355,0.00075864204,0.00044461436,0.0009861509,0.030358296],"genre_scores_gemma":[0.84913015,0.0007292926,0.13972151,0.00014363664,0.000041455496,0.00064553943,0.00020286131,0.00012756849,0.009257959],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989164,0.00040974078,0.000045419423,0.00019757371,0.00024288286,0.00018804042],"domain_scores_gemma":[0.9987847,0.00036968233,0.00012457083,0.00025508262,0.00028821986,0.00017770246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012307204,0.0007768091,0.00044223448,0.00055439986,0.0007053498,0.001644704,0.0023474477,0.0009795714,0.009099742],"category_scores_gemma":[0.0032460173,0.0003747404,0.00068256335,0.00072060555,0.0011462545,0.0018312146,0.0027480754,0.0007235345,0.0012858062],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054196815,0.0003923899,0.0053356425,0.00078355405,0.000082508646,0.0006584333,0.0009348835,0.5383718,0.02172685,0.18460488,0.006830693,0.23973641],"study_design_scores_gemma":[0.00012627747,0.0010411021,0.002095824,0.00019740307,0.00012483857,0.0005451308,0.0013522583,0.8683422,0.01187714,0.072458245,0.04174731,0.000092249335],"about_ca_topic_score_codex":0.0067427247,"about_ca_topic_score_gemma":0.006652,"teacher_disagreement_score":0.009099742,"about_ca_system_score_codex":0.0020719247,"about_ca_system_score_gemma":0.0019875416,"threshold_uncertainty_score":0.030441701},"labels":[],"label_agreement":null},{"id":"W3123344099","doi":"10.1155/2021/8863985","title":"Vehicle Assignment considering Battery Endurance for Electric Vehicle Carsharing Systems","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Key Science and Technology Program of Shaanxi Province; Key Research and Development Projects of Shaanxi Province; Fundamental Research Funds for the Central Universities; National Postdoctoral Program for Innovative Talents; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Reservation; Battery (electricity); Computer science; Mode (computer interface); Service (business); Electric cars; Term (time); Matching (statistics); Instant; Automotive engineering; Simulation; Engineering; Computer network","score_opus":0.013992664870235287,"score_gpt":0.23522538600120213,"score_spread":0.22123272113096684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123344099","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39015016,0.00030510014,0.6023153,0.00021891751,0.000050842646,0.00009392006,0.000060713417,0.0002488723,0.0065561766],"genre_scores_gemma":[0.9934815,0.000041937503,0.0053671864,0.000009913183,0.000005788361,0.000015230329,0.00001411006,0.000009667498,0.0010546616],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997261,0.000071369686,0.000010157496,0.000045503857,0.00005016741,0.00009673314],"domain_scores_gemma":[0.9995745,0.00019176997,0.00006347636,0.000027257736,0.000076442644,0.000066492714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044509876,0.00046847205,0.00052228407,0.00034849977,0.00053861516,0.00077630515,0.0007274252,0.0003713431,0.0025818911],"category_scores_gemma":[0.0012991775,0.0002690217,0.00039158404,0.00036741403,0.00038571577,0.00091150746,0.0006448074,0.00036633277,0.00013087734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008210292,0.000034199682,0.0010736755,0.000030206338,0.000014144011,0.00006489551,0.000046206333,0.98235303,0.0020507758,0.0038795327,0.000195542,0.0101756705],"study_design_scores_gemma":[0.0000038246853,0.00002875501,0.00019477974,0.0000015081441,0.0000063987804,0.000011865731,0.000029004537,0.99817157,0.00037667918,0.0009989485,0.0001738645,0.000002741315],"about_ca_topic_score_codex":0.0063723256,"about_ca_topic_score_gemma":0.005281913,"teacher_disagreement_score":0.0063723256,"about_ca_system_score_codex":0.00079748983,"about_ca_system_score_gemma":0.00066901755,"threshold_uncertainty_score":0.012670457},"labels":[],"label_agreement":null},{"id":"W3123447939","doi":"10.1111/jems.12306","title":"A theory of multihoming in rideshare competition","year":2019,"lang":"en","type":"article","venue":"Journal of Economics & Management Strategy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Multihoming; Duopoly; Monopoly; Competition (biology); Microeconomics; Face (sociological concept); Economics; Industrial organization; Business; Computer science; The Internet; Cournot competition; Sociology","score_opus":0.015111398472068655,"score_gpt":0.21311698174325017,"score_spread":0.1980055832711815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123447939","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20381565,0.0020214242,0.37142855,0.00729653,0.00032663904,0.00021812173,0.00038428398,0.00016844422,0.41434044],"genre_scores_gemma":[0.9763865,0.0004888319,0.007353385,0.00040585457,0.000139783,0.000101535275,0.000049058155,0.00002004136,0.015055022],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986669,0.0005390998,0.000037025206,0.00019229803,0.00022984354,0.0003347618],"domain_scores_gemma":[0.99672973,0.0020074756,0.00033969618,0.00024484083,0.000280215,0.00039806208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015891765,0.0006363607,0.001152857,0.0010353704,0.0019814295,0.0040267827,0.0018569919,0.0029997376,0.031276435],"category_scores_gemma":[0.003461622,0.00043022458,0.001052923,0.0011927611,0.0044978866,0.00458749,0.0023165685,0.0019607113,0.0013991739],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001560947,0.000027922217,0.00021570701,0.000031749798,0.00000986364,0.00007363859,0.00010462612,0.015036098,0.00017547897,0.98087525,0.0013026372,0.0021314498],"study_design_scores_gemma":[0.000041748248,0.000054929922,0.00030818375,0.000026319294,0.000010497595,0.00010016021,0.00018870345,0.09250852,0.000068095454,0.9026202,0.0040522744,0.000020419113],"about_ca_topic_score_codex":0.004118213,"about_ca_topic_score_gemma":0.0025699756,"teacher_disagreement_score":0.031276435,"about_ca_system_score_codex":0.0024520736,"about_ca_system_score_gemma":0.001507488,"threshold_uncertainty_score":0.10463011},"labels":[],"label_agreement":null},{"id":"W3123594944","doi":"10.2139/ssrn.3177496","title":"A Smart-City Scope of Operations Management","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Scope (computer science); Business; Smart city; Process management; Computer science; Computer security; Internet of Things","score_opus":0.0075828363537486345,"score_gpt":0.23060726652382427,"score_spread":0.22302443017007564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123594944","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13344803,0.004559127,0.09590176,0.038010724,0.00075868296,0.00021448823,0.00037440014,0.00057495607,0.72615796],"genre_scores_gemma":[0.94807905,0.0022980014,0.012916173,0.0021408782,0.00039141407,0.00009623277,0.00017693771,0.00006781691,0.03383352],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991949,0.0002208193,0.000036741847,0.00015201634,0.00018933558,0.00020614565],"domain_scores_gemma":[0.9984432,0.0003585266,0.00014177669,0.0003073817,0.00029162434,0.00045760928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017685529,0.00039814872,0.00035408966,0.0014153119,0.0018863452,0.0093217185,0.0010819837,0.0017440029,0.014805857],"category_scores_gemma":[0.0015814196,0.00034107175,0.0004904376,0.0021024023,0.0046356306,0.010678,0.005618915,0.0023835353,0.001288137],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031141422,0.000068078174,0.0025968046,0.00009011069,0.000014939083,0.00009058113,0.0011991939,0.0032437625,0.000799771,0.94327027,0.0077792634,0.04081609],"study_design_scores_gemma":[0.000024341478,0.00014428693,0.011086457,0.00032161456,0.000026761816,0.00017656838,0.007785634,0.013338053,0.0008631981,0.60928184,0.35689205,0.00005924088],"about_ca_topic_score_codex":0.0036401814,"about_ca_topic_score_gemma":0.0064076083,"teacher_disagreement_score":0.014805857,"about_ca_system_score_codex":0.0037637183,"about_ca_system_score_gemma":0.0055458206,"threshold_uncertainty_score":0.049530506},"labels":[],"label_agreement":null},{"id":"W3124118038","doi":"","title":"Truck Driver Scheduling in Canada","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Truck; Heuristics; Scheduling (production processes); Operations research; Transport engineering; Business; Service (business); Computer science; Operations management; Engineering; Automotive engineering; Marketing; Operating system","score_opus":0.003164656494267692,"score_gpt":0.18572211951172066,"score_spread":0.18255746301745296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124118038","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5990994,0.004610049,0.09762707,0.00832596,0.00078361336,0.0011395741,0.013177684,0.0015232048,0.27371335],"genre_scores_gemma":[0.9330709,0.0016419555,0.027161501,0.00038056396,0.00004151535,0.00010148623,0.003464602,0.00011444996,0.03402307],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902534,0.00009247987,0.00002239858,0.0001598354,0.0002448731,0.00045514028],"domain_scores_gemma":[0.999297,0.00013021361,0.000041565618,0.000027823773,0.00029559547,0.00020783284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006378827,0.0006094557,0.0004395753,0.00073421805,0.003498722,0.002050403,0.0016233302,0.000858036,0.010841937],"category_scores_gemma":[0.0016703964,0.0003835515,0.0005499122,0.0025050843,0.0009781203,0.00077464466,0.00080989674,0.0007824271,0.0006132889],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060998957,0.00021614638,0.01999377,0.00049898983,0.00011387377,0.0008370601,0.00097214174,0.70098627,0.0033467333,0.09440243,0.06931459,0.10870802],"study_design_scores_gemma":[0.00026946852,0.00018645826,0.024633314,0.00011144011,0.00012572149,0.00027121263,0.0049175387,0.70948976,0.0029865673,0.031173574,0.22564428,0.00019063619],"about_ca_topic_score_codex":0.9749723,"about_ca_topic_score_gemma":0.9819624,"teacher_disagreement_score":0.03336796,"about_ca_system_score_codex":0.03336796,"about_ca_system_score_gemma":0.061320458,"threshold_uncertainty_score":0.24210262},"labels":[],"label_agreement":null},{"id":"W3124830855","doi":"10.2139/ssrn.3223735","title":"Charging Electric Vehicle Sharing Fleet","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Electric vehicle; Automotive engineering; Fleet management; Car sharing; Transport engineering; Business; Aeronautics; Computer science; Engineering; Physics","score_opus":0.007964348244207902,"score_gpt":0.22527454398454466,"score_spread":0.21731019574033675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124830855","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68688864,0.00024979096,0.12356569,0.00052036636,0.00033966158,0.0002724236,0.0014604087,0.0010356165,0.1856674],"genre_scores_gemma":[0.97994655,0.000046805297,0.0022304433,0.000021080992,0.00001540516,0.000023697023,0.00038373258,0.000029098814,0.017303195],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961287,0.000061088016,0.000011814241,0.0000779065,0.00012833934,0.00010808936],"domain_scores_gemma":[0.99977213,0.000040357936,0.000014758145,0.00006405475,0.0000747139,0.000033940865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030973696,0.00039787707,0.00043805852,0.00053080515,0.00081163313,0.0009199975,0.0008901801,0.00057035487,0.020296253],"category_scores_gemma":[0.0008000672,0.00016400349,0.0004111794,0.0008728793,0.00019136906,0.0015585204,0.0010327607,0.00039840426,0.0018534174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011722374,0.00022309339,0.01255529,0.00015810838,0.00014371226,0.0011975777,0.00023857673,0.6431939,0.02170578,0.05804198,0.020844763,0.24052495],"study_design_scores_gemma":[0.00006259487,0.000625998,0.0124005955,0.000029220184,0.000075167874,0.0010046518,0.00088958547,0.885679,0.013260855,0.0315319,0.054369096,0.000071241535],"about_ca_topic_score_codex":0.0030335432,"about_ca_topic_score_gemma":0.0029735153,"teacher_disagreement_score":0.020296253,"about_ca_system_score_codex":0.00070052553,"about_ca_system_score_gemma":0.00059359014,"threshold_uncertainty_score":0.06789768},"labels":[],"label_agreement":null},{"id":"W3124889190","doi":"10.1287/msom.2018.0769","title":"Pricing and Matching with Forward-Looking Buyers and Sellers","year":2019,"lang":"en","type":"article","venue":"Manufacturing & Service Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":97,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Microeconomics; Economics; Matching (statistics); Ask price; Profit (economics); Dynamic pricing; Heuristic; Computer science","score_opus":0.0033210953159906035,"score_gpt":0.176739172208014,"score_spread":0.1734180768920234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124889190","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08654967,0.00079326605,0.8872319,0.0042834836,0.00022429021,0.0005450096,0.00050545926,0.00018448307,0.01968249],"genre_scores_gemma":[0.8648793,0.0007666867,0.118834816,0.0004676433,0.00032189413,0.0005429211,0.00021689461,0.00006737986,0.013902498],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9959883,0.0018788732,0.00017115967,0.000980027,0.00044649947,0.0005349926],"domain_scores_gemma":[0.9901792,0.0072140386,0.0010999922,0.0005015698,0.00045487218,0.0005502556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005948308,0.0012835762,0.0027068264,0.00088007364,0.0012899769,0.0036335792,0.004251493,0.0051076123,0.009772126],"category_scores_gemma":[0.021154404,0.0013882398,0.0016607651,0.0019474364,0.0030318783,0.0063213035,0.0024494566,0.0029088599,0.0010629684],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046840883,0.00035851132,0.002833602,0.0003403836,0.00015147548,0.0005632986,0.00030994022,0.5460659,0.0010221286,0.42455554,0.003167263,0.020163538],"study_design_scores_gemma":[0.00018293141,0.00014702023,0.00041448107,0.000033742876,0.000044396667,0.00018235749,0.0001224504,0.78663886,0.0004104717,0.20944849,0.0023328962,0.000041916388],"about_ca_topic_score_codex":0.0032556138,"about_ca_topic_score_gemma":0.0013158965,"teacher_disagreement_score":0.009772126,"about_ca_system_score_codex":0.002837968,"about_ca_system_score_gemma":0.0029037376,"threshold_uncertainty_score":0.032691002},"labels":[],"label_agreement":null},{"id":"W3124994661","doi":"10.1111/poms.13330","title":"From the Classics to New Tunes: A Neoclassical View on Sharing Economy and Innovative Marketplaces","year":2020,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":72,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Sharing economy; Matching (statistics); Process (computing); Perspective (graphical); Point (geometry); Computer science; Economics; Industrial organization; Business model; Business; Economy; Knowledge management; Management","score_opus":0.024309979162066363,"score_gpt":0.23479416209608658,"score_spread":0.21048418293402021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124994661","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07233425,0.03598323,0.12570342,0.0790759,0.0011723624,0.00008415973,0.00027324556,0.00013495622,0.68523854],"genre_scores_gemma":[0.9247504,0.015213917,0.014308422,0.0044886,0.001183341,0.0001113111,0.000059803977,0.000052499774,0.039831735],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993038,0.00024583086,0.000019315823,0.000104421946,0.0002295057,0.000097015014],"domain_scores_gemma":[0.9993185,0.0003065263,0.00008610218,0.000089700894,0.00010236059,0.00009678726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001141097,0.00053027825,0.0004687975,0.0016537351,0.001631847,0.005299765,0.0011055293,0.002113529,0.0039530145],"category_scores_gemma":[0.0015774192,0.00024441123,0.0005757613,0.0017509084,0.01681684,0.009661453,0.0023144886,0.0028989029,0.0006014323],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035132805,0.000005277551,0.000050022412,0.000012871051,0.0000013970293,0.000022202266,0.0002046076,0.00040180093,0.000020739835,0.9971361,0.00069097127,0.0014504486],"study_design_scores_gemma":[0.0000038054177,0.0000074478044,0.00009527037,0.000046357312,0.0000017500823,0.000030498599,0.00018567078,0.0012149533,0.000035686477,0.9813405,0.017031873,0.000006075255],"about_ca_topic_score_codex":0.0036375884,"about_ca_topic_score_gemma":0.0025003047,"teacher_disagreement_score":0.0066339667,"about_ca_system_score_codex":0.0066339667,"about_ca_system_score_gemma":0.0019251169,"threshold_uncertainty_score":0.048133016},"labels":[],"label_agreement":null},{"id":"W3125130527","doi":"10.1155/2021/8818548","title":"Understanding the Operational Efficiency of Bicycle-Sharing Based on the Influencing Factor Analyses: A Case Study in Nanjing, China","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Renting; Inflow; Outflow; Transport engineering; Evening; Business; Geography; Engineering; Civil engineering; Meteorology","score_opus":0.07597473882461095,"score_gpt":0.3221244886845295,"score_spread":0.24614974985991853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125130527","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99912924,0.000028338527,0.00037817043,0.0000261645,6.539107e-7,0.000016095166,0.00002240078,0.0000021637568,0.0003968905],"genre_scores_gemma":[0.99888784,0.00008035271,0.0006959816,0.000006501048,0.0000013698915,0.0000124794,0.000045841218,0.000002064915,0.0002674513],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993098,0.0002093214,0.000056516103,0.00010535524,0.00014116669,0.00017796246],"domain_scores_gemma":[0.99914193,0.00041371194,0.00014014574,0.000043218035,0.00017949648,0.00008141671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011427886,0.00053144636,0.0003839598,0.0016543068,0.0010098905,0.0011353797,0.0006669511,0.00050805724,0.0009914284],"category_scores_gemma":[0.001577495,0.00030035796,0.00074344705,0.0022576603,0.0007922616,0.0009917298,0.00066643517,0.00030845273,0.00006949552],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012820568,0.000451111,0.9266749,0.00016641867,0.00012742046,0.0058831507,0.018253865,0.015540031,0.003919756,0.0021465127,0.0005226209,0.026186017],"study_design_scores_gemma":[0.000015882639,0.00025308973,0.8751397,0.000054675387,0.00009712313,0.00041108349,0.056833953,0.063853964,0.0011625104,0.00067534833,0.0014412281,0.00006142613],"about_ca_topic_score_codex":0.17065065,"about_ca_topic_score_gemma":0.22463281,"teacher_disagreement_score":0.17065065,"about_ca_system_score_codex":0.0038345866,"about_ca_system_score_gemma":0.0024120077,"threshold_uncertainty_score":0.3393147},"labels":[],"label_agreement":null},{"id":"W3125228316","doi":"","title":"Graph-based many-to-one dynamic ride-matching for shared mobility services in congested networks.","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Computer science; Blossom algorithm; Map matching; Traffic congestion; Graph; Quality of service; Computational complexity theory; IBM; Algorithm; Computer network; Transport engineering; Engineering; Theoretical computer science; Mathematics; Global Positioning System","score_opus":0.03499734852095777,"score_gpt":0.18843777301599512,"score_spread":0.15344042449503736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125228316","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.051974494,0.0004901873,0.9420148,0.00027307039,0.00008002738,0.00025707152,0.00021531695,0.0010187943,0.003676339],"genre_scores_gemma":[0.628951,0.00022416443,0.3662906,0.00014659026,0.000033953405,0.00014309485,0.00057724945,0.00014438477,0.0034890105],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993352,0.00020063385,0.00002880358,0.0001683374,0.0001436055,0.00012337575],"domain_scores_gemma":[0.99882525,0.000605349,0.0001422194,0.00019159899,0.00012905481,0.000106540974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010183943,0.00097192894,0.0013438149,0.0011189256,0.0010263401,0.0009858462,0.002492615,0.001368179,0.0036661392],"category_scores_gemma":[0.0031032956,0.00045554448,0.00092417555,0.0014218227,0.0007655786,0.0021078035,0.0021457032,0.0009061244,0.0005259685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023515546,0.00019290802,0.0013208794,0.00015391399,0.00012950168,0.00007920033,0.00011592415,0.84738773,0.002196457,0.015193642,0.003392705,0.129602],"study_design_scores_gemma":[0.000022337275,0.000056521152,0.00019457303,0.000004903405,0.000016271602,0.000045261488,0.000041267296,0.9898718,0.0007073373,0.007811956,0.0012209889,0.000006950241],"about_ca_topic_score_codex":0.011464025,"about_ca_topic_score_gemma":0.0120167555,"teacher_disagreement_score":0.011464025,"about_ca_system_score_codex":0.0014925913,"about_ca_system_score_gemma":0.0019530449,"threshold_uncertainty_score":0.022794604},"labels":[],"label_agreement":null},{"id":"W3125448763","doi":"","title":"The Canadian Minimum Duration Truck Driver Scheduling Problem","year":2012,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Truck; Duration (music); Integer programming; Schedule; Operations research; Scheduling (production processes); Dynamic programming; Service (business); Transport engineering; Linear programming; Computer science; Business; Operations management; Engineering; Automotive engineering; Marketing","score_opus":0.006769699727539461,"score_gpt":0.20945448321699142,"score_spread":0.20268478348945196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125448763","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29368404,0.0036627594,0.4961164,0.006427669,0.00060927484,0.0011665224,0.012464705,0.001482434,0.18438618],"genre_scores_gemma":[0.7681388,0.001802855,0.1724035,0.00051401654,0.00012776034,0.00046110566,0.005033235,0.00032797945,0.05119079],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906045,0.0001608291,0.000023108107,0.0001876553,0.0002624631,0.00030552706],"domain_scores_gemma":[0.99940014,0.0002247132,0.00005358772,0.00002666804,0.00015807866,0.00013678544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000893155,0.0012532324,0.0008580487,0.00063192484,0.0017940728,0.002051621,0.0023793199,0.0013948326,0.009318426],"category_scores_gemma":[0.0023427834,0.0005589419,0.00075188227,0.0015942067,0.0008124769,0.0009760309,0.00093664817,0.0013980396,0.00054864684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046860703,0.00014671088,0.0013691551,0.00034795434,0.000060163075,0.00021991802,0.00027886938,0.8623259,0.0026026738,0.054989614,0.02175443,0.05543596],"study_design_scores_gemma":[0.00019571383,0.00016386456,0.0030054664,0.000056559697,0.00007274283,0.00014629045,0.0004842987,0.92603636,0.0021821777,0.025481874,0.042088002,0.000086564105],"about_ca_topic_score_codex":0.69991606,"about_ca_topic_score_gemma":0.7216066,"teacher_disagreement_score":0.30008394,"about_ca_system_score_codex":0.012788773,"about_ca_system_score_gemma":0.028377073,"threshold_uncertainty_score":0.60370237},"labels":[],"label_agreement":null},{"id":"W3125644872","doi":"10.20944/preprints201911.0149.v1","title":"On Car Sharing Usage Prediction with Open Socio-Demographic Data","year":2019,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Provisioning; Computer science; Service provider; Service (business); Open data; Data science; Work (physics); Data mining; World Wide Web; Business; Engineering; Telecommunications","score_opus":0.16086679818499827,"score_gpt":0.3408292505993133,"score_spread":0.17996245241431502,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125644872","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9593239,0.0012931654,0.020268748,0.0007786066,0.00012338888,0.00008162385,0.015143831,0.0012022166,0.0017845504],"genre_scores_gemma":[0.95361024,0.00046340414,0.015368794,0.00009029029,0.00010623274,0.0000654454,0.029139087,0.00005520003,0.0011012687],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999148,0.0002972352,0.00005275573,0.00025720077,0.00013506522,0.00010972005],"domain_scores_gemma":[0.9948078,0.0034034767,0.00035933376,0.0005768359,0.0005821026,0.0002704219],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017618738,0.0014429649,0.00084585656,0.0032568644,0.00039188223,0.00097031525,0.0013155175,0.0013728779,0.0013220664],"category_scores_gemma":[0.0063819373,0.00038534641,0.0008143236,0.0030643067,0.00038554007,0.0014646616,0.0009961383,0.0012358138,0.0014106532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005553386,0.0010427323,0.36681896,0.00036484675,0.00033887735,0.0005138919,0.00027978653,0.46078643,0.0009394094,0.0010052121,0.013656612,0.15369795],"study_design_scores_gemma":[0.0000099587205,0.000043631015,0.027555417,0.00003575843,0.00002046195,0.00006496799,0.00014443752,0.9697244,0.00039169806,0.00083162764,0.0011631211,0.000014524522],"about_ca_topic_score_codex":0.06573839,"about_ca_topic_score_gemma":0.064349115,"teacher_disagreement_score":0.06573839,"about_ca_system_score_codex":0.0009611309,"about_ca_system_score_gemma":0.0007953975,"threshold_uncertainty_score":0.1307115},"labels":[],"label_agreement":null},{"id":"W3125979966","doi":"10.2139/ssrn.1515694","title":"Information Technology, Productivity and Asset Ownership: Evidence from Taxicab Fleets","year":2011,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Productivity; Business; Asset (computer security); Industrial organization; Finance; Economics; Computer science; Computer security","score_opus":0.015879259628441465,"score_gpt":0.21725637568951445,"score_spread":0.20137711606107297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125979966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970196,0.00038609802,0.0000784362,0.0001430386,0.000003368093,0.0000038070616,0.0005512256,0.0000016027662,0.0018127875],"genre_scores_gemma":[0.9964095,0.00069965253,0.000044678687,0.000031319072,0.0000072439,0.0000054683583,0.0012750591,0.0000028445297,0.001524158],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995016,0.00014078732,0.00004302854,0.000075471864,0.00011700733,0.00012207132],"domain_scores_gemma":[0.9809218,0.008687924,0.007007945,0.0010005706,0.0012777809,0.0011039689],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012173807,0.0003433977,0.0003658747,0.00207811,0.0008625379,0.0020315738,0.000508928,0.0006865809,0.00774077],"category_scores_gemma":[0.009445159,0.0003006886,0.0005324878,0.004059966,0.00096340314,0.001992738,0.0010516971,0.000996376,0.0010265249],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049304357,0.00027910122,0.9876243,0.000058780628,0.00036999278,0.0002466423,0.0009295889,0.00090013776,0.00016993837,0.00088664645,0.0009846715,0.0070570367],"study_design_scores_gemma":[0.000032908043,0.00021792363,0.9909576,0.00009681948,0.00020338478,0.00013197848,0.0047575487,0.0005727823,0.00021947706,0.0004302922,0.002364214,0.000015168763],"about_ca_topic_score_codex":0.05768451,"about_ca_topic_score_gemma":0.06965906,"teacher_disagreement_score":0.05768451,"about_ca_system_score_codex":0.0007124311,"about_ca_system_score_gemma":0.00059905037,"threshold_uncertainty_score":0.114697516},"labels":[],"label_agreement":null},{"id":"W3125987693","doi":"","title":"A Theory of Multihoming in Rideshare Competition","year":2018,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Multihoming; Monopoly; Competition (biology); Microeconomics; Industrial organization; Face (sociological concept); Economics; Business; Computer science; The Internet","score_opus":0.034679708087997176,"score_gpt":0.3007337685643597,"score_spread":0.2660540604763625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125987693","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14850381,0.0027817925,0.511939,0.008845899,0.00042704865,0.0002559065,0.00050209626,0.00021553165,0.3265289],"genre_scores_gemma":[0.9627788,0.0010079942,0.012875449,0.0006755282,0.00025756322,0.00017034107,0.00008562624,0.000038893766,0.022109797],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99870944,0.00050385704,0.000034178953,0.00020924033,0.00021124797,0.0003320368],"domain_scores_gemma":[0.9969043,0.0018333871,0.00039909262,0.0002214166,0.00024832907,0.00039343885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015859952,0.0008402101,0.0012652822,0.001090434,0.002065308,0.0041763936,0.0024208596,0.0038365144,0.030881234],"category_scores_gemma":[0.0047333827,0.0004814872,0.0012211138,0.0014665233,0.0044258228,0.0057505327,0.002583268,0.002412897,0.0018974158],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017563327,0.000034034867,0.00034472678,0.0000473625,0.000012588531,0.0000975418,0.00012495481,0.01968947,0.00021193712,0.9743435,0.0018792935,0.0031970697],"study_design_scores_gemma":[0.000039358863,0.00006250584,0.0003902682,0.000031675718,0.000013964105,0.000116398674,0.00020741601,0.10154209,0.00007813489,0.8922896,0.005202899,0.000025777459],"about_ca_topic_score_codex":0.004105866,"about_ca_topic_score_gemma":0.0023348648,"teacher_disagreement_score":0.030881234,"about_ca_system_score_codex":0.0024748563,"about_ca_system_score_gemma":0.0015228711,"threshold_uncertainty_score":0.10330802},"labels":[],"label_agreement":null},{"id":"W3126117318","doi":"10.1155/2021/5943567","title":"A Data-Driven Scalable Method for Profiling and Dynamic Analysis of Shared Mobility Solutions","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Scalability; Profiling (computer programming); Geolocation; Analytics; Data science; Data mining; Big data; Domain knowledge; Raw data; Distributed computing; Artificial intelligence; World Wide Web; Database","score_opus":0.029036497062293155,"score_gpt":0.3198594120097702,"score_spread":0.29082291494747703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126117318","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005156012,0.00009765364,0.9901125,0.00012202492,0.000048660888,0.00014129067,0.0008127136,0.00262303,0.00088601717],"genre_scores_gemma":[0.14656709,0.00021725561,0.84656215,0.000099505574,0.00007569667,0.0005354967,0.0035514338,0.0003716667,0.0020197113],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990526,0.00011485783,0.00007137264,0.0002662608,0.00041348915,0.000081472725],"domain_scores_gemma":[0.99857855,0.00042067905,0.00016204323,0.00035890946,0.00039916442,0.000080666294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007389551,0.0009885922,0.0007503315,0.0023538026,0.00060789834,0.001532628,0.0014248061,0.00077796215,0.002333448],"category_scores_gemma":[0.0046595796,0.00043931077,0.000844312,0.0031142505,0.0004154243,0.0021649017,0.001967797,0.0011241982,0.0013432142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021990252,0.0003908675,0.009226347,0.000517605,0.00020625528,0.0006824073,0.00077634346,0.18564993,0.046104755,0.03909876,0.026795462,0.69033134],"study_design_scores_gemma":[0.00001425611,0.000029003606,0.0012377546,0.000018805722,0.000015866131,0.000121739286,0.00016529785,0.9691993,0.004169551,0.015409791,0.009593928,0.00002477311],"about_ca_topic_score_codex":0.0056774667,"about_ca_topic_score_gemma":0.010175404,"teacher_disagreement_score":0.0056774667,"about_ca_system_score_codex":0.00071451336,"about_ca_system_score_gemma":0.0012612778,"threshold_uncertainty_score":0.011288822},"labels":[],"label_agreement":null},{"id":"W3127327510","doi":"10.3390/electronics10040379","title":"The Influence of Public Transport Delays on Mobility on Demand Services","year":2021,"lang":"en","type":"article","venue":"Electronics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Deutsche Forschungsgemeinschaft; Deutscher Akademischer Austauschdienst","keywords":"Public transport; Variance (accounting); Transport engineering; Business; Transit (satellite); Demand management; Service (business); Supply and demand; Economics; Microeconomics; Marketing; Engineering","score_opus":0.00778049464772589,"score_gpt":0.2180343828097039,"score_spread":0.21025388816197801,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127327510","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99616915,0.00011739798,0.00043236584,0.00015893237,0.000008461599,0.00000826844,0.0006995892,0.000010655555,0.0023952043],"genre_scores_gemma":[0.99921536,0.00003960505,0.000047154906,0.000007839307,0.0000082602,0.000003283322,0.00027130055,0.000004114762,0.00040316692],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988944,0.0002847781,0.00006206949,0.00018550348,0.00022190897,0.00035137677],"domain_scores_gemma":[0.9908372,0.005939143,0.0017677541,0.0004883745,0.00060992636,0.00035755773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067057187,0.0002808716,0.00027273982,0.00065221364,0.00033057728,0.0010657589,0.00035944235,0.00034494884,0.005348479],"category_scores_gemma":[0.0067159873,0.00018886568,0.00089140993,0.0010410656,0.00042298602,0.00070089113,0.0007204596,0.00065697555,0.00043595853],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036612546,0.00008468041,0.9715522,0.00004851262,0.00023224181,0.00026465493,0.00037088306,0.015251607,0.0016745963,0.0013087764,0.00063762895,0.008208204],"study_design_scores_gemma":[0.0000064844016,0.00007044496,0.987671,0.000008860151,0.000070951915,0.00008033016,0.0006211102,0.00929145,0.00059767254,0.00034974687,0.0012188805,0.000013066761],"about_ca_topic_score_codex":0.042618383,"about_ca_topic_score_gemma":0.03384663,"teacher_disagreement_score":0.042618383,"about_ca_system_score_codex":0.001391959,"about_ca_system_score_gemma":0.0009035643,"threshold_uncertainty_score":0.08474064},"labels":[],"label_agreement":null},{"id":"W3127510495","doi":"10.1007/s11116-021-10173-9","title":"Latent stage model for carsharing usage frequency estimation with Montréal case study","year":2021,"lang":"en","type":"article","venue":"Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"Japan Society for the Promotion of Science","keywords":"Computer science; Markov chain; Estimation; Markov model; Scheme (mathematics); Service (business); Operations research; Simulation; Econometrics; Engineering; Mathematics; Machine learning; Economics","score_opus":0.02839184266387008,"score_gpt":0.2526039133241295,"score_spread":0.22421207066025944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127510495","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6464118,0.00083498727,0.34052324,0.0011476013,0.0000710012,0.0002464169,0.0050205993,0.00055266137,0.0051917015],"genre_scores_gemma":[0.945517,0.00029182967,0.03268309,0.000068296846,0.000030441524,0.00023347464,0.0036102906,0.00006415772,0.017501341],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991881,0.00038708982,0.000026909505,0.00017571884,0.00006045188,0.00016163883],"domain_scores_gemma":[0.99725634,0.0018561279,0.00020129418,0.00021603706,0.0003690311,0.000101267564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024684737,0.0007664213,0.0010933273,0.00081994064,0.0007311344,0.0015603743,0.002487115,0.001570307,0.008987646],"category_scores_gemma":[0.004570943,0.0006709277,0.0013406327,0.0014047474,0.0006242766,0.0008951635,0.0007218551,0.0017148074,0.0009134193],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009653417,0.0005543745,0.07458801,0.00019587443,0.00066674163,0.0008312514,0.0008319794,0.8034112,0.002277859,0.056803316,0.007802761,0.051071346],"study_design_scores_gemma":[0.00004216066,0.000056596375,0.010330264,0.000013696846,0.000092353475,0.00002690414,0.00017272866,0.9839101,0.00032003727,0.003458806,0.0015377948,0.0000384445],"about_ca_topic_score_codex":0.40839162,"about_ca_topic_score_gemma":0.41768494,"teacher_disagreement_score":0.5916084,"about_ca_system_score_codex":0.0021840774,"about_ca_system_score_gemma":0.0023853749,"threshold_uncertainty_score":0.81202906},"labels":[],"label_agreement":null},{"id":"W3127588010","doi":"10.1287/msom.2020.0960","title":"Surge Pricing and Two-Sided Temporal Responses in Ride Hailing","year":2021,"lang":"en","type":"article","venue":"Manufacturing & Service Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":157,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Surge; Pricing strategies; Economics; Microeconomics; Dynamic pricing; Value (mathematics); Business; Marketing; Computer science; Engineering","score_opus":0.01270077899497341,"score_gpt":0.2350989768044004,"score_spread":0.222398197809427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127588010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5731683,0.0013471118,0.36576343,0.004955151,0.00026119573,0.0005361489,0.0007496057,0.00028242555,0.05293665],"genre_scores_gemma":[0.98804784,0.00029922026,0.005532792,0.00017700036,0.00005969767,0.00012053063,0.000076439435,0.00001954832,0.0056669833],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9986091,0.0005720794,0.000054215398,0.00031238585,0.00014809366,0.00030412854],"domain_scores_gemma":[0.99172956,0.0055966917,0.001424011,0.00027007898,0.0005179597,0.00046177176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028152529,0.00084083166,0.0010845889,0.00062507525,0.0006828903,0.0019834286,0.002095497,0.0031213108,0.014411254],"category_scores_gemma":[0.015235145,0.00062750315,0.0012860531,0.0006415267,0.0018809885,0.003079479,0.0016726722,0.0023979384,0.00071576465],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001018673,0.00077399577,0.024078138,0.001079202,0.0003498551,0.001995721,0.0014846319,0.45211163,0.007889368,0.45843726,0.0075656204,0.043215793],"study_design_scores_gemma":[0.000089858564,0.00043425977,0.006749652,0.000091738766,0.00011449971,0.00048701908,0.0014706043,0.80133134,0.0008715136,0.18561648,0.0026454588,0.000097453056],"about_ca_topic_score_codex":0.0038210808,"about_ca_topic_score_gemma":0.0019904843,"teacher_disagreement_score":0.014411254,"about_ca_system_score_codex":0.0015103567,"about_ca_system_score_gemma":0.0010864073,"threshold_uncertainty_score":0.048210382},"labels":[],"label_agreement":null},{"id":"W3127739937","doi":"10.1007/s12469-021-00268-y","title":"Preference-based and cyclic bus driver rostering problem with fixed days off","year":2021,"lang":"en","type":"article","venue":"Public Transport","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Preference; Computer science; Mathematics; Statistics","score_opus":0.02575625110858417,"score_gpt":0.19154025331502797,"score_spread":0.1657840022064438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127739937","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.61834985,0.001889693,0.34161696,0.007999679,0.0005093233,0.00079918397,0.0063350876,0.0005146336,0.02198559],"genre_scores_gemma":[0.9572906,0.0005927425,0.021485602,0.00037848286,0.0002630625,0.0002851826,0.0023122262,0.00012617437,0.017266084],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99695647,0.0010562292,0.00013728846,0.0007240216,0.00031761016,0.00080846425],"domain_scores_gemma":[0.98799896,0.0082243765,0.0010918616,0.00048239762,0.0006898136,0.0015126021],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033091607,0.0025880323,0.006253402,0.0014978788,0.0019168869,0.0029280805,0.0077031595,0.008041141,0.012675252],"category_scores_gemma":[0.01231108,0.002236214,0.0029512083,0.0025728913,0.0021836057,0.00473325,0.0030479103,0.004223113,0.0006713866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015286161,0.0006782921,0.004042484,0.00069064455,0.0004502063,0.0016628018,0.00031527286,0.907931,0.0011370712,0.053839676,0.014786172,0.012937674],"study_design_scores_gemma":[0.0001627569,0.00018010804,0.0008915935,0.000030468284,0.000074603566,0.00017743059,0.00022811344,0.96909684,0.00022810647,0.028157214,0.0007175533,0.000055091903],"about_ca_topic_score_codex":0.02759647,"about_ca_topic_score_gemma":0.014261106,"teacher_disagreement_score":0.02759647,"about_ca_system_score_codex":0.0030136695,"about_ca_system_score_gemma":0.0025141728,"threshold_uncertainty_score":0.05487168},"labels":[],"label_agreement":null},{"id":"W3128131967","doi":"10.48550/arxiv.2101.00775","title":"Resource Trading in Edge Computing-enabled IoV: An Efficient Futures-based Approach","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Futures contract; Computer science; Resource (disambiguation); Edge computing; Negotiation; Algorithmic trading; Low latency (capital markets); Enabling; Enhanced Data Rates for GSM Evolution; Distributed computing; Computer network; Business; Telecommunications; Finance","score_opus":0.049129693812800156,"score_gpt":0.17971505010079777,"score_spread":0.1305853562879976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128131967","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026430601,0.0005383942,0.96773595,0.00033517042,0.00005117508,0.000062971645,0.000046684403,0.00011506535,0.004683962],"genre_scores_gemma":[0.86073184,0.00035285117,0.13517909,0.00009936066,0.00004696653,0.00008070157,0.0000927683,0.000057531204,0.0033589837],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989225,0.00033649002,0.00005406608,0.00018104317,0.00033288807,0.0001730278],"domain_scores_gemma":[0.9991371,0.00041172325,0.00009387607,0.00009249252,0.00017738261,0.00008749477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018991278,0.0006858197,0.0012657039,0.00063340156,0.0008995411,0.0017887002,0.0022598386,0.0014319079,0.0023634657],"category_scores_gemma":[0.0027354548,0.00047368158,0.00074769626,0.0009311221,0.0009559582,0.0028311969,0.002090775,0.0011104293,0.00022842347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011647027,0.000059667873,0.0007755479,0.000059664628,0.000038090035,0.0001666059,0.00013137083,0.8969845,0.0027329032,0.053749908,0.00089976355,0.04428545],"study_design_scores_gemma":[0.000004500422,0.000016696893,0.000047091864,0.0000032896417,0.0000046804353,0.000028143042,0.000023766648,0.98695576,0.0003160035,0.011966915,0.00062739383,0.0000056881822],"about_ca_topic_score_codex":0.0046804184,"about_ca_topic_score_gemma":0.0029666994,"teacher_disagreement_score":0.0046804184,"about_ca_system_score_codex":0.0012041917,"about_ca_system_score_gemma":0.0017761219,"threshold_uncertainty_score":0.010043621},"labels":[],"label_agreement":null},{"id":"W3128161387","doi":"10.2139/ssrn.3774324","title":"Dynamic Relocations in Car-Sharing Networks","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Car sharing; Computer science; Computer network; Business; Transport engineering; Engineering","score_opus":0.004742493755653196,"score_gpt":0.218538828759134,"score_spread":0.2137963350034808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128161387","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6857947,0.00074707397,0.2818014,0.0011154483,0.00018974875,0.00024141614,0.000558859,0.00042607525,0.02912527],"genre_scores_gemma":[0.985693,0.0002000364,0.007404921,0.000049688217,0.000023152052,0.00004050471,0.00014064283,0.000043819262,0.006404176],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872917,0.00035816582,0.000052540356,0.00034790934,0.00013355144,0.00037864895],"domain_scores_gemma":[0.99537766,0.0021911885,0.0007442193,0.0006707559,0.0004094071,0.00060681195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013169748,0.0005385728,0.0010323884,0.0009793605,0.0020147352,0.0020354649,0.0030289062,0.0013844412,0.012699382],"category_scores_gemma":[0.008483321,0.0007532742,0.00071137847,0.0016046636,0.0015070287,0.004711254,0.002752878,0.0011864963,0.0012733999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012196718,0.00034168994,0.0072374474,0.00025046847,0.0001211905,0.0010998794,0.0011844947,0.69464564,0.005022017,0.2149286,0.0071251085,0.06682386],"study_design_scores_gemma":[0.00006175577,0.00024841973,0.0018570902,0.00006517293,0.00007609408,0.0006889469,0.0023822256,0.8423845,0.0020001105,0.14276071,0.007411781,0.00006313693],"about_ca_topic_score_codex":0.0044435295,"about_ca_topic_score_gemma":0.0051439404,"teacher_disagreement_score":0.012699382,"about_ca_system_score_codex":0.0012877549,"about_ca_system_score_gemma":0.00097114855,"threshold_uncertainty_score":0.042483687},"labels":[],"label_agreement":null},{"id":"W3128713367","doi":"10.1016/j.scitotenv.2021.145014","title":"Environmental impact of mutualized mobility: Evidence from a life cycle perspective","year":2021,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"Fonds de Recherche du Québec-Société et Culture","keywords":"Perspective (graphical); Environmental science; Psychology; Computer science","score_opus":0.0133620448730832,"score_gpt":0.2424163517683652,"score_spread":0.229054306895282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128713367","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9226049,0.0049518165,0.0045488593,0.003742364,0.00006328983,0.00007383238,0.0014127839,0.000040711788,0.0625615],"genre_scores_gemma":[0.9970291,0.0015038595,0.00018446005,0.000083508516,0.000018025552,0.000013337364,0.0001545864,0.000003960281,0.0010091044],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998315,0.0007978642,0.00005920576,0.00014945232,0.0003262067,0.00035241482],"domain_scores_gemma":[0.987933,0.0070290253,0.002560562,0.0006534418,0.0013221767,0.0005017548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017618663,0.00035236674,0.0003452053,0.0017369401,0.00049009675,0.0018058934,0.0007331742,0.001090109,0.009313853],"category_scores_gemma":[0.00863059,0.00016912281,0.0008157215,0.002865631,0.001483885,0.0030298019,0.0025305613,0.00069381204,0.0002922573],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0041059945,0.0019336852,0.3815488,0.00204672,0.0020931794,0.0013208248,0.0024268446,0.100513265,0.0028269878,0.3144625,0.0046149837,0.18210624],"study_design_scores_gemma":[0.00038218786,0.0033999484,0.5820769,0.00089890725,0.0016544414,0.0006245121,0.015986465,0.033019636,0.0056450157,0.2837182,0.0723916,0.00020229822],"about_ca_topic_score_codex":0.009591779,"about_ca_topic_score_gemma":0.009600054,"teacher_disagreement_score":0.009591779,"about_ca_system_score_codex":0.0018610619,"about_ca_system_score_gemma":0.0014076246,"threshold_uncertainty_score":0.03115791},"labels":[],"label_agreement":null},{"id":"W3128822300","doi":"","title":"Network-based time-distance computations for an Activity-based Cellular Automata (ACA) land-use model for Flanders","year":2013,"lang":"en","type":"article","venue":"VUBIR (Vrije Universiteit Brussel)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Cellular automaton; Computer science; Computation; Theoretical computer science; Geography; Artificial intelligence; Algorithm","score_opus":0.02292131296711787,"score_gpt":0.2114792779264311,"score_spread":0.1885579649593132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128822300","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45184228,0.00051717367,0.5259673,0.0009721568,0.00013570572,0.00011269395,0.0020121266,0.00046778907,0.017972825],"genre_scores_gemma":[0.975785,0.00012640496,0.019594382,0.00003344493,0.000021687198,0.00007734015,0.0003878453,0.00003159986,0.003942298],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982375,0.000039067043,0.000015676786,0.000056685334,0.000026892645,0.000037824873],"domain_scores_gemma":[0.9992811,0.00044108697,0.000072798655,0.000033799803,0.00012185575,0.00004936742],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002931852,0.00051771913,0.0007603289,0.00059156906,0.0005973846,0.0011354684,0.0011604776,0.0011987437,0.0027355158],"category_scores_gemma":[0.0023782097,0.00035144947,0.00088038563,0.0006720972,0.0006700909,0.0008441898,0.00070659816,0.0006198437,0.0002470392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010213182,0.000006189394,0.0003321058,0.000006600499,0.000004261749,0.000020220383,0.000020094241,0.99506795,0.00014663323,0.0033114706,0.000087235305,0.0009869989],"study_design_scores_gemma":[0.0000022926283,0.0000028528682,0.000062962805,0.0000015155545,0.0000023868956,0.0000038707763,0.0000057954817,0.9983531,0.00004076567,0.0014061917,0.00011627432,0.000001955849],"about_ca_topic_score_codex":0.12787747,"about_ca_topic_score_gemma":0.06394244,"teacher_disagreement_score":0.12787747,"about_ca_system_score_codex":0.0023958415,"about_ca_system_score_gemma":0.0015448852,"threshold_uncertainty_score":0.25426626},"labels":[],"label_agreement":null},{"id":"W3128830090","doi":"10.3390/su13031434","title":"How Does the Collaborative Economy Advance Better Product Lifetimes? A Case Study of Free-Floating Bike Sharing","year":2021,"lang":"en","type":"article","venue":"Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Profitability index; Beijing; Product (mathematics); Business; Scale (ratio); Finance","score_opus":0.006461320840476693,"score_gpt":0.24205040392097216,"score_spread":0.23558908308049548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128830090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9522838,0.00035737467,0.018258685,0.00090887386,0.000018560353,0.00016115482,0.0000868862,0.000044435314,0.027880339],"genre_scores_gemma":[0.99403244,0.00015469799,0.003775444,0.000021148833,0.0000039783286,0.000030196896,0.000031573094,0.000007238814,0.001943295],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9990847,0.00042786016,0.00003139118,0.00013444896,0.00013199869,0.0001896034],"domain_scores_gemma":[0.9982999,0.00088883,0.00021333343,0.00016329224,0.00020076614,0.00023386182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019494003,0.0004312994,0.0003023066,0.00079087215,0.0015699025,0.0019762677,0.00085306924,0.001328073,0.0045569227],"category_scores_gemma":[0.0035527367,0.00021153755,0.0006665197,0.0010257302,0.0011629902,0.0044415006,0.0019749883,0.0009152116,0.00042853047],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010593585,0.0033571508,0.13555665,0.0009349617,0.00021264983,0.016254589,0.016329618,0.2903076,0.014803135,0.28348437,0.0069483505,0.23075148],"study_design_scores_gemma":[0.0003091712,0.0023405605,0.07188047,0.00030508067,0.00029224352,0.0027154123,0.057370324,0.64931405,0.0102176815,0.11013185,0.09487156,0.00025161463],"about_ca_topic_score_codex":0.008084628,"about_ca_topic_score_gemma":0.011663999,"teacher_disagreement_score":0.008084628,"about_ca_system_score_codex":0.0022966636,"about_ca_system_score_gemma":0.0015907843,"threshold_uncertainty_score":0.016663492},"labels":[],"label_agreement":null},{"id":"W3129355323","doi":"10.5539/ibr.v14n3p26","title":"Time and Cost Efficiency of Autonomous Vehicles in the Last-Mile Delivery: A UK Case","year":2021,"lang":"en","type":"article","venue":"International Business Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Last mile (transportation); Mile; Computer science; Transport engineering; Robot; Business; Delivery Performance; Cost efficiency; Supply chain; Environmental economics; Engineering; Marketing; Economics; Process management","score_opus":0.03766725269271336,"score_gpt":0.3222734250976497,"score_spread":0.28460617240493635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129355323","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92441094,0.0018325787,0.0135172345,0.001990737,0.00006027107,0.00022099605,0.0008160515,0.000045042256,0.057106085],"genre_scores_gemma":[0.9907199,0.00051430886,0.0021967485,0.00004630762,0.000012732495,0.0000435503,0.00013586693,0.000021089014,0.006309472],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9976291,0.00088111457,0.00008915557,0.00023061085,0.00038525512,0.0007847647],"domain_scores_gemma":[0.995082,0.002929765,0.00063050544,0.00023953801,0.0006132711,0.0005049537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012395468,0.0005065886,0.00044744255,0.001998417,0.0010719753,0.0026078583,0.0013222628,0.0017131764,0.010422951],"category_scores_gemma":[0.007875365,0.00046483806,0.00095133844,0.0024312262,0.0014131193,0.002244529,0.0018220728,0.0011863065,0.00092089776],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003276147,0.0018369895,0.14308992,0.00072842673,0.0002736415,0.021574104,0.0041844933,0.47533202,0.004212477,0.22458355,0.012570372,0.10833783],"study_design_scores_gemma":[0.0004166464,0.0025298626,0.16602851,0.00034295057,0.000328478,0.008507644,0.022438925,0.6965578,0.003723281,0.044539627,0.054241374,0.00034491168],"about_ca_topic_score_codex":0.09672583,"about_ca_topic_score_gemma":0.044991013,"teacher_disagreement_score":0.09672583,"about_ca_system_score_codex":0.0067182463,"about_ca_system_score_gemma":0.0013362266,"threshold_uncertainty_score":0.19232565},"labels":[],"label_agreement":null},{"id":"W3129832217","doi":"10.1287/msom.2020.0955","title":"Introducing Autonomous Vehicles: Adoption Patterns and Impacts on Social Welfare","year":2021,"lang":"en","type":"article","venue":"Manufacturing & Service Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"York University; University of Toronto","funders":"","keywords":"TRIPS architecture; Welfare; Automation; Social Welfare; Business; Sharing economy; Economics; Traffic congestion; Public economics; Microeconomics; Marketing; Computer science; Transport engineering; Market economy; Engineering","score_opus":0.010912994788400247,"score_gpt":0.22299386619780132,"score_spread":0.21208087140940107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129832217","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9948224,0.00018802064,0.0019014737,0.00044509492,0.000003022261,0.000024176554,0.0001612509,0.000009681838,0.0024450591],"genre_scores_gemma":[0.99906045,0.00012511988,0.00046134554,0.000014334747,0.0000020766695,0.000010353387,0.000056482928,0.0000024489527,0.00026753455],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991036,0.00047882745,0.000032153315,0.00014156676,0.00010496478,0.00013891564],"domain_scores_gemma":[0.9926979,0.0047014416,0.0015510657,0.00022380774,0.0005188156,0.0003070034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014164965,0.00025103643,0.00021516145,0.00072268484,0.00037184867,0.0012484405,0.00057193625,0.00060969475,0.0029353425],"category_scores_gemma":[0.008865911,0.00012309279,0.00037079025,0.001380398,0.001026394,0.0015735682,0.001032539,0.00050412107,0.00018214747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005753455,0.00066296774,0.74108595,0.00033284264,0.00035350505,0.00079792243,0.004135081,0.13777913,0.0025205906,0.035652466,0.0022085926,0.07389574],"study_design_scores_gemma":[0.00010446682,0.0010041663,0.5557756,0.00014991363,0.00023216629,0.0007338815,0.02429961,0.35503876,0.0016042353,0.053154703,0.007810285,0.00009208101],"about_ca_topic_score_codex":0.015136066,"about_ca_topic_score_gemma":0.016496837,"teacher_disagreement_score":0.015136066,"about_ca_system_score_codex":0.0021283187,"about_ca_system_score_gemma":0.000624345,"threshold_uncertainty_score":0.030095935},"labels":[],"label_agreement":null},{"id":"W3129945018","doi":"10.1155/2021/8820701","title":"Structure Analysis of Factors Influencing the Preference of Ridesplitting","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Preference; Incentive; Structural equation modeling; Destinations; Cognition; The Internet; Marketing; Questionnaire; Modal; Service (business); Survey data collection; Path analysis (statistics); Business; Microeconomics; Psychology; Economics; Computer science; Tourism; Statistics; Geography; Mathematics","score_opus":0.013307833062271715,"score_gpt":0.23832982693459523,"score_spread":0.22502199387232352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129945018","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99828076,0.000017843204,0.00081413396,0.000031191063,0.0000024027065,0.000028899609,0.00010917692,0.000007198616,0.0007084397],"genre_scores_gemma":[0.9987348,0.000014683884,0.0005447926,0.0000075370353,0.000001926057,0.000021249507,0.0002893296,0.0000023505554,0.00038334588],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992411,0.00024242971,0.000067769535,0.00014215383,0.0001585272,0.0001479373],"domain_scores_gemma":[0.9937935,0.003327683,0.0009788391,0.00043697451,0.0010946003,0.00036833002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015078376,0.0003413481,0.00031489757,0.0014020061,0.00046938463,0.0008249355,0.00033659002,0.0004414313,0.0067011616],"category_scores_gemma":[0.0074219587,0.00018440034,0.0011163449,0.0010488204,0.00038488122,0.00047847303,0.0005665724,0.0005490551,0.00043325202],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008084641,0.00014988644,0.9904945,0.000020930813,0.00007737599,0.00007473171,0.00067584735,0.0006947206,0.00081003277,0.000576023,0.00013824906,0.0062068584],"study_design_scores_gemma":[0.0000140119355,0.00020137712,0.9844185,0.000010292396,0.00007103873,0.000058412024,0.0016292928,0.012408111,0.00032798017,0.00050905667,0.00033673365,0.000015129752],"about_ca_topic_score_codex":0.01360817,"about_ca_topic_score_gemma":0.015891835,"teacher_disagreement_score":0.01360817,"about_ca_system_score_codex":0.0008043066,"about_ca_system_score_gemma":0.0011920137,"threshold_uncertainty_score":0.027057886},"labels":[],"label_agreement":null},{"id":"W3130087870","doi":"10.3390/smartcities4010016","title":"A Dynamic Mobility Traffic Model Based on Two Modes of Transport in Smart Cities","year":2021,"lang":"en","type":"article","venue":"Smart Cities","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; University of Ottawa","keywords":"Public transport; Scheme (mathematics); Transport engineering; Bike sharing; Computer science; Smart city; Personal mobility; Travel time; Simulation; Computer network; Engineering; Computer security; Internet of Things","score_opus":0.013982795235225595,"score_gpt":0.23371374893458918,"score_spread":0.21973095369936357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3130087870","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24959451,0.00051159976,0.7203415,0.0012942763,0.00028681644,0.00017835965,0.0013903965,0.00048496568,0.025917483],"genre_scores_gemma":[0.9637026,0.0004543889,0.02455426,0.00006401265,0.000051766794,0.00019226289,0.00050160964,0.00004733782,0.010431752],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99967897,0.0000996283,0.000015388783,0.00008549662,0.00005278392,0.00006778721],"domain_scores_gemma":[0.9997961,0.000050582363,0.000032062148,0.000020740143,0.000066190834,0.00003441607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033886102,0.00071101723,0.000589663,0.0005954017,0.00057469634,0.0011814219,0.0011577234,0.0009354116,0.0026942038],"category_scores_gemma":[0.0007858973,0.00035296314,0.0008450743,0.00094561314,0.0005743593,0.0018624673,0.0008709473,0.00069231796,0.00041140645],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021953914,0.0000142453455,0.000456167,0.000013044854,0.000008236676,0.00004426577,0.000027923157,0.9793118,0.0004509095,0.016796611,0.00037935475,0.0024754796],"study_design_scores_gemma":[0.0000046916416,0.000009421306,0.00011421453,0.0000020600908,0.0000037640632,0.000008825777,0.0000141067385,0.997004,0.00004704395,0.0021560083,0.0006305574,0.000005310737],"about_ca_topic_score_codex":0.025699234,"about_ca_topic_score_gemma":0.0121860765,"teacher_disagreement_score":0.025699234,"about_ca_system_score_codex":0.0013446854,"about_ca_system_score_gemma":0.0010562902,"threshold_uncertainty_score":0.0510993},"labels":[],"label_agreement":null},{"id":"W3130489108","doi":"10.1016/j.jocm.2023.100451","title":"On-demand transit user preference analysis using hybrid choice models","year":2023,"lang":"en","type":"article","venue":"Journal of Choice Modelling","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Toronto Metropolitan University","keywords":"Latent class model; Preference; Service (business); Computer science; Public transport; Latent variable; TRIPS architecture; Discrete choice; Variable (mathematics); Revealed preference; Mode choice; Latent variable model; Service design; Operations research; Transport engineering; Business; Service provider; Econometrics; Marketing; Statistics; Economics; Engineering; Mathematics; Artificial intelligence; Machine learning","score_opus":0.08803331288135398,"score_gpt":0.27561199740919035,"score_spread":0.18757868452783638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3130489108","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51588804,0.00014872423,0.47989807,0.0002570268,0.00004311145,0.00017485842,0.00045858693,0.000102787635,0.003028717],"genre_scores_gemma":[0.9783775,0.000073930154,0.019009426,0.000023342758,0.000016127307,0.00010294045,0.00020313999,0.000017199844,0.0021763637],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99670863,0.0025109001,0.000068738496,0.0002369885,0.00017822658,0.00029645918],"domain_scores_gemma":[0.9858925,0.012712958,0.00030131123,0.00034474515,0.00047256623,0.0002759132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035049806,0.0008759876,0.001653514,0.0012837553,0.0004935055,0.0020849411,0.0015530614,0.0011752677,0.007340078],"category_scores_gemma":[0.0069254753,0.00084217073,0.0027558107,0.0016076197,0.00078582886,0.0022944382,0.0012387512,0.0012083702,0.00034268232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059098616,0.00032586564,0.0052132043,0.00010733301,0.00034229725,0.00015928916,0.00020115405,0.95371705,0.0007059983,0.027024388,0.00040982745,0.011202591],"study_design_scores_gemma":[0.0000093513445,0.0000345149,0.00033291295,0.0000020135155,0.000013866254,0.0000071433674,0.000040463066,0.99638546,0.00004765864,0.00307157,0.000047608173,0.000007492442],"about_ca_topic_score_codex":0.013177599,"about_ca_topic_score_gemma":0.011878564,"teacher_disagreement_score":0.013177599,"about_ca_system_score_codex":0.0017961757,"about_ca_system_score_gemma":0.0009994912,"threshold_uncertainty_score":0.026201785},"labels":[],"label_agreement":null},{"id":"W3130506297","doi":"10.1609/aimag.v36i2.2590","title":"Reports on the 2015 AAAI Workshop Series","year":2015,"lang":"en","type":"article","venue":"AI Magazine","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Université du Québec; McGill University; University of Toronto","funders":"","keywords":"Computer science; Artificial intelligence; Interactivity; Turing; Interpretability; Analytics; Big data; Data science; World Wide Web","score_opus":0.027449126906221786,"score_gpt":0.2577773790530213,"score_spread":0.2303282521467995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3130506297","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023686015,0.041202445,0.007587628,0.1120588,0.3391738,0.0008106227,0.019693779,0.0039854655,0.47311878],"genre_scores_gemma":[0.007528395,0.027355462,0.0062979856,0.01411708,0.03713117,0.0004926506,0.03788127,0.0013187762,0.86787724],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9953799,0.00047545007,0.00034810303,0.0005905365,0.0027203788,0.00048555876],"domain_scores_gemma":[0.9857544,0.0010733922,0.00044803545,0.0012988306,0.0077804564,0.0036448846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008899974,0.0024190755,0.0015122361,0.004797058,0.0034910399,0.011661658,0.003075184,0.0041053453,0.25824416],"category_scores_gemma":[0.013438784,0.00076617335,0.0014835134,0.0036715653,0.00084743125,0.01138486,0.004937474,0.0055146245,0.23890252],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020101119,0.000037485956,0.00008881413,0.000049346734,0.000004059653,0.000017115379,0.000013889673,0.000028915207,0.000073979034,0.00065151544,0.97987247,0.019142304],"study_design_scores_gemma":[0.0000065527424,0.000009832405,0.00035040925,0.00007524096,0.0000056562403,0.000021673943,0.000054737506,0.00009915955,0.00008763059,0.00054333213,0.99873453,0.000011129447],"about_ca_topic_score_codex":0.008397669,"about_ca_topic_score_gemma":0.019579152,"teacher_disagreement_score":0.25824416,"about_ca_system_score_codex":0.0039059436,"about_ca_system_score_gemma":0.005775628,"threshold_uncertainty_score":0.86391276},"labels":[],"label_agreement":null},{"id":"W3131203174","doi":"","title":"The True Cost of Sharing: A Detour Penalty Analysis Between Ridehailing and Shared Ridehailing Trips in Toronto","year":2021,"lang":"en","type":"article","venue":"Transportation Research Board 100th Annual MeetingTransportation Research BoardTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Computer science","score_opus":0.08016853840163857,"score_gpt":0.4042502121721459,"score_spread":0.32408167377050734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3131203174","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9684073,0.0012771039,0.0034758067,0.0020144298,0.000043272605,0.000101540754,0.0027338606,0.00003335719,0.02191333],"genre_scores_gemma":[0.9946503,0.00020721176,0.00028980424,0.000024025423,0.000006184436,0.000011698374,0.00033516518,0.000008553565,0.004467011],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9982705,0.0003603941,0.00006483058,0.00016534684,0.00033399352,0.00080485956],"domain_scores_gemma":[0.99459755,0.0025846567,0.0006738038,0.00024077212,0.000941528,0.0009616517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014296861,0.0004493054,0.000759516,0.0011249246,0.0017724861,0.0035318364,0.0019336424,0.001329586,0.009644914],"category_scores_gemma":[0.0081640445,0.00065913075,0.0009164302,0.0026788472,0.0018782297,0.0022984475,0.0016034052,0.0017680926,0.00025270446],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001701265,0.00021439143,0.22879475,0.0003395162,0.0006537201,0.0017604298,0.004252534,0.54161,0.0010093123,0.17396247,0.016665403,0.029036283],"study_design_scores_gemma":[0.00014651581,0.00032155478,0.42813477,0.00023531262,0.00056383887,0.00034476578,0.022829914,0.50767297,0.00073631585,0.023999862,0.014766827,0.00024739982],"about_ca_topic_score_codex":0.89321405,"about_ca_topic_score_gemma":0.9318345,"teacher_disagreement_score":0.10678595,"about_ca_system_score_codex":0.032015715,"about_ca_system_score_gemma":0.011060982,"threshold_uncertainty_score":0.23229134},"labels":[],"label_agreement":null},{"id":"W3133930048","doi":"10.1155/2021/8879908","title":"Research on Travel Behavior with Car Sharing under Smart City Conditions","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Transport engineering; Promotion (chess); Traffic congestion; Car sharing; Sample (material); Sustainable transport; Car ownership; Nested logit; China; Environmental economics; Binary logit model; Business; Empirical research; Computer science; Public transport; Engineering; Sustainability; Economics; Econometrics","score_opus":0.05112743389913063,"score_gpt":0.34064120167892503,"score_spread":0.28951376777979443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133930048","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99765944,0.00008609058,0.00019271031,0.000093249786,0.000003626772,0.000011631887,0.00008266076,0.0000023868208,0.001868224],"genre_scores_gemma":[0.9991715,0.000119708726,0.00012010427,0.000013781117,0.000003353455,0.0000071500535,0.00007384661,8.1595255e-7,0.00048974855],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99951386,0.00016677055,0.00003785233,0.00009315585,0.00009257912,0.00009572664],"domain_scores_gemma":[0.9980696,0.00045602198,0.0007939217,0.000120505014,0.00033067993,0.00022931844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056708214,0.00020884964,0.00017163683,0.0007827511,0.00055834313,0.001040308,0.00033584636,0.00043395176,0.0038432518],"category_scores_gemma":[0.002621144,0.00011454824,0.00042311204,0.0015006356,0.00043738258,0.0013852319,0.0006342312,0.00036197703,0.0003142225],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008097016,0.00029359938,0.9738825,0.000107636835,0.000102739534,0.00018466276,0.0051005306,0.001621464,0.0007181358,0.0010900965,0.0003578069,0.016459856],"study_design_scores_gemma":[0.000003489878,0.00017964696,0.9798614,0.000023000555,0.000058659636,0.00014468198,0.013972825,0.0033452706,0.00029988211,0.00043974974,0.001654901,0.000016434886],"about_ca_topic_score_codex":0.015658414,"about_ca_topic_score_gemma":0.024882287,"teacher_disagreement_score":0.015658414,"about_ca_system_score_codex":0.0009831819,"about_ca_system_score_gemma":0.00065214117,"threshold_uncertainty_score":0.031134546},"labels":[],"label_agreement":null},{"id":"W3135421110","doi":"10.1177/0361198121995832","title":"Longitudinal Analysis of Transit-Integrated Ridesourcing Users and Their Trips","year":2021,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"TRIPS architecture; Transport engineering; Transit (satellite); Cycling; Complementarity (molecular biology); Public transport; Business; Engineering; Geography","score_opus":0.07817934055324227,"score_gpt":0.3433945454683443,"score_spread":0.26521520491510203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135421110","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982412,0.00003666423,0.00017348788,0.000037664006,0.0000023804178,0.00002268167,0.001045789,0.000003945827,0.00043622294],"genre_scores_gemma":[0.9979924,0.000055258617,0.00017028014,0.000017948918,0.0000027169351,0.000037678863,0.0010109924,0.0000027950891,0.00070988236],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995827,0.00007758963,0.00003351127,0.000085874395,0.000111770205,0.00010855591],"domain_scores_gemma":[0.9974712,0.00026958442,0.0007597947,0.00023344475,0.00089976005,0.00036623934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009721816,0.00014858026,0.00022210124,0.0007434297,0.0008372651,0.0006151259,0.00037651852,0.00025209345,0.0018558415],"category_scores_gemma":[0.002942947,0.00017242829,0.00030904645,0.0014524403,0.00023029056,0.0005876852,0.00054795225,0.00045050966,0.0003323976],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040453688,0.000036778813,0.9937975,0.0000116233605,0.000026490407,0.000041938558,0.0018116672,0.00005725825,0.0001980806,0.000030357993,0.00024573389,0.0037021753],"study_design_scores_gemma":[0.0000011365464,0.00004863075,0.99682933,0.0000067683536,0.000011024851,0.000020765588,0.0022642594,0.000182916,0.000045268105,0.000011600615,0.000573489,0.0000048491374],"about_ca_topic_score_codex":0.2470571,"about_ca_topic_score_gemma":0.40410316,"teacher_disagreement_score":0.2470571,"about_ca_system_score_codex":0.0012284284,"about_ca_system_score_gemma":0.0012024725,"threshold_uncertainty_score":0.49123812},"labels":[],"label_agreement":null},{"id":"W3137316086","doi":"10.1049/pbtr020e_ch11","title":"Demand for shared mobility to replace private mobility using connected and automated vehicles","year":2021,"lang":"en","type":"preprint","venue":"Institution of Engineering and Technology eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"TRIPS architecture; Downtown; Transport engineering; Traffic congestion; Duration (music); Process (computing); Mode (computer interface); Business; Computer science; Engineering; Geography","score_opus":0.01656138693350122,"score_gpt":0.2477705576883692,"score_spread":0.23120917075486797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3137316086","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9931585,0.000049930757,0.003598266,0.00016933437,0.000014394848,0.000017594199,0.00025455494,0.00003817248,0.0026992375],"genre_scores_gemma":[0.9987801,0.000014693951,0.00055490254,0.000008294793,0.0000027508427,0.0000057722173,0.000117667965,0.0000036068052,0.0005122614],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996941,0.00007166094,0.000011148387,0.00007567388,0.0000822343,0.00006512363],"domain_scores_gemma":[0.99929035,0.00023596926,0.00017511816,0.000081818165,0.00013839861,0.00007829505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041044515,0.00022300817,0.00020391693,0.00023201712,0.0002128289,0.00056706136,0.00060929946,0.00032322996,0.0038427557],"category_scores_gemma":[0.002075728,0.00011087667,0.00027993968,0.00051245984,0.00031911477,0.00082287943,0.0005318292,0.00028837816,0.00026985942],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011607053,0.0006159206,0.30898252,0.00033794754,0.00025485715,0.0009704144,0.00075285323,0.47722036,0.040124267,0.015205761,0.006682711,0.1476918],"study_design_scores_gemma":[0.00009935193,0.0011452181,0.25347868,0.000044959736,0.00013576225,0.0004306479,0.002429569,0.7134839,0.009531566,0.0052628443,0.013899057,0.00005846991],"about_ca_topic_score_codex":0.01975322,"about_ca_topic_score_gemma":0.03811499,"teacher_disagreement_score":0.01975322,"about_ca_system_score_codex":0.0014283423,"about_ca_system_score_gemma":0.0007256237,"threshold_uncertainty_score":0.03927648},"labels":[],"label_agreement":null},{"id":"W3137368530","doi":"","title":"On- Demand Instant Delivery Services Around the World","year":2020,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Instant; On demand; Computer science; Video on demand; Instant messaging; Telecommunications; World Wide Web; Multimedia","score_opus":0.014129595804399164,"score_gpt":0.21637964651139768,"score_spread":0.20225005070699853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3137368530","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.056870937,0.016941946,0.07124785,0.060608063,0.008970472,0.0005884177,0.03545104,0.019056356,0.7302649],"genre_scores_gemma":[0.21195264,0.014017393,0.05017743,0.006066879,0.0018960688,0.00029932722,0.05004976,0.0033269871,0.6622136],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99941385,0.0000820524,0.000019639838,0.000085674044,0.00023999163,0.00015880718],"domain_scores_gemma":[0.9987984,0.00014966194,0.000056417783,0.000119132594,0.0004608615,0.00041543707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011160966,0.00093313685,0.00033853686,0.0012064409,0.0009034679,0.0036417402,0.0012815349,0.0023706409,0.058629397],"category_scores_gemma":[0.0014006676,0.0003503554,0.00028530322,0.0018692743,0.000366268,0.0036219885,0.0018062356,0.0010979029,0.0248997],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036231,0.00015144607,0.0007785156,0.000268192,0.000013951952,0.00012552232,0.0002691468,0.0015175915,0.0067570875,0.02152002,0.713322,0.25491422],"study_design_scores_gemma":[0.00002838193,0.00006306145,0.002209523,0.00010593903,0.00001545234,0.000077603465,0.0005055813,0.0049927365,0.0028791584,0.0040523047,0.98505175,0.000018537683],"about_ca_topic_score_codex":0.018051324,"about_ca_topic_score_gemma":0.02087824,"teacher_disagreement_score":0.058629397,"about_ca_system_score_codex":0.0014234349,"about_ca_system_score_gemma":0.002399623,"threshold_uncertainty_score":0.19613487},"labels":[],"label_agreement":null},{"id":"W3137606531","doi":"10.1161/str.52.suppl_1.p529","title":"Abstract P529: Optimal Transport Scenario for Access to Endovascular Therapy With Consideration of Patient Outcomes and Cost","year":2021,"lang":"en","type":"article","venue":"Stroke","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital; Sunnybrook Health Science Centre; Nova Scotia Health Authority; Dalhousie University","funders":"","keywords":"Medicine; Thrombolysis; Fixed wing; Outcome (game theory); Engineering; Cardiology; Aerospace engineering","score_opus":0.02190123676677259,"score_gpt":0.2636658546283499,"score_spread":0.24176461786157732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3137606531","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9250479,0.00027743372,0.04070534,0.002286177,0.000077965946,0.0005451365,0.008275981,0.00019285019,0.022591198],"genre_scores_gemma":[0.9921091,0.000074918025,0.0029440538,0.000051639752,0.000012699211,0.00016056163,0.0011656136,0.000016862818,0.0034645197],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992072,0.00030570952,0.000024106714,0.0001385902,0.00006633865,0.0002581437],"domain_scores_gemma":[0.9976407,0.0014958652,0.0002354553,0.000057510828,0.00033205975,0.00023836484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001571659,0.0012360145,0.001254377,0.0013447187,0.0006769516,0.0020365529,0.0016873305,0.002937357,0.011983998],"category_scores_gemma":[0.005145754,0.00085390493,0.0018829394,0.0009941482,0.0007489463,0.0016818861,0.0008718939,0.001665472,0.0007925353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020325405,0.00006836916,0.0036928717,0.00003183196,0.000027903103,0.00024123667,0.00001580774,0.99205047,0.00010010265,0.0018486215,0.0008543811,0.0008651178],"study_design_scores_gemma":[0.00010141812,0.00022921874,0.0042237225,0.000030790867,0.00006266199,0.00011272361,0.00016255763,0.9914705,0.00027283267,0.002766462,0.0005402568,0.000026816548],"about_ca_topic_score_codex":0.03858959,"about_ca_topic_score_gemma":0.015008466,"teacher_disagreement_score":0.03858959,"about_ca_system_score_codex":0.00499113,"about_ca_system_score_gemma":0.0031693082,"threshold_uncertainty_score":0.07672995},"labels":[],"label_agreement":null},{"id":"W3137643240","doi":"10.1109/comst.2021.3108466","title":"Applications of Game Theory in Vehicular Networks: A Survey","year":2021,"lang":"en","type":"preprint","venue":"IEEE Communications Surveys & Tutorials","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Computer science; Key (lock); Game theory; Service (business); Quality of service; Intelligent transportation system; Internet of Things; Computer security; Computer network; Transport engineering; Engineering; Business","score_opus":0.04099991965339903,"score_gpt":0.29549329130674784,"score_spread":0.2544933716533488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3137643240","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006168861,0.5701936,0.3366073,0.0048987786,0.0020557467,0.0002128525,0.00039065443,0.00017667485,0.07929558],"genre_scores_gemma":[0.14111982,0.77202684,0.07078667,0.001527394,0.003453438,0.00031494765,0.00070966297,0.0001332263,0.009928038],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99778616,0.0009975524,0.00018479596,0.00026250782,0.00061641796,0.000152544],"domain_scores_gemma":[0.997566,0.0018898519,0.00008745881,0.000108410175,0.00028756636,0.000060877355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019051435,0.0016245276,0.0018004932,0.00276598,0.00080636435,0.0038168882,0.0018891107,0.0022098226,0.003327592],"category_scores_gemma":[0.004157766,0.0007784238,0.0016152889,0.005168258,0.0016628775,0.0039891927,0.0017296548,0.0026660312,0.0011840628],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050386683,0.0001501985,0.002472495,0.0035355284,0.00018664982,0.0004573233,0.0005879017,0.05013053,0.0005443256,0.6357859,0.020091498,0.28600731],"study_design_scores_gemma":[0.00002156831,0.00012661767,0.0012640009,0.0017057383,0.00008108873,0.0008724863,0.00074312626,0.11241138,0.00039076828,0.5639891,0.3182925,0.000101693695],"about_ca_topic_score_codex":0.0055007506,"about_ca_topic_score_gemma":0.0034365356,"teacher_disagreement_score":0.0055007506,"about_ca_system_score_codex":0.0021654107,"about_ca_system_score_gemma":0.0019234336,"threshold_uncertainty_score":0.015711188},"labels":[],"label_agreement":null},{"id":"W3138388414","doi":"10.37394/23205.2020.19.7","title":"An Algorithm for Computing Solutions to the Range Limited Routing Problem Using Electrical Trucks","year":2020,"lang":"en","type":"article","venue":"WSEAS TRANSACTIONS ON COMPUTERS","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Truck; Routing (electronic design automation); Computer science; Vehicle routing problem; Firefly algorithm; Range (aeronautics); Process (computing); Metaheuristic; Transport engineering; Mathematical optimization; Operations research; Algorithm; Automotive engineering; Engineering; Mathematics; Computer network","score_opus":0.0345452358104031,"score_gpt":0.25466801470749195,"score_spread":0.22012277889708887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3138388414","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010709962,0.00021111482,0.9822051,0.00019311593,0.00006553874,0.00017238363,0.00011083076,0.0007325459,0.005599331],"genre_scores_gemma":[0.065920606,0.00018693143,0.9304947,0.000071571165,0.000025049485,0.0004206772,0.00022503317,0.00006162652,0.002593672],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999742,0.000052763342,0.000019217405,0.000066589535,0.000074258794,0.000045176865],"domain_scores_gemma":[0.999616,0.00022811495,0.000034950244,0.000022573366,0.00007642139,0.000021919854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066815515,0.0011446009,0.0007577625,0.0010869757,0.0008184283,0.0009897546,0.0015423709,0.0015198137,0.0051073483],"category_scores_gemma":[0.0018026043,0.00044810647,0.00076255365,0.0013872221,0.0005624303,0.00096596475,0.001014801,0.00078850216,0.00068912667],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008029659,0.00009683567,0.00052736705,0.0001314369,0.00003704538,0.00008946923,0.00008972779,0.8427412,0.0016909174,0.016324269,0.003409001,0.13478245],"study_design_scores_gemma":[0.00003794959,0.000043147407,0.00006209862,0.000010593783,0.0000084576595,0.00002941441,0.000025134274,0.99384016,0.00033965133,0.0037610303,0.0018365992,0.000005707183],"about_ca_topic_score_codex":0.007724292,"about_ca_topic_score_gemma":0.008824541,"teacher_disagreement_score":0.007724292,"about_ca_system_score_codex":0.0008403195,"about_ca_system_score_gemma":0.0020570366,"threshold_uncertainty_score":0.01708579},"labels":[],"label_agreement":null},{"id":"W3138745551","doi":"10.5198/jtlu.2021.1827","title":"Differences in ride-hailing adoption by older Californians among types of locations","year":2021,"lang":"en","type":"article","venue":"Journal of Transport and Land Use","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"San José State University","keywords":"Market segmentation; Public transport; Business; Demographic economics; Socioeconomics; Household income; Advertising; Marketing; Geography; Sociology; Transport engineering; Economics; Engineering","score_opus":0.011715847559981845,"score_gpt":0.20697761006307902,"score_spread":0.19526176250309718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3138745551","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990363,0.00006607314,0.00002585155,0.000025949686,0.0000015237098,0.000007401001,0.00025250763,0.0000011321414,0.0005832987],"genre_scores_gemma":[0.9990728,0.000083994615,0.00005298298,0.000022711132,0.0000024786898,0.000008387507,0.0003363074,0.000001066834,0.00041918005],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996985,0.00004742744,0.000042370644,0.000081632075,0.000069267946,0.000060823342],"domain_scores_gemma":[0.99848324,0.00027956933,0.00064450776,0.00008200626,0.00027806856,0.00023263763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007002665,0.00014752473,0.00019018071,0.0006621633,0.00042228203,0.0006194149,0.0002969166,0.00034332438,0.0024510894],"category_scores_gemma":[0.003077909,0.00018226092,0.00033252977,0.0005603536,0.00024744368,0.00059926364,0.00050260324,0.00036366493,0.00028003415],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000075955686,0.0000706039,0.99504256,0.000015763388,0.000026295462,0.000029139834,0.0011429315,0.000042627806,0.000118503885,0.000030087205,0.00018943351,0.0032160685],"study_design_scores_gemma":[0.0000019012831,0.00004041485,0.9982399,0.000008139429,0.0000065250333,0.000026156671,0.0014121559,0.000056925954,0.000014645317,0.000008134588,0.00018218198,0.0000028867203],"about_ca_topic_score_codex":0.06988672,"about_ca_topic_score_gemma":0.14086653,"teacher_disagreement_score":0.06988672,"about_ca_system_score_codex":0.00040835072,"about_ca_system_score_gemma":0.00024684824,"threshold_uncertainty_score":0.13895988},"labels":[],"label_agreement":null},{"id":"W3144845068","doi":"10.1109/tsc.2021.3070746","title":"Resource Trading in Edge Computing-Enabled IoV: An Efficient Futures-Based Approach","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Services Computing","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Futures contract; Edge computing; Resource (disambiguation); Negotiation; Low latency (capital markets); Algorithmic trading; Distributed computing; Enhanced Data Rates for GSM Evolution; Computer network; Telecommunications; Business","score_opus":0.01384344171392852,"score_gpt":0.23216014590570422,"score_spread":0.2183167041917757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3144845068","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025213854,0.0006020781,0.96847624,0.0003337989,0.000055072327,0.00006965467,0.000047505477,0.00012233533,0.005079495],"genre_scores_gemma":[0.866979,0.000371343,0.1289343,0.000107531145,0.00004681851,0.00008324211,0.00009104613,0.000055889042,0.003330801],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987947,0.0003651425,0.000060693405,0.00020009189,0.00037779094,0.00020150474],"domain_scores_gemma":[0.9991491,0.00039654123,0.00009675867,0.00009254489,0.00017391647,0.000091244365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019471211,0.0006882843,0.0012936033,0.0006376216,0.0009121573,0.0018191014,0.0023483683,0.0013770472,0.0024303636],"category_scores_gemma":[0.0026929409,0.0004711171,0.0007258242,0.00093340274,0.00096111576,0.002844174,0.0021251764,0.0011089942,0.00022896926],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012552421,0.000069211404,0.000842383,0.00006561721,0.000041155035,0.0001971463,0.000137128,0.88185537,0.0029863333,0.06319592,0.0010452518,0.049438946],"study_design_scores_gemma":[0.000004751031,0.000018695775,0.000047964862,0.0000036156248,0.000004990895,0.000033031636,0.00002470923,0.9861822,0.00032401973,0.012642495,0.0007071577,0.0000063269295],"about_ca_topic_score_codex":0.0046057184,"about_ca_topic_score_gemma":0.0030163557,"teacher_disagreement_score":0.0046057184,"about_ca_system_score_codex":0.001223042,"about_ca_system_score_gemma":0.0019778258,"threshold_uncertainty_score":0.010297477},"labels":[],"label_agreement":null},{"id":"W3145961009","doi":"10.1155/2021/5585542","title":"Survey Data Analysis on Intention to Use Shared Mobility Services","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Korea Advanced Institute of Science and Technology; National Research Foundation of Korea; Ministry of Science, ICT and Future Planning; National Research Foundation","keywords":"Service (business); Business; Public transport; Logistic regression; Transport engineering; Survey data collection; Marketing; Computer science; Engineering","score_opus":0.04028869140619083,"score_gpt":0.2969693377119397,"score_spread":0.2566806463057488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3145961009","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99468464,0.000034099925,0.000776965,0.00006895861,0.00000592064,0.0001388216,0.0028101457,0.000015312147,0.0014650826],"genre_scores_gemma":[0.99433833,0.00006612088,0.0011819375,0.000054694,0.000005765205,0.0005088329,0.0031977112,0.000005694556,0.00064088666],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997072,0.0013779532,0.00047888982,0.00021547146,0.0005537685,0.00030191138],"domain_scores_gemma":[0.98460555,0.008690098,0.0032075422,0.00056381506,0.0024154442,0.0005174872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037491485,0.00023934888,0.0003651938,0.0016725329,0.00030790243,0.00059107307,0.00036701688,0.0003767659,0.0035532385],"category_scores_gemma":[0.012410826,0.00020775627,0.00090141373,0.0027677275,0.00033545741,0.00063070253,0.00054299977,0.00078396226,0.00059672195],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006445707,0.00023883225,0.9923848,0.000058626345,0.00007695939,0.00002164773,0.0006263588,0.0002698816,0.00010877904,0.00013631332,0.000418722,0.005594608],"study_design_scores_gemma":[0.000010309017,0.00040257128,0.99344987,0.000029586818,0.00004727644,0.000042185988,0.002774143,0.0021761793,0.00022847718,0.000062323896,0.0007642823,0.0000127690655],"about_ca_topic_score_codex":0.00912043,"about_ca_topic_score_gemma":0.006767475,"teacher_disagreement_score":0.00912043,"about_ca_system_score_codex":0.0005421865,"about_ca_system_score_gemma":0.00078967784,"threshold_uncertainty_score":0.019827604},"labels":[],"label_agreement":null},{"id":"W3149254007","doi":"10.21314/jfmi.2021.003","title":"Predicting payment migration in Canada","year":2021,"lang":"en","type":"article","venue":"The Journal of Financial Market Infrastructures","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Settlement (finance); Payment; Collateral; Clearing; Counterfactual thinking; Payment system; Business; Value (mathematics); Database transaction; Actuarial science; Transaction cost; Finance; Economics; Computer science","score_opus":0.003364132960477012,"score_gpt":0.17766925608302964,"score_spread":0.1743051231225526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3149254007","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9762729,0.00030274954,0.0012805789,0.0014165683,0.00002933103,0.00006746339,0.013595521,0.00009833443,0.0069365795],"genre_scores_gemma":[0.9834009,0.00035707682,0.0016669675,0.00016323286,0.000006927113,0.000026161955,0.009382808,0.00002200714,0.004974015],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933296,0.00006584507,0.000032302,0.00010664475,0.00019874085,0.00026352098],"domain_scores_gemma":[0.9975914,0.00029635834,0.00025106838,0.00009587923,0.0014367484,0.00032864814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084761746,0.0004180745,0.00035470322,0.0017395249,0.0018935574,0.0017087751,0.0013439034,0.0006432407,0.004124726],"category_scores_gemma":[0.005002346,0.00029241838,0.00057391357,0.0040554954,0.0005851692,0.00079269736,0.0009303591,0.0009963395,0.0006380651],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003570311,0.00017122552,0.87791723,0.00010544956,0.0001056799,0.0005463943,0.0016843706,0.04144901,0.00063020666,0.0067231017,0.028610922,0.04169945],"study_design_scores_gemma":[0.000053376385,0.000059062557,0.7152735,0.00010675404,0.000045521636,0.00015982792,0.0062373956,0.24168082,0.0008172305,0.0014193457,0.034053624,0.00009358294],"about_ca_topic_score_codex":0.9942667,"about_ca_topic_score_gemma":0.99492174,"teacher_disagreement_score":0.039304998,"about_ca_system_score_codex":0.039304998,"about_ca_system_score_gemma":0.027463164,"threshold_uncertainty_score":0.28517908},"labels":[],"label_agreement":null},{"id":"W3149688885","doi":"","title":"Understanding the Factors Affecting Vehicle Usage and Availability in Carsharing Networks:A Case Study of Communauto Carsharing System from Montreal, Canada","year":2011,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University","funders":"McGill University","keywords":"Transport engineering; Novelty; Car sharing; Computer science; Operations research; Business; Engineering","score_opus":0.06260553825392295,"score_gpt":0.2129125062500799,"score_spread":0.15030696799615695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3149688885","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976991,0.000062047984,0.00017486331,0.00012290152,0.0000017875416,0.00004272535,0.00018632539,0.0000045393085,0.0017058168],"genre_scores_gemma":[0.996799,0.0001596463,0.00043957218,0.000035124864,0.0000020756354,0.000022236052,0.00021808203,0.000004384844,0.0023198202],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995285,0.00007976766,0.000011782506,0.00005601015,0.00009740352,0.00022661625],"domain_scores_gemma":[0.9990464,0.00029792523,0.0000956212,0.000026909638,0.00031542557,0.00021766886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042299228,0.00041632305,0.00024003036,0.00092385465,0.0040911054,0.0014469485,0.0009955629,0.0005905539,0.0024398884],"category_scores_gemma":[0.0015171105,0.00022528248,0.00029869712,0.0021168767,0.00094798027,0.0005790984,0.0006162881,0.0006054473,0.00017172293],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020406583,0.0007614196,0.9030048,0.0001504496,0.0000835095,0.0099708205,0.036964044,0.008363583,0.0038553486,0.0019663551,0.0027261241,0.03194949],"study_design_scores_gemma":[0.00002038597,0.0003057623,0.8554574,0.00006169224,0.000057297773,0.00065620535,0.11988822,0.014313281,0.0011644536,0.00017417342,0.0078342995,0.0000667923],"about_ca_topic_score_codex":0.98733413,"about_ca_topic_score_gemma":0.99505323,"teacher_disagreement_score":0.026239287,"about_ca_system_score_codex":0.026239287,"about_ca_system_score_gemma":0.014159973,"threshold_uncertainty_score":0.19038028},"labels":[],"label_agreement":null},{"id":"W3154106394","doi":"","title":"The Evolution of Community Consultation in GTA Transit Planning","year":2020,"lang":"en","type":"article","venue":"TSpace","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"University of Toronto","keywords":"Transit (satellite); Environmental planning; Business; Geography; Transport engineering; Public transport; Engineering","score_opus":0.037850862941994905,"score_gpt":0.2973756126639694,"score_spread":0.2595247497219745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154106394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49930033,0.003350948,0.028542982,0.07189122,0.0004892977,0.00042429674,0.00008034474,0.00021994933,0.39570066],"genre_scores_gemma":[0.9937961,0.00021680637,0.0017107793,0.000653494,0.00002646146,0.000041229872,0.000010057651,0.000026175056,0.003518885],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9687774,0.021957254,0.00039861008,0.0016417986,0.0021038153,0.0051209596],"domain_scores_gemma":[0.9791915,0.01136701,0.0011549764,0.00076128007,0.002300617,0.0052245506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014280027,0.0002544306,0.0002501102,0.0027788363,0.026456133,0.011100244,0.0024397576,0.004095158,0.0067544268],"category_scores_gemma":[0.024670253,0.00072268175,0.00036491154,0.003545361,0.031448223,0.006097617,0.017361691,0.0064323097,0.00040612996],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012712565,0.00016532626,0.007127313,0.00016746645,0.000019234825,0.0030292058,0.42967656,0.0027906406,0.0006720869,0.4726935,0.009701421,0.07383002],"study_design_scores_gemma":[0.000052866784,0.00016121483,0.015180354,0.0005935722,0.000018283865,0.0011614736,0.50666183,0.0059733284,0.0007502589,0.12477893,0.3445211,0.00014685035],"about_ca_topic_score_codex":0.109996565,"about_ca_topic_score_gemma":0.16954258,"teacher_disagreement_score":0.89000344,"about_ca_system_score_codex":0.042472348,"about_ca_system_score_gemma":0.03710798,"threshold_uncertainty_score":0.3081599},"labels":[],"label_agreement":null},{"id":"W3154394899","doi":"10.1155/2021/8835859","title":"Context-Aware Services Using MANETs for Long-Distance Vehicular Systems: A Cognitive Agent-Based Model","year":2021,"lang":"en","type":"article","venue":"Scientific Programming","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"NetLogo; Computer science; Context (archaeology); Traffic congestion; Intelligent transportation system; Scarcity; Fleet management; Operations research; Transport engineering; Computer security; Risk analysis (engineering); Telecommunications; Engineering; Business","score_opus":0.033242015123420864,"score_gpt":0.27050221534019825,"score_spread":0.23726020021677738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154394899","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04721971,0.0038808638,0.89931434,0.0026009826,0.0006245315,0.00031031948,0.0005280363,0.0004942602,0.04502709],"genre_scores_gemma":[0.9191435,0.0034921698,0.060859006,0.000350493,0.00025721555,0.000434723,0.00024817412,0.00007012334,0.015144627],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995876,0.00013028053,0.000022744927,0.00009870086,0.000085790496,0.000074865355],"domain_scores_gemma":[0.9996834,0.00012464677,0.000041011735,0.00001920765,0.000082533224,0.00004916042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041907083,0.0009752115,0.00083553715,0.0006811539,0.0010251836,0.002350032,0.0021482725,0.0019839818,0.0029941879],"category_scores_gemma":[0.0009806551,0.00041757803,0.0010909095,0.0009642853,0.0008667013,0.0019994397,0.0014037932,0.0013709298,0.00064617617],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003711222,0.00006227872,0.00071612134,0.000094949944,0.000053912652,0.00037460166,0.00017477396,0.9152784,0.0010069208,0.07223761,0.0012709136,0.008692432],"study_design_scores_gemma":[0.000007863926,0.000023629053,0.000102022954,0.000012600046,0.000019718727,0.00004178366,0.000048961796,0.9884107,0.00008755387,0.009320132,0.0019144199,0.000010667669],"about_ca_topic_score_codex":0.02279613,"about_ca_topic_score_gemma":0.01611645,"teacher_disagreement_score":0.02279613,"about_ca_system_score_codex":0.0015329446,"about_ca_system_score_gemma":0.0016111624,"threshold_uncertainty_score":0.04532689},"labels":[],"label_agreement":null},{"id":"W3156394716","doi":"","title":"Report 3: Taxi Time-Series Analysis","year":2019,"lang":"en","type":"article","venue":"TSpace","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Series (stratigraphy); Time series; Computer science; Mathematics; Statistics; Geology","score_opus":0.007414598324178226,"score_gpt":0.2677947285231888,"score_spread":0.2603801301990106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3156394716","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042620998,0.00051222654,0.044744227,0.003078402,0.0009783994,0.0029020081,0.84766465,0.006131956,0.051367167],"genre_scores_gemma":[0.086355835,0.0011561739,0.057764582,0.0005638913,0.00086448994,0.0037635372,0.7767492,0.0018704538,0.07091187],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9934842,0.00064531254,0.0004273262,0.0005790637,0.004464294,0.00039976704],"domain_scores_gemma":[0.98105353,0.0033895262,0.0012381097,0.0028499383,0.010866677,0.0006021986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055302167,0.00093066046,0.0008362273,0.0036786452,0.00081392867,0.0028781618,0.0011259452,0.0006809151,0.03153081],"category_scores_gemma":[0.021544404,0.0004986388,0.0010586472,0.006090391,0.00029380835,0.0010248076,0.0011189539,0.0013977294,0.019064993],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015204746,0.00022245059,0.04660814,0.00041267416,0.00024566063,0.00035709885,0.00082711095,0.013488194,0.0012100122,0.010034397,0.8176091,0.10883318],"study_design_scores_gemma":[0.00006736502,0.00018465612,0.13662525,0.00028830365,0.0001294353,0.00025306962,0.001199853,0.029936783,0.0036530194,0.0028258986,0.8246985,0.00013778577],"about_ca_topic_score_codex":0.2214326,"about_ca_topic_score_gemma":0.15269168,"teacher_disagreement_score":0.2214326,"about_ca_system_score_codex":0.0029966403,"about_ca_system_score_gemma":0.00798843,"threshold_uncertainty_score":0.4402874},"labels":[],"label_agreement":null},{"id":"W3157093429","doi":"","title":"An Assessment of the Use of Autonomous Ground Vehicles for Last-mile Parcel Delivery","year":2020,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Mile; Last mile (transportation); Transport engineering; Aeronautics; Engineering; Geography; Geodesy","score_opus":0.04300379087858028,"score_gpt":0.33496620695037455,"score_spread":0.2919624160717943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157093429","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89052856,0.0049195834,0.014503496,0.0010960493,0.000088158486,0.00025337093,0.0018870017,0.0002326218,0.08649123],"genre_scores_gemma":[0.9840401,0.0022602587,0.0053327386,0.00003854592,0.000017736866,0.00003673976,0.00062041724,0.00002554318,0.0076279524],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99865085,0.00038409783,0.000027559732,0.000117590826,0.0006749049,0.00014499454],"domain_scores_gemma":[0.9965397,0.0018489828,0.0003368839,0.00023517189,0.0009071437,0.00013210354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012804186,0.00041214816,0.00021271224,0.0014598555,0.00038354268,0.0015139234,0.0009484085,0.0005583019,0.005202945],"category_scores_gemma":[0.0039295927,0.0001561252,0.0003720976,0.0018497048,0.0003061949,0.0017355855,0.0004780561,0.00031861162,0.0007517815],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007829139,0.0005652805,0.07815264,0.00085952325,0.00016953821,0.00034875906,0.00027841635,0.36023307,0.007029258,0.024485938,0.008560107,0.5185345],"study_design_scores_gemma":[0.00010359581,0.006032085,0.23577343,0.00035527127,0.0004232798,0.0009608616,0.0055556633,0.60098356,0.015727341,0.0115642585,0.122392245,0.00012838586],"about_ca_topic_score_codex":0.019051166,"about_ca_topic_score_gemma":0.024088865,"teacher_disagreement_score":0.019051166,"about_ca_system_score_codex":0.0020819511,"about_ca_system_score_gemma":0.0010051572,"threshold_uncertainty_score":0.03788054},"labels":[],"label_agreement":null},{"id":"W3157579470","doi":"10.1109/tcns.2021.3077830","title":"Rebalancing Self-Interested Drivers in Ride-Sharing Networks to Improve Customer Wait-Time","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Control of Network Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Control (management); Payment; Information sharing; Profit (economics); Operations research; Engineering","score_opus":0.005887144990799904,"score_gpt":0.2008933028981284,"score_spread":0.1950061579073285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157579470","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36480454,0.0010706893,0.6252252,0.00035029778,0.00015053009,0.00022368229,0.00013916832,0.0010728757,0.006963153],"genre_scores_gemma":[0.98264503,0.00013805159,0.015917381,0.000055363667,0.000017693013,0.000047718135,0.00004843581,0.000038934373,0.0010913872],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912435,0.00021154383,0.00004004098,0.00022625687,0.00014774718,0.00025009556],"domain_scores_gemma":[0.9979498,0.00081605464,0.0003653944,0.00028898474,0.00035663895,0.0002231451],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017845323,0.0013345076,0.00096666353,0.0004938106,0.0007731428,0.001322962,0.0022452318,0.0008494654,0.0032316656],"category_scores_gemma":[0.003877512,0.0003515735,0.0005452535,0.0006233556,0.00081574405,0.0020200633,0.0013385428,0.0010991498,0.0005195472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005187734,0.0005243496,0.0043343096,0.00021054158,0.000102744314,0.00015668415,0.00044045027,0.8652543,0.016159033,0.010827102,0.0021684116,0.09930332],"study_design_scores_gemma":[0.00003230157,0.00019180814,0.0008385096,0.000011564134,0.000042226733,0.000070323775,0.00023321275,0.9886856,0.0038212908,0.0043553617,0.0016915309,0.000026099502],"about_ca_topic_score_codex":0.0061957138,"about_ca_topic_score_gemma":0.0075908755,"teacher_disagreement_score":0.0061957138,"about_ca_system_score_codex":0.0009999046,"about_ca_system_score_gemma":0.0012521239,"threshold_uncertainty_score":0.012319326},"labels":[],"label_agreement":null},{"id":"W3157652862","doi":"10.1016/j.knosys.2022.108489","title":"A deep reinforcement learning approach for the meal delivery problem","year":2022,"lang":"en","type":"article","venue":"Knowledge-Based Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Reinforcement learning; Markov decision process; Computer science; Operations research; Order (exchange); Service (business); Set (abstract data type); Process (computing); Markov process; Variety (cybernetics); Artificial intelligence; Marketing; Business; Engineering; Statistics; Mathematics","score_opus":0.02092170731942637,"score_gpt":0.2242285503242626,"score_spread":0.20330684300483623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157652862","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04348683,0.0008270518,0.9476877,0.0012120339,0.00015038394,0.000064900036,0.00029718434,0.00069117855,0.005582688],"genre_scores_gemma":[0.8458284,0.00037210534,0.14015932,0.00044195182,0.00015695515,0.00015891604,0.0005174808,0.000119941695,0.012244845],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997329,0.00007761358,0.0000109773655,0.00007699879,0.00004507696,0.00005650726],"domain_scores_gemma":[0.99919933,0.0005356033,0.000053362477,0.000040040395,0.00010667667,0.000064907494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006864206,0.00062209886,0.0012081681,0.00038903658,0.00038037705,0.00073426036,0.0018623946,0.0019129898,0.0060537136],"category_scores_gemma":[0.0022719565,0.0005168139,0.0005080734,0.0004961463,0.00065358664,0.0011374565,0.0012631465,0.0021006262,0.00058872264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011482544,0.0001222322,0.00057154597,0.000069845286,0.00003835676,0.000067129215,0.00003358803,0.91805017,0.000616463,0.012485312,0.0034313104,0.06439927],"study_design_scores_gemma":[0.0000077511595,0.000008394905,0.00002977144,0.0000031699012,0.0000027963745,0.0000030341882,0.0000022027525,0.99636155,0.0000628896,0.0033632666,0.00015379363,0.0000014822651],"about_ca_topic_score_codex":0.015060995,"about_ca_topic_score_gemma":0.013270366,"teacher_disagreement_score":0.015060995,"about_ca_system_score_codex":0.0011302899,"about_ca_system_score_gemma":0.0014704166,"threshold_uncertainty_score":0.029946625},"labels":[],"label_agreement":null},{"id":"W3157755817","doi":"10.2139/ssrn.3675888","title":"Dynamic Dispatch and Centralized Relocation of Cars in Ride-Hailing Platforms","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Relocation; Business; Computer science; Car sharing; Transport engineering; Automotive engineering; Engineering; Operating system","score_opus":0.005198289184932382,"score_gpt":0.20500728992831388,"score_spread":0.1998090007433815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157755817","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8486329,0.00016031737,0.13754304,0.000379702,0.00013442995,0.00006627943,0.00012168512,0.00018967157,0.01277193],"genre_scores_gemma":[0.99520016,0.000029868814,0.002424014,0.0000077324885,0.000010678398,0.000009473068,0.000029119057,0.000016674165,0.0022722813],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999443,0.0001249562,0.00001513464,0.00014363948,0.000058190726,0.0002150942],"domain_scores_gemma":[0.9987185,0.0004545095,0.00022665599,0.00016116352,0.00015459147,0.00028463564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007199562,0.00043534036,0.0007926233,0.00049285695,0.0013002743,0.0018707792,0.0016150867,0.0008340358,0.0063907006],"category_scores_gemma":[0.0038320015,0.00044312872,0.00048012487,0.00045509113,0.000960578,0.0017795941,0.00172006,0.0010196563,0.0006278346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066724553,0.00012572145,0.003228759,0.000052589592,0.00004162747,0.000583771,0.00033424396,0.93039894,0.004894189,0.04023663,0.0016377892,0.017798452],"study_design_scores_gemma":[0.000024063747,0.00009385038,0.0016110719,0.0000062801405,0.000015412319,0.00005474881,0.0004075584,0.9830308,0.0008460155,0.013247433,0.00064362906,0.00001919243],"about_ca_topic_score_codex":0.007945628,"about_ca_topic_score_gemma":0.0069245277,"teacher_disagreement_score":0.007945628,"about_ca_system_score_codex":0.0011681754,"about_ca_system_score_gemma":0.0011694696,"threshold_uncertainty_score":0.021378994},"labels":[],"label_agreement":null},{"id":"W3157874279","doi":"10.1007/s11116-021-10193-5","title":"Exploring the correlation between ride-hailing and multimodal transit ridership in toronto","year":2021,"lang":"en","type":"article","venue":"Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Transport engineering; Transit (satellite); Public transport; TRIPS architecture; Geography; Traffic congestion; Vehicle miles of travel; Business; Agricultural economics; Engineering; Economics","score_opus":0.05210916012808748,"score_gpt":0.2484828912236147,"score_spread":0.19637373109552722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157874279","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9975521,0.000064399974,0.000079734695,0.0001376565,0.000003974484,0.000008472231,0.0004921641,0.000002930425,0.0016586115],"genre_scores_gemma":[0.99885607,0.000050312014,0.000043299424,0.0000074942195,0.0000024902774,0.000007147353,0.00020879462,0.0000012634044,0.0008231525],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99948454,0.000101452315,0.000034953617,0.000075709846,0.00010368708,0.0001996807],"domain_scores_gemma":[0.9966449,0.0006370504,0.0007260636,0.00013116124,0.00092572975,0.00093504216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054958946,0.00021053829,0.0002487978,0.0009033857,0.0018762113,0.001727147,0.00065512257,0.00040924354,0.0049127173],"category_scores_gemma":[0.003523211,0.00026865312,0.0004950721,0.002234725,0.0007369456,0.00071408076,0.0014691036,0.0007268244,0.000285359],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048483973,0.000034291315,0.990542,0.000013143544,0.00005165706,0.00010679223,0.0060498165,0.00030734157,0.0001569539,0.00041513552,0.0005540575,0.0017204174],"study_design_scores_gemma":[0.0000016090086,0.00001555848,0.98855245,0.000012215813,0.000018350265,0.000014358098,0.01015414,0.0005221809,0.000041120893,0.000024179328,0.0006380416,0.000005924252],"about_ca_topic_score_codex":0.9545934,"about_ca_topic_score_gemma":0.98284525,"teacher_disagreement_score":0.04540658,"about_ca_system_score_codex":0.0115499385,"about_ca_system_score_gemma":0.007873421,"threshold_uncertainty_score":0.09134793},"labels":[],"label_agreement":null},{"id":"W3158441464","doi":"10.22215/timreview/1433","title":"Managing the Disruption of Mobility Services: How to align the value propositions of key ecosystem players","year":2021,"lang":"en","type":"article","venue":"Technology Innovation Management Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Business Finland","keywords":"Urbanization; Automotive industry; Business; Key (lock); Politics; Value (mathematics); Industrial organization; Economics; Computer science; Computer security; Political science; Economic growth; Engineering","score_opus":0.011634681626419906,"score_gpt":0.2513651186676537,"score_spread":0.2397304370412338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158441464","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025859084,0.099470936,0.14502689,0.51941615,0.005045105,0.0010919881,0.0002296016,0.0004246804,0.20343551],"genre_scores_gemma":[0.6785972,0.13892739,0.13391708,0.02855484,0.0017298193,0.00078753143,0.00026577857,0.00019787485,0.017022591],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9906878,0.0048368396,0.0004135089,0.0005224277,0.0024210722,0.0011184196],"domain_scores_gemma":[0.98674417,0.0047326577,0.001413393,0.0005382979,0.005379425,0.0011920643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017648945,0.0013543474,0.00095756305,0.0033849701,0.0035917864,0.015662376,0.0033864055,0.005176316,0.0072232205],"category_scores_gemma":[0.029851634,0.0004866952,0.0008324788,0.002862055,0.006299109,0.020406684,0.0072964476,0.0050861137,0.0015353105],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051742627,0.00016347127,0.004543446,0.0036511167,0.00024232706,0.00043066518,0.0042271037,0.0067860917,0.0013221458,0.5179408,0.05715371,0.40348735],"study_design_scores_gemma":[0.000037957907,0.00019942917,0.0045463494,0.012047494,0.00025902723,0.00040085707,0.029641004,0.007131481,0.0017339872,0.40826738,0.53561306,0.000121999896],"about_ca_topic_score_codex":0.007566341,"about_ca_topic_score_gemma":0.014160606,"teacher_disagreement_score":0.017648945,"about_ca_system_score_codex":0.009910839,"about_ca_system_score_gemma":0.026468981,"threshold_uncertainty_score":0.093337715},"labels":[],"label_agreement":null},{"id":"W3158561246","doi":"10.1155/2021/6654909","title":"Real-Time Return Demand Prediction Based on Multisource Data of One-Way Carsharing Systems","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Relocation; Computer science; Demand forecasting; Real-time data; Operations research; Supply and demand; Field (mathematics); Simulation; Real-time computing; Engineering","score_opus":0.02083661272008519,"score_gpt":0.24857175131515027,"score_spread":0.22773513859506508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158561246","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94680756,0.00022873124,0.049049295,0.00019172438,0.000075942124,0.00006256451,0.0009532673,0.0008202739,0.0018106172],"genre_scores_gemma":[0.99569356,0.000052914067,0.003332035,0.000011160625,0.0000072863395,0.000016490294,0.00058876176,0.000010503402,0.00028738184],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960893,0.00005207023,0.000032288805,0.000115655355,0.00012904046,0.00006206054],"domain_scores_gemma":[0.99904627,0.00032697784,0.000111921574,0.00008924774,0.00036045135,0.00006506511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055170245,0.0010721816,0.0007301526,0.0009182486,0.00038354236,0.00068954617,0.0007611999,0.00055418035,0.0008220138],"category_scores_gemma":[0.0016476073,0.00033310376,0.00046255594,0.0010038285,0.00020464872,0.0010730937,0.00047700328,0.00075169024,0.00028888616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044431337,0.0003869974,0.061822526,0.00019946203,0.000085382955,0.0005594307,0.00021501434,0.86182815,0.0099207,0.00048408317,0.0018533744,0.062200543],"study_design_scores_gemma":[0.0000055860246,0.000039482977,0.0074934918,0.0000033385304,0.000009194948,0.000016483438,0.00005780488,0.99105364,0.0010596188,0.00010416981,0.00014643649,0.000010825146],"about_ca_topic_score_codex":0.01768963,"about_ca_topic_score_gemma":0.014075619,"teacher_disagreement_score":0.01768963,"about_ca_system_score_codex":0.0006145498,"about_ca_system_score_gemma":0.0005570865,"threshold_uncertainty_score":0.035173357},"labels":[],"label_agreement":null},{"id":"W3159284201","doi":"10.24963/ijcai.2021/60","title":"Reducing Bus Bunching with Asynchronous Multi-Agent Reinforcement Learning","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Natural Science Foundation of China","keywords":"Reinforcement learning; Computer science; Asynchronous communication; Artificial neural network; Local bus; Distributed computing; Reliability (semiconductor); Control bus; System bus; Computer network; Artificial intelligence","score_opus":0.018076509116372135,"score_gpt":0.23714334595990494,"score_spread":0.21906683684353281,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3159284201","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07130001,0.00025864298,0.92430073,0.0002659835,0.00006556348,0.00005193546,0.00003915889,0.00053191726,0.00318608],"genre_scores_gemma":[0.979456,0.000056517594,0.019069338,0.000064669584,0.000022258893,0.000043902757,0.00003607198,0.000028611365,0.0012225405],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996728,0.00010791311,0.000013589148,0.00007642479,0.00006583662,0.00006353094],"domain_scores_gemma":[0.99877495,0.0006953211,0.00016886847,0.00007094271,0.00020171129,0.00008827717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010862827,0.0008312481,0.0007955487,0.00030652055,0.00034932335,0.00053228356,0.0010021625,0.0007299807,0.0014838319],"category_scores_gemma":[0.0028913622,0.00039384843,0.00038222084,0.00021227301,0.0006551507,0.00079757767,0.0008632167,0.0011051807,0.00019891096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032777796,0.00002481251,0.0003493022,0.000016026946,0.000012272522,0.000023186836,0.000014465999,0.989702,0.00041650122,0.0016671263,0.00023056925,0.007511006],"study_design_scores_gemma":[0.0000039435527,0.0000078283365,0.000028322886,8.1770816e-7,0.0000015100634,0.0000013556532,0.0000010399875,0.99942183,0.000057998957,0.00043357722,0.000040969462,8.9488515e-7],"about_ca_topic_score_codex":0.008672058,"about_ca_topic_score_gemma":0.0068262015,"teacher_disagreement_score":0.008672058,"about_ca_system_score_codex":0.00077651197,"about_ca_system_score_gemma":0.0009280899,"threshold_uncertainty_score":0.017243147},"labels":[],"label_agreement":null},{"id":"W3160709508","doi":"","title":"Regulation and competition in the taxi industry in Vancouver","year":2019,"lang":"en","type":"article","venue":"Munich Personal RePEc Archive (Munich University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Competition (biology); Externality; Industrial organization; Business; Economics; Microeconomics","score_opus":0.007268073834050759,"score_gpt":0.1793339440005012,"score_spread":0.17206587016645045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3160709508","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8210135,0.0014407207,0.0004922997,0.004375294,0.000039384235,0.000031980857,0.00023143848,0.000014684695,0.17236067],"genre_scores_gemma":[0.9659958,0.0007612955,0.00017342082,0.00028862385,0.0000054034663,0.000008710425,0.000094377036,0.0000048646434,0.032667432],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9988856,0.00012497124,0.00002166001,0.00010439297,0.00037430009,0.0004891664],"domain_scores_gemma":[0.9989801,0.00012753007,0.000113375136,0.00003093919,0.000545584,0.00020243594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038666467,0.00008593393,0.00017069625,0.0008803759,0.005831053,0.0045907334,0.00057015725,0.00086618646,0.0041538114],"category_scores_gemma":[0.0016284528,0.00019274506,0.00013885919,0.00222852,0.002414161,0.00038727725,0.000985372,0.0010423805,0.00030219654],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040586904,0.00036974665,0.24280903,0.00021505925,0.00008097626,0.0028321461,0.040924016,0.015142225,0.008454623,0.4834655,0.03785504,0.16744576],"study_design_scores_gemma":[0.00006963441,0.00013403043,0.5769236,0.00031140042,0.000054878074,0.00042997158,0.048473366,0.011021736,0.0020730342,0.019177917,0.34115094,0.00017955755],"about_ca_topic_score_codex":0.9588757,"about_ca_topic_score_gemma":0.9803765,"teacher_disagreement_score":0.043862592,"about_ca_system_score_codex":0.043862592,"about_ca_system_score_gemma":0.022482557,"threshold_uncertainty_score":0.3182469},"labels":[],"label_agreement":null},{"id":"W3163100035","doi":"10.1016/j.tra.2021.04.020","title":"A discrete choice experiment on consumer’s willingness-to-pay for vehicle automation in the Greater Toronto Area","year":2021,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Willingness to pay; Automation; Discrete choice; Transport engineering; Business; Economics; Marketing; Engineering; Advertising; Microeconomics; Econometrics","score_opus":0.12462602091582863,"score_gpt":0.43693472030298425,"score_spread":0.3123086993871556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163100035","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99826604,0.000012629008,0.0000821665,0.00010768104,0.0000038243834,0.000056660258,0.00007031378,0.0000019068949,0.0013988981],"genre_scores_gemma":[0.99801195,0.000017506241,0.000214952,0.000040559004,0.0000031650845,0.00006122452,0.000075864875,0.0000010241625,0.0015737102],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988932,0.00059172744,0.000033036387,0.00014374952,0.00012748505,0.00021086351],"domain_scores_gemma":[0.9927608,0.00507991,0.0005982204,0.00032233523,0.0004586671,0.0007799981],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015911578,0.00034574416,0.0003921182,0.00028111486,0.0020667885,0.0013816067,0.00068340276,0.0010733078,0.008738096],"category_scores_gemma":[0.005140938,0.0003380537,0.00043161673,0.0004987115,0.0014683343,0.0007092962,0.0005287535,0.00091440754,0.000348516],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.08497892,0.038411744,0.6483331,0.00081469957,0.0011499344,0.0033249774,0.06673086,0.03184164,0.045468815,0.02204391,0.01279972,0.044101663],"study_design_scores_gemma":[0.0046235695,0.009528108,0.92150474,0.00006760646,0.00032756716,0.00008846376,0.024915138,0.025048792,0.003312104,0.0017844974,0.008602287,0.00019704523],"about_ca_topic_score_codex":0.80576104,"about_ca_topic_score_gemma":0.85706,"teacher_disagreement_score":0.19423896,"about_ca_system_score_codex":0.014470126,"about_ca_system_score_gemma":0.0059633492,"threshold_uncertainty_score":0.39076573},"labels":[],"label_agreement":null},{"id":"W3164694654","doi":"10.1155/2021/5515909","title":"Optimization of Rider Scheduling for a Food Delivery Service in O2O Business","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Computer science; Scheduling (production processes); Service provider; Operations research; Integer programming; Service (business); Marketing; Operations management; Business; Engineering; Algorithm","score_opus":0.012617569832034718,"score_gpt":0.23296614695188167,"score_spread":0.22034857711984696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3164694654","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28881577,0.0015273672,0.68613946,0.0011328812,0.00019960033,0.00061278994,0.00073796196,0.0005395828,0.020294681],"genre_scores_gemma":[0.95702016,0.00046534507,0.036398705,0.000111034155,0.00002796214,0.00017904825,0.00020818289,0.00008422073,0.0055052927],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923706,0.0002496093,0.000024537005,0.00018494471,0.00009325982,0.00021058657],"domain_scores_gemma":[0.9991179,0.0004879282,0.00011279123,0.000031380758,0.00009795875,0.00015212077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011226566,0.0015621464,0.0017099442,0.00060454797,0.00079632003,0.0018228021,0.0014866791,0.0016068836,0.004969007],"category_scores_gemma":[0.0020917293,0.00093612535,0.0010568121,0.00075030787,0.00067773013,0.0013643184,0.0010452076,0.0012000089,0.0004418839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014766584,0.00008050564,0.00048438035,0.00007309765,0.000024617852,0.00007337417,0.000027985476,0.98962003,0.00088424515,0.0019368067,0.00062705454,0.00602026],"study_design_scores_gemma":[0.000013246382,0.00006386436,0.00020253343,0.0000041295657,0.000010396341,0.000009648434,0.000033765682,0.99855787,0.000151341,0.000644213,0.0003037755,0.000005268383],"about_ca_topic_score_codex":0.02015351,"about_ca_topic_score_gemma":0.012845589,"teacher_disagreement_score":0.02015351,"about_ca_system_score_codex":0.0018914497,"about_ca_system_score_gemma":0.0021021974,"threshold_uncertainty_score":0.04007244},"labels":[],"label_agreement":null},{"id":"W3167838610","doi":"10.4230/lipics.isaac.2021.39","title":"Multimodal Transportation with Ridesharing of Personal Vehicles","year":2021,"lang":"en","type":"preprint","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Public transport; Transport engineering; Transit (satellite); Occupancy; Travel behavior; Travel time; Population; Transit system; Computer science; Engineering","score_opus":0.012633370514550827,"score_gpt":0.22722743999134454,"score_spread":0.21459406947679371,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3167838610","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17231525,0.00052178855,0.81593615,0.00023142571,0.00007350735,0.0001302229,0.0004148364,0.0026767664,0.0077000237],"genre_scores_gemma":[0.9194552,0.00020643984,0.07484088,0.000042768945,0.0000441576,0.000051160783,0.0004287672,0.000063293635,0.004867392],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993573,0.0001571896,0.000028950508,0.00023350996,0.000115976436,0.00010705751],"domain_scores_gemma":[0.999556,0.00008001504,0.0000488408,0.00018928987,0.000079570935,0.000046198253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042403268,0.00064874603,0.0009509319,0.0004396298,0.000953588,0.0011793594,0.0012482449,0.00074489054,0.0043302993],"category_scores_gemma":[0.0015649295,0.00028293495,0.0008880795,0.0010679364,0.00064229633,0.001263356,0.0013996289,0.0006749462,0.0009369659],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019749119,0.00013511057,0.004175978,0.00012665089,0.00008139244,0.0002811095,0.00022487839,0.7673522,0.010593711,0.0080967145,0.0027633633,0.2059714],"study_design_scores_gemma":[0.000010608872,0.00009783157,0.0014693866,0.0000081153075,0.000030697087,0.00013193295,0.00006175069,0.9881776,0.0027197879,0.0037071449,0.003564414,0.000020766649],"about_ca_topic_score_codex":0.020137787,"about_ca_topic_score_gemma":0.020674089,"teacher_disagreement_score":0.020137787,"about_ca_system_score_codex":0.0009898131,"about_ca_system_score_gemma":0.000919181,"threshold_uncertainty_score":0.04004115},"labels":[],"label_agreement":null},{"id":"W3169160774","doi":"10.1155/2021/6627660","title":"Incentives for Ridesharing: A Case Study of Welfare and Traffic Congestion","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Traffic congestion; Incentive; Subsidy; Congestion pricing; Mode choice; Transport engineering; Computer science; Business; Public transport; Economics; Microeconomics; Engineering","score_opus":0.014413991125292331,"score_gpt":0.26503066424888316,"score_spread":0.2506166731235908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3169160774","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96213347,0.00023956735,0.019400446,0.0018103605,0.000034483473,0.00023355559,0.00043414478,0.000067637484,0.015646243],"genre_scores_gemma":[0.9938792,0.000110404195,0.0041856105,0.00005671183,0.000010066475,0.000072979754,0.000070344024,0.000010692413,0.001603927],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9981055,0.0012671322,0.000038190472,0.00013643393,0.00014859306,0.0003040592],"domain_scores_gemma":[0.9933209,0.0049868436,0.00042353556,0.00031650744,0.0004216316,0.00053049024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002571318,0.0006950138,0.0007144096,0.00084559823,0.0015785198,0.0016143973,0.0015236354,0.002674233,0.0039025557],"category_scores_gemma":[0.006784802,0.00040556045,0.0011757761,0.0013294664,0.0017100533,0.0022554584,0.0015594943,0.0021261363,0.00018920093],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005754349,0.0015607127,0.022855433,0.00018510004,0.00015360078,0.0033877292,0.0010089426,0.8709396,0.0016086441,0.0818894,0.0038694765,0.0119659025],"study_design_scores_gemma":[0.00024901563,0.00042169567,0.006552457,0.000035725287,0.00006827846,0.00028707428,0.002399425,0.9672377,0.0008988439,0.01800251,0.00378192,0.000065349646],"about_ca_topic_score_codex":0.02897374,"about_ca_topic_score_gemma":0.02836314,"teacher_disagreement_score":0.02897374,"about_ca_system_score_codex":0.0034699768,"about_ca_system_score_gemma":0.0015679209,"threshold_uncertainty_score":0.057610154},"labels":[],"label_agreement":null},{"id":"W3172646104","doi":"10.1155/2021/9950834","title":"Integrated Optimization Strategy for Sustainable Shared Designated Driver Ferry Vehicle Scheduling","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Schedule; Tabu search; Scheduling (production processes); Computer science; Residual; Mathematical optimization; Energy consumption; Operations research; Transport engineering; Real-time computing; Simulation; Engineering; Algorithm","score_opus":0.016229942296912794,"score_gpt":0.25211945178206313,"score_spread":0.23588950948515033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3172646104","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04635292,0.00018600751,0.9488213,0.00008413003,0.000026658288,0.00005975301,0.00004304102,0.00020858414,0.004217503],"genre_scores_gemma":[0.9384681,0.0001441512,0.057968847,0.000033057026,0.000013782059,0.00009439685,0.000094645286,0.000041896335,0.0031412232],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957806,0.000087273744,0.000014396837,0.000091175745,0.00011502009,0.000114082235],"domain_scores_gemma":[0.999843,0.000043734708,0.0000334213,0.00001343673,0.00004475682,0.00002165027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005773049,0.0008219081,0.0007769761,0.00048621788,0.0004019672,0.0007856034,0.0009742731,0.00054612575,0.0015722937],"category_scores_gemma":[0.00071887055,0.0003789674,0.0005683865,0.00062638486,0.0003203456,0.00081926276,0.0008658857,0.0005737582,0.00016650316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002875415,0.000022829941,0.00020664089,0.000016078258,0.000014886631,0.00002466444,0.000021034977,0.9840004,0.0010195427,0.0027681252,0.00026601218,0.01161111],"study_design_scores_gemma":[0.000004905743,0.00002545747,0.00008863467,0.0000013084995,0.0000055545743,0.0000056706085,0.000009851941,0.9983872,0.00026113712,0.00096118153,0.00024652906,0.0000025079776],"about_ca_topic_score_codex":0.009050593,"about_ca_topic_score_gemma":0.0062728114,"teacher_disagreement_score":0.009050593,"about_ca_system_score_codex":0.0009919215,"about_ca_system_score_gemma":0.0016683057,"threshold_uncertainty_score":0.017995834},"labels":[],"label_agreement":null},{"id":"W3174320929","doi":"10.37394/23201.2021.20.13","title":"A Multicriteria, Bat Algorithm Approach for Computing the Range Limited Routing Problem for Electric Trucks","year":2021,"lang":"en","type":"article","venue":"WSEAS TRANSACTIONS ON CIRCUITS AND SYSTEMS","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Truck; Computer science; Transshipment (information security); Vehicle routing problem; Process (computing); Range (aeronautics); Metaheuristic; Sustainability; Analytic hierarchy process; Operations research; Routing (electronic design automation); Transport engineering; Algorithm; Engineering; Automotive engineering","score_opus":0.02571538195576123,"score_gpt":0.23529567933681858,"score_spread":0.20958029738105735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174320929","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027235083,0.00035014754,0.9664396,0.0003283563,0.000052802796,0.00008582011,0.000060435796,0.0003997613,0.0050479225],"genre_scores_gemma":[0.32376894,0.00030846943,0.67116296,0.00016958015,0.000038945036,0.00033590657,0.00019741477,0.00010742636,0.0039104144],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973875,0.00011084211,0.000013272903,0.000047094327,0.000054782824,0.00003526092],"domain_scores_gemma":[0.99950564,0.0003079498,0.000042308162,0.000016975386,0.00009470711,0.000032400767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007233101,0.00080073194,0.0007713631,0.0006705086,0.00059908605,0.0010651362,0.0010880169,0.0012711745,0.0031008448],"category_scores_gemma":[0.0017240496,0.00048261025,0.00066349906,0.00084602466,0.00049597706,0.00083631545,0.00073905755,0.00094586145,0.0004530097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036669404,0.000030527543,0.00024696824,0.00003985132,0.000016404732,0.00003727145,0.00003367548,0.9715949,0.0006758478,0.004019162,0.0006714785,0.022597149],"study_design_scores_gemma":[0.0000051292113,0.00001251072,0.000023758956,0.0000026772168,0.0000018830916,0.000006841085,0.000007818078,0.9988092,0.0000810185,0.00084334984,0.00020399364,0.0000017943139],"about_ca_topic_score_codex":0.0079738,"about_ca_topic_score_gemma":0.010776792,"teacher_disagreement_score":0.0079738,"about_ca_system_score_codex":0.0007059244,"about_ca_system_score_gemma":0.0014757933,"threshold_uncertainty_score":0.015854776},"labels":[],"label_agreement":null},{"id":"W3174884755","doi":"10.1609/aaai.v35i13.17424","title":"A Complexity-theoretic Analysis of Green Pickup-and-Delivery Problems","year":2021,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pickup; Heuristics; Computer science; Range (aeronautics); Mathematical optimization; Vehicle routing problem; Computational complexity theory; Routing (electronic design automation); Mathematics; Algorithm; Engineering; Artificial intelligence","score_opus":0.08345310543386872,"score_gpt":0.2718103838468567,"score_spread":0.18835727841298797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174884755","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06529591,0.003315757,0.84389096,0.011970915,0.0002918594,0.00027247492,0.0013016283,0.00028857362,0.07337179],"genre_scores_gemma":[0.80900025,0.004425987,0.15670158,0.0015956354,0.0013554735,0.0006443674,0.0016598877,0.00031388688,0.024302848],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976954,0.00068692624,0.000084389845,0.000413674,0.0007500139,0.00036956414],"domain_scores_gemma":[0.9916011,0.0066445954,0.00044128284,0.00047190604,0.00047505964,0.00036603297],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019184904,0.0012993847,0.0010632718,0.0016117042,0.0013637085,0.0039625806,0.0022635271,0.0016678292,0.0065765153],"category_scores_gemma":[0.011158447,0.00063348934,0.0016835605,0.002073792,0.0028831542,0.006714894,0.0025026451,0.0050436193,0.0007501453],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000110024266,0.0001297068,0.0008359416,0.00034447716,0.00006043967,0.00016269188,0.00029198296,0.19878934,0.0015904192,0.766159,0.010689821,0.02083625],"study_design_scores_gemma":[0.000023375394,0.000035959925,0.0005275707,0.00003734661,0.00002419255,0.000102984326,0.00011262621,0.40105227,0.0005342166,0.5894862,0.0080412915,0.000021889107],"about_ca_topic_score_codex":0.0031661445,"about_ca_topic_score_gemma":0.0020116034,"teacher_disagreement_score":0.0065765153,"about_ca_system_score_codex":0.004324487,"about_ca_system_score_gemma":0.001800692,"threshold_uncertainty_score":0.03137648},"labels":[],"label_agreement":null},{"id":"W3175175630","doi":"10.1155/2021/6677010","title":"Studying the Simultaneous Effect of Autonomous Vehicles and Distracted Driving on Safety at Unsignalized Intersections","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"VisSim; Distraction; Microsimulation; Distracted driving; Simulation; Transport engineering; Poison control; Collision; Computer science; Driving simulator; Engineering; Automotive engineering; Computer security","score_opus":0.005745265899368917,"score_gpt":0.2326335908100016,"score_spread":0.22688832491063268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175175630","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99508506,0.0001092766,0.0040600235,0.000019608739,0.0000059423282,0.00001325993,0.000038711503,0.000016996883,0.0006510426],"genre_scores_gemma":[0.99898154,0.00005979874,0.0008012475,0.0000039664624,0.0000013975848,0.0000059371328,0.000026253232,0.0000013721788,0.000118330616],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918646,0.00029712933,0.00003765752,0.00010302433,0.00023974536,0.00013591952],"domain_scores_gemma":[0.99558026,0.0028855347,0.0005569102,0.00020307934,0.0005987368,0.00017545091],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007046218,0.00063577417,0.0002911368,0.00067863107,0.0002146289,0.00060736726,0.00041954088,0.00047526025,0.0007477115],"category_scores_gemma":[0.0037706026,0.0002398963,0.0006304489,0.00033827857,0.00035015424,0.0005397224,0.00064079015,0.0003154772,0.000086721484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012530776,0.0006642079,0.09696316,0.00029593694,0.00036328036,0.0006076661,0.00038971507,0.8490389,0.023767276,0.0012579635,0.00020374841,0.025195004],"study_design_scores_gemma":[0.00005328143,0.003444865,0.061462995,0.000031522388,0.00028115136,0.00023939527,0.00060738024,0.9080133,0.024388146,0.0009871538,0.0004352934,0.000055667675],"about_ca_topic_score_codex":0.0053083617,"about_ca_topic_score_gemma":0.004915504,"teacher_disagreement_score":0.0053083617,"about_ca_system_score_codex":0.0006114204,"about_ca_system_score_gemma":0.0007338567,"threshold_uncertainty_score":0.01055491},"labels":[],"label_agreement":null},{"id":"W3175185496","doi":"10.1186/s12889-021-12066-z","title":"Differential impacts of ridesharing on alcohol-related crashes by socioeconomic municipalities: rate of technology adoption matters","year":2021,"lang":"en","type":"review","venue":"BMC Public Health","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Socioeconomic status; Environmental health; Poison control; Medicine; Biostatistics; Injury prevention; Demography; Confidence interval; Geography; Suicide prevention; Human factors and ergonomics; Occupational safety and health; Socioeconomics; Epidemiology; Economics; Population; Sociology","score_opus":0.06012343184561875,"score_gpt":0.3324067984294326,"score_spread":0.27228336658381386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175185496","genre_codex":"empirical","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8208766,0.15552591,0.005030111,0.0066987956,0.00041342565,0.0003134938,0.0033922552,0.00007378013,0.0076755243],"genre_scores_gemma":[0.98596895,0.011629629,0.00082329643,0.00057371054,0.00010277847,0.00008354236,0.00044339304,0.000020848356,0.00035387548],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9920082,0.004500014,0.00092409685,0.001242365,0.0007992288,0.0005261513],"domain_scores_gemma":[0.9657251,0.023077944,0.007151035,0.0020920453,0.0014319178,0.0005219823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009537302,0.0005128823,0.001311766,0.001613198,0.0004950827,0.0023220167,0.0012061243,0.0009803463,0.0033400233],"category_scores_gemma":[0.03579352,0.0004349623,0.006924081,0.0026955071,0.0012879346,0.0016894388,0.0019844368,0.0013388825,0.00023502106],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012973762,0.00009206339,0.9218026,0.0071966317,0.022172537,0.00029063545,0.0010249763,0.0009928945,0.00035251948,0.0012742892,0.0010377598,0.042465776],"study_design_scores_gemma":[0.00018216424,0.00046614744,0.95745873,0.0042690635,0.025383122,0.00025565436,0.002058879,0.001241885,0.00053030596,0.0020486463,0.006058647,0.00004673611],"about_ca_topic_score_codex":0.03007378,"about_ca_topic_score_gemma":0.025469309,"teacher_disagreement_score":0.03007378,"about_ca_system_score_codex":0.0011133299,"about_ca_system_score_gemma":0.0018383038,"threshold_uncertainty_score":0.059797466},"labels":[],"label_agreement":null},{"id":"W3176450486","doi":"10.1155/2021/6688803","title":"Optimal Tradable Credit Scheme Design with Recommended Credit Price","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Government of Jiangsu Province; National Natural Science Foundation of China","keywords":"Economics; Scheme (mathematics); Value (mathematics); Credit valuation adjustment; Microeconomics; Order (exchange); Computer science; Econometrics; Credit risk; Actuarial science; Finance; Credit reference; Mathematics","score_opus":0.016175196197545275,"score_gpt":0.23495505267400396,"score_spread":0.2187798564764587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3176450486","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09415157,0.00035187206,0.893696,0.0007223224,0.0000979783,0.00023935798,0.00017433903,0.00019406108,0.010372537],"genre_scores_gemma":[0.9509516,0.00017387244,0.04570101,0.00006231034,0.000014601068,0.0001229575,0.00007194084,0.00002827499,0.0028734996],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988116,0.0004470317,0.000059290087,0.0002583599,0.00019814297,0.0002256498],"domain_scores_gemma":[0.9979944,0.00091406197,0.00032213127,0.0001567489,0.00041498235,0.00019770596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016400699,0.0009147875,0.0011176373,0.0005796982,0.00058756454,0.0020761103,0.0018806959,0.002085487,0.0061412896],"category_scores_gemma":[0.0064890105,0.0004912335,0.0007002331,0.00089144346,0.0009761606,0.0027096558,0.001341947,0.0015696895,0.00039072713],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018774722,0.000089562236,0.0009920914,0.00014002243,0.000026811307,0.0001316403,0.000115202376,0.935391,0.002158129,0.036283676,0.0011684041,0.023315618],"study_design_scores_gemma":[0.000025381347,0.000066478555,0.00016143423,0.000010305972,0.00001206714,0.000022193724,0.000038402726,0.9879004,0.0003305495,0.01081094,0.0006116493,0.000010356496],"about_ca_topic_score_codex":0.0063484134,"about_ca_topic_score_gemma":0.00410115,"teacher_disagreement_score":0.0063484134,"about_ca_system_score_codex":0.0018657794,"about_ca_system_score_gemma":0.0019387743,"threshold_uncertainty_score":0.020544589},"labels":[],"label_agreement":null},{"id":"W3176874956","doi":"10.34989/swp-2021-28","title":"Consumer Cash Withdrawal Behaviour: Branch Networks and Online Financial Innovation","year":2021,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Cash; TRIPS architecture; Business; Payment; Work (physics); Finance; Economics; Engineering","score_opus":0.021110732118079956,"score_gpt":0.2868774090203302,"score_spread":0.26576667690225025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3176874956","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98809344,0.0002771197,0.0010267898,0.0013355145,0.000008297445,0.000026539594,0.000299463,0.000016365108,0.008916622],"genre_scores_gemma":[0.9980071,0.00013417912,0.0001689994,0.00004585001,0.000009180118,0.000009192023,0.00009669722,0.0000021274575,0.0015267635],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996462,0.00013836962,0.000014656707,0.000056856403,0.000058577145,0.000085246305],"domain_scores_gemma":[0.992763,0.0036849908,0.0023512547,0.00022490682,0.00035189264,0.0006239493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008237181,0.0001810281,0.0002523895,0.00060179865,0.00043159304,0.0016304718,0.00042591547,0.0009666419,0.011070422],"category_scores_gemma":[0.005688652,0.00012262874,0.00043700726,0.0010198127,0.0007039151,0.0015166259,0.00077225885,0.00095374114,0.00058775244],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005022859,0.00089628005,0.92284894,0.00009436439,0.0001607849,0.00040543533,0.0020636932,0.008991369,0.00066215487,0.014695564,0.0037070396,0.04497207],"study_design_scores_gemma":[0.00006446628,0.0002663441,0.9241797,0.00008631256,0.00016998812,0.00017095446,0.0036875438,0.055001058,0.00041774288,0.010493696,0.0054033147,0.000058904865],"about_ca_topic_score_codex":0.034223884,"about_ca_topic_score_gemma":0.028559513,"teacher_disagreement_score":0.034223884,"about_ca_system_score_codex":0.0022096594,"about_ca_system_score_gemma":0.0006102174,"threshold_uncertainty_score":0.06804937},"labels":[],"label_agreement":null},{"id":"W3177337900","doi":"10.1504/ijal.2021.10039184","title":"Feasibility of autonomous vehicles in Canada: a literature review","year":2021,"lang":"en","type":"review","venue":"International Journal of Automation and Logistics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Aeronautics; History; Engineering","score_opus":0.04285053521753142,"score_gpt":0.32741265936484093,"score_spread":0.2845621241473095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3177337900","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006979314,0.9970391,0.00007664623,0.00053785415,0.00009819623,0.0000105439285,0.00018036591,0.0000025222835,0.0013569074],"genre_scores_gemma":[0.0043500247,0.9950421,0.00016090917,0.00016028844,0.000043985678,0.00000553675,0.000078394325,0.0000017908071,0.00015696677],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.9979684,0.00021452158,0.00027846108,0.00026122652,0.0011033167,0.00017403779],"domain_scores_gemma":[0.9812775,0.011208682,0.0013693689,0.00014904485,0.005616227,0.00037919043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036500164,0.00090273214,0.0018061126,0.010332208,0.0012307931,0.0050455914,0.0020429592,0.0017849308,0.0054959375],"category_scores_gemma":[0.012413088,0.0006364156,0.0014103645,0.018533349,0.001755388,0.0023738625,0.0010932201,0.001430786,0.00041532033],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020909641,0.00010138838,0.008031841,0.16990103,0.00065194827,0.000537656,0.0010088226,0.0015723578,0.00038804548,0.009286861,0.031790365,0.7765205],"study_design_scores_gemma":[0.00003391837,0.00015447494,0.033880312,0.20337617,0.0034961365,0.001153784,0.004794535,0.00071481365,0.0007024468,0.0031303752,0.74837476,0.00018828153],"about_ca_topic_score_codex":0.551666,"about_ca_topic_score_gemma":0.68984336,"teacher_disagreement_score":0.44833398,"about_ca_system_score_codex":0.013749484,"about_ca_system_score_gemma":0.058112852,"threshold_uncertainty_score":0.90194863},"labels":[],"label_agreement":null},{"id":"W3177588140","doi":"10.1109/mdm52706.2021.00045","title":"Transitive Halifax: An Activity-Based Search Engine for Bus Routes","year":2021,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Memorial University of Newfoundland; Dalhousie University","funders":"","keywords":"Transitive relation; Computer science; Service (business); Search engine; Interface (matter); World Wide Web; Mathematics; Operating system; Business","score_opus":0.026581354605886728,"score_gpt":0.2708934056641829,"score_spread":0.24431205105829618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3177588140","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.087593436,0.0043586027,0.34742543,0.00072494854,0.00027997117,0.001434755,0.08994091,0.40522677,0.06301529],"genre_scores_gemma":[0.3675583,0.002878959,0.40024617,0.0007706971,0.00011048336,0.00096685323,0.17486194,0.006700976,0.045905758],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997049,0.000054283068,0.0000369645,0.000057530317,0.00011079524,0.000035431978],"domain_scores_gemma":[0.99944586,0.00028981542,0.000040753624,0.00006328819,0.00009927854,0.00006099161],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038650734,0.0011324865,0.00087617664,0.0028614346,0.00038651563,0.0011694774,0.0012542575,0.0008205172,0.024768963],"category_scores_gemma":[0.0020458146,0.00032152573,0.0006767685,0.0015716599,0.00018588408,0.002040109,0.0012687214,0.00048138006,0.009294496],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0039537027,0.0007801758,0.011208543,0.0044163982,0.0003962938,0.0013769824,0.0013104619,0.0138616385,0.034901395,0.019890014,0.38128498,0.5266195],"study_design_scores_gemma":[0.00095143355,0.0010010354,0.015592428,0.00060711236,0.0003691257,0.0019901758,0.0014248181,0.41296086,0.048979204,0.023531297,0.49220052,0.0003919928],"about_ca_topic_score_codex":0.008376036,"about_ca_topic_score_gemma":0.016780643,"teacher_disagreement_score":0.99162394,"about_ca_system_score_codex":0.00051478756,"about_ca_system_score_gemma":0.0005798101,"threshold_uncertainty_score":0.08286047},"labels":[],"label_agreement":null},{"id":"W3178554437","doi":"10.1155/2021/6654254","title":"Autonomous Bus Fleet Control Using Multiagent Reinforcement Learning","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Taiwan University; Ministry of Science and Technology, Taiwan","keywords":"Reinforcement learning; Computer science; Public transport; Domain (mathematical analysis); Control (management); Multi-agent system; Intelligent transportation system; Autonomous agent; Q-learning; Real-time computing; Distributed computing; Artificial intelligence; Transport engineering; Engineering","score_opus":0.011395873317954396,"score_gpt":0.24596474984558472,"score_spread":0.23456887652763034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3178554437","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.090238005,0.00025819422,0.9055764,0.00018264519,0.00005811966,0.00007695815,0.00003145854,0.00041161533,0.0031667124],"genre_scores_gemma":[0.98238933,0.00005081823,0.016667249,0.000029736635,0.000010970274,0.00005535153,0.000024705116,0.000010063311,0.0007617945],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996904,0.000094007635,0.00001598109,0.00006902721,0.00007290797,0.000057724585],"domain_scores_gemma":[0.99919087,0.00040878693,0.000148998,0.000039142902,0.00014757014,0.00006459632],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000828659,0.0006670436,0.0007713124,0.00034638005,0.00041164574,0.000567779,0.00081493374,0.0006575293,0.0008378616],"category_scores_gemma":[0.0016004819,0.00030551784,0.00040715354,0.00023374059,0.0006217589,0.0005283152,0.00064363074,0.0007952698,0.000109154746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020612637,0.000020923826,0.00024413105,0.000010934319,0.000012172607,0.000022822507,0.000011544692,0.99328583,0.00046260358,0.00089281326,0.000086926986,0.004928656],"study_design_scores_gemma":[0.0000041417366,0.000011039543,0.000027840626,6.3417286e-7,0.0000012003218,0.0000016576498,0.0000011213428,0.9996648,0.000063380954,0.00019066663,0.000032482567,0.0000010925178],"about_ca_topic_score_codex":0.012113047,"about_ca_topic_score_gemma":0.006658345,"teacher_disagreement_score":0.012113047,"about_ca_system_score_codex":0.000720816,"about_ca_system_score_gemma":0.0009872904,"threshold_uncertainty_score":0.024085045},"labels":[],"label_agreement":null},{"id":"W3179040299","doi":"10.1155/2021/5577500","title":"SAV Operations on a Bus Line Corridor: Travel Demand, Service Frequency, and Vehicle Size","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Transport engineering; Service (business); Dwell time; Business; Computer science; Engineering; Public transport; Marketing","score_opus":0.009709207867467694,"score_gpt":0.2343145101155001,"score_spread":0.2246053022480324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3179040299","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938455,0.00003481493,0.0034638743,0.00003785726,0.0000039143683,0.000010944143,0.00028676994,0.000041567637,0.0022746234],"genre_scores_gemma":[0.9985222,0.000029248988,0.0006000498,0.0000029415637,0.000001203958,0.0000086915115,0.00016453522,0.0000070332258,0.0006640613],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980694,0.00005018568,0.0000063873586,0.000035145757,0.000030939147,0.000070335795],"domain_scores_gemma":[0.9994362,0.0002211732,0.0001298489,0.000041663803,0.00009678149,0.00007431124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023349978,0.0004953029,0.0002255292,0.00034866392,0.00023798036,0.00061915815,0.00042537093,0.00032331224,0.0030389677],"category_scores_gemma":[0.0010344307,0.00018228925,0.00035154098,0.0005495355,0.0003146983,0.00080348237,0.00044412017,0.00029889992,0.00024054857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053299125,0.00029162667,0.05755461,0.000095929194,0.00008993838,0.00028681807,0.00014630245,0.9070398,0.018914185,0.0029273094,0.0007575359,0.011363044],"study_design_scores_gemma":[0.000024486664,0.0005114019,0.05568529,0.000014350022,0.00006610958,0.0001383587,0.0005644991,0.9330347,0.007423337,0.0009857079,0.0015129726,0.000038846254],"about_ca_topic_score_codex":0.020289898,"about_ca_topic_score_gemma":0.02584073,"teacher_disagreement_score":0.020289898,"about_ca_system_score_codex":0.0007567331,"about_ca_system_score_gemma":0.00054367667,"threshold_uncertainty_score":0.040343583},"labels":[],"label_agreement":null},{"id":"W3179310461","doi":"10.5267/j.msl.2021.6.001","title":"Human factors concern on autonomous vehicles’ safety, ethics and cost saving for the ridesharing industries","year":2021,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Purdue University","keywords":"Timeline; Liability; Business; Perception; Marketing; Transport engineering; Industrial organization; Computer science; Risk analysis (engineering); Engineering; Finance","score_opus":0.06591519910848238,"score_gpt":0.29595327005823174,"score_spread":0.23003807094974937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3179310461","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8457354,0.0010656938,0.0026527797,0.016909558,0.00014155904,0.00007596529,0.00008861673,0.00002837222,0.13330211],"genre_scores_gemma":[0.99427754,0.00028483302,0.000276664,0.0009112528,0.000021738178,0.000012560449,0.000017025952,0.0000038291423,0.00419454],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99634355,0.0016087852,0.0001322733,0.00022461254,0.0012525666,0.0004381478],"domain_scores_gemma":[0.9801671,0.008787709,0.0041656373,0.0006304768,0.00444465,0.0018044498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002200827,0.00015585762,0.0000947327,0.0006030213,0.002599277,0.004103404,0.00027331954,0.0007409436,0.009042167],"category_scores_gemma":[0.011685809,0.00008470985,0.00020062753,0.00048381728,0.0025782883,0.0013368871,0.0010158026,0.0009966722,0.0007373597],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010163298,0.0004235907,0.6393612,0.00039678565,0.00007611646,0.0014714058,0.09658938,0.0015370868,0.0027032201,0.044629388,0.02733805,0.18537228],"study_design_scores_gemma":[0.000011589612,0.0003858524,0.59113204,0.00041808758,0.00004745197,0.0012091976,0.2119021,0.0014664243,0.0018184007,0.014711891,0.17680344,0.00009346499],"about_ca_topic_score_codex":0.0142202135,"about_ca_topic_score_gemma":0.019060673,"teacher_disagreement_score":0.0142202135,"about_ca_system_score_codex":0.0035674316,"about_ca_system_score_gemma":0.0042588254,"threshold_uncertainty_score":0.03024906},"labels":[],"label_agreement":null},{"id":"W3179881929","doi":"10.3390/designs5030040","title":"Impact of Autonomous Vehicles on the Physical Infrastructure: Changes and Challenges","year":2021,"lang":"en","type":"article","venue":"Designs","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Truck; Transport engineering; Computer science; Risk analysis (engineering); Blocking (statistics); Business; Computer security; Engineering; Automotive engineering","score_opus":0.05025824623360127,"score_gpt":0.264254609853444,"score_spread":0.21399636361984276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3179881929","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5392556,0.055823624,0.11546512,0.039101053,0.0019635987,0.00013208845,0.0006391131,0.00040086813,0.24721888],"genre_scores_gemma":[0.9747628,0.01134075,0.0063204058,0.00056785,0.00024712243,0.00002414465,0.000097253775,0.000036168967,0.006603416],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986092,0.00033180125,0.000033378947,0.0001493288,0.00067923416,0.00019711138],"domain_scores_gemma":[0.9982704,0.0005682195,0.00023177784,0.00011831327,0.000636664,0.00017455462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007104753,0.00037656105,0.00027827546,0.0004565783,0.000773647,0.0022148252,0.0008535469,0.0011773794,0.0038260934],"category_scores_gemma":[0.0022208178,0.00023968915,0.0003212411,0.00046391686,0.0015497043,0.0030721873,0.0016830019,0.0011114997,0.00050651375],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016645475,0.00023980092,0.031610813,0.0012509706,0.00012967628,0.0020428947,0.0016565494,0.18187474,0.014181779,0.21876939,0.022537539,0.52553946],"study_design_scores_gemma":[0.000028139651,0.0010208292,0.06425786,0.0010528226,0.00017168278,0.0027835434,0.023273839,0.16913436,0.012282418,0.2251114,0.5006195,0.00026368225],"about_ca_topic_score_codex":0.0063226963,"about_ca_topic_score_gemma":0.005953112,"teacher_disagreement_score":0.0063226963,"about_ca_system_score_codex":0.0015316622,"about_ca_system_score_gemma":0.0011161184,"threshold_uncertainty_score":0.012799501},"labels":[],"label_agreement":null},{"id":"W3182108330","doi":"10.1155/2021/6577439","title":"Friend-Invitation Promotion Scheme Used in Electric Carsharing: Empirical Analysis and Policy Implications","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Renting; TRIPS architecture; Promotion (chess); Electric cars; Electric vehicle; Flexibility (engineering); Car ownership; Scheme (mathematics); Business; Transport engineering; Marketing; Travel behavior; Advertising; Computer science; Engineering; Public transport; Economics; Political science; Mathematics; Management; Law","score_opus":0.020483140679557935,"score_gpt":0.3092970000769443,"score_spread":0.28881385939738635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3182108330","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99556077,0.00010999293,0.00062331464,0.00043559674,0.0000120893665,0.00024229284,0.00008999091,0.0000056649237,0.0029203752],"genre_scores_gemma":[0.9979102,0.00015889977,0.00067410304,0.00005816296,0.000010598062,0.00017280661,0.000068434754,0.0000019502368,0.0009448194],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99107295,0.006219587,0.0003021663,0.00055621774,0.00077795907,0.0010710605],"domain_scores_gemma":[0.96324944,0.0252144,0.006311091,0.0012845234,0.0019827837,0.0019578203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010090758,0.00026100487,0.00031357398,0.000950388,0.0012843698,0.0015234649,0.0013043818,0.0009545243,0.0065203924],"category_scores_gemma":[0.028787998,0.00027722496,0.0005573181,0.0014753663,0.00092894974,0.002504678,0.0011378115,0.0013744746,0.0005432845],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010948133,0.008230744,0.87277734,0.0004423273,0.00014548082,0.0007248834,0.0125628505,0.0017353614,0.00076278317,0.009284775,0.002052453,0.090186104],"study_design_scores_gemma":[0.00013296992,0.0022667141,0.9005008,0.00032065436,0.00025974255,0.00026241137,0.07512629,0.010996755,0.0010418844,0.0012277897,0.00779941,0.000064661326],"about_ca_topic_score_codex":0.015337871,"about_ca_topic_score_gemma":0.013334424,"teacher_disagreement_score":0.015337871,"about_ca_system_score_codex":0.0022582135,"about_ca_system_score_gemma":0.0030604838,"threshold_uncertainty_score":0.053365648},"labels":[],"label_agreement":null},{"id":"W3183587152","doi":"10.1007/s11116-021-10215-2","title":"Eliminating barriers to nighttime activity participation: the case of on-demand transit in Belleville, Canada","year":2021,"lang":"en","type":"article","venue":"Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"The Scarborough Hospital; Environment and Climate Change Canada; University of Toronto","funders":"Social Sciences and Humanities Research Council; Social Sciences and Humanities Research Council of Canada; University of Toronto","keywords":"Service (business); Business; Investment (military); Level of service; Structural equation modeling; Transport engineering; Marketing; Computer science; Engineering","score_opus":0.009614120236577239,"score_gpt":0.23489439334068943,"score_spread":0.2252802731041122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183587152","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94693327,0.00036697276,0.0007910711,0.006894705,0.00005292386,0.00019986556,0.00028415132,0.000026122318,0.044450883],"genre_scores_gemma":[0.9830914,0.00023686727,0.00065196987,0.0005351133,0.0000097494085,0.000034797526,0.00012588505,0.000016195092,0.015298143],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99617344,0.0004006632,0.000027549577,0.0001223798,0.00024366118,0.0030323141],"domain_scores_gemma":[0.99709594,0.0004895667,0.000097644406,0.000066801986,0.00081969483,0.0014304433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012224226,0.00048601907,0.0006080858,0.0006636682,0.013318329,0.004940957,0.0032727756,0.0029006288,0.006528317],"category_scores_gemma":[0.002850262,0.00032982207,0.00063332036,0.0019402981,0.0028651978,0.0012062524,0.0026093693,0.0026245422,0.0002708913],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016607573,0.0036394985,0.36753255,0.00087501574,0.00042510542,0.031461336,0.11161684,0.049687613,0.005827625,0.21371032,0.08501301,0.1285503],"study_design_scores_gemma":[0.00029214905,0.00044590488,0.29900005,0.00043751972,0.00024267068,0.0010619524,0.56415665,0.024064757,0.0012196052,0.008379391,0.10048976,0.00020954204],"about_ca_topic_score_codex":0.99509466,"about_ca_topic_score_gemma":0.9986395,"teacher_disagreement_score":0.060166307,"about_ca_system_score_codex":0.060166307,"about_ca_system_score_gemma":0.101358235,"threshold_uncertainty_score":0.43653917},"labels":[],"label_agreement":null},{"id":"W3183899846","doi":"10.36939/cjur/vol30no1/art324","title":"Ride-hailing applications in Vancouver, Canada: Representation, local empowerment and resistance","year":2021,"lang":"en","type":"article","venue":"Canadian journal of urban research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Simon Fraser University","funders":"Global Affairs Canada","keywords":"Normative; Variety (cybernetics); Politics; Resistance (ecology); Government (linguistics); Representation (politics); Civil society; Empowerment; Subject (documents); Authorization; Public administration; Business; Political science; Political economy; Sociology; Law; Computer security","score_opus":0.024495016524907796,"score_gpt":0.28105220316564455,"score_spread":0.25655718664073673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183899846","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91913974,0.00091253885,0.00035641782,0.009075953,0.000048508984,0.000089962705,0.0001698261,0.000021260688,0.07018567],"genre_scores_gemma":[0.97902405,0.0006361854,0.0002065699,0.00059659785,0.000005815582,0.000022694674,0.000071741764,0.000012272468,0.01942398],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9972257,0.00043286776,0.00003538431,0.00019018438,0.0006063775,0.0015094441],"domain_scores_gemma":[0.9971909,0.000548349,0.00017071908,0.00008559419,0.0010516179,0.0009529686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013503418,0.0002684301,0.0003463964,0.0013367828,0.025129382,0.006809889,0.0016452842,0.0011207792,0.006466182],"category_scores_gemma":[0.0037067155,0.00033298723,0.00019851801,0.0034252082,0.007603998,0.0011686083,0.0041394704,0.002047777,0.00036452457],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027056716,0.00034967455,0.18439412,0.00028602273,0.00005268867,0.0045038266,0.55377054,0.00090696826,0.002192281,0.06436621,0.043875303,0.14503178],"study_design_scores_gemma":[0.000021719612,0.00004964524,0.13585389,0.00021435754,0.00002930813,0.00024369823,0.74885994,0.00085709005,0.000519771,0.002029803,0.11123993,0.00008084621],"about_ca_topic_score_codex":0.9962999,"about_ca_topic_score_gemma":0.99889874,"teacher_disagreement_score":0.12283245,"about_ca_system_score_codex":0.12283245,"about_ca_system_score_gemma":0.1307781,"threshold_uncertainty_score":0.8912159},"labels":[],"label_agreement":null},{"id":"W3185123191","doi":"10.1109/jiot.2022.3152139","title":"A Bilevel Programming Framework for Joint Edge Resource Management and Pricing","year":2022,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Arizona State University","keywords":"Computer science; Computation offloading; Mathematical optimization; Distributed computing; Bilevel optimization; Edge computing; Enhanced Data Rates for GSM Evolution; Service (business); Optimization problem; Operations research; Computer network; Artificial intelligence; Algorithm","score_opus":0.023071111135235058,"score_gpt":0.2461021750750926,"score_spread":0.22303106393985755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3185123191","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0041398345,0.00051687396,0.9871094,0.0005342701,0.00007266662,0.0000405871,0.00008943177,0.00008143298,0.0074153882],"genre_scores_gemma":[0.58430845,0.0021646551,0.3938444,0.00054966984,0.0002860592,0.0006907396,0.00044075106,0.00023923763,0.017475987],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985935,0.0006782454,0.0000474432,0.00019473092,0.00024543158,0.00024053971],"domain_scores_gemma":[0.9986247,0.0009022629,0.00010382784,0.00004555271,0.00020420975,0.00011950203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002566259,0.0016456767,0.002076065,0.00095312303,0.00086091954,0.0032823277,0.0019438361,0.0025111672,0.005825063],"category_scores_gemma":[0.0045204684,0.0009654159,0.0014179554,0.0018589275,0.0015305637,0.0022685155,0.0024456833,0.0035229784,0.0007002819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024966628,0.000047059246,0.00022636008,0.00008529279,0.00003345342,0.000085711916,0.000054868706,0.87794256,0.00020999271,0.11188499,0.0017279059,0.007676696],"study_design_scores_gemma":[0.000007995416,0.000012443433,0.00002896133,0.000010427074,0.0000054068687,0.000012577367,0.000021274089,0.9629422,0.000043950684,0.03584384,0.001064797,0.000006257309],"about_ca_topic_score_codex":0.0072086724,"about_ca_topic_score_gemma":0.006316432,"teacher_disagreement_score":0.0072086724,"about_ca_system_score_codex":0.0020009493,"about_ca_system_score_gemma":0.003394544,"threshold_uncertainty_score":0.019486785},"labels":[],"label_agreement":null},{"id":"W3185883273","doi":"","title":"Fighting for Fares: Uber and the Declining Market Price of Licensed Taxicabs","year":2021,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"License; Revenue; Value (mathematics); Business; Dividend; Economics; Incentive; Obsolescence; Economic rent; Transaction cost; Commerce; Monetary economics; Finance; Market economy; Marketing","score_opus":0.027753378349771186,"score_gpt":0.2985089147971622,"score_spread":0.270755536447391,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3185883273","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9826047,0.0003045173,0.0009018868,0.0019537976,0.00002116042,0.0000165195,0.0002146574,0.0000144675105,0.01396835],"genre_scores_gemma":[0.99781585,0.00012307885,0.000106820844,0.000088783876,0.000010392629,0.0000032169175,0.00007118347,0.000004400474,0.0017763898],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997178,0.00006559747,0.0000073556157,0.000051909003,0.000066781766,0.00009055154],"domain_scores_gemma":[0.9970535,0.0008764247,0.001178976,0.000115269184,0.000392591,0.00038323484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007339805,0.00017370837,0.00036306548,0.00039283454,0.0010724345,0.0039093774,0.0006434777,0.0012672559,0.011644029],"category_scores_gemma":[0.005064172,0.00018393112,0.00041534627,0.00053281046,0.0018087066,0.0024125162,0.00076877885,0.001941062,0.0006369973],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079348474,0.0012062289,0.74940735,0.00020556222,0.00029685203,0.002754412,0.005221047,0.08561973,0.0034351076,0.10018198,0.019156812,0.031721424],"study_design_scores_gemma":[0.00027865486,0.0007083915,0.65627015,0.00014793631,0.00020985183,0.00050112547,0.026028963,0.22733164,0.0023922892,0.04660407,0.039295323,0.00023155272],"about_ca_topic_score_codex":0.1313401,"about_ca_topic_score_gemma":0.18748745,"teacher_disagreement_score":0.1313401,"about_ca_system_score_codex":0.004238358,"about_ca_system_score_gemma":0.0012688913,"threshold_uncertainty_score":0.2611512},"labels":[],"label_agreement":null},{"id":"W3186927444","doi":"10.1111/cag.12705","title":"Governance matters: Regulating ride hailing platforms in Canada's largest city‐regions","year":2021,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Metropolitan area; Corporate governance; Unintended consequences; Subject (documents); Regional science; Public administration; Business; Political science; Economic geography; Sociology; Geography; Finance; Law","score_opus":0.0073624330039090925,"score_gpt":0.17302362254189954,"score_spread":0.16566118953799044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3186927444","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8217964,0.0014299942,0.0040813508,0.012643796,0.00008205847,0.00018799714,0.00064223906,0.000079468664,0.15905659],"genre_scores_gemma":[0.9923968,0.00035503044,0.00041815577,0.00036768906,0.0000049135037,0.000015586129,0.000091122594,0.000008589127,0.006342092],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.99702567,0.00028772184,0.000050411614,0.0002763932,0.0007203052,0.0016395578],"domain_scores_gemma":[0.9966979,0.00046717288,0.00038635425,0.00016636813,0.0013642316,0.0009179173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016691294,0.00020540743,0.0002253624,0.0009517632,0.00816657,0.005698378,0.0010976812,0.000830278,0.0024473043],"category_scores_gemma":[0.0046549775,0.00022084944,0.00034593357,0.002182647,0.004876445,0.00085076224,0.0022572489,0.0011412269,0.00016589873],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026679417,0.00018274407,0.36701998,0.00038601345,0.00018220999,0.0018385093,0.039231908,0.025888633,0.0059703034,0.40657058,0.03960518,0.11285721],"study_design_scores_gemma":[0.00006743578,0.00009898455,0.70377785,0.0003926259,0.00018893163,0.00020563624,0.07086456,0.010196906,0.0030465513,0.014493875,0.19648595,0.0001806802],"about_ca_topic_score_codex":0.99026895,"about_ca_topic_score_gemma":0.99640024,"teacher_disagreement_score":0.91463184,"about_ca_system_score_codex":0.08536815,"about_ca_system_score_gemma":0.11339024,"threshold_uncertainty_score":0.61939216},"labels":[],"label_agreement":null},{"id":"W3188586497","doi":"10.1109/tits.2021.3095765","title":"A Dynamic Ridesplitting Method With Potential Pick-Up Probability Based on GPS Trajectories","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Global Positioning System; Computer science; Telecommunications","score_opus":0.016303533324292765,"score_gpt":0.2504028060098083,"score_spread":0.23409927268551553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3188586497","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020403113,0.00047780853,0.97396153,0.00020577607,0.00008206764,0.00014570364,0.0004585352,0.0027980767,0.0014674743],"genre_scores_gemma":[0.42479604,0.0007097984,0.56338334,0.00022500551,0.00019272281,0.0004485619,0.0032396358,0.0005082014,0.006496658],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999151,0.00011245888,0.00006423267,0.00033780048,0.00021579515,0.00011874956],"domain_scores_gemma":[0.9990891,0.00033472548,0.00008179671,0.00011791504,0.00029358637,0.00008281995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089016143,0.0011257988,0.0017902931,0.0021691448,0.00079906796,0.0012436338,0.002900084,0.0011920808,0.004194212],"category_scores_gemma":[0.003162712,0.0008581876,0.0015019337,0.0025192832,0.000516387,0.0021550222,0.0013272417,0.0014151501,0.0013231195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034550714,0.00014213541,0.004394963,0.00019685616,0.000110717025,0.00013392097,0.0001524403,0.5382088,0.0037045297,0.0048246165,0.007853536,0.43993202],"study_design_scores_gemma":[0.000022134862,0.000021479987,0.00025389864,0.0000067276724,0.000014155845,0.000028336986,0.000019040854,0.9968688,0.00046808858,0.0011923101,0.0010937152,0.000011343819],"about_ca_topic_score_codex":0.023334354,"about_ca_topic_score_gemma":0.014296569,"teacher_disagreement_score":0.023334354,"about_ca_system_score_codex":0.0008995073,"about_ca_system_score_gemma":0.0024124645,"threshold_uncertainty_score":0.04639709},"labels":[],"label_agreement":null},{"id":"W3190940781","doi":"","title":"The Coming Transit Apocalypse","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Subsidy; Public transport; Business; Per capita; Kilometer; Transit (satellite); TRIPS architecture; Memphis; Agricultural economics; Quarter (Canadian coin); Geography; Economics; Transport engineering; Engineering; Population; Environmental health; Medicine","score_opus":0.007524546834965823,"score_gpt":0.22858011759506894,"score_spread":0.22105557076010313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3190940781","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006908768,0.009141874,0.0042056832,0.46701285,0.116757736,0.00012865744,0.0012992716,0.0014543603,0.39309072],"genre_scores_gemma":[0.04078317,0.0051516504,0.002668897,0.13751377,0.022717703,0.00011450088,0.0010520081,0.0007716072,0.7892267],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99817586,0.00016017935,0.00006783403,0.00039691624,0.00079056347,0.0004086052],"domain_scores_gemma":[0.99584264,0.00049944024,0.0001760562,0.000446789,0.001552024,0.0014829895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017900979,0.00084166334,0.00038574924,0.001160214,0.0049011875,0.00776785,0.0012750669,0.0049398555,0.13488086],"category_scores_gemma":[0.009850419,0.00031318024,0.00052140065,0.000739642,0.0030399775,0.008262548,0.005450947,0.010989669,0.0365987],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026042491,0.000028306355,0.00029682054,0.000051740877,0.0000031654108,0.0002400835,0.00032315837,0.000029514313,0.0002479603,0.036096,0.931074,0.031583164],"study_design_scores_gemma":[0.0000031300513,0.000010248235,0.0002395675,0.000031084208,9.720094e-7,0.00012253613,0.00017811413,0.000034032342,0.000046877645,0.0020372793,0.99729174,0.0000044235617],"about_ca_topic_score_codex":0.010370853,"about_ca_topic_score_gemma":0.016966585,"teacher_disagreement_score":0.13488086,"about_ca_system_score_codex":0.003253815,"about_ca_system_score_gemma":0.003653611,"threshold_uncertainty_score":0.4512214},"labels":[],"label_agreement":null},{"id":"W31915299","doi":"10.1126/scitranslmed.aau3538","title":"Malaysia network transit route adviser system","year":2010,"lang":"en","type":"article","venue":"Science Translational Medicine","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Krembil Foundation","keywords":"Monorail; Public transport; Ticket; Transit (satellite); Transport engineering; Customer base; Reservation; Computer science; Business; Engineering; Computer security; Marketing; Computer network","score_opus":0.007477249233523512,"score_gpt":0.23051517332513796,"score_spread":0.22303792409161444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W31915299","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0051934165,0.00069717143,0.006864868,0.0012937123,0.00089567766,0.00020761228,0.0063498407,0.005697986,0.97279954],"genre_scores_gemma":[0.011128544,0.0004726114,0.0017614322,0.0001492541,0.00006977416,0.00006343965,0.0027764002,0.00048091996,0.9830976],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975616,0.000039721643,0.000017663799,0.000064440224,0.000082271574,0.000039785373],"domain_scores_gemma":[0.99946326,0.00006982942,0.00005204204,0.00009371839,0.00014473892,0.00017642505],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00039822428,0.0010373677,0.0003344131,0.0010218648,0.00087216974,0.001889811,0.0007078784,0.0011894851,0.78365123],"category_scores_gemma":[0.0007974196,0.00027524735,0.00021753427,0.00082008564,0.0002691079,0.0019171815,0.0020418328,0.00077758305,0.64092094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005179209,0.00024722566,0.0022835163,0.0004108583,0.000017235241,0.00045806766,0.00023190616,0.0007219417,0.0057237935,0.01383625,0.43872657,0.5368248],"study_design_scores_gemma":[0.000020367348,0.000047071208,0.00070139737,0.000041398256,0.0000040510886,0.0001564641,0.00005709675,0.00054033863,0.0009970193,0.00057845755,0.9968484,0.000007942502],"about_ca_topic_score_codex":0.0017348669,"about_ca_topic_score_gemma":0.0021803344,"teacher_disagreement_score":0.78365123,"about_ca_system_score_codex":0.0005165585,"about_ca_system_score_gemma":0.0011356102,"threshold_uncertainty_score":0.30859524},"labels":[],"label_agreement":null},{"id":"W3192568905","doi":"10.1016/j.trc.2021.103304","title":"Social welfare maximizing fleet charging scheduling through voting-based negotiation","year":2021,"lang":"en","type":"article","venue":"Transportation Research Part C Emerging Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Negotiation; Voting; Social Welfare; Schedule; Computer science; Scheduling (production processes); Operations research; Welfare; Business; Microeconomics; Economics; Operations management; Engineering","score_opus":0.07979171417355621,"score_gpt":0.3521396327058323,"score_spread":0.27234791853227613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3192568905","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07546964,0.00015374743,0.9097065,0.00051964464,0.00013037155,0.0002259161,0.00010664643,0.00021849688,0.013469087],"genre_scores_gemma":[0.94197834,0.00007436241,0.052072935,0.00008795086,0.000052926527,0.00014319917,0.00008874208,0.000064824795,0.005436747],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978009,0.0010686564,0.00008090082,0.0003253293,0.000313955,0.00041032513],"domain_scores_gemma":[0.9959959,0.0028825135,0.00024759743,0.00024365769,0.00031455213,0.00031586338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003181585,0.0007541336,0.0022484527,0.00065067946,0.0012010215,0.0021948894,0.002932459,0.0016297564,0.0067581804],"category_scores_gemma":[0.008479509,0.0006762523,0.00095288514,0.0011123647,0.0010771013,0.0024195414,0.0020077312,0.0016085499,0.0006147361],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065378466,0.0002660758,0.0007021618,0.0001330952,0.000084447456,0.00016064575,0.00020813565,0.8783912,0.0031767376,0.06785963,0.0038347028,0.044529457],"study_design_scores_gemma":[0.000027705228,0.000033784352,0.000055866007,0.0000038287817,0.000007406653,0.00001473794,0.000025843452,0.9844481,0.00023740323,0.014835108,0.00030457694,0.000005647009],"about_ca_topic_score_codex":0.001893715,"about_ca_topic_score_gemma":0.0019070666,"teacher_disagreement_score":0.0067581804,"about_ca_system_score_codex":0.0011931629,"about_ca_system_score_gemma":0.0014821043,"threshold_uncertainty_score":0.0226084},"labels":[],"label_agreement":null},{"id":"W3193473085","doi":"","title":"Ridesharing Equity: the Role of Ridesharing in Providing Access to Employment – A Case Study of Toronto, Canada","year":2021,"lang":"en","type":"article","venue":"Transportation Research Board 100th Annual MeetingTransportation Research BoardTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Equity (law); Labour economics; Transport engineering; Economic growth; Economics; Engineering; Political science","score_opus":0.10000868130810184,"score_gpt":0.418859658743784,"score_spread":0.31885097743568214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3193473085","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94365895,0.0012760533,0.00028914676,0.0033747759,0.00004332928,0.00010823198,0.00026842832,0.000011544359,0.050969485],"genre_scores_gemma":[0.9899979,0.00072048156,0.00024080506,0.00018682086,0.0000062208915,0.000019971696,0.00006753574,0.000009294613,0.008750792],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.9976701,0.00044588506,0.000054548225,0.00014383158,0.00044977106,0.0012357533],"domain_scores_gemma":[0.9973411,0.00062881235,0.00019555724,0.00010599885,0.00075669884,0.00097176695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011299535,0.00038968856,0.00045728107,0.0014220082,0.024944939,0.0056652296,0.0022251857,0.0018960255,0.008318335],"category_scores_gemma":[0.0035304653,0.00039012122,0.00047570237,0.004397778,0.005262499,0.0016433648,0.0032692729,0.0022238386,0.00028367314],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044215537,0.00078084186,0.2558602,0.0005826649,0.00013367269,0.020220706,0.50135684,0.0038077116,0.001618675,0.07869733,0.031097904,0.105401345],"study_design_scores_gemma":[0.000039742736,0.0001078695,0.1556766,0.0004419407,0.000073852105,0.0009707681,0.77680093,0.001955354,0.00035337894,0.0013502566,0.062142674,0.00008665748],"about_ca_topic_score_codex":0.9954122,"about_ca_topic_score_gemma":0.9988457,"teacher_disagreement_score":0.10992387,"about_ca_system_score_codex":0.10992387,"about_ca_system_score_gemma":0.11580421,"threshold_uncertainty_score":0.79755723},"labels":[],"label_agreement":null},{"id":"W3193751648","doi":"10.1002/net.22074","title":"A combinatorial auction‐based approach for ridesharing in a student transportation system","year":2021,"lang":"en","type":"article","venue":"Networks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Qatar National Library; Sultan Qaboos University","keywords":"Combinatorial auction; Mathematical optimization; Computer science; Heuristics; Vehicle routing problem; Heuristic; Metaheuristic; Routing (electronic design automation); Particle swarm optimization; Integer programming; Common value auction; Artificial intelligence; Mathematics","score_opus":0.01175298652035959,"score_gpt":0.2293458067570131,"score_spread":0.21759282023665352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3193751648","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026319288,0.00032645467,0.9600571,0.00033135182,0.000059033613,0.00012305527,0.00013523306,0.00012914666,0.012519323],"genre_scores_gemma":[0.8561699,0.00040482281,0.1325274,0.00011428116,0.000051024275,0.00025669456,0.00013539747,0.000050682906,0.010289765],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946314,0.00030123195,0.00001605845,0.00007238169,0.00007642917,0.00007083779],"domain_scores_gemma":[0.9997502,0.00011865952,0.000031524723,0.000019423298,0.000050298207,0.000029826235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081111543,0.000587326,0.0009717987,0.000636442,0.0006680902,0.0018305053,0.0017368367,0.001280454,0.003910726],"category_scores_gemma":[0.00094496063,0.00048991246,0.0011190402,0.0008224294,0.0005949813,0.0010739327,0.0007454395,0.0009908892,0.00030617038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013866807,0.00002005414,0.000112125024,0.00002188419,0.000014325842,0.00004538516,0.000016297323,0.98084426,0.00026704578,0.014393913,0.00034965837,0.0039010425],"study_design_scores_gemma":[0.0000032061157,0.000011187733,0.000025229168,0.000002138426,0.000003770364,0.000008765389,0.000010480267,0.99777323,0.00005385606,0.0017404874,0.00036454687,0.0000029912715],"about_ca_topic_score_codex":0.013975423,"about_ca_topic_score_gemma":0.010294883,"teacher_disagreement_score":0.013975423,"about_ca_system_score_codex":0.0015504298,"about_ca_system_score_gemma":0.0019807036,"threshold_uncertainty_score":0.027788103},"labels":[],"label_agreement":null},{"id":"W3194116877","doi":"","title":"Ford recalls 2 million F-150 pickups over seat belt fire concerns","year":2018,"lang":"en","type":"article","venue":"FOXBusiness","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Seat belt; Advertising; Business; Forensic engineering; Geology; Aeronautics; Engineering","score_opus":0.019395222934331786,"score_gpt":0.25597643818219046,"score_spread":0.23658121524785866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194116877","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22112438,0.01020129,0.0032158215,0.4101751,0.018825866,0.0001839215,0.00564503,0.0020851782,0.32854328],"genre_scores_gemma":[0.35868967,0.005446955,0.0015210791,0.15162125,0.0031768351,0.000059339287,0.0030045663,0.00031493066,0.47616535],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99862075,0.00007375686,0.00006042793,0.0001250481,0.0007766314,0.00034335817],"domain_scores_gemma":[0.9968161,0.0006207448,0.00027714932,0.00011655893,0.0016281825,0.0005413537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011429497,0.0005541531,0.00024058392,0.001347345,0.005998339,0.0022247022,0.0005269412,0.005132954,0.025841588],"category_scores_gemma":[0.003759253,0.00048992835,0.0005955688,0.0006550814,0.0007022373,0.0011373406,0.00073987787,0.0040449873,0.0053913547],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015231976,0.00014730736,0.040141154,0.00008366039,0.000030342348,0.0017686817,0.0022918223,0.000063693675,0.0011453725,0.0018355153,0.89305055,0.059289485],"study_design_scores_gemma":[0.00002564095,0.00021232043,0.04267725,0.00020602957,0.00007272717,0.002773523,0.009559155,0.00022260839,0.002845819,0.00031462646,0.9410188,0.00007134581],"about_ca_topic_score_codex":0.2313083,"about_ca_topic_score_gemma":0.39810577,"teacher_disagreement_score":0.2313083,"about_ca_system_score_codex":0.0031769534,"about_ca_system_score_gemma":0.0025240676,"threshold_uncertainty_score":0.45992386},"labels":[],"label_agreement":null},{"id":"W3194750996","doi":"10.24908/cpp-apc.v2021i01.14362","title":"Private Car, Public Oversight: Municipal Regulation of Ride-hailing Platforms in Toronto and the Greater Golden Horseshoe","year":2021,"lang":"en","type":"article","venue":"Canadian Planning and Policy / Aménagement et politique au Canada","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"University of Toronto; University of Waterloo","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Service (business); Government (linguistics); Business; Public administration; Municipal services; Local government; Control (management); Public relations; Political science; Marketing; Management; Economics","score_opus":0.014003157002600939,"score_gpt":0.24247072057099062,"score_spread":0.22846756356838968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194750996","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94489527,0.0014617839,0.0012414994,0.010589219,0.00006143919,0.00012019359,0.00018657626,0.00003471761,0.04140934],"genre_scores_gemma":[0.9925001,0.0003933656,0.00028515887,0.00029715328,0.0000072601865,0.000019604768,0.000038767572,0.000007778161,0.0064507555],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9941571,0.0015007305,0.0001984064,0.00045486094,0.0015822601,0.0021066251],"domain_scores_gemma":[0.9887833,0.003405891,0.0017073938,0.0004712099,0.0031175844,0.0025146406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003335729,0.00019601006,0.00023191715,0.0008820019,0.016449302,0.005291657,0.0011821678,0.0010191591,0.0024260704],"category_scores_gemma":[0.008676047,0.00033992747,0.00018011883,0.0024743937,0.009490163,0.0013177383,0.0029497114,0.001259999,0.00012859347],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017572848,0.00007515438,0.13219331,0.00061102584,0.000052695676,0.0061456705,0.70565075,0.0021853284,0.0055028866,0.07196724,0.020043304,0.05539706],"study_design_scores_gemma":[0.000015484595,0.00006311238,0.18978883,0.0002962598,0.00004447524,0.00026131963,0.65160394,0.00084115495,0.0012142239,0.0015955452,0.15419362,0.00008198486],"about_ca_topic_score_codex":0.9833362,"about_ca_topic_score_gemma":0.9954846,"teacher_disagreement_score":0.12558301,"about_ca_system_score_codex":0.12558301,"about_ca_system_score_gemma":0.1449493,"threshold_uncertainty_score":0.91117275},"labels":[],"label_agreement":null},{"id":"W3196522954","doi":"10.1177/03611981211028620","title":"Impacts of Holding Area Policies on Shared Autonomous Vehicle Operations","year":2021,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Pooling; Service (business); TRIPS architecture; Transport engineering; Cluster analysis; Computer science; Fleet management; Bottleneck; Operations research; Business; Environmental economics; Marketing; Engineering; Economics","score_opus":0.0987443202799558,"score_gpt":0.37198237613382296,"score_spread":0.2732380558538672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196522954","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9872077,0.000095078714,0.0105671985,0.00011806057,0.0000143403995,0.00002846698,0.00016556754,0.000061284365,0.0017421535],"genre_scores_gemma":[0.9988268,0.000030409316,0.0007702778,0.0000068985905,0.0000014856338,0.000007089455,0.000046710327,0.0000045110655,0.00030592174],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994174,0.00013024034,0.00001927694,0.000102475424,0.0000830519,0.00024749804],"domain_scores_gemma":[0.9985697,0.000653683,0.0002842379,0.000115450195,0.0002044214,0.00017250674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087047153,0.0006356115,0.00039749852,0.00033005202,0.0005536014,0.0012149689,0.0009544188,0.0006464694,0.0014750299],"category_scores_gemma":[0.0028099315,0.0003336568,0.0006197441,0.00045306803,0.0009425028,0.0012617307,0.00079155754,0.0006150092,0.0001061547],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045254135,0.000023956898,0.008886683,0.000008756498,0.00001725577,0.000050488783,0.000029926283,0.9878874,0.00062587665,0.00068019726,0.00009044499,0.00165385],"study_design_scores_gemma":[0.000012597998,0.00013530633,0.010253598,0.000005330504,0.000029340483,0.000023146174,0.00029566447,0.98758113,0.00079887256,0.0005932941,0.00025528835,0.00001647903],"about_ca_topic_score_codex":0.14329892,"about_ca_topic_score_gemma":0.10758213,"teacher_disagreement_score":0.14329892,"about_ca_system_score_codex":0.00392067,"about_ca_system_score_gemma":0.002312984,"threshold_uncertainty_score":0.28492963},"labels":[],"label_agreement":null},{"id":"W3198173555","doi":"10.1109/tits.2021.3106243","title":"BM-DDPG: An Integrated Dispatching Framework for Ride-Hailing Systems","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Matching (statistics); Bipartite graph; Social Welfare; Computer science; Operations research; Service (business); Blossom algorithm; Optimal matching; Transport engineering; Engineering; Business; Mathematics; Marketing; Theoretical computer science","score_opus":0.03377923867412172,"score_gpt":0.2790595080806754,"score_spread":0.2452802694065537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3198173555","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033860388,0.00015964203,0.9928618,0.00009777484,0.00004884969,0.000073807416,0.00019118717,0.0013434698,0.0018374968],"genre_scores_gemma":[0.37550846,0.00047890522,0.6175774,0.0001561028,0.000093661,0.00041365114,0.0010534071,0.00040936784,0.0043089837],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993624,0.00018588993,0.000037219426,0.00014070838,0.00016449016,0.00010935924],"domain_scores_gemma":[0.99965477,0.000121281286,0.000034572713,0.000047280995,0.0000850022,0.000057145655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012993774,0.0012512906,0.0011872426,0.0006482778,0.000664119,0.0015261758,0.0025719272,0.0011398564,0.004627653],"category_scores_gemma":[0.0019920527,0.00057954184,0.0010868883,0.0007542285,0.00047763434,0.0014699271,0.0020458302,0.0016002366,0.0009803819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040990883,0.00002937734,0.00028133063,0.000056074136,0.000025451187,0.00003594101,0.000035119894,0.95892,0.00060372456,0.013304614,0.0021094857,0.024557905],"study_design_scores_gemma":[0.000007958785,0.000011695143,0.00003659268,0.0000036540282,0.0000043137466,0.0000065645863,0.000006780388,0.9944448,0.00012705864,0.0038911584,0.001455362,0.0000040478544],"about_ca_topic_score_codex":0.019491762,"about_ca_topic_score_gemma":0.014785137,"teacher_disagreement_score":0.019491762,"about_ca_system_score_codex":0.0013397754,"about_ca_system_score_gemma":0.0026799825,"threshold_uncertainty_score":0.03875661},"labels":[],"label_agreement":null},{"id":"W3198370555","doi":"","title":"The Heterogeneous Effects of Peer-to-Peer Ride-Hailing on Traffic: Evidence from Uber's Entry in California","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Pooling; Crowding; Sharing economy; Natural experiment; Crowding out; Public transport; Popularity; TRIPS architecture; Matching (statistics); Advertising; Business; Economics; Transport engineering; Computer science; Engineering; Monetary economics; Political science","score_opus":0.006578904118751656,"score_gpt":0.23061927026638138,"score_spread":0.22404036614762973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3198370555","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99603397,0.0001536648,0.0000660555,0.00014482922,0.000007236055,0.000020847083,0.0005715062,0.000007149011,0.0029946428],"genre_scores_gemma":[0.99785644,0.00022475375,0.000081181635,0.000054800792,0.000017988401,0.000015318565,0.0008142293,0.0000059370504,0.0009294344],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974274,0.0006589244,0.000112640875,0.0007084757,0.00059010426,0.0005024535],"domain_scores_gemma":[0.98893166,0.0037987283,0.0034536808,0.0009415819,0.0017081036,0.0011661839],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020201632,0.0003208475,0.00060981704,0.0010052846,0.0015401358,0.002246733,0.0016721148,0.0007097803,0.0033851792],"category_scores_gemma":[0.0071145403,0.0003868282,0.000662352,0.0019250454,0.0015203448,0.0010936789,0.001493411,0.001466934,0.00034933118],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005290394,0.00088677905,0.9807457,0.00009441367,0.00038070194,0.00032430614,0.0028434037,0.0011353679,0.00021521111,0.0007193423,0.00417347,0.007952312],"study_design_scores_gemma":[0.00003867066,0.00015870763,0.9942105,0.000029438901,0.00011004873,0.000029022127,0.002899362,0.0009084421,0.0000699611,0.00008775064,0.0014352384,0.000022924194],"about_ca_topic_score_codex":0.4476689,"about_ca_topic_score_gemma":0.57502,"teacher_disagreement_score":0.4476689,"about_ca_system_score_codex":0.0021471004,"about_ca_system_score_gemma":0.0012909042,"threshold_uncertainty_score":0.89012635},"labels":[],"label_agreement":null},{"id":"W3199408807","doi":"10.1155/2021/4014837","title":"A Novel Convex Hull Coverage Algorithm for the Deployment of Electric Taxi Swap Stations Based on Urban Traffic Flow","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Office for Philosophy and Social Sciences","keywords":"Taxis; Software deployment; Swap (finance); Computer science; Transport engineering; Engineering","score_opus":0.009526782483126214,"score_gpt":0.23226386163396873,"score_spread":0.2227370791508425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199408807","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010144411,0.00013897642,0.9872196,0.00008190192,0.00002567199,0.000050220624,0.00007253472,0.00039630607,0.0018705159],"genre_scores_gemma":[0.47062185,0.00047738125,0.52365625,0.00010749031,0.00007563868,0.0003204679,0.00080687733,0.00021826342,0.003715802],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965334,0.000068765,0.000015259988,0.00007839396,0.00011245298,0.00007180229],"domain_scores_gemma":[0.99950314,0.00023888226,0.000063251406,0.00004370971,0.00011205009,0.00003899125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003403151,0.0010622238,0.0010258118,0.0008569656,0.0004643436,0.00080397906,0.0011065555,0.0006456191,0.0023545788],"category_scores_gemma":[0.0014643666,0.00049944175,0.0006765824,0.0012536036,0.0003497542,0.000939977,0.00092657283,0.0007881138,0.0005018155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006863881,0.000034498422,0.0006076629,0.00005294192,0.00002425245,0.000073168405,0.00006367964,0.89831316,0.0021183162,0.0044211494,0.0030632662,0.091159314],"study_design_scores_gemma":[0.000004850157,0.000012000969,0.00006776517,0.0000018908977,0.0000030284657,0.00001587408,0.000008368268,0.9986833,0.00025395333,0.00056174374,0.00038467319,0.0000024945525],"about_ca_topic_score_codex":0.012580263,"about_ca_topic_score_gemma":0.008430813,"teacher_disagreement_score":0.012580263,"about_ca_system_score_codex":0.0008656585,"about_ca_system_score_gemma":0.0013369368,"threshold_uncertainty_score":0.025014102},"labels":[],"label_agreement":null},{"id":"W3199472824","doi":"","title":"Off-line approximate dynamic programming for the vehicle routing problem with stochastic customers and demands via decentralized decision-making","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Markov decision process; Computer science; Mathematical optimization; Vehicle routing problem; Reinforcement learning; Heuristic; Benchmark (surveying); Dynamic programming; Set (abstract data type); Routing (electronic design automation); Dimension (graph theory); Stochastic programming; Operations research; Markov process; Artificial intelligence; Mathematics; Algorithm","score_opus":0.02276891013377397,"score_gpt":0.20027146496413617,"score_spread":0.1775025548303622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199472824","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02730552,0.0004463614,0.9667635,0.0005600439,0.000053244625,0.00011385673,0.0000995101,0.0001858147,0.0044721276],"genre_scores_gemma":[0.8601236,0.00047027765,0.13411976,0.00023179832,0.00008380924,0.0004274603,0.00025665542,0.00009284572,0.0041937623],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987722,0.00055543514,0.000036377096,0.0002236739,0.00022522298,0.00018695925],"domain_scores_gemma":[0.99631137,0.002873311,0.0003367454,0.000094902,0.00023861842,0.00014509892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020973405,0.0014542997,0.0019582168,0.0005700554,0.000559251,0.0013785365,0.0013314424,0.0016873016,0.002864127],"category_scores_gemma":[0.005518881,0.00080316584,0.000836329,0.0008404804,0.0012770254,0.001232446,0.0013781926,0.0019443933,0.00033802068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002415543,0.000024898285,0.00013854618,0.000025158595,0.000010868814,0.000025339094,0.000015073831,0.9911192,0.000084657186,0.0047720918,0.00020978448,0.0035501902],"study_design_scores_gemma":[0.000006227532,0.000008647498,0.000019543459,0.000002345527,0.0000016748248,0.0000029039481,0.0000033795116,0.9970432,0.000026611035,0.002786521,0.000097682925,0.0000012653555],"about_ca_topic_score_codex":0.008157298,"about_ca_topic_score_gemma":0.007267231,"teacher_disagreement_score":0.008157298,"about_ca_system_score_codex":0.0017000538,"about_ca_system_score_gemma":0.0026651793,"threshold_uncertainty_score":0.016219676},"labels":[],"label_agreement":null},{"id":"W3199509052","doi":"10.1007/s13177-021-00269-y","title":"A Data-Driven Approach for Vehicle Relocation in Car-Sharing Services with Balanced Supply-Demand Ratios","year":2021,"lang":"en","type":"article","venue":"International Journal of Intelligent Transportation Systems Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Relocation; Computer science; Parametric statistics; Profit (economics); Operations research; Mathematical optimization; Simulation; Engineering; Mathematics; Economics; Statistics","score_opus":0.08580103071600141,"score_gpt":0.35844838418251695,"score_spread":0.27264735346651553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199509052","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020100024,0.00019196337,0.9749985,0.00048975454,0.00013678164,0.00022170306,0.00065152993,0.0007707867,0.0024389955],"genre_scores_gemma":[0.7766488,0.00019478747,0.21739784,0.00023454438,0.00012139245,0.0002974121,0.0010633103,0.00022230264,0.0038196195],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981748,0.00039872227,0.000111383735,0.00048621497,0.00052206975,0.00030688584],"domain_scores_gemma":[0.9969279,0.0016040816,0.0002181452,0.0002953698,0.0007481951,0.0002061575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024703096,0.001133562,0.0020183579,0.0013729347,0.0010060885,0.0028925298,0.0040996,0.0016801001,0.005746715],"category_scores_gemma":[0.006408565,0.0011922158,0.0015301701,0.0020419687,0.00087231724,0.0030266778,0.0025398072,0.0015699085,0.0011170986],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020405713,0.00014864029,0.0012254578,0.00011758123,0.000055075383,0.00018035993,0.000101291684,0.94222844,0.0017751969,0.011172955,0.0019803902,0.04081055],"study_design_scores_gemma":[0.0000054943002,0.000012282172,0.00004782815,0.0000029989592,0.0000060448947,0.000014531419,0.000023781111,0.9959997,0.00024730127,0.003342722,0.00029225572,0.000005066599],"about_ca_topic_score_codex":0.013318317,"about_ca_topic_score_gemma":0.017692117,"teacher_disagreement_score":0.013318317,"about_ca_system_score_codex":0.0017305895,"about_ca_system_score_gemma":0.002950567,"threshold_uncertainty_score":0.026481628},"labels":[],"label_agreement":null},{"id":"W3200575476","doi":"10.1080/10630732.2021.1950501","title":"Shifting Gears for the Automated Vehicle: Findings from Focus Groups in the Greater Toronto and Hamilton Area","year":2021,"lang":"en","type":"article","venue":"Journal of Urban Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Psychosocial; Focus group; Public economics; Public policy; Public relations; Psychology; Sociology; Social psychology; Marketing; Economics; Political science; Business; Economic growth","score_opus":0.010926565237112886,"score_gpt":0.2219143930366387,"score_spread":0.21098782779952582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3200575476","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99808997,0.00007813294,0.00015607593,0.00034358044,0.000005629065,0.000050214203,0.00003405286,0.0000023123105,0.0012400579],"genre_scores_gemma":[0.997801,0.00019312883,0.00024103056,0.0002515562,0.000007077623,0.000064638436,0.000025592528,0.0000034025263,0.001412321],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.99818367,0.0009078736,0.00006003165,0.00017931475,0.00028226126,0.00038686357],"domain_scores_gemma":[0.9933323,0.004011167,0.000678363,0.00013896193,0.0010055718,0.0008335268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026688385,0.00028552176,0.00026922184,0.00075669563,0.0063591306,0.0013464304,0.0009119579,0.0007326545,0.002058861],"category_scores_gemma":[0.0057694297,0.00026883656,0.00016925254,0.0012405106,0.0034535467,0.0007856139,0.0020793066,0.0006017619,0.00011595471],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006489101,0.000073538016,0.038350854,0.00013886757,0.000009858034,0.0006301429,0.94846356,0.000066492095,0.0028603158,0.0003132418,0.00079963246,0.008228661],"study_design_scores_gemma":[0.000008193578,0.000093592564,0.07182819,0.000078708355,0.000016953394,0.00008296785,0.92135584,0.00011821745,0.0006666498,0.00006646461,0.005667269,0.000016868162],"about_ca_topic_score_codex":0.745925,"about_ca_topic_score_gemma":0.8750143,"teacher_disagreement_score":0.254075,"about_ca_system_score_codex":0.010381101,"about_ca_system_score_gemma":0.01187669,"threshold_uncertainty_score":0.51114255},"labels":[],"label_agreement":null},{"id":"W3200834638","doi":"10.1155/2021/5141798","title":"Public Preferences of Shared Autonomous Vehicles in Developing Countries: A Cross-National Study of Pakistan and China","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China; Fundamental Research Funds for the Central Universities; Ministry of Education of the People's Republic of China; Youth Foundation","keywords":"Multinomial logistic regression; China; Developing country; Public transport; Preference; Business; Ordered logit; Marketing; Public economics; Geography; Economics; Economic growth; Engineering; Transport engineering","score_opus":0.027743558969677923,"score_gpt":0.2973345348252116,"score_spread":0.2695909758555337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3200834638","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999703,0.00001455016,0.000012422348,0.000028321425,0.0000012722267,0.000005069502,0.00003695364,2.6609726e-7,0.00019806238],"genre_scores_gemma":[0.99968505,0.000046931294,0.000022921813,0.000025050414,0.000001342648,0.000005803988,0.000056315726,3.900002e-7,0.00015626707],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995427,0.00007938282,0.000039182385,0.000075746095,0.00008149233,0.00018145851],"domain_scores_gemma":[0.9986413,0.00023349626,0.00040390657,0.00007898138,0.00025882383,0.00038348898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009210909,0.00036380455,0.00036395318,0.00088267704,0.0018286784,0.0008500536,0.00032614305,0.00044993818,0.0020133338],"category_scores_gemma":[0.0011758236,0.00040178525,0.0004884411,0.0013895843,0.0008810083,0.0007528806,0.00072282535,0.0005778706,0.00026648625],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004758299,0.00015734564,0.9848977,0.000026524996,0.000031094227,0.00045745872,0.0107946675,0.00004928262,0.00030432895,0.000108672546,0.00018619245,0.002939092],"study_design_scores_gemma":[0.0000052407304,0.00016931465,0.97849315,0.000013919495,0.000012904158,0.00020074117,0.020414893,0.0001831601,0.00008179841,0.00002726051,0.0003848295,0.000012705915],"about_ca_topic_score_codex":0.077843696,"about_ca_topic_score_gemma":0.08475943,"teacher_disagreement_score":0.077843696,"about_ca_system_score_codex":0.0012268884,"about_ca_system_score_gemma":0.0015021075,"threshold_uncertainty_score":0.15478116},"labels":[],"label_agreement":null},{"id":"W3201196337","doi":"10.1016/j.jtrangeo.2021.103197","title":"Shared mobility adoption from 2016 to 2018 in the Greater Toronto and Hamilton Area: Demographic or geographic diffusion?","year":2021,"lang":"en","type":"article","venue":"Journal of Transport Geography","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Distance decay; Business; Travel survey; Demographic economics; Diffusion of innovations; Descriptive statistics; Geography; Travel behavior; Economic geography; Marketing; Economics; Transport engineering; Statistics; Engineering","score_opus":0.012789750352012394,"score_gpt":0.21970544408670156,"score_spread":0.20691569373468915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3201196337","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98942417,0.0006301694,0.00016077161,0.0023950431,0.00004811906,0.000029928962,0.0050429665,0.000012341507,0.002256502],"genre_scores_gemma":[0.99633586,0.00035550678,0.00008971114,0.00011153174,0.00002040424,0.00002116001,0.0017231356,0.000005385246,0.0013372671],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99894994,0.00011572228,0.00008833222,0.00019277382,0.00024864083,0.00040460014],"domain_scores_gemma":[0.9959532,0.00029433143,0.0013241335,0.00019888015,0.0010839022,0.0011455585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011066905,0.00018786387,0.00031822943,0.0014846503,0.0012198165,0.0022017886,0.0010043799,0.00068827934,0.004049358],"category_scores_gemma":[0.004810695,0.00024443175,0.000561131,0.0037229764,0.0009090304,0.0021502208,0.0025155223,0.0011383855,0.0003048646],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056242727,0.00003189652,0.98012024,0.00005193245,0.00007543886,0.00009281095,0.008290129,0.00013258215,0.000100571575,0.00076844235,0.0032134845,0.007066262],"study_design_scores_gemma":[0.0000022895163,0.000016136813,0.98514104,0.00005543558,0.000018988641,0.00004543186,0.010984508,0.00021912948,0.00004384228,0.00006374769,0.003398605,0.000010656947],"about_ca_topic_score_codex":0.8552381,"about_ca_topic_score_gemma":0.9335804,"teacher_disagreement_score":0.14476192,"about_ca_system_score_codex":0.007970527,"about_ca_system_score_gemma":0.010118445,"threshold_uncertainty_score":0.2912289},"labels":[],"label_agreement":null},{"id":"W3201840680","doi":"10.1109/icas49788.2021.9551114","title":"Matching Models for Crowd-Shipping Considering Shipper’s Acceptance Uncertainty","year":2021,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Matching (statistics); Flexibility (engineering); Computer science; Compensation (psychology); Operations research; Engineering; Economics","score_opus":0.04016002141142644,"score_gpt":0.2641059082719683,"score_spread":0.22394588686054184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3201840680","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09361798,0.000615803,0.8989843,0.0005285621,0.00009029417,0.00014207489,0.00025881376,0.00020606977,0.00555605],"genre_scores_gemma":[0.9562689,0.000430574,0.03445542,0.000106243715,0.000051213497,0.0001929407,0.00022686973,0.000076261334,0.0081914915],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988176,0.00035376352,0.000054215707,0.00026067428,0.00019390872,0.00031979414],"domain_scores_gemma":[0.99687684,0.0019789585,0.00050024176,0.00011270676,0.00033665032,0.00019460279],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027444789,0.001507302,0.002038751,0.00081516866,0.00068006874,0.0016161951,0.002362617,0.0019348641,0.00541627],"category_scores_gemma":[0.0051133945,0.0009780541,0.0014370962,0.0011379794,0.0010970248,0.0017981611,0.0016352985,0.0015643002,0.00046310722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030194875,0.000018547113,0.00027723983,0.000020929565,0.000014004876,0.000041101153,0.00002202581,0.9936465,0.00016615818,0.0033741132,0.00022658081,0.002162633],"study_design_scores_gemma":[0.0000039940137,0.000010443843,0.00008395622,0.0000016964168,0.0000049423684,0.0000039559163,0.000008981099,0.9985304,0.000037988586,0.001225331,0.00008502944,0.0000032854925],"about_ca_topic_score_codex":0.015656408,"about_ca_topic_score_gemma":0.005997791,"teacher_disagreement_score":0.015656408,"about_ca_system_score_codex":0.0018161235,"about_ca_system_score_gemma":0.001600302,"threshold_uncertainty_score":0.031130552},"labels":[],"label_agreement":null},{"id":"W3203406821","doi":"10.1155/2021/2156964","title":"Exploring the Potential of Using Privately-Owned, Self-Driving Autonomous Vehicles for Evacuation Assistance","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Clemson University; U.S. Department of Transportation","keywords":"Self driving; Transport engineering; Aeronautics; Business; Engineering; Computer security; Computer science","score_opus":0.0334288066065268,"score_gpt":0.25725828183433064,"score_spread":0.22382947522780383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203406821","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9924499,0.00007462282,0.0036298353,0.0006284939,0.000008682604,0.000043354063,0.00027757068,0.000017636996,0.0028699497],"genre_scores_gemma":[0.9978064,0.00006268867,0.00085390644,0.00003117172,0.0000044222706,0.000018670928,0.00010204656,0.0000024745116,0.0011182782],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99877936,0.0006517065,0.000025645022,0.00016603393,0.0000848261,0.00029255083],"domain_scores_gemma":[0.99120575,0.006243248,0.0013061218,0.00027704774,0.0005328976,0.00043488466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023635195,0.00038941784,0.00028234426,0.0006085641,0.00055893575,0.0019537255,0.0012225827,0.0009914412,0.0040571694],"category_scores_gemma":[0.009292749,0.0003700395,0.0006621996,0.0006113085,0.0007008246,0.0016242919,0.0011263384,0.000712988,0.0003763549],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004587098,0.0006118053,0.71987545,0.0001369553,0.00034146497,0.0012478156,0.0017017305,0.23160559,0.0011200573,0.010418773,0.001972386,0.03050926],"study_design_scores_gemma":[0.00007496295,0.0012261086,0.1544511,0.00008163407,0.0002770469,0.00053100375,0.011328912,0.81776685,0.0008239278,0.008008198,0.0053409724,0.00008937075],"about_ca_topic_score_codex":0.048382625,"about_ca_topic_score_gemma":0.08272704,"teacher_disagreement_score":0.048382625,"about_ca_system_score_codex":0.0014529112,"about_ca_system_score_gemma":0.00171452,"threshold_uncertainty_score":0.096202016},"labels":[],"label_agreement":null},{"id":"W3203728894","doi":"10.1155/2021/5563205","title":"Morning Peak-Period Pricing Surcharge of Elderly Passengers Taking Express Buses","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; Government of Jiangsu Province; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Transport engineering; Scheme (mathematics); Morning; Computer science; Elderly people; Operations research; Measure (data warehouse); Engineering; Mathematics","score_opus":0.01199209214920895,"score_gpt":0.24424688074559425,"score_spread":0.2322547885963853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203728894","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8846952,0.00058056135,0.10678557,0.00045404848,0.00013000391,0.000079547906,0.00017707852,0.00012612458,0.006971934],"genre_scores_gemma":[0.99722373,0.000084465464,0.0018017039,0.000015715505,0.000013779367,0.0000073955384,0.000038764636,0.0000064507617,0.0008080061],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9988943,0.00033401613,0.000037443348,0.00015253383,0.00017033327,0.00041148326],"domain_scores_gemma":[0.9983197,0.0007042722,0.00027931252,0.00013057709,0.00034140586,0.00022469174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015599731,0.0006744913,0.0008701435,0.0004553285,0.00084483594,0.0014956262,0.0012875636,0.001043639,0.00281203],"category_scores_gemma":[0.004710212,0.0003566011,0.0007994008,0.0005106924,0.00068388256,0.0017869737,0.0011243348,0.0010611735,0.0001677514],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008000225,0.0002617706,0.02475741,0.00021927891,0.00012478442,0.0032005752,0.00043349748,0.9063823,0.005868536,0.028632088,0.0028258178,0.026493909],"study_design_scores_gemma":[0.00001819501,0.00012585355,0.003160232,0.000008714914,0.000051103638,0.00026485114,0.00039218465,0.9903082,0.0010810432,0.0040905564,0.00047140627,0.000027680017],"about_ca_topic_score_codex":0.010573906,"about_ca_topic_score_gemma":0.007564834,"teacher_disagreement_score":0.010573906,"about_ca_system_score_codex":0.0013346189,"about_ca_system_score_gemma":0.0011891599,"threshold_uncertainty_score":0.021024704},"labels":[],"label_agreement":null},{"id":"W3204063593","doi":"10.1016/j.tbs.2021.09.003","title":"Modelling the adoption of autonomous vehicle: How historical experience inform the future preference","year":2021,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multivariate probit model; Preference; Bivariate analysis; Ordered probit; Car ownership; Business; Probit model; Travel behavior; Marketing; Demographic economics; Computer science; Economics; Transport engineering; Econometrics; Engineering; Public transport; Microeconomics","score_opus":0.034607458955541216,"score_gpt":0.22481414692663132,"score_spread":0.1902066879710901,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3204063593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95230144,0.00065578695,0.018142344,0.0020945964,0.0000576673,0.000020699297,0.0008377586,0.000028018172,0.025861682],"genre_scores_gemma":[0.9960337,0.00029590295,0.0009792845,0.000024390167,0.000009145362,0.0000085034335,0.00018095467,0.000012137492,0.0024559528],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997565,0.00009966662,0.000013132659,0.00005723853,0.000022617205,0.000050813545],"domain_scores_gemma":[0.9983203,0.001004125,0.00020435787,0.00012825176,0.00016009776,0.00018295248],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000950079,0.00023755597,0.00021807109,0.00073524384,0.00044185718,0.0027715666,0.00090535556,0.0012943821,0.010399105],"category_scores_gemma":[0.006339928,0.00026676132,0.00035734687,0.0011903753,0.0008321214,0.004595462,0.0008941763,0.0011243782,0.0006989737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006076138,0.00048564785,0.26631278,0.0003138781,0.0002539334,0.0022520556,0.014196712,0.36481896,0.0018324595,0.2833493,0.005661243,0.059915382],"study_design_scores_gemma":[0.000045429268,0.00024376209,0.076393165,0.00020800275,0.00015268935,0.0005979102,0.0122457305,0.71847385,0.0007320231,0.16356045,0.027180703,0.00016638618],"about_ca_topic_score_codex":0.02175742,"about_ca_topic_score_gemma":0.029931808,"teacher_disagreement_score":0.02175742,"about_ca_system_score_codex":0.0013280142,"about_ca_system_score_gemma":0.0005269435,"threshold_uncertainty_score":0.043261588},"labels":[],"label_agreement":null},{"id":"W3204187165","doi":"","title":"Consultation sur les déplacements à vélo à Québec 2015 — Recommandations","year":2015,"lang":"fr","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine","score_opus":0.04720110729541249,"score_gpt":0.2583050627666578,"score_spread":0.21110395547124533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3204187165","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011257792,0.06647563,0.0015816157,0.64302105,0.031834047,0.0014791787,0.017983437,0.00065015064,0.22571711],"genre_scores_gemma":[0.085270055,0.036366865,0.0049780165,0.506848,0.0053722374,0.0022230078,0.010853434,0.00029635185,0.34779206],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9917468,0.0014276472,0.0007428197,0.0004313116,0.0033315292,0.0023199604],"domain_scores_gemma":[0.9822949,0.0026839876,0.0008902032,0.00043237727,0.010291623,0.0034069372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008648396,0.000649914,0.00088148017,0.0019077612,0.005625934,0.0046872743,0.0031045603,0.010220302,0.031680483],"category_scores_gemma":[0.02833678,0.0006849575,0.0017565507,0.0019981149,0.0021418608,0.0016160097,0.0024649268,0.007851705,0.004537764],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006408944,0.00003935241,0.0023831415,0.00035093242,0.000034237506,0.00024559608,0.00028135904,0.00009504688,0.00016668778,0.0019474403,0.9733883,0.02100369],"study_design_scores_gemma":[0.00007891437,0.000028779847,0.01211641,0.002115685,0.00005226398,0.000110302324,0.00050533644,0.00009731844,0.00017786105,0.00036660724,0.98430324,0.000047184785],"about_ca_topic_score_codex":0.9533509,"about_ca_topic_score_gemma":0.9703408,"teacher_disagreement_score":0.0466491,"about_ca_system_score_codex":0.027011782,"about_ca_system_score_gemma":0.15138368,"threshold_uncertainty_score":0.19598514},"labels":[],"label_agreement":null},{"id":"W3205360844","doi":"10.1109/isc253183.2021.9562775","title":"Driver guidance and rebalancing in ride-hailing systems through mixture density networks and stochastic programming","year":2021,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ericsson (Canada); Concordia University","funders":"","keywords":"Computer science; Matching (statistics); Stochastic programming; Quality (philosophy); Time series; Mathematical optimization; Operations research; Machine learning; Engineering","score_opus":0.007290523922671352,"score_gpt":0.21009772548325673,"score_spread":0.20280720156058538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3205360844","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029346924,0.00020667692,0.9685572,0.00022705818,0.000030708354,0.00003664666,0.000057921727,0.00026231268,0.0012745381],"genre_scores_gemma":[0.92537874,0.00024901368,0.07075178,0.00009357831,0.00004092667,0.0001417005,0.00011520718,0.000069984926,0.0031590154],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993605,0.0002027256,0.0000221579,0.00015015573,0.00013817949,0.00012628821],"domain_scores_gemma":[0.99889636,0.00063246826,0.00013699294,0.000040813884,0.00020605889,0.00008737239],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012835212,0.000987408,0.001259444,0.00076638185,0.00059572037,0.0011299106,0.0019353365,0.001121787,0.0018183041],"category_scores_gemma":[0.0027463916,0.00094136887,0.0010838968,0.00082077127,0.00082817225,0.0015184112,0.0012168231,0.0014389778,0.00020782325],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012310762,0.000010378888,0.00017227637,0.000008053677,0.000008216502,0.000008215233,0.000009167988,0.99491644,0.00011328855,0.001673286,0.00009740867,0.0029710035],"study_design_scores_gemma":[0.0000011945995,0.0000044369012,0.000024353625,5.696543e-7,0.0000017794101,0.0000010294674,0.0000018446187,0.9994677,0.000030961142,0.00042047378,0.00004431326,0.0000013075404],"about_ca_topic_score_codex":0.031849902,"about_ca_topic_score_gemma":0.018587315,"teacher_disagreement_score":0.031849902,"about_ca_system_score_codex":0.0016364907,"about_ca_system_score_gemma":0.0019233072,"threshold_uncertainty_score":0.06332898},"labels":[],"label_agreement":null},{"id":"W3205376791","doi":"10.5592/co/cetra.2020.1298","title":"Alteration in modal share due to autonomous vehicle-based mobility services","year":2021,"lang":"en","type":"article","venue":"Road and rail infrastructure","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Modal shift; Modal; Transport engineering; Variable (mathematics); Computer science; Service (business); Environmental economics; Business; Telecommunications; Public transport; Engineering; Marketing; Economics; Mathematics","score_opus":0.004576175075911466,"score_gpt":0.20929366196057644,"score_spread":0.20471748688466498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3205376791","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9917008,0.00003473665,0.0050305063,0.000032052885,0.0000058531796,0.000029125624,0.00031226725,0.000028080154,0.0028264816],"genre_scores_gemma":[0.9985801,0.000017989554,0.0006910947,0.0000056198223,0.000001707643,0.000016089356,0.00019608083,0.0000040869445,0.0004872223],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988398,0.0003890513,0.00005969716,0.0001877703,0.000347751,0.00017593756],"domain_scores_gemma":[0.9956787,0.002350495,0.00069192075,0.00041219653,0.0007187351,0.00014801536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010783703,0.00022122942,0.00016726075,0.0007253157,0.00019246775,0.0006198502,0.00040182163,0.00026735177,0.005106001],"category_scores_gemma":[0.0070551415,0.00011519276,0.00057031785,0.0009048868,0.00025609432,0.000755017,0.0008067752,0.00026843036,0.0003665443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008972193,0.00040997248,0.79505885,0.0002386233,0.00040974698,0.00063478923,0.0013473097,0.08976901,0.018764107,0.0038412537,0.0008981607,0.08773105],"study_design_scores_gemma":[0.000013368731,0.00071894616,0.87268,0.00002494275,0.00017733076,0.00036214996,0.0025825659,0.11063565,0.008039166,0.0021747437,0.0025326703,0.000058473575],"about_ca_topic_score_codex":0.0044539855,"about_ca_topic_score_gemma":0.0052082217,"teacher_disagreement_score":0.005106001,"about_ca_system_score_codex":0.00068379845,"about_ca_system_score_gemma":0.00031244956,"threshold_uncertainty_score":0.01708126},"labels":[],"label_agreement":null},{"id":"W3205444096","doi":"10.36939/cjur/vol30no1/art256","title":"Ride-hailing applications in Vancouver, Canada","year":2021,"lang":"en","type":"article","venue":"Canadian journal of urban research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Variety (cybernetics); Politics; Normative; Government (linguistics); Authorization; Representation (politics); Control (management); Business; Public administration; Political science; Economics; Law; Management","score_opus":0.030475357597093907,"score_gpt":0.2734884974355338,"score_spread":0.24301313983843986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3205444096","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8116895,0.0012580572,0.00078155455,0.0037511257,0.000060742186,0.00025904694,0.0020097601,0.000084162486,0.18010594],"genre_scores_gemma":[0.9233407,0.0013105368,0.0010925609,0.00043556554,0.0000091239135,0.00004745087,0.00092161313,0.000030546376,0.07281194],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99901867,0.0000823947,0.000019147066,0.00008487831,0.00032027822,0.00047461476],"domain_scores_gemma":[0.99850684,0.00019586163,0.000050440307,0.000038135717,0.0008625329,0.00034620348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005378946,0.00022609998,0.00021266662,0.001046977,0.0108797625,0.0035966635,0.0010655442,0.00074653,0.006867819],"category_scores_gemma":[0.0016076273,0.00023730788,0.00019040516,0.003418008,0.0013770459,0.00059699244,0.0010804983,0.0009770915,0.0007314786],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005901863,0.0008283352,0.36938557,0.0007781348,0.00009404224,0.01089652,0.066503026,0.009521455,0.0053856433,0.08656925,0.14151265,0.3079352],"study_design_scores_gemma":[0.00006219993,0.0001382218,0.42105293,0.00030083844,0.000050192317,0.0006123727,0.16689353,0.009057209,0.0017785239,0.0029160348,0.39697468,0.00016333607],"about_ca_topic_score_codex":0.99774903,"about_ca_topic_score_gemma":0.9993881,"teacher_disagreement_score":0.06940771,"about_ca_system_score_codex":0.06940771,"about_ca_system_score_gemma":0.1028957,"threshold_uncertainty_score":0.5035905},"labels":[],"label_agreement":null},{"id":"W3206251279","doi":"10.1145/3472749.3474764","title":"Space, Time, and Choice: A Unified Approach to Flexible Personal Scheduling","year":2021,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Scheduling (production processes); Workflow; Distributed computing; Human–computer interaction; Spacetime; Mathematical optimization; Database","score_opus":0.01772863803716422,"score_gpt":0.23560827671931447,"score_spread":0.21787963868215027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3206251279","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0044275676,0.00021211826,0.9862075,0.00032970784,0.00005256257,0.00007475986,0.00004499831,0.00039859166,0.008252173],"genre_scores_gemma":[0.20257047,0.00059494097,0.78696525,0.00014463547,0.00009772945,0.00047247863,0.00012183199,0.0003843864,0.008648312],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979352,0.00082566316,0.0001657748,0.00034580665,0.00053475366,0.0001928728],"domain_scores_gemma":[0.9982844,0.0006082265,0.00013979356,0.0004938744,0.00018285906,0.00029070504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002310493,0.0009368052,0.0008189521,0.0013195387,0.0016460803,0.0048967986,0.002515411,0.0013083789,0.008616712],"category_scores_gemma":[0.0051830704,0.00083697954,0.0018526097,0.001348896,0.0036537917,0.006100849,0.0042409003,0.0022137265,0.0015044127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017561307,0.00009970391,0.0009835601,0.00019097919,0.000056602777,0.00022802613,0.0032986149,0.06983649,0.004582441,0.8276632,0.0031170463,0.08976775],"study_design_scores_gemma":[0.00007932879,0.0001835709,0.00043445738,0.00013417723,0.00010110356,0.0003456556,0.0010636941,0.34959093,0.0045508756,0.5296426,0.1137643,0.00010941821],"about_ca_topic_score_codex":0.0054735797,"about_ca_topic_score_gemma":0.005834205,"teacher_disagreement_score":0.008616712,"about_ca_system_score_codex":0.0016327586,"about_ca_system_score_gemma":0.0025215622,"threshold_uncertainty_score":0.02882576},"labels":[],"label_agreement":null},{"id":"W3208246097","doi":"10.1155/2021/9665340","title":"Dynamic Capacitated Arc Routing Problem in E-Bike Sharing System: A Monte Carlo Tree Search Approach","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Computer science; Routing (electronic design automation); Mathematical optimization; Markov decision process; Process (computing); Tree (set theory); Monte Carlo method; Operations research; Monte Carlo tree search; Markov process; Engineering; Mathematics","score_opus":0.012556159678477315,"score_gpt":0.2341548302023777,"score_spread":0.2215986705239004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3208246097","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07282058,0.001392301,0.9170113,0.0007521377,0.00007751965,0.00010949071,0.00015598974,0.00023576648,0.0074448613],"genre_scores_gemma":[0.84756964,0.0011707363,0.1450911,0.00021663103,0.00006830406,0.00029553162,0.0002688763,0.00008595573,0.0052331556],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995454,0.00020098346,0.00001775232,0.00007996841,0.0000710773,0.000084750565],"domain_scores_gemma":[0.998321,0.0013307986,0.000106057574,0.0000278638,0.00013765912,0.00007661943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010473811,0.00077442033,0.0014359301,0.0009361633,0.00072090805,0.0010386513,0.001280112,0.001776526,0.0032231156],"category_scores_gemma":[0.0023606913,0.00062283006,0.0009156412,0.0014448735,0.0007148689,0.0013137402,0.00070387387,0.000995893,0.000185966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008563003,0.000007648753,0.0001575627,0.000013186752,0.0000068753707,0.000015007513,0.000006839611,0.9961515,0.000047313006,0.0019536347,0.000109761975,0.001522091],"study_design_scores_gemma":[0.000002143064,0.00000346553,0.000020790283,0.0000014427945,0.0000021503236,0.0000029222372,0.000004071749,0.9991518,0.0000139890935,0.0007384801,0.000057546215,0.0000011519977],"about_ca_topic_score_codex":0.018985517,"about_ca_topic_score_gemma":0.014414302,"teacher_disagreement_score":0.018985517,"about_ca_system_score_codex":0.0014397475,"about_ca_system_score_gemma":0.0019776188,"threshold_uncertainty_score":0.037750006},"labels":[],"label_agreement":null},{"id":"W3208895056","doi":"10.1002/nav.22027","title":"Capacity expansion strategies for electric vehicle charging networks: Model, algorithms, and case study","year":2021,"lang":"en","type":"article","venue":"Naval Research Logistics (NRL)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Range (aeronautics); Electric vehicle; Solver; Mathematical optimization; Heuristic; Operations research; Charging station; Algorithm; Engineering; Mathematics; Power (physics)","score_opus":0.17174004318455505,"score_gpt":0.3823817313621871,"score_spread":0.21064168817763207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3208895056","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6139155,0.0018797326,0.3176161,0.0027050471,0.00011079834,0.0008945203,0.0014071835,0.00050654204,0.06096467],"genre_scores_gemma":[0.9624875,0.0004155965,0.030805338,0.000056498888,0.00001979488,0.00027517628,0.00019396553,0.000024903184,0.005721124],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993476,0.00036902638,0.0000148816225,0.00006244757,0.000064480766,0.0001414927],"domain_scores_gemma":[0.9962457,0.0030341193,0.0002505452,0.00006454575,0.00026614068,0.00013885078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019220838,0.0011812397,0.0010569033,0.0015704512,0.0011191762,0.0019505315,0.0017993795,0.002414949,0.005281645],"category_scores_gemma":[0.004235831,0.00072041195,0.0008317081,0.002186194,0.0010490282,0.0015217114,0.0011467765,0.0016327937,0.00020089497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001960253,0.00003626299,0.00028805103,0.000017404118,0.000004991054,0.00004516188,0.000010224739,0.9950546,0.000041216626,0.0028261663,0.00027941,0.0013768041],"study_design_scores_gemma":[0.000010468699,0.000014966444,0.000069475194,0.0000045190845,0.0000041929757,0.0000091682205,0.00003306424,0.9984395,0.000049981438,0.0012103165,0.00015049738,0.0000037894727],"about_ca_topic_score_codex":0.049177255,"about_ca_topic_score_gemma":0.035434004,"teacher_disagreement_score":0.049177255,"about_ca_system_score_codex":0.005093339,"about_ca_system_score_gemma":0.0021072198,"threshold_uncertainty_score":0.097782016},"labels":[],"label_agreement":null},{"id":"W3209615620","doi":"10.32920/ryerson.14654697.v1","title":"Uber vs. Public Transit : friend or foe? An Empirical Study of Ridership Trends Across Uber Cities in the USA","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; McGill University","funders":"","keywords":"Public transport; Descriptive statistics; Transit (satellite); Business; Order (exchange); Service (business); Complement (music); Rail transit; Demographic economics; Marketing; Transport engineering; Economics; Finance; Engineering","score_opus":0.131734711918154,"score_gpt":0.3655757401839659,"score_spread":0.23384102826581188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209615620","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985815,0.00004859981,0.000038943486,0.00014443534,0.000002788725,0.000004516918,0.00024179005,0.0000021695987,0.0009352625],"genre_scores_gemma":[0.99845505,0.000104126695,0.000060574712,0.00008748509,0.000006400964,0.000007270556,0.00039858895,0.0000029530302,0.00087750726],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995003,0.00016545833,0.000033094348,0.000107970765,0.000099095516,0.00009405683],"domain_scores_gemma":[0.9933356,0.0024027466,0.0020569807,0.00024097374,0.001385097,0.0005785595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001077828,0.000081750375,0.00023489314,0.0010509328,0.000734589,0.0011720423,0.00033875008,0.00033224648,0.0024842538],"category_scores_gemma":[0.0055488483,0.00010880744,0.00016674052,0.0025124396,0.00041256522,0.0011983025,0.0006771023,0.0007893614,0.0003374073],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008671591,0.00011891495,0.98794425,0.000013128228,0.000032982844,0.00006525946,0.0038590555,0.000046746503,0.000082051905,0.00019052839,0.0012617754,0.0062985155],"study_design_scores_gemma":[0.0000020167922,0.000045926197,0.9880585,0.00001010839,0.000017299495,0.00002553057,0.010422767,0.00032008937,0.000056981207,0.000022421245,0.0010139195,0.0000044810895],"about_ca_topic_score_codex":0.07597613,"about_ca_topic_score_gemma":0.17356262,"teacher_disagreement_score":0.07597613,"about_ca_system_score_codex":0.00081271736,"about_ca_system_score_gemma":0.00040767514,"threshold_uncertainty_score":0.1510678},"labels":[],"label_agreement":null},{"id":"W3209654027","doi":"10.32920/ryerson.14648973.v1","title":"Will autonomous vehicles undermine Ontario provincial policies to concentrate jobs and housing? Evidence from the Greater Toronto-Hamilton area","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Relocation; Work (physics); Pedestrian; Land use; Residence; Business; Journey to work; Cycling; Service (business); Transport engineering; Geography; Environmental planning; Public transport; Engineering; Demographic economics; Civil engineering; Economics; Computer science; Marketing","score_opus":0.03312357348549458,"score_gpt":0.2417685077624137,"score_spread":0.20864493427691913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209654027","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95472085,0.001242054,0.00027269297,0.0060325586,0.000043550266,0.000058272864,0.0021515281,0.00001245298,0.035466067],"genre_scores_gemma":[0.99447745,0.00058690953,0.000108960616,0.00025306744,0.0000089817095,0.000013335468,0.00026761435,0.0000052308474,0.004278554],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99825877,0.00023975589,0.00005741818,0.00015520188,0.000609736,0.00067919784],"domain_scores_gemma":[0.9941942,0.00076858775,0.0011317101,0.00030185096,0.00233774,0.0012658746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010973801,0.00015099268,0.0002132449,0.00065895834,0.0040459516,0.0022289867,0.0010454477,0.0004396187,0.0052799233],"category_scores_gemma":[0.005761672,0.00026180263,0.00030863276,0.002223537,0.0022820886,0.0010502433,0.0015528759,0.00054472237,0.000324715],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029084092,0.000081380356,0.8959725,0.00042286806,0.00010642776,0.0004149134,0.02994182,0.0006801637,0.0005985263,0.012369731,0.018075524,0.041045394],"study_design_scores_gemma":[0.000024138055,0.000052497187,0.933693,0.00021187965,0.000051224244,0.000044257304,0.035446707,0.00040866158,0.0001986729,0.00044976833,0.02939753,0.00002169811],"about_ca_topic_score_codex":0.99370956,"about_ca_topic_score_gemma":0.9981346,"teacher_disagreement_score":0.049867485,"about_ca_system_score_codex":0.049867485,"about_ca_system_score_gemma":0.061834358,"threshold_uncertainty_score":0.36181557},"labels":[],"label_agreement":null},{"id":"W3210448246","doi":"10.32920/ryerson.14664711.v1","title":"What's Steering Consumer Preferences for Autonomous Vehicles in the Greater Toronto and Hamilton Area?","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Respondent; The Internet; Business; Public transport; Willingness to pay; Marketing; Advertising; Transport engineering; Economics; Engineering; Computer science; Political science; Microeconomics","score_opus":0.038808766103921616,"score_gpt":0.2557451725738443,"score_spread":0.2169364064699227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210448246","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99803954,0.000101990714,0.000035809106,0.00032589686,0.0000038867843,0.000009542281,0.00018737043,0.0000015108595,0.001294511],"genre_scores_gemma":[0.9992416,0.000097846496,0.000032111697,0.000041121846,0.0000026031976,0.0000037805496,0.00008652548,0.000001117215,0.00049326784],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99968505,0.000067792535,0.000011869971,0.000037965547,0.00009424015,0.00010306798],"domain_scores_gemma":[0.998863,0.00018344498,0.00030153437,0.000036995796,0.00027472174,0.00034037675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035915204,0.00011935034,0.00014493229,0.0004545219,0.00073271175,0.0011671147,0.00029452774,0.0003508792,0.003225704],"category_scores_gemma":[0.0013056826,0.0001744766,0.0003324185,0.0011638857,0.0007277109,0.00039704636,0.00032884185,0.00029118816,0.00023547884],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008765627,0.0000364644,0.985783,0.00002868124,0.00004203893,0.0001443271,0.00544333,0.00010081441,0.00035398267,0.00020690508,0.0013303615,0.00644242],"study_design_scores_gemma":[0.0000034372224,0.000022293827,0.9887664,0.000014431403,0.000012426098,0.000036928504,0.010030247,0.00019604102,0.000033557124,0.00003391825,0.00084354635,0.0000067461533],"about_ca_topic_score_codex":0.8060264,"about_ca_topic_score_gemma":0.918919,"teacher_disagreement_score":0.1939736,"about_ca_system_score_codex":0.004823382,"about_ca_system_score_gemma":0.0023711731,"threshold_uncertainty_score":0.39023185},"labels":[],"label_agreement":null},{"id":"W3211213143","doi":"","title":"Understanding the Supply of and Demand for Volunteer Driving in Canada: Knowledge Sources, Gaps, and Proposed Framework for Future Research to Support Transportation Planning for Older Adults","year":2018,"lang":"en","type":"article","venue":"Transportation Research Board 97th Annual MeetingTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Supply and demand; Marketing; Knowledge management; Computer science; Economics","score_opus":0.07195400115266602,"score_gpt":0.368677297454725,"score_spread":0.29672329630205896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211213143","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9055422,0.013867774,0.0017692805,0.04347236,0.0001905282,0.00026236408,0.016034815,0.00003814516,0.018822452],"genre_scores_gemma":[0.9818981,0.009565192,0.0022641295,0.0014824031,0.000035798883,0.00015300672,0.0032748198,0.000013860582,0.0013125865],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9975575,0.0002443376,0.00028540418,0.0003024467,0.0007078137,0.0009024844],"domain_scores_gemma":[0.983269,0.004196272,0.0018164064,0.00034960866,0.007874257,0.002494462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051917736,0.0004483902,0.0011876526,0.003966431,0.0055148993,0.0057136687,0.0025626668,0.0009678584,0.003943775],"category_scores_gemma":[0.01860311,0.0005506985,0.000963099,0.01186746,0.0015519024,0.0045900885,0.0029781188,0.0028516133,0.00020183805],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007605052,0.0003082903,0.8115458,0.0019094,0.00026191468,0.0002609309,0.063895896,0.00061574846,0.00019711825,0.006909897,0.01218351,0.101835474],"study_design_scores_gemma":[0.000016618069,0.000046567435,0.75999725,0.005356154,0.0002597491,0.00010568998,0.20912015,0.0021431572,0.00017733651,0.0039085015,0.01875867,0.00011014288],"about_ca_topic_score_codex":0.9945018,"about_ca_topic_score_gemma":0.9960055,"teacher_disagreement_score":0.047774818,"about_ca_system_score_codex":0.047774818,"about_ca_system_score_gemma":0.20433255,"threshold_uncertainty_score":0.34663224},"labels":[],"label_agreement":null},{"id":"W3211238524","doi":"10.1109/itsc48978.2021.9564977","title":"Ride-Sharing Matching under Travel Time Uncertainty through A Data-Driven Robust Optimization Approach","year":2021,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Artificial Intelligence in Medicine (Canada); Ericsson (Canada)","funders":"","keywords":"Robust optimization; Computer science; Robustness (evolution); Matching (statistics); Set (abstract data type); Mathematical optimization; Data set; Optimization problem; Data mining; Data modeling; Algorithm; Artificial intelligence; Mathematics; Statistics; Database","score_opus":0.05768482603284318,"score_gpt":0.25532223241072327,"score_spread":0.19763740637788008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211238524","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011413866,0.00014117212,0.9863566,0.00016494685,0.00002307787,0.000034997043,0.000089971734,0.00021820693,0.0015571014],"genre_scores_gemma":[0.9204455,0.00017885258,0.07631852,0.00012638453,0.0000410453,0.0001874781,0.0002482166,0.00013473748,0.0023192365],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990213,0.00027352656,0.000049878006,0.0002924995,0.00021317185,0.00014965794],"domain_scores_gemma":[0.9986008,0.00072700094,0.00021127133,0.00010666911,0.00029230918,0.00006183009],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019309756,0.0013066522,0.0018333442,0.00070010405,0.00046309837,0.0013755634,0.0019615542,0.0013315084,0.0023421317],"category_scores_gemma":[0.0038922264,0.00094355945,0.0012114374,0.00078295363,0.00089143415,0.0019642175,0.0019522049,0.0016529685,0.00028806654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009624439,0.000006264176,0.00007323603,0.000010474226,0.000012775019,0.0000102138465,0.0000074045934,0.99516124,0.00013878776,0.0018051034,0.00011590236,0.0026490355],"study_design_scores_gemma":[0.0000019307968,0.0000065522513,0.000021318117,0.00000124238,0.000002942081,0.0000018408527,0.000002457617,0.9987864,0.000081577426,0.0010087268,0.00008295404,0.0000020957798],"about_ca_topic_score_codex":0.01146583,"about_ca_topic_score_gemma":0.004809552,"teacher_disagreement_score":0.01146583,"about_ca_system_score_codex":0.001251737,"about_ca_system_score_gemma":0.0016984968,"threshold_uncertainty_score":0.02279818},"labels":[],"label_agreement":null},{"id":"W3212025653","doi":"10.1016/j.tra.2021.10.022","title":"How older adults use Ride-hailing booking technology in California","year":2021,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"TRIPS architecture; Respondent; Phone; Ordered probit; Landline; Advertising; Psychology; Business; Marketing; Gerontology; Internet privacy; Medicine; Transport engineering; Engineering; Economics; Computer science; Political science","score_opus":0.06439089619165454,"score_gpt":0.3705766325477074,"score_spread":0.30618573635605284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3212025653","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9947842,0.00051358534,0.000021759257,0.0005549782,0.000014477823,0.000010664492,0.00017669218,0.0000022787515,0.0039214334],"genre_scores_gemma":[0.9962812,0.0009156144,0.000064212814,0.00032976927,0.000013807339,0.000010970776,0.00021440658,0.000002508592,0.002167527],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995415,0.00006710987,0.000052460622,0.00010603311,0.00011856757,0.000114324095],"domain_scores_gemma":[0.9978777,0.00033781092,0.00057504995,0.0000760129,0.0006343915,0.0004990594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006899225,0.00013508058,0.0002383973,0.00068807014,0.0014112688,0.0016998185,0.00054058037,0.0006893445,0.0037088275],"category_scores_gemma":[0.004003876,0.00021627788,0.00031442297,0.00095478265,0.0004899872,0.0012335805,0.0008288117,0.000900047,0.00024457838],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014911439,0.000489701,0.9422197,0.00009164166,0.0000594281,0.00015038499,0.024200913,0.0000922436,0.00014770615,0.00035360266,0.005265716,0.026779909],"study_design_scores_gemma":[0.000011398469,0.000104785984,0.957208,0.00013549454,0.000065524255,0.000076867465,0.035562772,0.00011496499,0.000045340214,0.00008007867,0.0065816417,0.000013186541],"about_ca_topic_score_codex":0.4302756,"about_ca_topic_score_gemma":0.651738,"teacher_disagreement_score":0.4302756,"about_ca_system_score_codex":0.0024362146,"about_ca_system_score_gemma":0.0015864702,"threshold_uncertainty_score":0.8555422},"labels":[],"label_agreement":null},{"id":"W3212249121","doi":"10.1145/3474717.3483919","title":"Last Mile Delivery Considering Time-Dependent Locations","year":2021,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Last mile (transportation); Pruning; Heuristic; Task (project management); Mile; Facility location problem; Operations research; Artificial intelligence; Engineering","score_opus":0.010253950827106733,"score_gpt":0.19942631923423354,"score_spread":0.1891723684071268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3212249121","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18274692,0.005741758,0.7703448,0.005065238,0.00056966,0.00045582317,0.012227369,0.0026729298,0.020175487],"genre_scores_gemma":[0.73558104,0.0026422036,0.23986633,0.0005688993,0.0002989826,0.00032252786,0.009722428,0.0005013012,0.010496237],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99838173,0.0005175316,0.0000856504,0.00054541475,0.00023066206,0.00023898068],"domain_scores_gemma":[0.99524873,0.0028273999,0.00049278315,0.00078317674,0.00035302498,0.00029487876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016489954,0.0015306546,0.001475643,0.0012671135,0.0017630432,0.0021520325,0.0027722165,0.002495829,0.006508101],"category_scores_gemma":[0.009940247,0.001001366,0.0015455076,0.0033248053,0.001151608,0.005339041,0.0020620192,0.0021219582,0.0011820658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041346392,0.00014132037,0.0036674233,0.00044502568,0.00008647562,0.00053602556,0.00020688056,0.876204,0.0014414417,0.0315362,0.02387023,0.061451595],"study_design_scores_gemma":[0.00008418135,0.00011118394,0.0009573121,0.000056425022,0.0000507233,0.0004188182,0.0002975207,0.93597984,0.0012958396,0.045589037,0.015127059,0.00003209355],"about_ca_topic_score_codex":0.013296715,"about_ca_topic_score_gemma":0.015245472,"teacher_disagreement_score":0.013296715,"about_ca_system_score_codex":0.0023232112,"about_ca_system_score_gemma":0.0023570939,"threshold_uncertainty_score":0.026438653},"labels":[],"label_agreement":null},{"id":"W3212360012","doi":"10.32920/ryerson.14662929.v1","title":"Design and Development of an Intelligent Agent-Based Supply Chain Simulation System","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Supply chain; Point of sale; Supply chain management; Computer science; Product (mathematics); Loan; Production (economics); Order (exchange); Business; Finance; Marketing; Economics; Microeconomics","score_opus":0.04549506273547051,"score_gpt":0.26278866660790723,"score_spread":0.21729360387243674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3212360012","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015129665,0.00008582355,0.97103405,0.00014294565,0.00004801642,0.000512879,0.00015312826,0.008311256,0.0045821397],"genre_scores_gemma":[0.27249888,0.00029679705,0.72034127,0.00011872997,0.000023886154,0.0011669537,0.0007318018,0.0002600989,0.0045617362],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996191,0.00010901626,0.00004926586,0.00007775928,0.00011333747,0.000031539803],"domain_scores_gemma":[0.99949896,0.00016232039,0.000046207428,0.00006302221,0.00016647822,0.0000630551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007462601,0.0005867028,0.0008455697,0.0004701416,0.00056591316,0.001225425,0.0016816133,0.00082819874,0.004137615],"category_scores_gemma":[0.0012973351,0.00047940828,0.00051808194,0.00041574278,0.00031871127,0.0011032053,0.00078128895,0.00088899885,0.0011336084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041781826,0.0004909885,0.0041431407,0.0004877012,0.0001659255,0.0004945582,0.00048178682,0.77961326,0.030981766,0.028329471,0.005924212,0.14846945],"study_design_scores_gemma":[0.000040111336,0.00003606058,0.00013498502,0.000010075207,0.000020049367,0.00002793514,0.000015509522,0.99005365,0.0031830408,0.0009431272,0.0055243983,0.000011005872],"about_ca_topic_score_codex":0.0036513382,"about_ca_topic_score_gemma":0.0019276995,"teacher_disagreement_score":0.004137615,"about_ca_system_score_codex":0.0007786189,"about_ca_system_score_gemma":0.001516669,"threshold_uncertainty_score":0.013841689},"labels":[],"label_agreement":null},{"id":"W3213464317","doi":"10.1007/978-3-030-90275-9_29","title":"Crowdsourcing Electrified Mobility for Omni-Sharing Distributed Energy Resources","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in operations research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Energy storage; Scalability; Energy market; Distributed computing; Distributed generation; Environmental economics; Renewable energy; Engineering; Economics","score_opus":0.04848640905911988,"score_gpt":0.31772847684202776,"score_spread":0.2692420677829079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3213464317","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08209711,0.0011229764,0.8537007,0.00088440627,0.00078949914,0.00012394538,0.00012909598,0.0007525598,0.060399584],"genre_scores_gemma":[0.93399656,0.00041557985,0.03672361,0.00012333786,0.00010663735,0.00006301548,0.00009781097,0.00008882726,0.028384596],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997981,0.00004249453,0.000005536021,0.00004551265,0.00007049164,0.00003795985],"domain_scores_gemma":[0.9997603,0.00012968667,0.000010893495,0.0000415789,0.000038290436,0.000019301327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042858234,0.00047816554,0.0006073198,0.000263824,0.0005961171,0.0008900245,0.0012196574,0.0007952459,0.0049851947],"category_scores_gemma":[0.001121749,0.00023015951,0.0005238443,0.000478104,0.00052157266,0.0009859425,0.0019045876,0.0006673501,0.00066974165],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025558623,0.000117249474,0.00051479926,0.00015990471,0.00007942361,0.00045060826,0.00034648055,0.73484975,0.012769845,0.047936015,0.012158617,0.19036177],"study_design_scores_gemma":[0.000017255905,0.00005688367,0.000196089,0.000014640441,0.000012623799,0.00006731925,0.00013420015,0.96127397,0.0016276818,0.027162442,0.0094200615,0.000016873317],"about_ca_topic_score_codex":0.0030136767,"about_ca_topic_score_gemma":0.004902378,"teacher_disagreement_score":0.0049851947,"about_ca_system_score_codex":0.0006117792,"about_ca_system_score_gemma":0.00043348645,"threshold_uncertainty_score":0.016677082},"labels":[],"label_agreement":null},{"id":"W3214007060","doi":"10.1016/j.tra.2021.11.013","title":"How has the COVID-19 pandemic affected the use of ride-sourcing services? An empirical evidence-based investigation for the Greater Toronto Area","year":2021,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Business; Strategic sourcing; Marketing; Strategic planning","score_opus":0.6210030759530426,"score_gpt":0.46697405107261275,"score_spread":0.15402902488042985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214007060","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9765912,0.005493571,0.00013335871,0.006599409,0.000061498446,0.0001770261,0.002890529,0.000004444705,0.008048989],"genre_scores_gemma":[0.9954165,0.0025639362,0.000112443595,0.00064303854,0.000028445977,0.000047143567,0.00053016545,0.0000032353548,0.0006551438],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9957028,0.0013022071,0.0003326817,0.000390348,0.0008883398,0.0013835706],"domain_scores_gemma":[0.97388655,0.008027985,0.009355744,0.00076351565,0.004976319,0.002989838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046886336,0.00041088636,0.0005799234,0.0015659642,0.002333002,0.0036259363,0.0017241283,0.0015122448,0.004863749],"category_scores_gemma":[0.027466193,0.00046464137,0.00078829104,0.0047276826,0.0032618574,0.0021027245,0.0027791155,0.0021451693,0.00021865884],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031826532,0.00021726465,0.9621489,0.0009973997,0.00046338077,0.0004416178,0.016666675,0.00067489827,0.00016491323,0.0037941998,0.0034000077,0.010712459],"study_design_scores_gemma":[0.000039253053,0.00017160717,0.94617695,0.0009683602,0.0004116795,0.00006960587,0.045674514,0.00058792863,0.00012680082,0.00028355097,0.0054512075,0.000038555],"about_ca_topic_score_codex":0.94327873,"about_ca_topic_score_gemma":0.97261345,"teacher_disagreement_score":0.05672127,"about_ca_system_score_codex":0.04142899,"about_ca_system_score_gemma":0.047408663,"threshold_uncertainty_score":0.3005898},"labels":[],"label_agreement":null},{"id":"W3214394391","doi":"10.1155/2021/1368286","title":"Modeling and Optimization of Multiaction Dynamic Dispatching Problem for Shared Autonomous Electric Vehicles","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Reinforcement learning; Markov decision process; Process (computing); Mathematical optimization; Automation; Microsimulation; Operations research; Dynamic programming; Optimization problem; Revenue; Simulation; Markov process; Engineering; Algorithm; Artificial intelligence; Transport engineering","score_opus":0.007377329882275684,"score_gpt":0.23632263157251018,"score_spread":0.2289453016902345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214394391","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08942675,0.0011337191,0.89562744,0.0010883465,0.00014756346,0.00009659025,0.00037026865,0.0002461776,0.011863098],"genre_scores_gemma":[0.95337266,0.0005260636,0.038624644,0.00014961096,0.00005138014,0.00022881888,0.000303913,0.00007319066,0.0066696135],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994698,0.00014804018,0.000027589542,0.00013628599,0.00009102384,0.0001272447],"domain_scores_gemma":[0.9989794,0.0006476649,0.00012070969,0.000026988584,0.00015784448,0.000067408655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010188246,0.0012987055,0.0015296894,0.00058023934,0.0005683091,0.0016545501,0.001114649,0.0017014699,0.0027835604],"category_scores_gemma":[0.0020265519,0.0008169275,0.0011836613,0.00071261,0.0009368177,0.00087328703,0.0010380137,0.0016038371,0.00020097083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011430606,0.000008073644,0.00019025373,0.00001665918,0.000009040318,0.000026339092,0.000009895819,0.99663085,0.00008724959,0.0018440456,0.00015646727,0.0010096927],"study_design_scores_gemma":[0.0000022516813,0.000003016875,0.000034515113,0.0000010151551,0.0000017635093,0.0000014061492,0.00000359268,0.9994466,0.000017611927,0.00043880293,0.00004822353,0.0000012083317],"about_ca_topic_score_codex":0.033785325,"about_ca_topic_score_gemma":0.015549799,"teacher_disagreement_score":0.033785325,"about_ca_system_score_codex":0.0013742913,"about_ca_system_score_gemma":0.002365927,"threshold_uncertainty_score":0.067177296},"labels":[],"label_agreement":null},{"id":"W3214881281","doi":"10.32920/ryerson.14644080.v1","title":"Among four traveller types in the Greater Toronto and Hamilton Region, who uses ride-hailing?","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Popularity; Business; Variety (cybernetics); Service (business); Advertising; Geography; Marketing; Psychology; Computer science","score_opus":0.026101884929456712,"score_gpt":0.2251534011919231,"score_spread":0.19905151626246637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214881281","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982639,0.00010788411,0.00004765173,0.00015082449,0.0000022178197,0.000019524923,0.00048641188,0.0000043134883,0.00091731624],"genre_scores_gemma":[0.9971981,0.00022865544,0.000107086504,0.0000452659,0.0000021837438,0.000016770808,0.0004102789,0.0000031841048,0.001988549],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99975103,0.00003026719,0.00001566115,0.000037818296,0.000054648346,0.00011058004],"domain_scores_gemma":[0.9993961,0.000050332208,0.00018622518,0.000023738547,0.00012474877,0.00021888182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021346135,0.00017443168,0.00017793183,0.00084946904,0.0016358123,0.0012461684,0.0005330937,0.0003218898,0.0032700063],"category_scores_gemma":[0.0010623018,0.00017721292,0.00023788578,0.001849628,0.00068412046,0.0006255932,0.00077597605,0.00036505767,0.00039626306],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041474545,0.000017157627,0.9786128,0.000050594637,0.000019399205,0.00026584658,0.01385339,0.00005864565,0.00039411863,0.00017125055,0.0008340086,0.0056814468],"study_design_scores_gemma":[0.0000011293132,0.000021043179,0.9593276,0.000020581156,0.000007747417,0.000081397644,0.039571036,0.0000989172,0.00005208893,0.000020251584,0.00079024635,0.000008057137],"about_ca_topic_score_codex":0.8798364,"about_ca_topic_score_gemma":0.96005297,"teacher_disagreement_score":0.12016362,"about_ca_system_score_codex":0.0044446816,"about_ca_system_score_gemma":0.003412795,"threshold_uncertainty_score":0.24174255},"labels":[],"label_agreement":null},{"id":"W3215645715","doi":"","title":"Multimodal Transportation with Ridesharing of Personal Vehicles.","year":2021,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Public transport; Transport engineering; Matching (statistics); Transit (satellite); Occupancy; Travel behavior; Computer science; Population; Engineering; Mathematics","score_opus":0.030107747745740057,"score_gpt":0.1537111175561983,"score_spread":0.12360336981045823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215645715","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13462818,0.0013662141,0.8439802,0.0004089018,0.00016373389,0.00021179586,0.00091908826,0.003996558,0.01432536],"genre_scores_gemma":[0.9065144,0.00040832665,0.08565198,0.00009129665,0.000080292724,0.00006861568,0.00093820505,0.00007475338,0.0061721113],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994985,0.00012695187,0.000020630652,0.00017640804,0.000097498916,0.00008005584],"domain_scores_gemma":[0.9995433,0.0000747936,0.000067683446,0.00018035136,0.00007984404,0.00005411511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004566686,0.00067231915,0.0006591622,0.0005360155,0.0008351873,0.0009975262,0.0010901593,0.00064795197,0.0040491465],"category_scores_gemma":[0.0016326583,0.00023830596,0.00068421796,0.00097267557,0.0004878829,0.0012816894,0.0013699573,0.00058951747,0.0012703683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027452025,0.00022521737,0.00951356,0.00026789695,0.00017459273,0.00034217388,0.00022256444,0.5078803,0.014283393,0.0120919645,0.009583495,0.44514042],"study_design_scores_gemma":[0.000014164907,0.00015891102,0.0036051774,0.0000170968,0.00006595287,0.0002524796,0.00011062969,0.9745345,0.00376902,0.006213806,0.011226887,0.00003140372],"about_ca_topic_score_codex":0.014711068,"about_ca_topic_score_gemma":0.02167798,"teacher_disagreement_score":0.014711068,"about_ca_system_score_codex":0.0009078952,"about_ca_system_score_gemma":0.0008021367,"threshold_uncertainty_score":0.02925092},"labels":[],"label_agreement":null},{"id":"W3215740398","doi":"10.1109/mascots53633.2021.9614305","title":"Simulation Modeling of Urban E-Scooter Mobility","year":2021,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Transport engineering; Workload; Globe; Computer science; Battery (electricity); Battery capacity; Engineering","score_opus":0.023418134768916785,"score_gpt":0.24984632598924225,"score_spread":0.22642819122032548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215740398","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8820224,0.00024466385,0.08656263,0.0007801763,0.00010158657,0.00020748854,0.0025490173,0.000604508,0.026927467],"genre_scores_gemma":[0.98814917,0.00016409316,0.0069302046,0.000050121,0.000011311645,0.00012236842,0.00091120886,0.00003639047,0.0036251936],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996873,0.00010182645,0.000018376426,0.00005365114,0.000052482388,0.00008644858],"domain_scores_gemma":[0.99903417,0.0004853745,0.00009663872,0.000064472464,0.00020357642,0.00011583007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041147252,0.00071230106,0.0006188561,0.0006036726,0.0006764415,0.0009825559,0.0014257032,0.001413091,0.0029015667],"category_scores_gemma":[0.0014806681,0.00041532607,0.0006838464,0.0011726298,0.0005791293,0.000844677,0.00073655974,0.00070650625,0.00039567682],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012497205,0.000016642556,0.0005872214,0.000005370707,0.0000046953273,0.000023003246,0.000016825777,0.9981337,0.0001644902,0.0005686198,0.000101373196,0.0003656617],"study_design_scores_gemma":[0.0000058327114,0.000008573522,0.00019772242,0.0000014841836,0.000002268724,0.000003798941,0.000021447517,0.9993032,0.00007376195,0.00020352427,0.00017572854,0.0000026527155],"about_ca_topic_score_codex":0.055451505,"about_ca_topic_score_gemma":0.029863426,"teacher_disagreement_score":0.055451505,"about_ca_system_score_codex":0.0015381295,"about_ca_system_score_gemma":0.0012545491,"threshold_uncertainty_score":0.11025751},"labels":[],"label_agreement":null},{"id":"W32441414","doi":"10.1111/acem.14033","title":"Ruimtelijk beleid om mobiliteitsredenen","year":2012,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fonds de Recherche du Québec - Santé","keywords":"Theology; Political science; Philosophy","score_opus":0.0091819455059171,"score_gpt":0.2040423911109448,"score_spread":0.1948604456050277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W32441414","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.492642,0.2496105,0.033017892,0.039525874,0.013540562,0.0005096855,0.007978516,0.00076378055,0.16241118],"genre_scores_gemma":[0.7594955,0.1422632,0.019415855,0.003919485,0.001716655,0.0005032421,0.0045984015,0.00063854386,0.06744918],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974414,0.0008769823,0.00024114989,0.0001910052,0.00096921384,0.00028021698],"domain_scores_gemma":[0.9987018,0.0005731944,0.00024081694,0.000049380178,0.00021298218,0.00022170374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001628648,0.0008889862,0.0010109566,0.0008353008,0.00094214955,0.004299392,0.001028592,0.0013352336,0.033033375],"category_scores_gemma":[0.008716715,0.0005457168,0.0011087771,0.00064647465,0.00084136025,0.0017515753,0.0019645372,0.0026215173,0.004280244],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020055524,0.0021627797,0.022066744,0.010219455,0.0009910024,0.0056323977,0.0062426263,0.0046567433,0.011734285,0.016948067,0.091325745,0.82601464],"study_design_scores_gemma":[0.0007238175,0.0018283859,0.08618131,0.01450282,0.0010252062,0.0067904564,0.012303079,0.0046246783,0.006460005,0.02626604,0.8389652,0.00032905847],"about_ca_topic_score_codex":0.020472853,"about_ca_topic_score_gemma":0.034772687,"teacher_disagreement_score":0.033033375,"about_ca_system_score_codex":0.0012184602,"about_ca_system_score_gemma":0.0024106828,"threshold_uncertainty_score":0.11050761},"labels":[],"label_agreement":null},{"id":"W331616981","doi":"","title":"On the Net : PDAs and medicine","year":2001,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; World Wide Web; Data science; Multimedia","score_opus":0.007515074951412573,"score_gpt":0.21195797971775862,"score_spread":0.20444290476634605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W331616981","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002128347,0.29136845,0.002465052,0.40507206,0.017344851,0.000020014573,0.00018454774,0.00024434068,0.28117236],"genre_scores_gemma":[0.076731704,0.45253858,0.005278452,0.17738903,0.03599334,0.000108066655,0.00027677134,0.00015940044,0.2515247],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988973,0.0004764663,0.00004760309,0.00012442173,0.0003389725,0.00011510367],"domain_scores_gemma":[0.99764085,0.0009494752,0.00017936462,0.00012132668,0.00040946348,0.00069952913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013577221,0.0005725987,0.00054604455,0.0015967885,0.0023209443,0.009815182,0.00084108685,0.005986164,0.04502338],"category_scores_gemma":[0.0044231736,0.00019669115,0.0002742023,0.0014804143,0.0062332735,0.011038659,0.00371629,0.0049722875,0.014838101],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010309056,0.000074992684,0.0016829506,0.00056756433,0.00002405775,0.00023810544,0.000939136,0.00018344462,0.00026663058,0.16352381,0.49505687,0.3373394],"study_design_scores_gemma":[0.000013758501,0.00004679914,0.001142287,0.000998603,0.000011384572,0.00050959404,0.0010418791,0.00007498292,0.00007151973,0.06298486,0.93308246,0.000021951057],"about_ca_topic_score_codex":0.0045007337,"about_ca_topic_score_gemma":0.00696526,"teacher_disagreement_score":0.04502338,"about_ca_system_score_codex":0.0021762406,"about_ca_system_score_gemma":0.0021507978,"threshold_uncertainty_score":0.1506182},"labels":[],"label_agreement":null},{"id":"W340734473","doi":"10.1609/aaai.v28i1.9050","title":"Schedule-Based Robotic Search for Multiple Residents in a Retirement Home Environment","year":2014,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; Deutscher Akademischer Austauschdienst","keywords":"Schedule; USB; Plan (archaeology); Computer science; Order (exchange); Robot; Recreation; Operations research; Artificial intelligence; Business; Engineering; Finance; Geography","score_opus":0.07801174600256178,"score_gpt":0.280347239729494,"score_spread":0.20233549372693221,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W340734473","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26827013,0.00032562696,0.7273583,0.00023958829,0.000026320264,0.00010719129,0.00012086072,0.0008169758,0.0027349764],"genre_scores_gemma":[0.8581876,0.000096796255,0.13898283,0.00004440328,0.000008812723,0.00010910134,0.00011398091,0.000055879224,0.0024005263],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998242,0.00005518299,0.0000067458677,0.000041791183,0.000042289248,0.000029705494],"domain_scores_gemma":[0.99967575,0.00015805426,0.000053751926,0.000026470607,0.000038048885,0.00004793395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004121346,0.00046560503,0.0006450972,0.0004127385,0.00040182853,0.00032202332,0.0007525499,0.0006038314,0.0018161028],"category_scores_gemma":[0.001234418,0.00037271497,0.00043680132,0.00029696105,0.0004648137,0.00060118636,0.0007606996,0.00034062643,0.00020449093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000188916,0.000063667794,0.0014414503,0.000065047054,0.0000356971,0.00014067297,0.00014846724,0.9522842,0.0031199947,0.0039415383,0.00075627543,0.037813995],"study_design_scores_gemma":[0.00002409473,0.000094576724,0.0004052329,0.000004502894,0.000010186892,0.00004093433,0.000052952655,0.99529135,0.00077060354,0.002703246,0.0005956404,0.0000066054135],"about_ca_topic_score_codex":0.006259966,"about_ca_topic_score_gemma":0.007916914,"teacher_disagreement_score":0.006259966,"about_ca_system_score_codex":0.0005144309,"about_ca_system_score_gemma":0.0010904382,"threshold_uncertainty_score":0.012447059},"labels":[],"label_agreement":null},{"id":"W4200085142","doi":"10.1155/2021/8868291","title":"Dispatching Design for Customized Bus of Hybrid Vehicles Based on Reservation Data","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Reservation; Public transport; Scheduling (production processes); Genetic algorithm; Plan (archaeology); Computer science; Transport engineering; Operations research; Engineering; Computer network; Operations management","score_opus":0.04120117330979483,"score_gpt":0.28423757127861465,"score_spread":0.24303639796881982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200085142","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06775938,0.00024022235,0.92144674,0.00017093208,0.00007913967,0.00013273463,0.00013459442,0.0002471244,0.009789189],"genre_scores_gemma":[0.94624174,0.00019244691,0.04888812,0.00002729475,0.0000233198,0.00018063962,0.00013376508,0.00004112817,0.0042715822],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997396,0.000052555704,0.000012669718,0.00007801951,0.000056932477,0.000060178285],"domain_scores_gemma":[0.9998518,0.0000379388,0.000027490125,0.000009776755,0.00005390293,0.000019041927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040474435,0.00066075474,0.00063238305,0.00037651454,0.00049344834,0.00082051125,0.0010513419,0.00044886165,0.0028570583],"category_scores_gemma":[0.00049216097,0.00043491233,0.00063611753,0.00036334596,0.00030018104,0.00059463916,0.00052053883,0.00043855887,0.00027033838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004838472,0.000018725714,0.00039828266,0.0000556652,0.000016882299,0.00005539274,0.000041948908,0.97812486,0.0031384774,0.00658694,0.00056715345,0.010947176],"study_design_scores_gemma":[0.000005725103,0.000027881135,0.00008125214,0.0000015286281,0.0000046862147,0.000007662999,0.000012662607,0.9986545,0.00028233838,0.0005445304,0.00037396202,0.000003209471],"about_ca_topic_score_codex":0.010215002,"about_ca_topic_score_gemma":0.006305189,"teacher_disagreement_score":0.010215002,"about_ca_system_score_codex":0.00087054947,"about_ca_system_score_gemma":0.0012908237,"threshold_uncertainty_score":0.020311117},"labels":[],"label_agreement":null},{"id":"W4200209333","doi":"10.1186/s10033-021-00652-6","title":"Key Technologies in Connected Autonomous Electrified Vehicles","year":2021,"lang":"en","type":"article","venue":"Chinese Journal of Mechanical Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Key (lock); Computer science; Computer security","score_opus":0.006649091057080913,"score_gpt":0.21121564727647216,"score_spread":0.20456655621939124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200209333","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14893433,0.022297781,0.5618655,0.0041776597,0.00183403,0.00024567885,0.00059943734,0.0008619202,0.25918353],"genre_scores_gemma":[0.90218,0.010663541,0.030471565,0.00031290995,0.00026918502,0.00014428276,0.00034126386,0.000056435492,0.055560797],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99983776,0.000024795294,0.000008541716,0.000051588013,0.00005100606,0.00002626704],"domain_scores_gemma":[0.9998944,0.000030694857,0.000013519764,0.000015410355,0.000033263772,0.000012831814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012726602,0.00028494495,0.0002528857,0.0006392539,0.0005576095,0.0012406004,0.00066242996,0.00090795534,0.007462169],"category_scores_gemma":[0.00033792047,0.0001434905,0.00023063707,0.0008917434,0.0005852473,0.002604259,0.001037596,0.0006431521,0.0013650579],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012392832,0.00007284363,0.0014606816,0.0005660432,0.000030705552,0.0007115841,0.00053416804,0.026697008,0.026358431,0.73265773,0.007907583,0.20287938],"study_design_scores_gemma":[0.00003953222,0.00031996114,0.0031253896,0.00025663336,0.000060595634,0.0014265312,0.0011928792,0.14210549,0.019441338,0.5559954,0.27598256,0.000053733726],"about_ca_topic_score_codex":0.00056808104,"about_ca_topic_score_gemma":0.00036145115,"teacher_disagreement_score":0.007462169,"about_ca_system_score_codex":0.00061482546,"about_ca_system_score_gemma":0.0004335168,"threshold_uncertainty_score":0.024963439},"labels":[],"label_agreement":null},{"id":"W4200271168","doi":"10.1016/j.resglo.2021.100077","title":"Does ridesharing affect road safety? the introduction of Moto-Uber and other factors in the Dominican Republic","year":2021,"lang":"en","type":"article","venue":"Research in Globalization","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Public Health Ontario; University of Toronto; McGill University Health Centre; Université de Sherbrooke","funders":"Fonds de Recherche du Québec - Santé; Social Sciences and Humanities Research Council of Canada","keywords":"Affect (linguistics); Transport engineering; Psychology; Engineering","score_opus":0.04444851853249384,"score_gpt":0.34459406307431956,"score_spread":0.30014554454182574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200271168","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99596715,0.0011680458,0.000044408833,0.0009886513,0.00001545764,0.000011021904,0.00039655858,0.000004203583,0.0014046049],"genre_scores_gemma":[0.99891317,0.00044570933,0.00002915893,0.00012034605,0.000013525677,0.0000051144457,0.00016799949,0.0000023181583,0.00030261313],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999521,0.0001511745,0.000034655033,0.00008839553,0.000056695524,0.00014805005],"domain_scores_gemma":[0.9987871,0.00017558134,0.0006941853,0.000058174224,0.0001071871,0.00017790889],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005210042,0.00021259728,0.00020406437,0.0007073396,0.00044027754,0.0011153824,0.0004035575,0.0004020057,0.0018103437],"category_scores_gemma":[0.0022651055,0.00013326654,0.00039334584,0.0010535406,0.0006618655,0.000500619,0.00059563323,0.00062119414,0.00009189736],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004843047,0.000052194613,0.9942854,0.000037296046,0.00007398531,0.00017860833,0.00057004014,0.00015987566,0.00024263712,0.00012013837,0.00037135463,0.0038600946],"study_design_scores_gemma":[0.0000017830928,0.000013403227,0.99814355,0.000022892908,0.000016400269,0.000029244366,0.0009309919,0.00007728413,0.00002770161,0.000017418846,0.0007169169,0.0000024300205],"about_ca_topic_score_codex":0.1964616,"about_ca_topic_score_gemma":0.20506486,"teacher_disagreement_score":0.1964616,"about_ca_system_score_codex":0.0018893867,"about_ca_system_score_gemma":0.001202795,"threshold_uncertainty_score":0.39063615},"labels":[],"label_agreement":null},{"id":"W4200320960","doi":"10.18280/mmep.080612","title":"A SMDP Approach to Evaluate the Performance of a Vehicular Cloud Computing System with Prioritize Requests","year":2021,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Cloud computing; Markov decision process; Resource allocation; Scheme (mathematics); Service (business); Computation; Distributed computing; Process (computing); Resource (disambiguation); Operations research; Mathematical optimization; Markov process; Computer network; Engineering; Algorithm","score_opus":0.020167480870826315,"score_gpt":0.2040294575473703,"score_spread":0.183861976676544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200320960","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20185682,0.00048828596,0.7882344,0.000583349,0.00011316331,0.00021277172,0.00029025006,0.0002827466,0.007938155],"genre_scores_gemma":[0.9744299,0.00012877607,0.024255222,0.000028699453,0.000011845843,0.00010817393,0.00007230181,0.00001314779,0.00095195323],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993319,0.0003298133,0.00003024054,0.00007166696,0.00011208304,0.00012429817],"domain_scores_gemma":[0.99868685,0.0009349509,0.000098785014,0.000032607295,0.0001811298,0.00006571871],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013378412,0.0008595392,0.0008769037,0.00056484505,0.00049176544,0.0009016494,0.000731981,0.00094580016,0.001897525],"category_scores_gemma":[0.0023243818,0.00033018517,0.0007122752,0.0005057021,0.0005880105,0.00043971612,0.0006874232,0.0008927627,0.0000886567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002881591,0.000014017501,0.0002674606,0.00001717501,0.000013506584,0.000017371332,0.000008692764,0.9959346,0.00031290698,0.0019972816,0.000080925354,0.0013072503],"study_design_scores_gemma":[0.0000016211025,0.000013706774,0.00003876986,7.780509e-7,0.000002109038,0.0000013288235,0.0000041666976,0.99956816,0.000069658214,0.00026746458,0.00003109354,0.0000011880095],"about_ca_topic_score_codex":0.017008446,"about_ca_topic_score_gemma":0.007353156,"teacher_disagreement_score":0.017008446,"about_ca_system_score_codex":0.0018550518,"about_ca_system_score_gemma":0.0014889437,"threshold_uncertainty_score":0.0338189},"labels":[],"label_agreement":null},{"id":"W4200391575","doi":"10.1287/trsc.2021.1101","title":"Vehicle Routing with Stochastic Supply of Crowd Vehicles and Time Windows","year":2021,"lang":"en","type":"article","venue":"Transportation Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Polytechnique Montréal; Transport Canada","funders":"","keywords":"Column generation; Heuristic; Vehicle routing problem; Computer science; Crowdsourcing; Operations research; Last mile (transportation); Routing (electronic design automation); Transport engineering; Mathematical optimization; Engineering; Computer network; Mile; Mathematics","score_opus":0.00854635132175214,"score_gpt":0.2179255727113468,"score_spread":0.20937922138959467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200391575","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2753992,0.00071923574,0.71375436,0.00066473236,0.00015365762,0.00025551187,0.0009523878,0.00059066026,0.0075102947],"genre_scores_gemma":[0.9374904,0.00033055595,0.054364216,0.000087850945,0.00006101581,0.00017411418,0.00039733993,0.000086971166,0.007007517],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986935,0.00041999007,0.000055240253,0.0002746023,0.00018941244,0.00036721115],"domain_scores_gemma":[0.99798167,0.001151573,0.00035620338,0.000107278844,0.00016241685,0.00024086186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015106171,0.0014328401,0.001848228,0.0008420227,0.0008474139,0.0019944042,0.0017929033,0.0016427853,0.0035505753],"category_scores_gemma":[0.0029848532,0.0014896181,0.0013452517,0.0014478893,0.0012324026,0.001588749,0.001263611,0.0012047534,0.00039331525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000348828,0.000009706281,0.00013394139,0.000010176685,0.000010038766,0.000035651356,0.000009061505,0.9961468,0.00014889381,0.0024179853,0.00013197036,0.000910801],"study_design_scores_gemma":[0.000009149591,0.000013899919,0.00005428862,0.0000014912927,0.0000037248112,0.000009017315,0.000008483152,0.99720937,0.000079419726,0.0024585447,0.0001488119,0.0000038507465],"about_ca_topic_score_codex":0.012726817,"about_ca_topic_score_gemma":0.009041779,"teacher_disagreement_score":0.012726817,"about_ca_system_score_codex":0.0023103498,"about_ca_system_score_gemma":0.0016453454,"threshold_uncertainty_score":0.02530545},"labels":[],"label_agreement":null},{"id":"W4200484434","doi":"10.15353/cjds.v10i3.821","title":"The Time Has Come, the Walrus Said, to Talk of Many Things: Wheelchair Securement Spaces on Commercial Airlines","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Disability Studies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Wheelchair; Dignity; Process (computing); Autonomy; Pace; Business; Internet privacy; Statute; Legislation; CONTEST; Public relations; Computer security; Computer science; Marketing; Law and economics; Law; Sociology; Political science","score_opus":0.03270607420462409,"score_gpt":0.2610127637745249,"score_spread":0.22830668956990083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200484434","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014956186,0.0061704125,0.00043816786,0.95859915,0.023936402,0.0000147554965,0.00007676643,0.0000603362,0.009208366],"genre_scores_gemma":[0.02725222,0.008866096,0.0011591122,0.828447,0.010107305,0.000053419673,0.000078500576,0.00016720376,0.12386924],"study_design_codex":"not_applicable","study_design_gemma":"qualitative","domain_scores_codex":[0.9971623,0.0007740965,0.00016757488,0.00036155825,0.0009500448,0.00058443716],"domain_scores_gemma":[0.9937644,0.002182084,0.00025773846,0.00023019273,0.0021508657,0.0014146002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043334826,0.0010032348,0.00068725133,0.0012061686,0.009738973,0.008599902,0.0012245482,0.016190281,0.013201008],"category_scores_gemma":[0.0113116,0.0005848149,0.0011822027,0.0007329744,0.006137816,0.011981554,0.0043397704,0.024465816,0.0055165756],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031448726,0.000032229713,0.000457941,0.00006580508,0.000010535982,0.00013307945,0.0026975563,0.000038339454,0.0002479094,0.013240403,0.96784884,0.015195918],"study_design_scores_gemma":[0.000010543139,0.000031130723,0.0007696537,0.0002014782,0.000013231742,0.0001555079,0.005940357,0.000057764286,0.00023154508,0.0019040812,0.99063444,0.000050385213],"about_ca_topic_score_codex":0.042051062,"about_ca_topic_score_gemma":0.054096453,"teacher_disagreement_score":0.9579489,"about_ca_system_score_codex":0.005677559,"about_ca_system_score_gemma":0.00911791,"threshold_uncertainty_score":0.08361262},"labels":[],"label_agreement":null},{"id":"W4200616981","doi":"10.1109/vtc2021-fall52928.2021.9625353","title":"Taxi Dispatch and AEV Management in AEV Taxi Services","year":2021,"lang":"en","type":"article","venue":"2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Adaptability; Scheduling (production processes); Computer science; Service (business); Idle; Transport engineering; Operations research; Business; Operations management; Engineering; Marketing","score_opus":0.007292265237174774,"score_gpt":0.21233062287952895,"score_spread":0.20503835764235417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200616981","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36864087,0.000699538,0.5713241,0.001078218,0.0003046252,0.0003477821,0.00067559956,0.0025775142,0.054351743],"genre_scores_gemma":[0.95577437,0.00020925619,0.03262194,0.000062291234,0.00003247847,0.000054976645,0.00031686484,0.0000681463,0.010859693],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978334,0.000031551364,0.000014279547,0.000056706725,0.00005536655,0.00005869468],"domain_scores_gemma":[0.9999068,0.000012009015,0.000010812862,0.000013438894,0.000038057027,0.00001887459],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016805495,0.00026536637,0.0002954057,0.0003206955,0.00061398133,0.0012341123,0.00064284937,0.0004397239,0.0031423313],"category_scores_gemma":[0.00034780754,0.00016644014,0.00020188886,0.00045118007,0.0001746792,0.0008531982,0.0005731169,0.000382488,0.0009169644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005544374,0.00037820812,0.019496972,0.00018597343,0.000058845886,0.0006981557,0.00086833164,0.3307487,0.08122733,0.040104315,0.017575245,0.50810355],"study_design_scores_gemma":[0.000017780114,0.000084173626,0.004501433,0.000013456134,0.000020601545,0.00017393209,0.000510524,0.94395775,0.014865323,0.00412854,0.031699296,0.000027160424],"about_ca_topic_score_codex":0.010499401,"about_ca_topic_score_gemma":0.008350529,"teacher_disagreement_score":0.010499401,"about_ca_system_score_codex":0.0007256261,"about_ca_system_score_gemma":0.0011986808,"threshold_uncertainty_score":0.020876527},"labels":[],"label_agreement":null},{"id":"W4205164708","doi":"10.1155/2021/2145716","title":"The Impact of Fleet Coordination on Taxi Operations","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Agence Nationale de la Recherche","keywords":"Operator (biology); Work (physics); Fleet management; Service (business); Mode (computer interface); Quality (philosophy); Service quality","score_opus":0.00903848489271022,"score_gpt":0.2738776465939428,"score_spread":0.2648391617012326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205164708","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98230916,0.00017093372,0.01174976,0.00022153801,0.000032780452,0.000035686222,0.00025219878,0.00009861489,0.005129376],"genre_scores_gemma":[0.99870896,0.000037086065,0.0009053004,0.000007573681,0.000003068109,0.000007209606,0.000082597435,0.0000123344125,0.00023584525],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99910057,0.00031831537,0.00002666437,0.00016077422,0.00013456064,0.00025913233],"domain_scores_gemma":[0.9957969,0.0024960926,0.00051166303,0.00040926525,0.00037444098,0.00041166815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012104916,0.0005764279,0.00049393513,0.00053677626,0.00064044824,0.0012311524,0.0006427259,0.0006188847,0.0022819724],"category_scores_gemma":[0.006834495,0.0003026789,0.00043943056,0.0006519461,0.00074095355,0.0014965537,0.0010174651,0.00076202775,0.00015703235],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013184814,0.00004451138,0.007539724,0.000015879801,0.00003017296,0.00009435981,0.000029707664,0.9859822,0.00070939,0.0013516297,0.0002284661,0.003842185],"study_design_scores_gemma":[0.00003170596,0.00036024812,0.02137402,0.000013213181,0.000044308254,0.00008201453,0.00035219692,0.9735569,0.0016688901,0.0015933,0.000895138,0.000028078783],"about_ca_topic_score_codex":0.025541827,"about_ca_topic_score_gemma":0.011159747,"teacher_disagreement_score":0.025541827,"about_ca_system_score_codex":0.001820787,"about_ca_system_score_gemma":0.0009875863,"threshold_uncertainty_score":0.050786316},"labels":[],"label_agreement":null},{"id":"W4205185790","doi":"10.24251/hicss.2022.257","title":"Assisting People of Determination and the Elderly Using Social Robot: A Case Study","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Robot; Computer science; Human–computer interaction; Artificial intelligence","score_opus":0.05330518037555829,"score_gpt":0.30462378107905813,"score_spread":0.2513186007034998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205185790","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9878584,0.00079155795,0.0012518205,0.0020190119,0.0000811382,0.0002586332,0.00010289974,0.000015444406,0.007621113],"genre_scores_gemma":[0.98702294,0.0020221232,0.0025500653,0.0009268172,0.00007595473,0.0003229318,0.000059337337,0.000012018974,0.007007859],"study_design_codex":"qualitative","study_design_gemma":"case_report","domain_scores_codex":[0.99851936,0.0008660443,0.00005611033,0.000100723206,0.00015230275,0.00030541193],"domain_scores_gemma":[0.9986743,0.0005359792,0.00014143025,0.000090142355,0.00013230041,0.00042599344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018357787,0.00080864434,0.00055342814,0.0011766107,0.010039636,0.0016685383,0.0013362628,0.0034304156,0.0026316051],"category_scores_gemma":[0.0027662723,0.00029421793,0.0007002315,0.0007810958,0.0022931,0.0014728907,0.0032518022,0.0017833028,0.0005194264],"study_design_candidate":"case_report","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048746823,0.0067881267,0.06949553,0.000950342,0.00009414741,0.19377744,0.63034827,0.0012666926,0.0023512016,0.011443007,0.014856894,0.06814082],"study_design_scores_gemma":[0.000096210286,0.0019732844,0.024369642,0.00042421152,0.00007676861,0.043898888,0.85982364,0.0018914801,0.0013017555,0.001867178,0.0641903,0.00008664581],"about_ca_topic_score_codex":0.009774474,"about_ca_topic_score_gemma":0.026793517,"teacher_disagreement_score":0.010039636,"about_ca_system_score_codex":0.001699075,"about_ca_system_score_gemma":0.0014931201,"threshold_uncertainty_score":0.019435167},"labels":[],"label_agreement":null},{"id":"W4205274468","doi":"10.2139/ssrn.4010338","title":"The Impact of High-Occupancy Vehicle Lanes on Carpooling","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Occupancy; Transport engineering; Business; Engineering; Civil engineering","score_opus":0.005637856215390175,"score_gpt":0.2343062127859232,"score_spread":0.22866835657053303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205274468","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9871157,0.00010528343,0.00022082173,0.00013694758,0.000025437073,0.000009598784,0.00031727538,0.000016614484,0.012052326],"genre_scores_gemma":[0.99823004,0.000033231372,0.000037148824,0.000009836543,0.000004840486,0.0000018472008,0.0000883564,0.0000056508657,0.0015889714],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989604,0.0002402053,0.000024189365,0.00007363777,0.00017506015,0.0005265052],"domain_scores_gemma":[0.99503374,0.0022295434,0.0005112514,0.00018221392,0.0012370792,0.00080619013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067192916,0.00025555943,0.0002566849,0.00067060575,0.0007912133,0.001956379,0.00084665447,0.000673895,0.02309349],"category_scores_gemma":[0.0054905475,0.00020709966,0.0006411884,0.000774158,0.00052206434,0.001186545,0.0010337328,0.000712203,0.0014038433],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008923734,0.0027002934,0.7277366,0.00038692812,0.00051171536,0.0022434818,0.0016702968,0.14182003,0.008815716,0.009134313,0.0063505005,0.08970642],"study_design_scores_gemma":[0.000050819977,0.0013956196,0.9359447,0.00008323391,0.0002837188,0.00020343157,0.011706148,0.039880294,0.002512895,0.0040221433,0.0038215425,0.00009548121],"about_ca_topic_score_codex":0.044610895,"about_ca_topic_score_gemma":0.08987279,"teacher_disagreement_score":0.044610895,"about_ca_system_score_codex":0.001303443,"about_ca_system_score_gemma":0.0013200891,"threshold_uncertainty_score":0.08870244},"labels":[],"label_agreement":null},{"id":"W4205362551","doi":"10.1002/atr.5670390101","title":"Masthead","year":2005,"lang":"en","type":"paratext","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Citation; Computer science; World Wide Web; Library science","score_opus":0.009196915609928047,"score_gpt":0.2518180302066815,"score_spread":0.24262111459675342,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205362551","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005463491,0.0005703008,0.0018987422,0.0009121962,0.0017353931,0.00007919197,0.002178652,0.0024350996,0.98964405],"genre_scores_gemma":[0.00062479865,0.00012833999,0.00023445259,0.00011870923,0.00007889811,0.000012197943,0.0005054752,0.00021207827,0.99808514],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996182,0.000030058947,0.00001841266,0.00008697472,0.00020075076,0.000045469842],"domain_scores_gemma":[0.99878126,0.00017355094,0.00004737674,0.00020197687,0.0005560297,0.00023979331],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000495574,0.0010865321,0.00072846335,0.0020906457,0.0017488078,0.004038304,0.0012780664,0.001711155,0.90249366],"category_scores_gemma":[0.0020943745,0.00055065495,0.0005216686,0.0017074626,0.00035885445,0.0027416316,0.0022084003,0.0015351768,0.82100993],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043814875,0.000030757637,0.000084648746,0.000062530824,0.0000013428566,0.000058878057,0.000041445404,0.00005021786,0.00049911527,0.0022634834,0.8777074,0.119156405],"study_design_scores_gemma":[0.000008277222,0.000017318122,0.00038313153,0.00003893164,0.0000021654848,0.00007458479,0.000053098018,0.00008850146,0.0002352491,0.00078168884,0.99831295,0.000004295158],"about_ca_topic_score_codex":0.0020078993,"about_ca_topic_score_gemma":0.005550825,"teacher_disagreement_score":0.097506344,"about_ca_system_score_codex":0.00050295045,"about_ca_system_score_gemma":0.0009737228,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4205597172","doi":"10.4018/978-1-6684-3694-3.ch044","title":"Who Wants an Automated Vehicle?","year":2021,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Electrification; Software deployment; Emerging technologies; Automation; Business; Computer security; Political science; Transport engineering; Internet privacy; Engineering; Risk analysis (engineering); Computer science; Electricity","score_opus":0.016645335925267814,"score_gpt":0.2522062673823676,"score_spread":0.2355609314570998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205597172","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0049085906,0.012088358,0.0017536085,0.050647367,0.0026884277,0.00002298851,0.00011171702,0.000069522175,0.9277094],"genre_scores_gemma":[0.12083895,0.019820351,0.0015831307,0.011100697,0.0012853832,0.000052157113,0.00026348772,0.00010756749,0.84494823],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992175,0.00021752661,0.000016638063,0.00015940426,0.00022637447,0.00016254296],"domain_scores_gemma":[0.99957067,0.00018007151,0.000022884355,0.00002263095,0.000113800175,0.00008998472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008384755,0.00045822136,0.00027321247,0.0005991537,0.0028507295,0.00635107,0.00073668157,0.0029086804,0.038907867],"category_scores_gemma":[0.001546091,0.00024097395,0.00023431068,0.00084111455,0.0026329497,0.008788001,0.0011992548,0.0022770413,0.0150867505],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002081519,0.000038887963,0.0011935638,0.00021834372,0.0000052043183,0.0003544802,0.00603633,0.00020398488,0.00022888073,0.54579955,0.3275712,0.1183288],"study_design_scores_gemma":[0.0000016997582,0.000008774018,0.00034640334,0.00016082588,0.0000020167656,0.00022472444,0.0046825185,0.00015061985,0.00005290128,0.026368821,0.9679938,0.0000068669015],"about_ca_topic_score_codex":0.0066700624,"about_ca_topic_score_gemma":0.011820526,"teacher_disagreement_score":0.038907867,"about_ca_system_score_codex":0.0029191636,"about_ca_system_score_gemma":0.002165072,"threshold_uncertainty_score":0.13015974},"labels":[],"label_agreement":null},{"id":"W4205619198","doi":"10.1109/smc52423.2021.9658762","title":"Charging Pile Siting with Group Multirole Assignment","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Research and Development; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Integer programming; Computer science; Mathematical optimization; IBM; Process (computing); Cluster analysis; Pile; Assignment problem; Algorithm; Mathematics","score_opus":0.033303884087883776,"score_gpt":0.2501901607591624,"score_spread":0.21688627667127863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205619198","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014945788,0.00010200407,0.9771617,0.00016269732,0.000103361104,0.00021430342,0.00004920468,0.00037343113,0.006887492],"genre_scores_gemma":[0.5937207,0.00015426485,0.39729226,0.00012121721,0.000060274142,0.00029015364,0.00014732612,0.00012554294,0.008088276],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99808735,0.00082968385,0.00008044138,0.00034500193,0.00038620588,0.00027131443],"domain_scores_gemma":[0.9990446,0.00027495885,0.00014131158,0.00023820135,0.00014272772,0.00015823988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012206488,0.0011686432,0.0011905987,0.0007845164,0.0017201311,0.0013201928,0.0028483542,0.0015079826,0.008820659],"category_scores_gemma":[0.0023324136,0.0003982231,0.0013096001,0.0013245866,0.00090577186,0.0023597258,0.0022508544,0.0012117323,0.0017067385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046582203,0.00049120514,0.0011863711,0.0004651047,0.000086397085,0.0006811645,0.0006033516,0.6528515,0.013027088,0.097698525,0.0075558913,0.22488761],"study_design_scores_gemma":[0.00003393212,0.0001705239,0.00018786649,0.000017004199,0.000020452517,0.00028062696,0.00022176738,0.9648616,0.0033323166,0.023725914,0.0071100127,0.000038016453],"about_ca_topic_score_codex":0.0021466804,"about_ca_topic_score_gemma":0.0022172672,"teacher_disagreement_score":0.008820659,"about_ca_system_score_codex":0.0009207715,"about_ca_system_score_gemma":0.0012936305,"threshold_uncertainty_score":0.029507995},"labels":[],"label_agreement":null},{"id":"W4205923831","doi":"10.3390/su14020876","title":"System Optimization of Shared Mobility in Suburban Contexts","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Context (archaeology); Battery electric vehicle; Powertrain; Transport engineering; Battery (electricity); Public transport; Electric vehicle; Internal combustion engine; Total cost of ownership; Environmental economics; Sustainable transport; Computer science; Automotive engineering; Engineering; Sustainability; Economics","score_opus":0.005565728960542414,"score_gpt":0.21836249202594035,"score_spread":0.21279676306539794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205923831","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.67222226,0.00044815044,0.3125864,0.0005478405,0.000060139566,0.00019620411,0.0006077352,0.0003786332,0.012952659],"genre_scores_gemma":[0.98941094,0.000064251595,0.008949645,0.000020333795,0.000004430076,0.000053806667,0.000095039606,0.000017490705,0.0013840208],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994326,0.00021189466,0.00001711576,0.00010828808,0.000050963758,0.00017896472],"domain_scores_gemma":[0.9990615,0.00053743186,0.00013446648,0.00004903173,0.00012784015,0.00008976904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008795279,0.0008751266,0.0011478618,0.00035762432,0.00055256736,0.0011779262,0.0009669546,0.0008560511,0.0033165466],"category_scores_gemma":[0.0018244593,0.0004893699,0.00059946557,0.00053326745,0.0005738422,0.00096787955,0.0017172408,0.0006189142,0.00018318834],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032781863,0.000017414468,0.00033939522,0.000015690646,0.000016635251,0.00004362376,0.000015266849,0.99608326,0.0001910752,0.0010515874,0.00011432844,0.0020789467],"study_design_scores_gemma":[0.000008919027,0.000035680732,0.00027690714,0.0000020457749,0.0000069845664,0.000007110841,0.000046584806,0.99816823,0.00009955251,0.0011789324,0.00016633302,0.0000027224332],"about_ca_topic_score_codex":0.01683331,"about_ca_topic_score_gemma":0.016442938,"teacher_disagreement_score":0.01683331,"about_ca_system_score_codex":0.0013455913,"about_ca_system_score_gemma":0.0014545545,"threshold_uncertainty_score":0.03347063},"labels":[],"label_agreement":null},{"id":"W4206271634","doi":"10.1155/2022/7304148","title":"Evaluating the Impacts of Optimization Horizon on the Shared Autonomous Vehicle Reservation Request System","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Hebei Provincial Department of Bureau of Science and Technology; National Natural Science Foundation of China","keywords":"Reservation; Relocation; Time horizon; Scheduling (production processes); Computer science; Term (time); Operations research; Real-time computing; Scheme (mathematics); TRIPS architecture; Service (business); Matching (statistics); Computer network; Transport engineering; Mathematical optimization; Engineering; Operations management","score_opus":0.030771875751840556,"score_gpt":0.2901235949784912,"score_spread":0.2593517192266507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206271634","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9514704,0.0006950886,0.04115269,0.00026312508,0.000054878554,0.00009161078,0.00020075693,0.00018756771,0.005883986],"genre_scores_gemma":[0.9975502,0.000079328,0.0020371699,0.000009563049,0.0000033887968,0.00001070788,0.000043359934,0.000008231577,0.00025807915],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900013,0.00043886635,0.000030256286,0.00009226243,0.00015516642,0.00028330338],"domain_scores_gemma":[0.99565744,0.0032579615,0.00030716142,0.0001394475,0.0004005571,0.00023741413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002349281,0.0006828347,0.00071840454,0.00039664836,0.00041017798,0.0008394067,0.0005164763,0.00047180607,0.0023150027],"category_scores_gemma":[0.0055305315,0.00025776372,0.000420264,0.00045514863,0.00038658912,0.0011625045,0.00061870157,0.0006403359,0.000080515754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003495938,0.000064674765,0.0011372529,0.00005912142,0.000024083518,0.00004430562,0.000013773757,0.99181575,0.00081461377,0.0006490692,0.00016067219,0.0048672114],"study_design_scores_gemma":[0.000012271829,0.00016920346,0.0010026484,0.0000026354312,0.000021455708,0.000006767215,0.00004509595,0.99790275,0.00051536097,0.0002579774,0.000057381993,0.0000064119363],"about_ca_topic_score_codex":0.018281018,"about_ca_topic_score_gemma":0.007522597,"teacher_disagreement_score":0.018281018,"about_ca_system_score_codex":0.0012583295,"about_ca_system_score_gemma":0.0014459781,"threshold_uncertainty_score":0.036349237},"labels":[],"label_agreement":null},{"id":"W4206871452","doi":"","title":"Appendix To Software Migration: A Theoretical Framework A Grounded Theory approach on Systematic Literature Review","year":2021,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Berger (Canada)","funders":"","keywords":"Computer science; Grounded theory; Epistemology; Sociology; Qualitative research; Philosophy; Social science","score_opus":0.009814570525816274,"score_gpt":0.2275454572870264,"score_spread":0.21773088676121014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206871452","genre_codex":"dataset","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0053991294,0.014048051,0.07424222,0.038696673,0.0050737453,0.08337813,0.68261236,0.00076338387,0.09578636],"genre_scores_gemma":[0.0470956,0.029456908,0.34496036,0.016324673,0.0014322656,0.26309386,0.23586532,0.00043409874,0.06133694],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99136364,0.003954523,0.002507852,0.00066277565,0.001231048,0.00028002172],"domain_scores_gemma":[0.87650675,0.09889945,0.004859275,0.0022741249,0.016182793,0.001277642],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0092718145,0.0010630707,0.001832266,0.015209212,0.0013976124,0.0030192123,0.0018725413,0.0029886742,0.33526593],"category_scores_gemma":[0.121530965,0.0012150789,0.0017689031,0.025825705,0.001115223,0.0035749974,0.00320435,0.0020947692,0.040966813],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022900407,0.00016107748,0.0015514704,0.06733883,0.0001430261,0.00035771655,0.0011210698,0.0019669167,0.0002551071,0.07394414,0.77269036,0.08024127],"study_design_scores_gemma":[0.0007710722,0.00017100175,0.0065154415,0.067777775,0.0003492743,0.0004516873,0.003460922,0.0011649841,0.00046232226,0.06940994,0.8493295,0.00013606378],"about_ca_topic_score_codex":0.008998622,"about_ca_topic_score_gemma":0.011679308,"teacher_disagreement_score":0.33526593,"about_ca_system_score_codex":0.006176296,"about_ca_system_score_gemma":0.021633502,"threshold_uncertainty_score":0.94816244},"labels":[],"label_agreement":null},{"id":"W4206942466","doi":"10.5267/j.ijdns.2021.11.010","title":"Consumer attitudes towards the use of autonomous vehicles: Evidence from United Kingdom taxi services","year":2022,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Taxis; Focus group; Sample (material); Psychology; Test (biology); Theory of planned behavior; Risk perception; Marketing; Service (business); Applied psychology; Control (management); Business; Social psychology; Perception; Engineering; Transport engineering; Computer science","score_opus":0.14449109790349599,"score_gpt":0.3316777613386866,"score_spread":0.1871866634351906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206942466","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99849164,0.00029227723,0.000016397744,0.00009293074,0.0000033753925,0.000004089253,0.000062760926,5.501854e-7,0.0010360844],"genre_scores_gemma":[0.9990645,0.0005225558,0.00002317485,0.000048415186,0.000002705767,0.0000052047503,0.00007170424,0.0000014225631,0.0002602756],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990575,0.0002754889,0.00011495362,0.00009402923,0.00032950204,0.00012854798],"domain_scores_gemma":[0.9932967,0.0026020845,0.0022996967,0.00020816347,0.0012156963,0.00037774054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010021252,0.00015078709,0.00028391747,0.0009852054,0.0006011801,0.0011472355,0.00029813833,0.00046010013,0.005368801],"category_scores_gemma":[0.0069362074,0.00024931476,0.00034658037,0.0018583013,0.00066269713,0.0005793786,0.00073882274,0.0005056768,0.00054014777],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019130248,0.00010233983,0.9612215,0.00023147426,0.000049041926,0.0002453638,0.022694627,0.00002287669,0.0002127815,0.000111006644,0.00045088783,0.014466789],"study_design_scores_gemma":[0.0000041981916,0.000096982,0.9835475,0.00010593666,0.000027963277,0.00016267534,0.015027365,0.00004851799,0.00006756883,0.00001338513,0.0008909462,0.000006921819],"about_ca_topic_score_codex":0.097508565,"about_ca_topic_score_gemma":0.08630915,"teacher_disagreement_score":0.097508565,"about_ca_system_score_codex":0.0010074141,"about_ca_system_score_gemma":0.0006635174,"threshold_uncertainty_score":0.19388199},"labels":[],"label_agreement":null},{"id":"W4207084466","doi":"10.1155/2022/8382754","title":"Fixed-Route vs. Demand-Responsive Transport Feeder Services: An Exploratory Study Using an Agent-Based Model","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"European Social Fund; Università di Catania","keywords":"Schedule; Demand patterns; Service (business); Context (archaeology); Computer science; Last mile (transportation); On demand; Peak demand; Transport engineering; Operations research; Demand management; Engineering; Business; Economics; Mile","score_opus":0.026339981534505074,"score_gpt":0.2749691806592676,"score_spread":0.24862919912476256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4207084466","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9618883,0.00025140244,0.025117612,0.00035377772,0.00002614128,0.00013042436,0.00046259968,0.000066990135,0.011702662],"genre_scores_gemma":[0.9933241,0.0001243105,0.0047014896,0.00002348571,0.000005929731,0.00006677414,0.00012309999,0.0000109985585,0.0016198079],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999749,0.00012590515,0.0000080194095,0.000030790714,0.000026053182,0.00006019372],"domain_scores_gemma":[0.99877435,0.00085113465,0.00012819916,0.00003669445,0.00012185529,0.00008776548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046805158,0.0007169826,0.00059083686,0.000501657,0.00041185337,0.0011809472,0.0010345209,0.001420079,0.0021850138],"category_scores_gemma":[0.0016130672,0.00032702668,0.0007404975,0.00049349986,0.0005513148,0.0007382516,0.00063676294,0.00076360663,0.00015710754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000069609734,0.000089538924,0.0015009649,0.000023910441,0.000016496606,0.00010726949,0.000033954657,0.9952193,0.00028333042,0.0017817814,0.00012543608,0.00074838725],"study_design_scores_gemma":[0.000013932608,0.000041374406,0.00028356633,0.0000037475727,0.000009683167,0.000007872832,0.000057575227,0.99901605,0.0000951256,0.00034167332,0.0001253984,0.000003829849],"about_ca_topic_score_codex":0.027156197,"about_ca_topic_score_gemma":0.011715972,"teacher_disagreement_score":0.027156197,"about_ca_system_score_codex":0.0012548293,"about_ca_system_score_gemma":0.00081850664,"threshold_uncertainty_score":0.053996265},"labels":[],"label_agreement":null},{"id":"W4210254317","doi":"10.32920/19027598","title":"Towards a equitable approach to tackling the fare evasion problem: a scoping literature review and case study analysis","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Evasion (ethics); Public economics; Disadvantage; Payment; Economics; Business; Actuarial science; Public relations; Political science; Finance; Law","score_opus":0.035719685963045866,"score_gpt":0.3123051883511133,"score_spread":0.27658550238806745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210254317","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011435907,0.8632882,0.041886996,0.032429297,0.0018031392,0.01642096,0.0013083129,0.00010187387,0.031325303],"genre_scores_gemma":[0.10078161,0.78029627,0.08414606,0.0071456954,0.00039310002,0.022544552,0.0011899008,0.00009601999,0.003406827],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.8717045,0.07131499,0.032085855,0.003806225,0.018695477,0.0023929365],"domain_scores_gemma":[0.7308857,0.20270272,0.018808799,0.008131905,0.038398277,0.0010726276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.14718436,0.0022925166,0.005524039,0.07436463,0.0052407156,0.018278193,0.005068114,0.008232348,0.004941686],"category_scores_gemma":[0.23524159,0.0021057825,0.0059537976,0.06332699,0.008291802,0.019220002,0.010231759,0.0044164974,0.001150409],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014307005,0.00022430465,0.0035341051,0.47082552,0.001975134,0.0027046786,0.036870077,0.0024174245,0.0008807073,0.12629941,0.016577095,0.33754846],"study_design_scores_gemma":[0.00004174275,0.00010162288,0.0010985984,0.8736388,0.001988671,0.00060072285,0.027473357,0.00060420064,0.00045780544,0.017406538,0.076526806,0.00006127373],"about_ca_topic_score_codex":0.014824104,"about_ca_topic_score_gemma":0.028943919,"teacher_disagreement_score":0.14718436,"about_ca_system_score_codex":0.021792052,"about_ca_system_score_gemma":0.07046153,"threshold_uncertainty_score":0.7783946},"labels":[],"label_agreement":null},{"id":"W4210285535","doi":"10.1049/pbtr020e_ch12","title":"Matching demand and supply under uncertainty","year":2021,"lang":"en","type":"book-chapter","venue":"Institution of Engineering and Technology eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Supply and demand; Balance (ability); Declaration; Matching (statistics); Operations research; Control (management); On demand; Computer science; Environmental economics; Engineering; Economics; Microeconomics; Artificial intelligence; Mathematics","score_opus":0.0078015009672280896,"score_gpt":0.191206555633105,"score_spread":0.18340505466587692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210285535","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04226751,0.00931868,0.48226106,0.012217158,0.0009784243,0.00013349346,0.001206693,0.00030835104,0.45130855],"genre_scores_gemma":[0.7524817,0.013042549,0.0806802,0.0013497814,0.0011225963,0.00033165156,0.0010238048,0.00029045698,0.14967716],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991652,0.00031142437,0.00002936282,0.00016455074,0.0002588895,0.00007044997],"domain_scores_gemma":[0.9988293,0.00087214686,0.000058802132,0.00006813229,0.00013772395,0.000033876862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00147531,0.000346701,0.0005151063,0.0007072425,0.00038848008,0.002419476,0.0006985199,0.0012999981,0.020177383],"category_scores_gemma":[0.007286283,0.00034676943,0.00037338428,0.0014672232,0.00078153284,0.002706014,0.0011478892,0.0009632133,0.0020033447],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006325983,0.000041284376,0.0012769256,0.00014742039,0.000025954207,0.00013605194,0.0003290669,0.07788201,0.0006137042,0.79063946,0.021171711,0.10767319],"study_design_scores_gemma":[0.000010105317,0.000036610225,0.0010594327,0.0001594385,0.000011198354,0.000113100024,0.00030062755,0.112666585,0.00054746517,0.8223049,0.06276827,0.00002227135],"about_ca_topic_score_codex":0.0015324929,"about_ca_topic_score_gemma":0.0010924658,"teacher_disagreement_score":0.020177383,"about_ca_system_score_codex":0.001932982,"about_ca_system_score_gemma":0.0013540868,"threshold_uncertainty_score":0.067500114},"labels":[],"label_agreement":null},{"id":"W4210308051","doi":"10.1016/j.cor.2022.105724","title":"Environmental and social implications of incorporating carpooling service on a customized bus system","year":2022,"lang":"en","type":"article","venue":"Computers & Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Incentive; Greenhouse gas; Heuristic; Service (business); Sustainable transport; Operations research; Pareto principle; Multi-objective optimization; Public transport; Sustainability; Mathematical optimization; Environmental economics; Transport engineering; Engineering; Business; Mathematics","score_opus":0.04012678617542295,"score_gpt":0.29438921384570893,"score_spread":0.25426242767028595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210308051","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9839497,0.000011109377,0.00013128582,0.00038094528,0.0000108258755,0.000021291458,0.00003255036,0.000008689168,0.015453679],"genre_scores_gemma":[0.9985002,0.000011752259,0.00010339489,0.00003207805,0.0000035925248,0.0000057831776,0.000012088495,0.0000029747423,0.0013280902],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990614,0.00041226664,0.000018106739,0.00004791738,0.00010545167,0.00035486164],"domain_scores_gemma":[0.9987251,0.00029632385,0.00015298477,0.000085389634,0.00039643326,0.00034367907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000620527,0.00022572174,0.000119256474,0.000590128,0.0030349423,0.0023811313,0.0007085233,0.0011155009,0.010340959],"category_scores_gemma":[0.0020875013,0.00017086529,0.00048091498,0.0006759984,0.0016006648,0.0011971758,0.0015991948,0.00084919063,0.00040058146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008030534,0.018638868,0.4679084,0.00044663606,0.0004976767,0.010131564,0.04300395,0.09768991,0.0464719,0.10353416,0.013420842,0.19022545],"study_design_scores_gemma":[0.00026129934,0.005088297,0.6161769,0.00015302763,0.00048858946,0.00039180796,0.26915345,0.042968053,0.009234182,0.021267002,0.034569792,0.0002476071],"about_ca_topic_score_codex":0.061222706,"about_ca_topic_score_gemma":0.15968119,"teacher_disagreement_score":0.061222706,"about_ca_system_score_codex":0.004021059,"about_ca_system_score_gemma":0.0027038236,"threshold_uncertainty_score":0.12173271},"labels":[],"label_agreement":null},{"id":"W4210309822","doi":"10.1049/pbtr020e_ch8","title":"Design of systems with nonautomated electric vehicles","year":2021,"lang":"en","type":"book-chapter","venue":"Institution of Engineering and Technology eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Declaration; Relocation; Service (business); Electric vehicle; Systems design; Transport engineering; Engineering; Computer science; Operations research; Business; Systems engineering; Operating system; Marketing","score_opus":0.009463605559994863,"score_gpt":0.17705961303896273,"score_spread":0.16759600747896786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210309822","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011742996,0.0011271243,0.94930375,0.00024088913,0.00021034382,0.0002498886,0.0001757879,0.0007411902,0.036208104],"genre_scores_gemma":[0.5747682,0.00254876,0.35553202,0.00021895515,0.00023542925,0.0012201248,0.0006560584,0.00030707414,0.0645135],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991615,0.000245302,0.000055056134,0.0001385013,0.00032401303,0.00007568205],"domain_scores_gemma":[0.9995378,0.00018277968,0.000049998594,0.000062700325,0.0001457469,0.000020990887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068192167,0.0007156358,0.00052509137,0.0003278586,0.00050949195,0.0017200295,0.001224119,0.0008584097,0.0111655],"category_scores_gemma":[0.0014320497,0.0005041266,0.00073672266,0.000335483,0.0005500485,0.000985234,0.0011830098,0.0005820234,0.001729542],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014828396,0.00007568419,0.0009681324,0.00082025985,0.00010621001,0.0002926116,0.00025715845,0.7113183,0.01364321,0.10827497,0.005856213,0.15823893],"study_design_scores_gemma":[0.000083060164,0.00031105572,0.0006367682,0.000101228,0.000056350196,0.00024612097,0.00009183424,0.84086406,0.00636403,0.05520844,0.09600914,0.000027894517],"about_ca_topic_score_codex":0.0011336651,"about_ca_topic_score_gemma":0.0013158219,"teacher_disagreement_score":0.0111655,"about_ca_system_score_codex":0.00054970547,"about_ca_system_score_gemma":0.001088101,"threshold_uncertainty_score":0.037352324},"labels":[],"label_agreement":null},{"id":"W4210328416","doi":"10.1016/b978-0-12-819130-9.00035-8","title":"Modeling and simulation for connected and automated vehicle (CAV) deployment and performance evaluation","year":2022,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Software deployment; Computer science; Simulation; Operating system","score_opus":0.02823731968278995,"score_gpt":0.2630526958255247,"score_spread":0.23481537614273476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210328416","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.111974806,0.0014716064,0.80146873,0.0011137088,0.0004248268,0.00027426053,0.0015513555,0.0023939838,0.079326674],"genre_scores_gemma":[0.854147,0.0016491667,0.11225628,0.00014454135,0.00012395236,0.0005291396,0.0013032254,0.0004283416,0.029418267],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997248,0.00008920868,0.000011167767,0.00003347004,0.000107700245,0.000033616805],"domain_scores_gemma":[0.9995402,0.00026204597,0.000028959535,0.000034744153,0.00011341221,0.000020643047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038742236,0.0007695987,0.0006900155,0.00048799062,0.0004930628,0.0009614744,0.0009928104,0.0012418211,0.00570217],"category_scores_gemma":[0.0012465352,0.00047975068,0.00057365245,0.00078763254,0.00037822247,0.00079691556,0.00056429784,0.0006666489,0.0010764279],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001578929,0.000020552407,0.00024739487,0.000016416763,0.000005126482,0.00001652688,0.000012578505,0.9882069,0.0005352493,0.0026686164,0.0012292428,0.007025482],"study_design_scores_gemma":[0.0000022001366,0.000008001359,0.000083767074,0.0000034865423,0.0000016623459,0.000004351533,0.000005513384,0.99795157,0.00018924917,0.0008724286,0.0008757563,0.0000021538199],"about_ca_topic_score_codex":0.03269046,"about_ca_topic_score_gemma":0.018476922,"teacher_disagreement_score":0.03269046,"about_ca_system_score_codex":0.0011656559,"about_ca_system_score_gemma":0.0013339436,"threshold_uncertainty_score":0.065000355},"labels":[],"label_agreement":null},{"id":"W4210422429","doi":"10.3386/w29712","title":"A Theory of Cash Flow-Based Financing with Distress Resolution","year":2022,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Cash flow; Asset (computer security); Finance; Business; Economics; Computer science; Computer security","score_opus":0.2041914634476723,"score_gpt":0.43070207541794986,"score_spread":0.22651061197027755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210422429","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03163313,0.003802378,0.7611632,0.011298428,0.00036876285,0.00028487173,0.00045628814,0.0002956815,0.19069724],"genre_scores_gemma":[0.84119344,0.005145855,0.049952816,0.0010563235,0.0013371583,0.00061650074,0.0003223286,0.00010944507,0.1002661],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989268,0.00034921372,0.000044948352,0.00017579105,0.00028081605,0.0002224688],"domain_scores_gemma":[0.9980259,0.0009976022,0.0003313337,0.00020583379,0.00022743735,0.00021189931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026260766,0.0010521079,0.0007945047,0.0017274143,0.0015271461,0.003992261,0.0026231594,0.0045143226,0.020512875],"category_scores_gemma":[0.00666853,0.0007232329,0.0012265152,0.0015740845,0.004058104,0.009475374,0.0018666923,0.0027842699,0.0014846758],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000044018298,0.000007647371,0.000058660964,0.000014593738,0.0000030957453,0.00003593829,0.00003509346,0.0070263445,0.00004744524,0.9895779,0.0008489918,0.0023399189],"study_design_scores_gemma":[0.000023804776,0.000015829311,0.00007581841,0.000025651325,0.0000070846477,0.000061420935,0.000020871868,0.029820539,0.00007076879,0.96505773,0.0048113675,0.000009037212],"about_ca_topic_score_codex":0.0021522902,"about_ca_topic_score_gemma":0.0010307025,"teacher_disagreement_score":0.020512875,"about_ca_system_score_codex":0.0034757296,"about_ca_system_score_gemma":0.0022339744,"threshold_uncertainty_score":0.06862241},"labels":[],"label_agreement":null},{"id":"W4210497080","doi":"10.1161/str.53.suppl_1.tmp32","title":"Abstract TMP32: Modeling Optimal Patient Transport In A Stroke Network Capable Of Telerobotic Endovascular Therapy","year":2022,"lang":"en","type":"article","venue":"Stroke","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; University of Calgary","funders":"","keywords":"Medicine; Catchment area; Robotics; Stroke (engine); Population; Robot; Artificial intelligence; Computer science; Drainage basin; Geography; Cartography; Engineering","score_opus":0.015562041018229401,"score_gpt":0.20770025041969156,"score_spread":0.19213820940146217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210497080","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9159601,0.0003499199,0.06171661,0.0022354617,0.00013427564,0.00028064026,0.0057404703,0.00046889382,0.0131135965],"genre_scores_gemma":[0.9839265,0.00012688078,0.008558047,0.00010381604,0.000028471595,0.00018588774,0.0013195508,0.000044889697,0.005706005],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944323,0.00019107376,0.000017502396,0.00015470893,0.000029721345,0.00016378949],"domain_scores_gemma":[0.99800366,0.0011945808,0.00023292715,0.00005260844,0.00026096235,0.00025534246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013485954,0.0015766397,0.00091144926,0.0010115592,0.0008859974,0.0018956467,0.00188108,0.0030898843,0.0077879494],"category_scores_gemma":[0.0036446534,0.0013476016,0.0015877192,0.0008708087,0.0013548144,0.0010680687,0.0015594943,0.0015922035,0.00055146957],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028375698,0.000016849639,0.0010819071,0.0000069166076,0.000006433935,0.000027314525,0.000008895638,0.99790037,0.0000334661,0.00038279974,0.0001898555,0.00031694336],"study_design_scores_gemma":[0.000016063846,0.000017741015,0.0003544005,0.0000036409856,0.0000048314914,0.000006368525,0.000022692793,0.99914706,0.000017213428,0.00031709124,0.00008952332,0.0000032980918],"about_ca_topic_score_codex":0.15542027,"about_ca_topic_score_gemma":0.0516523,"teacher_disagreement_score":0.15542027,"about_ca_system_score_codex":0.0039328136,"about_ca_system_score_gemma":0.0034242189,"threshold_uncertainty_score":0.30903125},"labels":[],"label_agreement":null},{"id":"W4210511519","doi":"10.32920/19027598.v1","title":"Towards a equitable approach to tackling the fare evasion problem: a scoping literature review and case study analysis","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Evasion (ethics); Public economics; Disadvantage; Payment; Business; Economics; Actuarial science; Political science; Finance; Law","score_opus":0.035719685963045866,"score_gpt":0.3123051883511133,"score_spread":0.27658550238806745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210511519","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011435907,0.8632882,0.041886996,0.032429297,0.0018031392,0.01642096,0.0013083129,0.00010187387,0.031325303],"genre_scores_gemma":[0.10078161,0.78029627,0.08414606,0.0071456954,0.00039310002,0.022544552,0.0011899008,0.00009601999,0.003406827],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.8717045,0.07131499,0.032085855,0.003806225,0.018695477,0.0023929365],"domain_scores_gemma":[0.7308857,0.20270272,0.018808799,0.008131905,0.038398277,0.0010726276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.14718436,0.0022925166,0.005524039,0.07436463,0.0052407156,0.018278193,0.005068114,0.008232348,0.004941686],"category_scores_gemma":[0.23524159,0.0021057825,0.0059537976,0.06332699,0.008291802,0.019220002,0.010231759,0.0044164974,0.001150409],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014307005,0.00022430465,0.0035341051,0.47082552,0.001975134,0.0027046786,0.036870077,0.0024174245,0.0008807073,0.12629941,0.016577095,0.33754846],"study_design_scores_gemma":[0.00004174275,0.00010162288,0.0010985984,0.8736388,0.001988671,0.00060072285,0.027473357,0.00060420064,0.00045780544,0.017406538,0.076526806,0.00006127373],"about_ca_topic_score_codex":0.014824104,"about_ca_topic_score_gemma":0.028943919,"teacher_disagreement_score":0.14718436,"about_ca_system_score_codex":0.021792052,"about_ca_system_score_gemma":0.07046153,"threshold_uncertainty_score":0.7783946},"labels":[],"label_agreement":null},{"id":"W4210534322","doi":"10.1155/2022/5841373","title":"Evaluation of the Cost of Intelligent Upgrades of Transportation Infrastructure for Intelligent Connected Vehicles","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Intelligent transportation system; Upgrade; Transport engineering; Advanced Traffic Management System; Engineering; Software deployment; Computer science","score_opus":0.022373035534900908,"score_gpt":0.27927171498128406,"score_spread":0.25689867944638317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210534322","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9495396,0.000865319,0.037437927,0.00040881208,0.000090731235,0.00027112875,0.0011842813,0.00016342045,0.010038729],"genre_scores_gemma":[0.99223363,0.00025989537,0.006032129,0.000012318404,0.000006142633,0.000055053417,0.00048947614,0.0000169699,0.0008945107],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984711,0.00054658577,0.0000719007,0.00016870494,0.00045849485,0.00028328088],"domain_scores_gemma":[0.997062,0.0014900953,0.00028943038,0.00021232812,0.0007920571,0.00015398265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016445161,0.0014145762,0.00052539527,0.0022983253,0.00058965967,0.0013614433,0.0011147567,0.0008933252,0.0022223652],"category_scores_gemma":[0.0054327324,0.0004741161,0.0010668783,0.0021197645,0.00058099837,0.0033111004,0.00073605176,0.0007188993,0.00016819539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063071295,0.0002461157,0.0319004,0.00026607772,0.00013124192,0.00049219176,0.00009837941,0.90330744,0.0031377971,0.008293186,0.0018122919,0.049684275],"study_design_scores_gemma":[0.00003089191,0.00048649628,0.024069851,0.00003309361,0.00020425288,0.00017480676,0.00059056055,0.96803916,0.0032532385,0.0016937908,0.0013637679,0.000060110913],"about_ca_topic_score_codex":0.021068845,"about_ca_topic_score_gemma":0.01686379,"teacher_disagreement_score":0.021068845,"about_ca_system_score_codex":0.004747353,"about_ca_system_score_gemma":0.0017525626,"threshold_uncertainty_score":0.04189241},"labels":[],"label_agreement":null},{"id":"W4210590506","doi":"10.3390/vehicles4010007","title":"Shared Automated Electric Vehicle Prospects for Low Carbon Road Transportation in British Columbia, Canada","year":2022,"lang":"en","type":"article","venue":"Vehicles","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Electrification; Automation; Transport engineering; Environmental economics; Electric vehicle; Energy (signal processing); Engineering; Electricity; Economics; Electrical engineering","score_opus":0.004715734943976558,"score_gpt":0.18178489473279483,"score_spread":0.17706915978881826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210590506","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.932055,0.0017456214,0.00094179274,0.002829535,0.000042870408,0.000054750108,0.008853874,0.000058081376,0.053418517],"genre_scores_gemma":[0.98273337,0.0010003531,0.00039080344,0.000120866716,0.000003507836,0.00001295805,0.0021660242,0.00001139592,0.013560645],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994261,0.000029637566,0.000010661478,0.000045240227,0.0001896635,0.0002987989],"domain_scores_gemma":[0.9993206,0.00003080918,0.000031733132,0.000015284613,0.0004964943,0.00010512414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002896418,0.0003967098,0.00024014528,0.00081763946,0.0023899022,0.0022614864,0.0008280389,0.0004883545,0.006127289],"category_scores_gemma":[0.0007811342,0.00019552904,0.00052938616,0.002092714,0.00052712735,0.0007540887,0.00086064154,0.00067377044,0.0003570227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00090921286,0.00032314126,0.55041236,0.0006091538,0.00045151665,0.0035986376,0.0021589787,0.15690155,0.0066316556,0.05013805,0.062252343,0.16561338],"study_design_scores_gemma":[0.00007453538,0.00015750845,0.7829605,0.00036648192,0.0002301683,0.0006048365,0.017908217,0.081648014,0.0029548528,0.004996304,0.107875705,0.000222903],"about_ca_topic_score_codex":0.9971686,"about_ca_topic_score_gemma":0.9989109,"teacher_disagreement_score":0.053056832,"about_ca_system_score_codex":0.053056832,"about_ca_system_score_gemma":0.048883222,"threshold_uncertainty_score":0.38495606},"labels":[],"label_agreement":null},{"id":"W4210648057","doi":"10.1016/j.erss.2022.102506","title":"Who will use new mobility technologies? Exploring demand for shared, electric, and automated vehicles in three Canadian metropolitan regions","year":2022,"lang":"en","type":"article","venue":"Energy Research & Social Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada; Pacific Institute for Climate Solutions","keywords":"Metropolitan area; Latent class model; Context (archaeology); Travel behavior; Supply and demand; Demand patterns; Business; Marketing; Economics; Demand management; Geography; Transport engineering; Computer science; Engineering","score_opus":0.10290724131139119,"score_gpt":0.3314118276635041,"score_spread":0.2285045863521129,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210648057","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99535286,0.000091126836,0.00009658096,0.00052438723,0.0000044064313,0.00003746131,0.0009999528,0.0000042865613,0.0028890176],"genre_scores_gemma":[0.99571264,0.0001652779,0.00022499496,0.00016310732,0.0000030256954,0.000048149504,0.00078582164,0.0000072931534,0.002889705],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989059,0.0001099832,0.000026776435,0.00011556586,0.00024382163,0.0005978557],"domain_scores_gemma":[0.99736917,0.0003352191,0.00026772762,0.000054614946,0.0012615388,0.00071170647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009659974,0.00043954304,0.0005068905,0.001430408,0.0063991775,0.003037513,0.0023982134,0.0010361731,0.0025374396],"category_scores_gemma":[0.0024801877,0.0004902126,0.00086175953,0.003746232,0.0014464484,0.0011730951,0.001985215,0.0015689946,0.00033283487],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025367105,0.00030325662,0.9198931,0.00007355066,0.00010521047,0.00036777384,0.05780948,0.0013626659,0.0010509399,0.0025655883,0.004627109,0.011587753],"study_design_scores_gemma":[0.000013381894,0.00004539427,0.7899964,0.000061248174,0.00004446531,0.00005863256,0.19884166,0.0029010472,0.00028491323,0.00023230685,0.007455225,0.00006529056],"about_ca_topic_score_codex":0.9980438,"about_ca_topic_score_gemma":0.99933773,"teacher_disagreement_score":0.06187019,"about_ca_system_score_codex":0.06187019,"about_ca_system_score_gemma":0.04942074,"threshold_uncertainty_score":0.4489017},"labels":[],"label_agreement":null},{"id":"W4210687283","doi":"10.1007/978-3-030-93904-5_13","title":"Design of a Vehicle for Modern Mobilities in Metropolitan Areas","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in networks and systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Metropolitan area; Automotive industry; Conceptual design; Engineering; Transport engineering; Systems engineering; Engineering management; Manufacturing engineering; Computer science; Mechanical engineering","score_opus":0.022645635206640456,"score_gpt":0.2235378826317365,"score_spread":0.20089224742509604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210687283","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01677651,0.0004478692,0.93506444,0.00030905643,0.00015600323,0.00025555494,0.00020628277,0.00086366927,0.04592058],"genre_scores_gemma":[0.53125995,0.0011821379,0.3683296,0.00017697316,0.00007235353,0.000847542,0.00053083873,0.00033234502,0.09726822],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997677,0.00004661062,0.000011223244,0.000046630717,0.000075183234,0.000052622883],"domain_scores_gemma":[0.99990404,0.000012962708,0.000009241405,0.000009751091,0.00005061509,0.000013339859],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029065064,0.0008273752,0.0004780311,0.00061207084,0.00092323334,0.001244054,0.0011260444,0.0014099993,0.008043069],"category_scores_gemma":[0.00031690003,0.00046258504,0.00058621255,0.0004103915,0.00046934703,0.0007609675,0.0010847693,0.0004048885,0.0024995024],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013987147,0.00008093704,0.0017590395,0.0004712835,0.00006794004,0.00047539725,0.0003867157,0.64159364,0.04204918,0.10007465,0.011271916,0.20162956],"study_design_scores_gemma":[0.000043535343,0.00054175756,0.0009928842,0.0001353975,0.00010030367,0.0004567648,0.0006602105,0.73473096,0.021485537,0.028498087,0.21229403,0.000060568225],"about_ca_topic_score_codex":0.003618294,"about_ca_topic_score_gemma":0.0044892305,"teacher_disagreement_score":0.008043069,"about_ca_system_score_codex":0.00063321803,"about_ca_system_score_gemma":0.0012857713,"threshold_uncertainty_score":0.026906788},"labels":[],"label_agreement":null},{"id":"W4210796673","doi":"10.1371/journal.pone.0263476","title":"User characteristics and service satisfaction of car sharing systems: Evidence from Hangzhou, China","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Science Foundation of Zhejiang Province","keywords":"Renting; Sharing economy; Business; Service (business); Government (linguistics); Marketing; Descriptive statistics; Travel behavior; Computer science; Advertising; Transport engineering; World Wide Web; Engineering; Statistics; Mathematics","score_opus":0.04090672966672492,"score_gpt":0.21399454351793396,"score_spread":0.17308781385120903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210796673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99945647,0.00011010828,0.000029165858,0.00005674314,0.0000016824803,0.0000050656326,0.000105105144,0.0000017146173,0.00023401713],"genre_scores_gemma":[0.9994299,0.00015892775,0.0000394106,0.00003184499,0.0000023467398,0.00000750095,0.00016011727,9.5365965e-7,0.00016894763],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993368,0.00016113199,0.00010806662,0.00008980979,0.00018030274,0.00012401969],"domain_scores_gemma":[0.99735945,0.00072224624,0.00075743115,0.00016503625,0.0005460371,0.0004496456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010823405,0.00023347106,0.00030304302,0.0013856019,0.000986911,0.00067238323,0.00041263443,0.00030969208,0.0023274103],"category_scores_gemma":[0.002322612,0.0002299097,0.0005449968,0.0034231513,0.00062779925,0.00047729688,0.0005463556,0.00025666485,0.00018358562],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044544016,0.000043405184,0.99148655,0.00006392177,0.000041144966,0.00015719874,0.0026459978,0.000054235577,0.00017308856,0.000056867786,0.00018345454,0.0050496603],"study_design_scores_gemma":[0.0000026627106,0.000054040767,0.99694014,0.0000125792485,0.000017484688,0.00003831012,0.0025422429,0.000112997936,0.000042170803,0.000008735006,0.00022478047,0.0000040331424],"about_ca_topic_score_codex":0.1408674,"about_ca_topic_score_gemma":0.1588604,"teacher_disagreement_score":0.1408674,"about_ca_system_score_codex":0.0015460014,"about_ca_system_score_gemma":0.0016634475,"threshold_uncertainty_score":0.28009492},"labels":[],"label_agreement":null},{"id":"W4210832428","doi":"10.1155/2022/6142950","title":"Station Location Optimization for the One-Way Carsharing System: Modeling and a Case Study","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Beijing University of Civil Engineering and Architecture","keywords":"Beijing; Computer science; Operations research; Integer programming; Mode (computer interface); Location model; Linear programming; Decomposition; Transport engineering; Mathematical optimization; China; Engineering; Algorithm","score_opus":0.022417140817619828,"score_gpt":0.25635166409133536,"score_spread":0.23393452327371553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210832428","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7367835,0.001450105,0.22761522,0.0009926747,0.000139393,0.00035210897,0.0011064183,0.00040507532,0.031155488],"genre_scores_gemma":[0.97413105,0.00037973994,0.018804798,0.000035991838,0.00001602326,0.00011773076,0.00027404254,0.00002941347,0.006211251],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961215,0.00011935003,0.000013357336,0.000063027546,0.00006641955,0.0001257576],"domain_scores_gemma":[0.9992495,0.0004151339,0.00008831794,0.000037906757,0.00012356981,0.00008560411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007042325,0.0012773874,0.0012328646,0.0007475053,0.0009049166,0.0015721605,0.001500875,0.002107668,0.0045273313],"category_scores_gemma":[0.0009388385,0.00071165984,0.0015520606,0.0015842151,0.00066455494,0.00095866126,0.00093120243,0.0012465275,0.00028209915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026198519,0.000044484503,0.0006842222,0.0000470994,0.00001412416,0.0002188393,0.000022888811,0.9957831,0.00031236658,0.0009720387,0.00024174585,0.0016329833],"study_design_scores_gemma":[0.000007805702,0.000032336186,0.00023282542,0.0000034714215,0.000011236405,0.000016282853,0.00005805899,0.99887854,0.00015961497,0.00032485274,0.00026893948,0.000006059806],"about_ca_topic_score_codex":0.045501962,"about_ca_topic_score_gemma":0.036741246,"teacher_disagreement_score":0.045501962,"about_ca_system_score_codex":0.0020301049,"about_ca_system_score_gemma":0.0017929827,"threshold_uncertainty_score":0.09047419},"labels":[],"label_agreement":null},{"id":"W4213168268","doi":"10.1002/atr.5670380201","title":"Masthead","year":2004,"lang":"en","type":"paratext","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Citation; Computer science; World Wide Web; Library science","score_opus":0.008990510154888751,"score_gpt":0.24801771858277127,"score_spread":0.23902720842788253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213168268","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005754049,0.0005990475,0.0018942475,0.0009515695,0.0016399021,0.00007292528,0.0019852405,0.0022479487,0.9900338],"genre_scores_gemma":[0.00060076965,0.00013394459,0.00023492923,0.00011184191,0.00007033964,0.0000113006745,0.00044651775,0.00020082072,0.9981895],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99964154,0.000029070809,0.00001755127,0.000086862936,0.0001810417,0.000043973338],"domain_scores_gemma":[0.9988048,0.0001759549,0.000046924237,0.00019956601,0.0005494416,0.00022324813],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004583769,0.0011100527,0.00074924185,0.0021344726,0.0018265549,0.0038591654,0.0013098995,0.0017410999,0.8978821],"category_scores_gemma":[0.001978289,0.0005801078,0.00052691886,0.0018586551,0.00036530854,0.0027248648,0.0020662213,0.0015531301,0.8123035],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048409263,0.00003468451,0.00010008807,0.00006720448,0.000001538066,0.000065399734,0.00004665963,0.00005585433,0.0006199232,0.0024721401,0.86587226,0.13061573],"study_design_scores_gemma":[0.000008565452,0.000017056687,0.00040915952,0.00003561638,0.0000024503013,0.000082701736,0.000055367644,0.00009217585,0.00026286644,0.0008280042,0.9982016,0.000004491167],"about_ca_topic_score_codex":0.0022743565,"about_ca_topic_score_gemma":0.005957897,"teacher_disagreement_score":0.102117896,"about_ca_system_score_codex":0.00052019214,"about_ca_system_score_gemma":0.0009644589,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4213181941","doi":"10.1002/atr.5670420201","title":"Masthead","year":2008,"lang":"en","type":"paratext","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Citation; Computer science; World Wide Web; Library science","score_opus":0.01112471556006841,"score_gpt":0.24605965801301335,"score_spread":0.23493494245294494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213181941","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00051276374,0.00048130433,0.0017800597,0.0011018091,0.0020185101,0.000081029015,0.002036096,0.0022534865,0.989735],"genre_scores_gemma":[0.00060330715,0.00012074282,0.00024009211,0.00014381771,0.000100725105,0.000014308054,0.00046190535,0.00023950345,0.9980755],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996057,0.000031451284,0.000018276953,0.00008801144,0.00021109484,0.00004562208],"domain_scores_gemma":[0.99865973,0.00019596188,0.0000520125,0.00020817068,0.0006260108,0.00025818712],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00048458227,0.0009960785,0.0006838278,0.0019630287,0.0016540627,0.0037222886,0.0012224336,0.0017108603,0.8985665],"category_scores_gemma":[0.0023221516,0.000526888,0.0005111208,0.0014972955,0.00037222356,0.002715874,0.002364145,0.0017245624,0.81815284],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037204252,0.000026444563,0.00008071465,0.000055196208,0.0000011408366,0.00005595741,0.00003533467,0.000043408698,0.0004474559,0.0021398945,0.8902099,0.10686726],"study_design_scores_gemma":[0.0000076464785,0.00001535194,0.0003506774,0.0000375642,0.0000018054287,0.00007827284,0.00004766464,0.000084044834,0.00021156938,0.00081351603,0.99834764,0.000004152856],"about_ca_topic_score_codex":0.0016549843,"about_ca_topic_score_gemma":0.0048415964,"teacher_disagreement_score":0.101433516,"about_ca_system_score_codex":0.0004897224,"about_ca_system_score_gemma":0.0009972901,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4213237177","doi":"10.1080/03155986.2022.2036034","title":"Pricing and matching for on-demand platform considering customer queuing and order cancellation","year":2022,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"National Social Science Fund of China","keywords":"Queueing theory; Computer science; Profit (economics); Order (exchange); Subsidy; Operations research; Point (geometry); Pricing strategies; Matching (statistics); Mathematical optimization; Microeconomics; Business; Economics; Computer network; Engineering; Mathematics; Finance","score_opus":0.04972577488704604,"score_gpt":0.3180729965969468,"score_spread":0.2683472217099008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213237177","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5675307,0.0004672448,0.39135113,0.0018075095,0.00028205218,0.0004825245,0.00026619507,0.00027635277,0.037536316],"genre_scores_gemma":[0.98837334,0.00010373067,0.0070668254,0.000054186792,0.000027958431,0.000042988915,0.000033908258,0.000021596074,0.004275576],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99755186,0.00081973104,0.000066324385,0.00033121865,0.0003405611,0.00089020934],"domain_scores_gemma":[0.99753404,0.0011457092,0.0004684892,0.00015938781,0.00030971476,0.00038266374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020644933,0.0011427678,0.0013188224,0.000883358,0.0010537293,0.0030715347,0.0026879087,0.0022601536,0.0062606665],"category_scores_gemma":[0.0064409636,0.00073050684,0.0016721492,0.0009607217,0.0013789318,0.0031196952,0.001707105,0.002096202,0.0004054996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024246825,0.00040170684,0.004084328,0.00011162142,0.00006701045,0.0006213844,0.00016015721,0.8744214,0.0025956607,0.102399915,0.0018370864,0.013057367],"study_design_scores_gemma":[0.000022624146,0.00006838393,0.00061532576,0.0000049257183,0.000021162363,0.0000449437,0.0000850161,0.98645544,0.00025197706,0.0120675005,0.0003452099,0.000017579052],"about_ca_topic_score_codex":0.018150736,"about_ca_topic_score_gemma":0.008079586,"teacher_disagreement_score":0.018150736,"about_ca_system_score_codex":0.003939033,"about_ca_system_score_gemma":0.0035160095,"threshold_uncertainty_score":0.036090195},"labels":[],"label_agreement":null},{"id":"W4214532979","doi":"10.1155/2022/9120129","title":"A Bi-Level Optimization Model for Ride-Sourcing Platform’s Spatial Pricing Strategy","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Profit (economics); Service provider; Operations research; Computer science; Pricing strategies; Mode (computer interface); Profit model; Service (business); Mathematical optimization; Microeconomics; Business; Economics; Marketing; Engineering; Mathematics","score_opus":0.029140878809404573,"score_gpt":0.2519471203740131,"score_spread":0.22280624156460854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214532979","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.083655596,0.0010109616,0.8706924,0.002398854,0.0001845762,0.00027354536,0.0012299231,0.00035086772,0.04020333],"genre_scores_gemma":[0.9048989,0.0009046278,0.05787382,0.00032911712,0.00007737396,0.0005223079,0.0005767079,0.00013252517,0.034684576],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989095,0.0003227115,0.000038528724,0.00029061615,0.0001580122,0.00028065563],"domain_scores_gemma":[0.9987362,0.0006299432,0.00015750594,0.00005321839,0.00025195337,0.00017124407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016739937,0.001672419,0.001958997,0.0009661839,0.001032646,0.003808984,0.0030438749,0.0035175153,0.0113199],"category_scores_gemma":[0.0032759535,0.0012785925,0.0015153815,0.0015855868,0.0014169444,0.0026649158,0.0021393765,0.0027628895,0.0012035106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004807803,0.000048083395,0.00053169054,0.000057388967,0.000031080133,0.00017052166,0.0000575501,0.95771384,0.0006866045,0.036842454,0.0012528633,0.002559776],"study_design_scores_gemma":[0.000008947908,0.0000126366,0.000106318286,0.000003854331,0.00000896954,0.000013200978,0.0000229893,0.9953734,0.000048774476,0.003980633,0.00041307523,0.00000717594],"about_ca_topic_score_codex":0.025722234,"about_ca_topic_score_gemma":0.011452601,"teacher_disagreement_score":0.025722234,"about_ca_system_score_codex":0.0037747982,"about_ca_system_score_gemma":0.0026246232,"threshold_uncertainty_score":0.051145017},"labels":[],"label_agreement":null},{"id":"W4214549156","doi":"10.1007/s41062-022-00763-6","title":"Exploring the implications of autonomous vehicles: a comprehensive review","year":2022,"lang":"en","type":"review","venue":"Innovative Infrastructure Solutions","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":168,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Risk analysis (engineering); Automation; Pandemic; Public transport; Business; Isolation (microbiology); Transport engineering; Computer security; Coronavirus disease 2019 (COVID-19); Environmental planning; Engineering; Computer science; Infectious disease (medical specialty); Environmental science","score_opus":0.16486272509273178,"score_gpt":0.32622122749275106,"score_spread":0.16135850240001928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214549156","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000051785377,0.99927145,0.000041820735,0.00022409834,0.00009766231,0.0000033639765,0.000018454028,0.0000015097843,0.0002898884],"genre_scores_gemma":[0.00036685925,0.9992643,0.00006513314,0.00014222942,0.000064030035,0.0000037551088,0.000013301874,4.8510606e-7,0.00007986493],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995419,0.000109938585,0.000071327006,0.00008193021,0.00015427114,0.000040632458],"domain_scores_gemma":[0.99765813,0.0017169927,0.00023911399,0.0000306697,0.00028879754,0.00006621276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013908513,0.0010185296,0.0017583108,0.00353442,0.00032647717,0.0019507265,0.001015373,0.001726704,0.0050861407],"category_scores_gemma":[0.0036319415,0.00038165503,0.0010951181,0.0041339975,0.00057189236,0.0022085893,0.0011358265,0.0015082081,0.0009116759],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000090508955,0.00006187739,0.00028926978,0.15372968,0.000364845,0.00014362126,0.00014869147,0.0006194669,0.0007331418,0.0071823928,0.031127786,0.8055088],"study_design_scores_gemma":[0.000033480595,0.00011782957,0.0011634486,0.07171447,0.0010648811,0.00042104456,0.0002516098,0.00012065809,0.00023277114,0.0038496791,0.92099637,0.000033759894],"about_ca_topic_score_codex":0.0028770347,"about_ca_topic_score_gemma":0.007184238,"teacher_disagreement_score":0.0050861407,"about_ca_system_score_codex":0.0010718318,"about_ca_system_score_gemma":0.0042159283,"threshold_uncertainty_score":0.017014861},"labels":[],"label_agreement":null},{"id":"W4220807550","doi":"10.28991/cej-sp2021-07-06","title":"Multidimension Analysis of Autonomous Vehicles: The Future of Mobility","year":2022,"lang":"en","type":"article","venue":"Civil Engineering Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Speculation; Sketch; Software deployment; Risk analysis (engineering); Investment (military); Order (exchange); Business; Transport engineering; Service (business); Developing country; Public transport; Affect (linguistics); Environmental economics; Computer science; Computer security; Marketing; Economics; Economic growth; Engineering; Finance; Political science; Sociology","score_opus":0.005612811385001315,"score_gpt":0.19671323705059737,"score_spread":0.19110042566559607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220807550","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33448425,0.04369286,0.46551406,0.0592977,0.0012478436,0.00009992278,0.0012621927,0.00021557833,0.09418563],"genre_scores_gemma":[0.9634606,0.011560533,0.017990906,0.00034005218,0.00034514084,0.000042806332,0.0001653795,0.000028296281,0.006066339],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99957365,0.00017116651,0.000016549817,0.000062495776,0.00011622833,0.00005996557],"domain_scores_gemma":[0.99913126,0.00032792005,0.00015298146,0.000071007555,0.0002134146,0.00010346999],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007479382,0.00036471902,0.00039094064,0.0010217854,0.00046113133,0.0026778206,0.0005319077,0.00071647984,0.0027637715],"category_scores_gemma":[0.0025116499,0.0001596814,0.0006670369,0.00089866004,0.0012736565,0.0031982698,0.0011375471,0.0008256964,0.0002470201],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038759357,0.000033156433,0.014927063,0.00022825699,0.000079484,0.00016317648,0.0005244496,0.11913948,0.0008504385,0.7909475,0.004571882,0.0684963],"study_design_scores_gemma":[0.0000041639782,0.00004557425,0.0120131895,0.00016000943,0.00002139441,0.00010595583,0.0010513589,0.30667314,0.00018840615,0.6543744,0.025321547,0.00004090274],"about_ca_topic_score_codex":0.007890275,"about_ca_topic_score_gemma":0.004349296,"teacher_disagreement_score":0.007890275,"about_ca_system_score_codex":0.0018251332,"about_ca_system_score_gemma":0.0011099904,"threshold_uncertainty_score":0.015688717},"labels":[],"label_agreement":null},{"id":"W4220824503","doi":"10.1016/j.trd.2022.103233","title":"Energy and greenhouse gas implications of shared automated electric vehicles","year":2022,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Greenhouse gas; Electrification; Relocation; Electricity; Electric vehicle; Environmental science; Automotive engineering; Environmental economics; Transport engineering; Engineering; Computer science; Electrical engineering; Power (physics)","score_opus":0.0295796858312935,"score_gpt":0.26385741084685643,"score_spread":0.23427772501556293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220824503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9904558,0.00034533822,0.000845468,0.0004032918,0.00004478644,0.000007865383,0.00021947514,0.00000905611,0.007668944],"genre_scores_gemma":[0.99918884,0.00008580446,0.000052148862,0.000009664718,0.0000064742203,0.0000017201043,0.000047450434,0.00000218358,0.0006058446],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99949276,0.00014871178,0.000013513663,0.000073405594,0.00011516272,0.00015638833],"domain_scores_gemma":[0.9989772,0.00048570774,0.00010350654,0.00005729327,0.00033471672,0.00004162775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046731377,0.00042467244,0.00023317033,0.0006670859,0.0006366595,0.001274367,0.0006281365,0.00094829773,0.0048313905],"category_scores_gemma":[0.0012528981,0.00015732912,0.00058790063,0.0009949048,0.00083160977,0.0020732326,0.0010319061,0.0005246891,0.00023625989],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007053842,0.0011522002,0.24443567,0.00057509245,0.0008017446,0.004293822,0.0017903745,0.50834405,0.047707397,0.078316964,0.005035301,0.10049356],"study_design_scores_gemma":[0.00032373535,0.0022437596,0.42715576,0.00018167002,0.0011724889,0.0010093808,0.036130752,0.2555879,0.08520558,0.16317694,0.027505789,0.0003062146],"about_ca_topic_score_codex":0.019260501,"about_ca_topic_score_gemma":0.024483986,"teacher_disagreement_score":0.019260501,"about_ca_system_score_codex":0.0022213948,"about_ca_system_score_gemma":0.00083847065,"threshold_uncertainty_score":0.03829676},"labels":[],"label_agreement":null},{"id":"W4221005454","doi":"10.1155/2022/2920532","title":"Pick‐Up and Delivery Problem for Sequentially Consolidated Urban Transportation with Mixed and Multi‐Purpose Vehicle Fleet","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Heuristics; Vehicle routing problem; Solver; Computer science; Heuristic; Sizing; Fleet management; Convergence (economics); Mathematical optimization; Routing (electronic design automation); Operations research; Engineering; Mathematics; Computer network; Artificial intelligence","score_opus":0.010526177361544183,"score_gpt":0.2200365884252207,"score_spread":0.20951041106367652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221005454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5552374,0.0006017346,0.43336463,0.00039817244,0.000062778534,0.00036391843,0.0007411881,0.00029071816,0.008939455],"genre_scores_gemma":[0.8910618,0.00030121923,0.102281995,0.00004272935,0.000024946425,0.00024110757,0.000780662,0.00007962805,0.005185896],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994727,0.00018689779,0.00002804789,0.0001134107,0.00007999006,0.000119053286],"domain_scores_gemma":[0.99928826,0.0004291215,0.0001206235,0.000039658968,0.00005217544,0.00007017485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010739691,0.0011040616,0.0010480353,0.000663207,0.0006645562,0.0009668988,0.0011853459,0.00075726624,0.0029986184],"category_scores_gemma":[0.0012971263,0.0006307434,0.0014623821,0.0009677611,0.00052523054,0.001173716,0.00072218507,0.0005795551,0.00019472864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017374614,0.00009579119,0.0009923086,0.00011680416,0.00006808547,0.00021203111,0.000044853925,0.97760665,0.0017070626,0.005095055,0.0006819988,0.013205582],"study_design_scores_gemma":[0.00003737626,0.00013814698,0.0006529966,0.0000072716084,0.00003251418,0.00008262849,0.00006455878,0.99455935,0.000923979,0.0026056345,0.00088696944,0.000008671411],"about_ca_topic_score_codex":0.009463552,"about_ca_topic_score_gemma":0.008808997,"teacher_disagreement_score":0.009463552,"about_ca_system_score_codex":0.0013009085,"about_ca_system_score_gemma":0.001726616,"threshold_uncertainty_score":0.018816948},"labels":[],"label_agreement":null},{"id":"W4223425545","doi":"10.1155/2022/8461212","title":"Factors Influencing the Acceptance of Robo-Taxi Services in China: An Extended Technology Acceptance Model Analysis","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China-Zhejiang Joint Fund for the Integration of Industrialization and Informatization; National Natural Science Foundation of China; China Association for Science and Technology","keywords":"Taxis; Beijing; Technology acceptance model; Structural equation modeling; China; Government (linguistics); Incentive; Business; Service (business); Marketing; Public transport; Unified theory of acceptance and use of technology; Social influence; Usability; Transport engineering; Psychology; Computer science; Engineering; Political science; Social psychology; Economics","score_opus":0.009476907246195697,"score_gpt":0.25221590320764764,"score_spread":0.24273899596145193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223425545","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989526,0.000026595259,0.00036463197,0.00006877076,0.000001929014,0.000022529812,0.00004818205,0.000004224934,0.00051056105],"genre_scores_gemma":[0.99948406,0.000034262433,0.00015146633,0.000010840974,0.0000017916947,0.000028540815,0.00009118943,0.0000019719282,0.00019572713],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977869,0.00069471146,0.0002432314,0.0002296835,0.0006542306,0.0003912589],"domain_scores_gemma":[0.99303836,0.0032448194,0.0011850937,0.00035386076,0.0015480844,0.00062987313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042070793,0.00072461064,0.0005936111,0.0021017801,0.000805398,0.0014975907,0.000683804,0.0006165948,0.002425528],"category_scores_gemma":[0.0074364846,0.00033318155,0.0016433148,0.002716521,0.0007946842,0.0010252157,0.0010887656,0.00072057155,0.00029326684],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000536563,0.00018304039,0.98492265,0.000044080563,0.000098199904,0.00015915067,0.0033780148,0.0012588793,0.00036497173,0.00047464616,0.00019676192,0.00886585],"study_design_scores_gemma":[0.000016751352,0.00025086457,0.97132516,0.000034719542,0.00008390466,0.0000836214,0.0041239187,0.023088517,0.00024298263,0.00025599622,0.00046402073,0.000029543837],"about_ca_topic_score_codex":0.040903583,"about_ca_topic_score_gemma":0.024306787,"teacher_disagreement_score":0.040903583,"about_ca_system_score_codex":0.0017456358,"about_ca_system_score_gemma":0.0026190982,"threshold_uncertainty_score":0.081330955},"labels":[],"label_agreement":null},{"id":"W4224290992","doi":"10.1155/2022/8042044","title":"Systematic Analysis and Modelling of Profit Maximization on Carsharing","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Fonds National de la Recherche Luxembourg","keywords":"Profit maximization; Profit (economics); Renting; Microeconomics; Supply and demand; Operations research; Computer science; Business; Economics; Environmental economics; Mathematical optimization; Industrial organization; Mathematics; Engineering","score_opus":0.013005464275898874,"score_gpt":0.21862822349891126,"score_spread":0.20562275922301237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224290992","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.116137765,0.0024281875,0.85210514,0.0005263359,0.000040968356,0.0001675038,0.00028531314,0.0001468417,0.02816193],"genre_scores_gemma":[0.9500917,0.0015430254,0.042106397,0.00003945427,0.000024666882,0.00016508375,0.00013346584,0.00006825355,0.005827923],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941087,0.0002848414,0.000018137114,0.000084423926,0.00011336174,0.00008829589],"domain_scores_gemma":[0.9978904,0.0016611301,0.00017292997,0.00006964696,0.00016873551,0.000037174173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016483746,0.00091365515,0.0010313311,0.0006845506,0.0004211732,0.0016402034,0.00095623283,0.00093334937,0.0020719345],"category_scores_gemma":[0.0044617243,0.0006114376,0.0010745069,0.0010438279,0.0012319842,0.0013244484,0.00087973237,0.0009144786,0.00021252269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013714521,0.00002193548,0.000296961,0.000056629702,0.000012571081,0.00003372776,0.00003808107,0.96390855,0.00037467055,0.032068074,0.00017363527,0.003001558],"study_design_scores_gemma":[0.0000022467136,0.000007017931,0.000104834224,0.0000072060398,0.0000044797116,0.000005275894,0.0000099808385,0.98907244,0.00015659958,0.010308025,0.00031812149,0.0000037077425],"about_ca_topic_score_codex":0.008388026,"about_ca_topic_score_gemma":0.0041789846,"teacher_disagreement_score":0.008388026,"about_ca_system_score_codex":0.0019271546,"about_ca_system_score_gemma":0.0016125577,"threshold_uncertainty_score":0.016678393},"labels":[],"label_agreement":null},{"id":"W4224485565","doi":"10.54932/obpe9357","title":"Introduction d’un télérobot en résidences privées : Enjeux légaux et organisationnels","year":2022,"lang":"fr","type":"report","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Humanities; Political science; Art","score_opus":0.032257170615205034,"score_gpt":0.2739127982911221,"score_spread":0.24165562767591706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224485565","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08581116,0.05056029,0.0747235,0.13823713,0.0053060176,0.00066090433,0.0030296578,0.0009963139,0.640675],"genre_scores_gemma":[0.23306802,0.030717114,0.02747668,0.008091016,0.0012583784,0.00027916412,0.0012257326,0.00038392097,0.69749993],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961687,0.0008695579,0.00011600387,0.00048236357,0.0016589023,0.00070456765],"domain_scores_gemma":[0.99580574,0.00082781806,0.00025211077,0.00024584075,0.0022056713,0.0006628591],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034078343,0.00058297114,0.00032269175,0.0015313165,0.0051602474,0.009118866,0.0010103042,0.0034143622,0.021400347],"category_scores_gemma":[0.0029663946,0.0005609949,0.00040138728,0.0029100925,0.0040892423,0.0039360933,0.001955195,0.0034281618,0.0024267803],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020612458,0.0002623921,0.010478094,0.0013308473,0.000035377576,0.0017159309,0.030794658,0.0047309333,0.00828261,0.34390795,0.22502077,0.37323436],"study_design_scores_gemma":[0.000004233962,0.000055265347,0.006151356,0.00024305558,0.0000056636904,0.0003163531,0.0027467927,0.00041053412,0.0007537718,0.0015385571,0.98774606,0.000028375385],"about_ca_topic_score_codex":0.5775642,"about_ca_topic_score_gemma":0.65077245,"teacher_disagreement_score":0.5775642,"about_ca_system_score_codex":0.02201002,"about_ca_system_score_gemma":0.026537139,"threshold_uncertainty_score":0.84984726},"labels":[],"label_agreement":null},{"id":"W4224860136","doi":"","title":"Sustainability, Scalability and Resiliency of the Town of Innisfil Mobility-on-Demand Experiment: Preliminary Results, Analyses, and Lessons Learned: Preprint","year":2022,"lang":"en","type":"paratext","venue":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Office of Energy Efficiency; Office of Energy Efficiency and Renewable Energy; National Renewable Energy Laboratory; U.S. Department of Energy","keywords":"Preprint; Scalability; Sustainability; Computer science; Environmental economics; World Wide Web; Database; Economics","score_opus":0.023581764148336244,"score_gpt":0.2928722046366818,"score_spread":0.26929044048834555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224860136","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98917496,0.00003388554,0.0014628156,0.0004284996,0.000023737679,0.00037084523,0.0010816884,0.000097817276,0.0073258756],"genre_scores_gemma":[0.99067277,0.000076283526,0.0030820947,0.00015267788,0.00003121889,0.00057691266,0.0015002326,0.000039761835,0.0038681526],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99903345,0.00030415156,0.000028924875,0.00016125494,0.00024377092,0.00022844164],"domain_scores_gemma":[0.9978217,0.0008812557,0.00021910839,0.0003635386,0.00034656658,0.00036786284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018605243,0.00045233508,0.00033009576,0.00028717562,0.0011046366,0.0009863625,0.00097079383,0.0007054779,0.0048972005],"category_scores_gemma":[0.0034262484,0.00022626884,0.0005436106,0.0004417163,0.0013356266,0.0011504863,0.0011309303,0.0012129511,0.00058020867],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.028578527,0.05844007,0.3393364,0.0016915327,0.0012097933,0.0035888962,0.007789232,0.17837074,0.12640588,0.034396388,0.04277147,0.17742099],"study_design_scores_gemma":[0.00439756,0.045395296,0.5291659,0.00020291838,0.0006152112,0.0005017438,0.013133261,0.23899826,0.07033245,0.023892773,0.072817095,0.00054746],"about_ca_topic_score_codex":0.048584364,"about_ca_topic_score_gemma":0.07360106,"teacher_disagreement_score":0.048584364,"about_ca_system_score_codex":0.0028713034,"about_ca_system_score_gemma":0.0014612817,"threshold_uncertainty_score":0.096603155},"labels":[],"label_agreement":null},{"id":"W4225259694","doi":"10.1155/2022/5894250","title":"Analyzing Ride-Sourcing Market Equilibrium and Its Transitions with Heterogeneous Users","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Partial equilibrium; General equilibrium theory; Aggregate (composite); Market analysis; Market share; Economics; Microeconomics; Computer science","score_opus":0.0070859576673170796,"score_gpt":0.21264322519420067,"score_spread":0.2055572675268836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225259694","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58791703,0.0002974088,0.40084866,0.00040136234,0.000023737188,0.0001686967,0.00030451594,0.0001530084,0.009885498],"genre_scores_gemma":[0.9888349,0.00013828475,0.008215698,0.000027776163,0.000008980575,0.000070250746,0.000083542815,0.000018566794,0.0026019972],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995334,0.00012279692,0.000014511194,0.00009944369,0.00005573489,0.00017404261],"domain_scores_gemma":[0.99850404,0.0008383924,0.00027374335,0.00010238842,0.00016748061,0.00011389621],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014293785,0.0005701143,0.0010826895,0.0009054659,0.0006239687,0.0011170497,0.0014349628,0.0011164891,0.0041788495],"category_scores_gemma":[0.0051073506,0.0005031305,0.0011412286,0.0010077783,0.0011286798,0.0027727478,0.0013750762,0.0009931376,0.00025448785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007637112,0.00009743035,0.005003898,0.00007129965,0.000049774324,0.0003457815,0.00019941408,0.91155404,0.001612952,0.0743326,0.00054046756,0.0061160387],"study_design_scores_gemma":[0.0000064848423,0.000022984492,0.00091123907,0.0000035417318,0.00001065611,0.000026342228,0.00009743414,0.98795766,0.00020422733,0.010520801,0.00022938038,0.000009303904],"about_ca_topic_score_codex":0.01635182,"about_ca_topic_score_gemma":0.0059366273,"teacher_disagreement_score":0.01635182,"about_ca_system_score_codex":0.0016236394,"about_ca_system_score_gemma":0.0013081192,"threshold_uncertainty_score":0.03251326},"labels":[],"label_agreement":null},{"id":"W4225286404","doi":"10.1155/2022/1710746","title":"Does Policy Matter in Carsharing Traveling? Evolution Game Model-Based Carsharing and Private Car Study","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Beijing Postdoctoral Science Foundation; China Postdoctoral Science Foundation; Beijing Advanced Innovation Center for Future Urban Design; Beijing University of Civil Engineering and Architecture; Ministry of Education of the People's Republic of China","keywords":"Car sharing; Mode choice; Government (linguistics); Mode (computer interface); Replicator equation; Process (computing); Business; Transport engineering; Computer science; Industrial organization; Engineering; Public transport","score_opus":0.007291261132146631,"score_gpt":0.2409137825400382,"score_spread":0.23362252140789158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225286404","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83731127,0.0017219639,0.116333365,0.004105052,0.00017115763,0.00015829071,0.0002544331,0.000035469235,0.039908946],"genre_scores_gemma":[0.9931815,0.00054719194,0.0021198904,0.00006784033,0.000015420006,0.000030605603,0.000024903451,0.000005420086,0.004007217],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994344,0.0002972796,0.000015119074,0.0000822316,0.00004029193,0.00013063604],"domain_scores_gemma":[0.99774504,0.0016466434,0.00025843372,0.0000422795,0.00016214763,0.00014548896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011441502,0.00045616043,0.00085813785,0.0005437181,0.0005951239,0.0016484791,0.00085595937,0.0014350319,0.004848772],"category_scores_gemma":[0.004414122,0.00027004085,0.00088717026,0.00056394836,0.00092347316,0.0023372008,0.0007492847,0.0014001582,0.00017219415],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027026795,0.00025449783,0.0161982,0.00026963413,0.00020131265,0.0014350853,0.0007549992,0.46297416,0.002399664,0.4994128,0.002224626,0.013604804],"study_design_scores_gemma":[0.000040754807,0.00013144978,0.0040231613,0.00003498002,0.00011045159,0.00011364644,0.0010166805,0.9290525,0.0003252504,0.06250353,0.0026121712,0.000035441702],"about_ca_topic_score_codex":0.013954936,"about_ca_topic_score_gemma":0.011528927,"teacher_disagreement_score":0.013954936,"about_ca_system_score_codex":0.0020163083,"about_ca_system_score_gemma":0.0013997736,"threshold_uncertainty_score":0.027747393},"labels":[],"label_agreement":null},{"id":"W4225584324","doi":"10.1287/msom.2021.1050","title":"When Shared Autonomous Electric Vehicles Meet Microgrids: Citywide Energy-Mobility Orchestration","year":2021,"lang":"en","type":"article","venue":"Manufacturing & Service Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Microgrid; Resilience (materials science); Computer science; Grid; Service (business); Electricity; Analytics; Distributed computing; Reliability engineering; Business; Engineering","score_opus":0.011068101356690408,"score_gpt":0.20689995595560032,"score_spread":0.19583185459890992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225584324","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3642867,0.0010103431,0.60247993,0.008269098,0.0002633998,0.0004364514,0.0033561753,0.00082502706,0.019072877],"genre_scores_gemma":[0.9680265,0.0002927494,0.027457476,0.00018692395,0.00007788612,0.00012936389,0.0008972264,0.00010434976,0.0028274974],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99844307,0.00042667333,0.00007373826,0.00058034546,0.00013262815,0.0003435211],"domain_scores_gemma":[0.9971825,0.0014324294,0.0005371601,0.00017684171,0.00032231922,0.000348844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020400262,0.0010975515,0.0011630406,0.0006965602,0.0009439983,0.0035194845,0.0020225316,0.002419134,0.0047150496],"category_scores_gemma":[0.007302097,0.00074308546,0.0009645898,0.0014106339,0.0013722178,0.0048490716,0.0030902354,0.0016750563,0.0003689507],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011109597,0.00005050927,0.0042161224,0.00011569341,0.000077057404,0.0002818019,0.00014602176,0.95395446,0.00052152853,0.026657064,0.0037525604,0.010116199],"study_design_scores_gemma":[0.000016790507,0.00003402976,0.0010291276,0.000021679494,0.000020185786,0.000069070644,0.00057384773,0.96243817,0.00046167997,0.033631198,0.0016873473,0.000016875265],"about_ca_topic_score_codex":0.018677969,"about_ca_topic_score_gemma":0.0098122815,"teacher_disagreement_score":0.018677969,"about_ca_system_score_codex":0.0022302459,"about_ca_system_score_gemma":0.0025813696,"threshold_uncertainty_score":0.03713852},"labels":[],"label_agreement":null},{"id":"W4225649930","doi":"10.1155/2024/9301691","title":"An Explainable Stacked Ensemble Model for Static Route‐Free Estimation of Time of Arrival","year":2024,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft","keywords":"Computer science; Ensemble learning; Artificial intelligence; Ensemble forecasting; Machine learning; State (computer science); Algorithm","score_opus":0.01096367825345512,"score_gpt":0.26321621429200054,"score_spread":0.2522525360385454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225649930","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09696736,0.0006138115,0.8977964,0.0005758411,0.00011309943,0.000027424985,0.00061904115,0.0007077052,0.0025794047],"genre_scores_gemma":[0.9441952,0.00044153514,0.048170608,0.00018682533,0.000118933836,0.00010498958,0.001124924,0.00008623894,0.005570661],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997527,0.0000596638,0.000012415587,0.00009584982,0.000034402336,0.00004495661],"domain_scores_gemma":[0.99935764,0.0003245319,0.00009239514,0.000054978056,0.00013483061,0.00003551194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075116206,0.00086220517,0.00080631755,0.00051007385,0.0003509026,0.0008297114,0.0011961397,0.0010346092,0.0020930634],"category_scores_gemma":[0.0018866162,0.0004577883,0.0011121188,0.00058716984,0.00037552236,0.0009899833,0.00074213365,0.0013380387,0.00046523768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037651993,0.000022341026,0.0015182744,0.00001685656,0.0000626345,0.00003712061,0.00004173415,0.97315264,0.0006998297,0.0058115325,0.00070489995,0.01789443],"study_design_scores_gemma":[0.0000010327911,0.000005241896,0.00015739295,0.0000017190915,0.000007771912,0.0000029267956,0.0000016032623,0.9984158,0.0000522979,0.0012563706,0.00009540741,0.0000023581918],"about_ca_topic_score_codex":0.016422708,"about_ca_topic_score_gemma":0.015742097,"teacher_disagreement_score":0.016422708,"about_ca_system_score_codex":0.00062591047,"about_ca_system_score_gemma":0.0007370176,"threshold_uncertainty_score":0.032654285},"labels":[],"label_agreement":null},{"id":"W4225700032","doi":"10.1287/msom.2021.1033","title":"Incentivizing Commuters to Carpool: A Large Field Experiment with Waze","year":2021,"lang":"en","type":"article","venue":"Manufacturing & Service Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Carpool; Transport engineering; Leverage (statistics); Service (business); Computer science; Business; Engineering; Marketing","score_opus":0.007672235384511321,"score_gpt":0.2175706914208045,"score_spread":0.2098984560362932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225700032","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99081135,0.00006622671,0.0014873837,0.0006480054,0.0000763557,0.0012479629,0.0012900204,0.00012954128,0.0042432696],"genre_scores_gemma":[0.9821525,0.00008038186,0.004973486,0.0015721782,0.00006045235,0.00433354,0.0011051269,0.000039485032,0.0056827413],"study_design_codex":"observational","study_design_gemma":"randomized_trial","domain_scores_codex":[0.99748117,0.0016292128,0.00008614944,0.0003727538,0.00017424021,0.00025662067],"domain_scores_gemma":[0.9766742,0.01659688,0.0022571194,0.0021832276,0.0009744988,0.001314115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059095616,0.0006415087,0.00067563134,0.00047156843,0.0013505509,0.0013669912,0.0012891159,0.0018645045,0.011503567],"category_scores_gemma":[0.017619604,0.0003918811,0.00068752316,0.0004379253,0.0012463026,0.002050474,0.0009743534,0.002413395,0.0027363305],"study_design_candidate":"randomized_trial","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.05164913,0.2409315,0.39759853,0.0030746583,0.0010488714,0.0014345865,0.016505402,0.01800089,0.016848788,0.017445557,0.089068346,0.1463937],"study_design_scores_gemma":[0.026501155,0.13005558,0.59031755,0.0008606365,0.0014892286,0.00060419453,0.031096185,0.09402388,0.010869337,0.025618926,0.08787019,0.000693101],"about_ca_topic_score_codex":0.0062560104,"about_ca_topic_score_gemma":0.008975223,"teacher_disagreement_score":0.011503567,"about_ca_system_score_codex":0.0008664779,"about_ca_system_score_gemma":0.0010398751,"threshold_uncertainty_score":0.03848332},"labels":[],"label_agreement":null},{"id":"W4225752380","doi":"10.2139/ssrn.4050232","title":"Muddling Through E-Scooters, an Impending Wave of E-Bikes: Examining Policy Approaches to Light Electric Vehicles in Canada's Transportation System","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Western University","funders":"","keywords":"Electric cars; Electric vehicle; Transport engineering; Engineering; Political science; Aeronautics; Automotive engineering; Physics","score_opus":0.03694723365844615,"score_gpt":0.211661225225635,"score_spread":0.17471399156718884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225752380","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.665309,0.0015621854,0.00096811564,0.22169891,0.00038050176,0.00016261988,0.0006151403,0.000043804837,0.10925965],"genre_scores_gemma":[0.9719216,0.0011456058,0.00035154735,0.01459883,0.00006133656,0.00003743919,0.000101200116,0.000016862406,0.011765546],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9935407,0.00070097536,0.00011567235,0.00028934437,0.0015793388,0.0037739545],"domain_scores_gemma":[0.9872907,0.0028017925,0.0012551894,0.00019133795,0.0048095016,0.003651493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032099232,0.00025848555,0.00031763627,0.0018143323,0.016724061,0.01260802,0.0031012679,0.005619392,0.007593387],"category_scores_gemma":[0.018138824,0.00031006316,0.00048273007,0.0032201663,0.0064592194,0.0038624976,0.003096429,0.0072723352,0.00028301508],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043401672,0.0008875347,0.20030099,0.00051026646,0.000155742,0.0015362069,0.11759592,0.0069568926,0.0024769844,0.42938605,0.123081796,0.11667763],"study_design_scores_gemma":[0.00007648684,0.00023332497,0.2855004,0.0009623196,0.00016371973,0.0001315739,0.47999877,0.0053126505,0.0009738364,0.021398872,0.20504089,0.00020724398],"about_ca_topic_score_codex":0.9921055,"about_ca_topic_score_gemma":0.99683845,"teacher_disagreement_score":0.113115,"about_ca_system_score_codex":0.113115,"about_ca_system_score_gemma":0.26546422,"threshold_uncertainty_score":0.8207106},"labels":[],"label_agreement":null},{"id":"W4226299952","doi":"10.2139/ssrn.4076484","title":"Implications of Worker Classification in On-Demand Economy","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Labour economics; Business; Economics","score_opus":0.011710998202129428,"score_gpt":0.23188068401723147,"score_spread":0.22016968581510205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226299952","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9028784,0.0009713116,0.006134123,0.02840969,0.00033059253,0.00016482332,0.0033508937,0.000077444834,0.057682596],"genre_scores_gemma":[0.9899635,0.0002110802,0.00025848398,0.00054238294,0.00015889801,0.000017615945,0.00037577204,0.000010240277,0.008462144],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966821,0.0011040737,0.00013263713,0.0004420082,0.00040278863,0.0012363805],"domain_scores_gemma":[0.9832199,0.007501372,0.004141723,0.0011203408,0.0017047281,0.0023120148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032131393,0.0004194205,0.0014595587,0.0014175659,0.0023558717,0.004886175,0.0018862572,0.0031158302,0.032204546],"category_scores_gemma":[0.0154037895,0.00035991226,0.00089437916,0.0018960887,0.002466177,0.0028757737,0.0021110172,0.0024131793,0.0016091204],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021338267,0.001301178,0.4760665,0.00029097428,0.0002044228,0.0012109092,0.0020473304,0.017445436,0.0012181896,0.41372812,0.031652473,0.052700616],"study_design_scores_gemma":[0.0007609094,0.0006272144,0.424259,0.0004026251,0.00016871856,0.00031494666,0.015762702,0.06448386,0.0012960106,0.47018194,0.02160007,0.0001420708],"about_ca_topic_score_codex":0.040711507,"about_ca_topic_score_gemma":0.03915916,"teacher_disagreement_score":0.040711507,"about_ca_system_score_codex":0.0037440187,"about_ca_system_score_gemma":0.0022182844,"threshold_uncertainty_score":0.10773492},"labels":[],"label_agreement":null},{"id":"W4226404244","doi":"10.2139/ssrn.4078721","title":"Developing a Flexible Activity Scheduling Model to Investigate Post-Pandemic ‘Work Arrangement Choice’ Induced Daily Activity-Travel Demands","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Pandemic; Scheduling (production processes); Computer science; Coronavirus disease 2019 (COVID-19); Operations management; Engineering; Medicine","score_opus":0.0408129350540193,"score_gpt":0.2770966535939213,"score_spread":0.23628371853990204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226404244","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34546122,0.0003746968,0.6308524,0.0016212215,0.00017012883,0.00023787326,0.0016392794,0.000298703,0.019344438],"genre_scores_gemma":[0.9697196,0.00013658746,0.019271087,0.00010561318,0.000031000298,0.0001903724,0.00053529686,0.000057146917,0.009953298],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999458,0.00017122032,0.000019841658,0.000119647964,0.000054941225,0.00017627292],"domain_scores_gemma":[0.9985056,0.0009568932,0.00016982428,0.00005122718,0.00018429855,0.00013221904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010890227,0.0007338763,0.0013073961,0.00057755504,0.00045269393,0.0013100479,0.0022802893,0.0019558475,0.0064564166],"category_scores_gemma":[0.0032043606,0.0008650318,0.00121266,0.0010763191,0.00061729155,0.0011457343,0.00088961626,0.0015225535,0.00046781718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000244974,0.000033131615,0.0005242328,0.0000150311635,0.000017825945,0.000047326914,0.000024658453,0.9943369,0.00021919482,0.003457082,0.00023714085,0.0010629233],"study_design_scores_gemma":[0.0000052663127,0.000009453462,0.0002017278,0.0000018039374,0.000004625617,0.0000039568845,0.000015094203,0.99848336,0.000024886704,0.0011474018,0.00009928657,0.0000031733694],"about_ca_topic_score_codex":0.043621812,"about_ca_topic_score_gemma":0.023978272,"teacher_disagreement_score":0.043621812,"about_ca_system_score_codex":0.0016070175,"about_ca_system_score_gemma":0.002606167,"threshold_uncertainty_score":0.086735785},"labels":[],"label_agreement":null},{"id":"W4226492525","doi":"10.1109/jiot.2022.3168661","title":"An Efficient and Privacy-Preserving Route Matching Scheme for Carpooling Services","year":2022,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"National Natural Science Foundation of China","keywords":"Computer science; Scheme (mathematics); Matching (statistics); Popularity; Computer network; Similarity (geometry); Service (business); Quality of service; Filter (signal processing); The Internet; Blossom algorithm; Computer security; Data mining; World Wide Web; Artificial intelligence","score_opus":0.010588578313652775,"score_gpt":0.24662050703065785,"score_spread":0.23603192871700507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226492525","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.059709653,0.0004259381,0.93217427,0.00026928732,0.000117013406,0.00022415542,0.00029392238,0.001090599,0.005695126],"genre_scores_gemma":[0.85619175,0.00030970786,0.13770242,0.000139344,0.00005694215,0.0001495743,0.00043827394,0.000057528487,0.0049544326],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976761,0.0005099876,0.00018549665,0.0004885002,0.0007654208,0.0003744456],"domain_scores_gemma":[0.99838424,0.0002490984,0.00021629398,0.0007410863,0.00031998355,0.00008933612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007887626,0.0005493781,0.00096797873,0.0008491202,0.0012138347,0.001151166,0.0016577535,0.0010548286,0.0025134867],"category_scores_gemma":[0.003633326,0.00024853178,0.0008710452,0.0020543886,0.000674898,0.0030301563,0.0023522703,0.0011884437,0.00089522963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018211721,0.00036313804,0.0022893278,0.0005307536,0.00019828347,0.0008381722,0.00087683817,0.21830459,0.07316385,0.2064235,0.0142415445,0.48094887],"study_design_scores_gemma":[0.00017981697,0.00047967062,0.00082706654,0.000030979303,0.000089412075,0.0015378852,0.0002699756,0.8958998,0.03661851,0.04323377,0.02069377,0.00013939549],"about_ca_topic_score_codex":0.0019392108,"about_ca_topic_score_gemma":0.0013678143,"teacher_disagreement_score":0.0025134867,"about_ca_system_score_codex":0.0011346872,"about_ca_system_score_gemma":0.0017044093,"threshold_uncertainty_score":0.008408487},"labels":[],"label_agreement":null},{"id":"W4229068799","doi":"10.1016/j.trc.2022.103677","title":"Crowdshipping: An open VRP variant with stochastic destinations","year":2022,"lang":"en","type":"article","venue":"Transportation Research Part C Emerging Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Secretaría de Educación Superior, Ciencia, Tecnología e Innovación; Polytechnique Montréal","keywords":"Vehicle routing problem; Destinations; Transport engineering; Computer science; Travelling salesman problem; Operations research; Engineering; Mathematical optimization; Geography; Mathematics; Routing (electronic design automation); Algorithm; Computer network; Tourism","score_opus":0.09971195842149394,"score_gpt":0.36157426140991433,"score_spread":0.2618623029884204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229068799","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09335922,0.0003174316,0.88914716,0.00061210437,0.0006021111,0.00013615325,0.00050884637,0.0016519957,0.0136649255],"genre_scores_gemma":[0.8555296,0.00011190689,0.13393451,0.00017584904,0.00013047182,0.00008515848,0.0004797772,0.0002529822,0.009299776],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901414,0.0002407898,0.0000358583,0.00024470326,0.00022272197,0.00024185675],"domain_scores_gemma":[0.99829,0.0007342376,0.00008854485,0.00037685342,0.00027017933,0.00024026558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011172072,0.00089885865,0.0013631184,0.0004420031,0.00081597414,0.0014703716,0.003764423,0.0022804402,0.0060920273],"category_scores_gemma":[0.0048088604,0.00040207987,0.0008888346,0.0009635349,0.001128632,0.0015379369,0.0035283072,0.0017055675,0.0006781381],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005936609,0.00022093809,0.00059830653,0.000090773356,0.00005694337,0.00035259037,0.00011532489,0.87630713,0.0036338859,0.05493731,0.0061900197,0.056903087],"study_design_scores_gemma":[0.000029245157,0.000037289366,0.000048871996,0.0000032371358,0.00000508672,0.000025629755,0.000015076299,0.9916408,0.00026328774,0.0070885583,0.0008345122,0.000008316019],"about_ca_topic_score_codex":0.009428992,"about_ca_topic_score_gemma":0.0074703246,"teacher_disagreement_score":0.009428992,"about_ca_system_score_codex":0.0006785522,"about_ca_system_score_gemma":0.0012222775,"threshold_uncertainty_score":0.020379901},"labels":[],"label_agreement":null},{"id":"W4229446693","doi":"10.1155/2022/2780711","title":"Rebalancing Docked Bicycle Sharing System with Approximate Dynamic Programming and Reinforcement Learning","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Ministry of Science and ICT, South Korea; National Research Foundation of Korea; Ministry of Education; Seoul National University; National Research Foundation","keywords":"Markov decision process; Reinforcement learning; Computer science; Dynamic programming; Q-learning; Markov chain; Operations research; Markov process; Renting; Mathematical optimization; Engineering; Machine learning","score_opus":0.004544719348684997,"score_gpt":0.2089140402128321,"score_spread":0.2043693208641471,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229446693","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12332782,0.0006698962,0.8681493,0.0003157993,0.00008783323,0.000112353686,0.00007777022,0.0005880208,0.0066712806],"genre_scores_gemma":[0.98535454,0.0000955234,0.013016916,0.000045863195,0.000011557566,0.00006197843,0.00003253459,0.000013606432,0.0013674676],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99959916,0.00009638312,0.000019283683,0.000099612924,0.0000754275,0.00011009429],"domain_scores_gemma":[0.9994118,0.00028356616,0.000111912246,0.00002550976,0.00010366738,0.00006362578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006931515,0.0009237539,0.0013548331,0.00037807034,0.0005022161,0.00096026954,0.0012012847,0.0008585103,0.002104194],"category_scores_gemma":[0.0011280355,0.00050123496,0.00064699486,0.00035826856,0.00052070635,0.00063494546,0.000982569,0.000999947,0.00021049434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031299947,0.000028170958,0.00026144218,0.000019527919,0.000011517836,0.00003954232,0.000015383963,0.99272037,0.00035055602,0.00086142163,0.00014055704,0.005520298],"study_design_scores_gemma":[0.0000031952893,0.000012565855,0.000028662897,0.0000010768002,0.0000025204724,0.0000029607168,0.000002679467,0.9996754,0.00004255562,0.00018860283,0.000038444,0.0000013584914],"about_ca_topic_score_codex":0.018977605,"about_ca_topic_score_gemma":0.0119124055,"teacher_disagreement_score":0.018977605,"about_ca_system_score_codex":0.0009327977,"about_ca_system_score_gemma":0.0015260144,"threshold_uncertainty_score":0.03773433},"labels":[],"label_agreement":null},{"id":"W4229569664","doi":"10.4018/978-1-60960-100-3.ch513","title":"Mobile Virtual Communities of Commuters","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Taxis; Public transport; Global Positioning System; Computer science; Telephony; Telecommunications; The Internet; Passenger information; Transport engineering; Software; Engineering; World Wide Web","score_opus":0.023134898790324838,"score_gpt":0.22485816054203453,"score_spread":0.20172326175170968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229569664","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06963888,0.008163346,0.068284206,0.0053951177,0.0012567642,0.0003563587,0.00038853736,0.0016486377,0.8448681],"genre_scores_gemma":[0.4606324,0.0057549225,0.03527489,0.0009480421,0.0005677966,0.00048064507,0.0007182041,0.0003191703,0.49530387],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99958664,0.00017968635,0.000015377973,0.00007408006,0.00008280258,0.00006146843],"domain_scores_gemma":[0.9992454,0.00019513178,0.00004508287,0.00013394121,0.000080428326,0.00030013555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059682544,0.0003932581,0.00021251662,0.0010344717,0.0025501482,0.00547496,0.0011079363,0.0011954535,0.036644418],"category_scores_gemma":[0.0015609255,0.00021314976,0.0002617138,0.0010759194,0.0011795847,0.0062145567,0.0049923286,0.00072531914,0.0057362784],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000120898825,0.0001695294,0.0015113199,0.0005516802,0.000019368032,0.0010910333,0.024518318,0.0015739133,0.0026334797,0.41657102,0.10557898,0.44566047],"study_design_scores_gemma":[0.00001600868,0.00004308289,0.0004972324,0.00013760926,0.000008102829,0.0006370908,0.004581862,0.0014477451,0.00036026453,0.03226247,0.9599953,0.000013170214],"about_ca_topic_score_codex":0.0010792234,"about_ca_topic_score_gemma":0.0019924727,"teacher_disagreement_score":0.036644418,"about_ca_system_score_codex":0.0007222604,"about_ca_system_score_gemma":0.0006732679,"threshold_uncertainty_score":0.1225878},"labels":[],"label_agreement":null},{"id":"W4229590830","doi":"10.32920/ryerson.14645334","title":"Evaluation methods of dynamic flexible transportation systems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Public transport; Computer science; Taxis; Context (archaeology); Carpool; Crowds; Sharing economy; Operations research; Transport engineering; Global Positioning System; Social Welfare; Engineering; Computer security; Telecommunications","score_opus":0.04662899032893214,"score_gpt":0.3684962793045367,"score_spread":0.32186728897560457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229590830","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0153866075,0.00048089962,0.9793616,0.00025190142,0.000042028194,0.0003202911,0.000121999656,0.00015362796,0.003881039],"genre_scores_gemma":[0.7041093,0.000661608,0.29006204,0.00008694845,0.00008188009,0.0010403822,0.00042562993,0.00011667388,0.003415463],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98923945,0.007335463,0.0005087391,0.0010079151,0.0015238031,0.0003846351],"domain_scores_gemma":[0.975086,0.019490538,0.0014639809,0.00085494254,0.0027458926,0.00035855567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015709747,0.0014178036,0.0013590235,0.003412051,0.00073423446,0.0029630752,0.001998771,0.0011156013,0.004470213],"category_scores_gemma":[0.04371355,0.0006519461,0.0011064411,0.002596144,0.0016147069,0.003240582,0.0023347393,0.0013501695,0.00025379343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008276907,0.000055390425,0.001704875,0.00020112049,0.00010095667,0.00006664853,0.00017618544,0.85145015,0.00039912423,0.0891155,0.00054169475,0.05610554],"study_design_scores_gemma":[0.000008621532,0.00003710765,0.00017384038,0.000017032842,0.000008211987,0.0000073516503,0.000041105774,0.9797847,0.00012718361,0.019297836,0.0004904118,0.0000065796403],"about_ca_topic_score_codex":0.008421554,"about_ca_topic_score_gemma":0.003360412,"teacher_disagreement_score":0.015709747,"about_ca_system_score_codex":0.00383874,"about_ca_system_score_gemma":0.0023680856,"threshold_uncertainty_score":0.08308208},"labels":[],"label_agreement":null},{"id":"W4229823162","doi":"10.1287/opre.1100.0901","title":"Contributors","year":2010,"lang":"en","type":"article","venue":"Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Operations research; Computer science; Game theory; Influence diagram; Markov decision process; Management science; Artificial intelligence; Mathematical economics; Mathematics; Engineering; Markov process; Decision tree","score_opus":0.037358503014294726,"score_gpt":0.363619421975952,"score_spread":0.32626091896165726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229823162","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013874716,0.0063281613,0.0051274803,0.029692052,0.051269755,0.00045339248,0.0070359823,0.0021656244,0.89654005],"genre_scores_gemma":[0.00460433,0.0034129685,0.0019823154,0.004691485,0.004701899,0.00017351561,0.004909812,0.00071391097,0.9748097],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977004,0.00030827287,0.00013208408,0.00045736737,0.0010914139,0.00031032172],"domain_scores_gemma":[0.99286073,0.0005622286,0.000174438,0.0007217282,0.0039817765,0.0016989812],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0019324677,0.0010446238,0.00084499177,0.0025835312,0.0023635747,0.0068509504,0.00252123,0.0029421148,0.6531896],"category_scores_gemma":[0.00973604,0.00036246082,0.00072943413,0.0028059524,0.0006265509,0.0052746874,0.003876063,0.002069301,0.4887409],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027534217,0.00001902627,0.00016697777,0.00009887814,0.0000029041203,0.0000463654,0.00006897377,0.00006948286,0.000117290416,0.007538209,0.927865,0.063979134],"study_design_scores_gemma":[0.0000032043993,0.000006098071,0.00011915335,0.000057588037,0.0000012797792,0.000040682608,0.00007342695,0.00003336922,0.000044353015,0.0011710263,0.99844664,0.0000032811529],"about_ca_topic_score_codex":0.0022419484,"about_ca_topic_score_gemma":0.003009462,"teacher_disagreement_score":0.6531896,"about_ca_system_score_codex":0.0025228576,"about_ca_system_score_gemma":0.0036707907,"threshold_uncertainty_score":0.4946829},"labels":[],"label_agreement":null},{"id":"W4229840547","doi":"10.32866/109371","title":"Modeling the Purpose for Renting Passenger Vehicles","year":2019,"lang":"en","type":"article","venue":"Findings","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Renting; Multinomial logistic regression; Sample (material); Econometrics; Business; Term (time); Marketing; Transport engineering; Statistics; Economics; Engineering; Mathematics","score_opus":0.015580958055202421,"score_gpt":0.22350098858590492,"score_spread":0.2079200305307025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229840547","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86252546,0.000753294,0.10571962,0.0022511543,0.00008592872,0.00034250677,0.006379916,0.00033800933,0.021604003],"genre_scores_gemma":[0.9784466,0.00030756296,0.009153614,0.000055004184,0.000018161372,0.00012851969,0.0013316759,0.000028118639,0.010530763],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894553,0.00040965818,0.00004152604,0.00018153542,0.0001560815,0.00026557167],"domain_scores_gemma":[0.99744415,0.0014332775,0.0004152338,0.00014455756,0.0004069057,0.00015588659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001831056,0.00061178475,0.00049851096,0.0017780564,0.00086062343,0.0024585219,0.0018839433,0.0012544738,0.00455995],"category_scores_gemma":[0.0058752447,0.00058347225,0.0010278705,0.0012990698,0.00089717226,0.0015793361,0.0011841294,0.0009874352,0.001115663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003264531,0.0005286873,0.3701056,0.00017706436,0.00020866872,0.0007312468,0.001706352,0.45087844,0.0009642673,0.12925462,0.0061189155,0.03899963],"study_design_scores_gemma":[0.000049134513,0.00010354299,0.043907408,0.000072930074,0.00011672512,0.0002453944,0.0009891535,0.9250933,0.0003727706,0.019910593,0.009069879,0.00006916862],"about_ca_topic_score_codex":0.2636714,"about_ca_topic_score_gemma":0.31142852,"teacher_disagreement_score":0.2636714,"about_ca_system_score_codex":0.0044449875,"about_ca_system_score_gemma":0.0032442084,"threshold_uncertainty_score":0.5242733},"labels":[],"label_agreement":null},{"id":"W4230416168","doi":"10.4018/9781930708266.ch013","title":"Understanding Credit Card User's Behaviour","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Credit card; Computer science; Business; World Wide Web; Payment","score_opus":0.07309550477133014,"score_gpt":0.24001330590697184,"score_spread":0.1669178011356417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230416168","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9837171,0.00048144563,0.0029821019,0.00093740603,0.000016133432,0.000068667505,0.0018297673,0.00015816306,0.009809219],"genre_scores_gemma":[0.99480295,0.00039333224,0.0016203308,0.00012064581,0.000012007481,0.000020136093,0.0006206359,0.000007859018,0.00240218],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997224,0.00006927833,0.000028224018,0.000055615703,0.000081095895,0.000043419306],"domain_scores_gemma":[0.9985422,0.00076526817,0.00020301466,0.000064090025,0.0002773881,0.00014820906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046900442,0.00022876609,0.0002944264,0.0018622988,0.00038004355,0.0012188699,0.00033464303,0.00073031546,0.0042172517],"category_scores_gemma":[0.004174171,0.0001181772,0.0001620795,0.0009517531,0.00021881048,0.0010561157,0.00034788315,0.0005538408,0.0015243443],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014405351,0.00022747509,0.9290256,0.000048662107,0.000023036126,0.00021145397,0.002757084,0.0005653413,0.001056114,0.00048510593,0.0028751967,0.06258083],"study_design_scores_gemma":[0.000005081397,0.00012225163,0.9699859,0.000056423687,0.00002817392,0.0006739929,0.004484984,0.017874265,0.00082706736,0.00070515246,0.005207543,0.000029123808],"about_ca_topic_score_codex":0.016228225,"about_ca_topic_score_gemma":0.013542617,"teacher_disagreement_score":0.016228225,"about_ca_system_score_codex":0.0005248682,"about_ca_system_score_gemma":0.0002453054,"threshold_uncertainty_score":0.03226751},"labels":[],"label_agreement":null},{"id":"W4230916325","doi":"10.32920/ryerson.14660943","title":"Multimodal Automated Last-Mile Delivery System: Design and Application","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Drone; Last mile (transportation); Hybrid system; Computer science; Food delivery; Robot; Delivery system; Mile; Simulation; Phase (matter); Transport engineering; Real-time computing; Engineering; Artificial intelligence; Business","score_opus":0.011823956805818533,"score_gpt":0.22452827548315207,"score_spread":0.21270431867733353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230916325","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3651309,0.0007801963,0.5983797,0.00044289255,0.00011433214,0.0009309105,0.00045624562,0.003906622,0.029858232],"genre_scores_gemma":[0.93035984,0.0002558373,0.058841735,0.0000453694,0.000013177436,0.00034275962,0.00015404684,0.00004836632,0.0099389],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998294,0.000037514983,0.000008173386,0.000036005833,0.00006483356,0.000024014695],"domain_scores_gemma":[0.99985933,0.000021708267,0.00001849772,0.000016330177,0.0000661393,0.000017998416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002064272,0.0003356132,0.0002831484,0.0002701194,0.000262523,0.00058837206,0.000678708,0.0005756173,0.0053228233],"category_scores_gemma":[0.00027562527,0.00015255158,0.00020457985,0.00023958176,0.00017120433,0.00032728555,0.0003695049,0.00019577939,0.0009729915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060038763,0.0004300966,0.006543562,0.0009445347,0.00009383084,0.00086424826,0.0005033737,0.46647412,0.19525792,0.0087486245,0.0060712434,0.31346798],"study_design_scores_gemma":[0.00007084673,0.0012498371,0.0033427782,0.000040191742,0.000054869728,0.00036551832,0.0001752457,0.9234044,0.04836078,0.0009785006,0.021917898,0.000039097755],"about_ca_topic_score_codex":0.0022441298,"about_ca_topic_score_gemma":0.001264228,"teacher_disagreement_score":0.0053228233,"about_ca_system_score_codex":0.00046471864,"about_ca_system_score_gemma":0.00045249745,"threshold_uncertainty_score":0.01780659},"labels":[],"label_agreement":null},{"id":"W4231495250","doi":"10.32920/ryerson.14660943.v1","title":"Multimodal Automated Last-Mile Delivery System: Design and Application","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Drone; Last mile (transportation); Hybrid system; Computer science; Food delivery; Robot; Delivery system; Mile; Real-time computing; Transport engineering; Simulation; Engineering; Artificial intelligence; Business; Geography","score_opus":0.011823956805818533,"score_gpt":0.22452827548315207,"score_spread":0.21270431867733353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231495250","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3651309,0.0007801963,0.5983797,0.00044289255,0.00011433214,0.0009309105,0.00045624562,0.003906622,0.029858232],"genre_scores_gemma":[0.93035984,0.0002558373,0.058841735,0.0000453694,0.000013177436,0.00034275962,0.00015404684,0.00004836632,0.0099389],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998294,0.000037514983,0.000008173386,0.000036005833,0.00006483356,0.000024014695],"domain_scores_gemma":[0.99985933,0.000021708267,0.00001849772,0.000016330177,0.0000661393,0.000017998416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002064272,0.0003356132,0.0002831484,0.0002701194,0.000262523,0.00058837206,0.000678708,0.0005756173,0.0053228233],"category_scores_gemma":[0.00027562527,0.00015255158,0.00020457985,0.00023958176,0.00017120433,0.00032728555,0.0003695049,0.00019577939,0.0009729915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060038763,0.0004300966,0.006543562,0.0009445347,0.00009383084,0.00086424826,0.0005033737,0.46647412,0.19525792,0.0087486245,0.0060712434,0.31346798],"study_design_scores_gemma":[0.00007084673,0.0012498371,0.0033427782,0.000040191742,0.000054869728,0.00036551832,0.0001752457,0.9234044,0.04836078,0.0009785006,0.021917898,0.000039097755],"about_ca_topic_score_codex":0.0022441298,"about_ca_topic_score_gemma":0.001264228,"teacher_disagreement_score":0.0053228233,"about_ca_system_score_codex":0.00046471864,"about_ca_system_score_gemma":0.00045249745,"threshold_uncertainty_score":0.01780659},"labels":[],"label_agreement":null},{"id":"W4231496721","doi":"10.5539/mas.v12n11p244","title":"The Ride-Hailing Mobile Application for Personalized Travelling","year":2018,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Business; Service (business); Marketing; Location-based service; Computer science; Telecommunications","score_opus":0.011393032865567565,"score_gpt":0.25259274803226384,"score_spread":0.24119971516669628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231496721","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28937918,0.008474142,0.20462552,0.0022521142,0.00080014864,0.0035701296,0.019484794,0.20186238,0.26955158],"genre_scores_gemma":[0.6348707,0.0039481036,0.103303425,0.001605391,0.0003249941,0.0013775905,0.011917779,0.0033525256,0.23929952],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99988997,0.000022244376,0.00000873464,0.000017655735,0.00003630684,0.000025006018],"domain_scores_gemma":[0.99978834,0.000044887438,0.000014409194,0.000049775357,0.000055679182,0.000046883848],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024735264,0.00042934314,0.00029599096,0.0005699478,0.0004889971,0.00076343847,0.00042368134,0.00057013554,0.030011648],"category_scores_gemma":[0.0006403795,0.00012880885,0.00031360987,0.00042853656,0.00010721033,0.0008096216,0.0011623607,0.00045031426,0.011886146],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009009943,0.0003631599,0.008134237,0.0009223418,0.000067597546,0.0011700072,0.002051968,0.00086674176,0.033891022,0.0034481946,0.18447162,0.7637122],"study_design_scores_gemma":[0.00020385378,0.00068302697,0.040919133,0.0003379739,0.00013947036,0.0034471562,0.001184931,0.027081745,0.022518221,0.0021258772,0.9011414,0.00021727334],"about_ca_topic_score_codex":0.0015956789,"about_ca_topic_score_gemma":0.0027436307,"teacher_disagreement_score":0.030011648,"about_ca_system_score_codex":0.00014599517,"about_ca_system_score_gemma":0.00028340227,"threshold_uncertainty_score":0.10039896},"labels":[],"label_agreement":null},{"id":"W4231727957","doi":"10.1002/atr.5670410101","title":"Masthead","year":2007,"lang":"en","type":"paratext","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Citation; Computer science; World Wide Web; Library science","score_opus":0.010923040297259172,"score_gpt":0.26434464492414084,"score_spread":0.2534216046268817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231727957","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00050444104,0.0005156188,0.0022294133,0.0010513122,0.0020746558,0.00008667356,0.0021378614,0.0025889794,0.98881114],"genre_scores_gemma":[0.00062022725,0.00014463757,0.00030654573,0.00015943746,0.00011049452,0.000015829744,0.00055629114,0.00030375726,0.9977829],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995741,0.00003364753,0.000018940877,0.00009227935,0.00023167343,0.00004934941],"domain_scores_gemma":[0.9986156,0.0002048801,0.0000507848,0.0002201985,0.0006415938,0.00026679467],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000511187,0.0010833926,0.00074322853,0.0020584948,0.0017284177,0.0038566291,0.001334282,0.0017667079,0.90239733],"category_scores_gemma":[0.0022902817,0.00056759885,0.00056628115,0.0016011754,0.0003917638,0.0027140586,0.0024602672,0.0017597685,0.8300991],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040882755,0.000030337478,0.00007842249,0.000059758117,0.000001382939,0.000057933587,0.000035407134,0.00005036546,0.0005208986,0.0022989744,0.88183314,0.11499253],"study_design_scores_gemma":[0.000008191295,0.000016050308,0.00032526712,0.000038284867,0.0000021435173,0.00008353781,0.00004786512,0.000094439296,0.00026338323,0.0009084633,0.9982078,0.0000046790024],"about_ca_topic_score_codex":0.0016447642,"about_ca_topic_score_gemma":0.0046748747,"teacher_disagreement_score":0.097602665,"about_ca_system_score_codex":0.0004915309,"about_ca_system_score_gemma":0.0010773275,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4232110773","doi":"10.32920/ryerson.14644080","title":"Among four traveller types in the Greater Toronto and Hamilton Region, who uses ride-hailing?","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Popularity; Business; Variety (cybernetics); Service (business); Key (lock); Advertising; Geography; Marketing; Computer science; Psychology; Computer security","score_opus":0.026101884929456712,"score_gpt":0.2251534011919231,"score_spread":0.19905151626246637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232110773","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982639,0.00010788411,0.00004765173,0.00015082449,0.0000022178197,0.000019524923,0.00048641188,0.0000043134883,0.00091731624],"genre_scores_gemma":[0.9971981,0.00022865544,0.000107086504,0.0000452659,0.0000021837438,0.000016770808,0.0004102789,0.0000031841048,0.001988549],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99975103,0.00003026719,0.00001566115,0.000037818296,0.000054648346,0.00011058004],"domain_scores_gemma":[0.9993961,0.000050332208,0.00018622518,0.000023738547,0.00012474877,0.00021888182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021346135,0.00017443168,0.00017793183,0.00084946904,0.0016358123,0.0012461684,0.0005330937,0.0003218898,0.0032700063],"category_scores_gemma":[0.0010623018,0.00017721292,0.00023788578,0.001849628,0.00068412046,0.0006255932,0.00077597605,0.00036505767,0.00039626306],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041474545,0.000017157627,0.9786128,0.000050594637,0.000019399205,0.00026584658,0.01385339,0.00005864565,0.00039411863,0.00017125055,0.0008340086,0.0056814468],"study_design_scores_gemma":[0.0000011293132,0.000021043179,0.9593276,0.000020581156,0.000007747417,0.000081397644,0.039571036,0.0000989172,0.00005208893,0.000020251584,0.00079024635,0.000008057137],"about_ca_topic_score_codex":0.8798364,"about_ca_topic_score_gemma":0.96005297,"teacher_disagreement_score":0.12016362,"about_ca_system_score_codex":0.0044446816,"about_ca_system_score_gemma":0.003412795,"threshold_uncertainty_score":0.24174255},"labels":[],"label_agreement":null},{"id":"W4232160242","doi":"10.32920/ryerson.14645334.v1","title":"Evaluation methods of dynamic flexible transportation systems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Public transport; Computer science; Taxis; Context (archaeology); Carpool; Sharing economy; Crowds; Transport engineering; Operations research; Global Positioning System; Social Welfare; Engineering; Computer security; Telecommunications","score_opus":0.04662899032893214,"score_gpt":0.3684962793045367,"score_spread":0.32186728897560457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232160242","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0153866075,0.00048089962,0.9793616,0.00025190142,0.000042028194,0.0003202911,0.000121999656,0.00015362796,0.003881039],"genre_scores_gemma":[0.7041093,0.000661608,0.29006204,0.00008694845,0.00008188009,0.0010403822,0.00042562993,0.00011667388,0.003415463],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98923945,0.007335463,0.0005087391,0.0010079151,0.0015238031,0.0003846351],"domain_scores_gemma":[0.975086,0.019490538,0.0014639809,0.00085494254,0.0027458926,0.00035855567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015709747,0.0014178036,0.0013590235,0.003412051,0.00073423446,0.0029630752,0.001998771,0.0011156013,0.004470213],"category_scores_gemma":[0.04371355,0.0006519461,0.0011064411,0.002596144,0.0016147069,0.003240582,0.0023347393,0.0013501695,0.00025379343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008276907,0.000055390425,0.001704875,0.00020112049,0.00010095667,0.00006664853,0.00017618544,0.85145015,0.00039912423,0.0891155,0.00054169475,0.05610554],"study_design_scores_gemma":[0.000008621532,0.00003710765,0.00017384038,0.000017032842,0.000008211987,0.0000073516503,0.000041105774,0.9797847,0.00012718361,0.019297836,0.0004904118,0.0000065796403],"about_ca_topic_score_codex":0.008421554,"about_ca_topic_score_gemma":0.003360412,"teacher_disagreement_score":0.015709747,"about_ca_system_score_codex":0.00383874,"about_ca_system_score_gemma":0.0023680856,"threshold_uncertainty_score":0.08308208},"labels":[],"label_agreement":null},{"id":"W4232372322","doi":"10.1002/atr.5670380301","title":"Masthead","year":2004,"lang":"en","type":"paratext","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Citation; Computer science; World Wide Web; Library science","score_opus":0.008990510154888751,"score_gpt":0.24801771858277127,"score_spread":0.23902720842788253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232372322","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005754049,0.0005990475,0.0018942475,0.0009515695,0.0016399021,0.00007292528,0.0019852405,0.0022479487,0.9900338],"genre_scores_gemma":[0.00060076965,0.00013394459,0.00023492923,0.00011184191,0.00007033964,0.0000113006745,0.00044651775,0.00020082072,0.9981895],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99964154,0.000029070809,0.00001755127,0.000086862936,0.0001810417,0.000043973338],"domain_scores_gemma":[0.9988048,0.0001759549,0.000046924237,0.00019956601,0.0005494416,0.00022324813],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004583769,0.0011100527,0.00074924185,0.0021344726,0.0018265549,0.0038591654,0.0013098995,0.0017410999,0.8978821],"category_scores_gemma":[0.001978289,0.0005801078,0.00052691886,0.0018586551,0.00036530854,0.0027248648,0.0020662213,0.0015531301,0.8123035],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048409263,0.00003468451,0.00010008807,0.00006720448,0.000001538066,0.000065399734,0.00004665963,0.00005585433,0.0006199232,0.0024721401,0.86587226,0.13061573],"study_design_scores_gemma":[0.000008565452,0.000017056687,0.00040915952,0.00003561638,0.0000024503013,0.000082701736,0.000055367644,0.00009217585,0.00026286644,0.0008280042,0.9982016,0.000004491167],"about_ca_topic_score_codex":0.0022743565,"about_ca_topic_score_gemma":0.005957897,"teacher_disagreement_score":0.102117896,"about_ca_system_score_codex":0.00052019214,"about_ca_system_score_gemma":0.0009644589,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4232741649","doi":"10.32920/ryerson.14666373.v1","title":"Impacts of autonomous vehicles on traffic volume: scenarios based on survey data for the City of Karlsruhe","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Transport engineering; Baseline (sea); Traffic volume; Mode (computer interface); Mode choice; Trip generation; Computer science; Survey data collection; Field survey; Engineering; Statistics; Civil engineering; Mathematics","score_opus":0.06998933320892542,"score_gpt":0.2912266871800168,"score_spread":0.2212373539710914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232741649","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977755,0.000050195653,0.00027811457,0.000046062254,0.0000019506392,0.000014463035,0.0014623477,0.000012827477,0.0003585073],"genre_scores_gemma":[0.9978514,0.000079740734,0.00029263907,0.0000044827802,0.0000012445976,0.000016923193,0.0016467758,0.0000017999422,0.00010516236],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991929,0.00035072438,0.000038625534,0.000101412654,0.00014027081,0.00017603635],"domain_scores_gemma":[0.9984931,0.00094802736,0.00018024916,0.00009734967,0.00020377802,0.0000775736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094294874,0.00043057205,0.0003524976,0.001267452,0.0002511468,0.00088037015,0.0004448536,0.00067707,0.0006918227],"category_scores_gemma":[0.001956084,0.00017512163,0.0007420573,0.0019590277,0.00040943574,0.0006756352,0.00054112374,0.00029452913,0.00014113089],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00082371064,0.00048223464,0.35811475,0.00027712155,0.00043920008,0.0015672973,0.00042876013,0.62082654,0.00130269,0.0019775738,0.002040821,0.011719256],"study_design_scores_gemma":[0.00010133825,0.00060435844,0.53616655,0.000056750378,0.0001885345,0.00040899919,0.0034344837,0.45261052,0.002619344,0.0012733273,0.0024042963,0.00013149521],"about_ca_topic_score_codex":0.045115177,"about_ca_topic_score_gemma":0.04129571,"teacher_disagreement_score":0.045115177,"about_ca_system_score_codex":0.0017826257,"about_ca_system_score_gemma":0.0005698511,"threshold_uncertainty_score":0.08970517},"labels":[],"label_agreement":null},{"id":"W4233286730","doi":"10.1016/s1365-6937(14)70216-3","title":"BluMetric re-mortgages Ottawa real estate","year":2014,"lang":"en","type":"article","venue":"Filtration Industry Analyst","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Real estate; Business; Property (philosophy); Real property; Finance; Political science; Law; Philosophy","score_opus":0.014934101125640475,"score_gpt":0.2422129561202349,"score_spread":0.22727885499459444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233286730","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022772199,0.0026092303,0.0015961989,0.01687611,0.0025827626,0.0003673176,0.015210903,0.0026181166,0.9353671],"genre_scores_gemma":[0.031222947,0.0004372575,0.00061099033,0.0007289508,0.00009623454,0.000025821835,0.0034322664,0.00018171802,0.9632638],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99679846,0.00009117445,0.00007332958,0.00027742574,0.0022964152,0.00046317576],"domain_scores_gemma":[0.9952468,0.00014339139,0.00013005939,0.0004115681,0.0034262184,0.0006420077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010498615,0.00086682517,0.00048849254,0.002111383,0.0056603593,0.004751074,0.0015625234,0.0018469968,0.22634031],"category_scores_gemma":[0.004863031,0.00082595734,0.00047576812,0.001423372,0.00092439173,0.0016354185,0.0014948637,0.0027599144,0.062819295],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012430588,0.000043418244,0.0046241144,0.00004026636,0.000008407287,0.0002355566,0.00026762942,0.00012153442,0.0011394994,0.0067362324,0.9492376,0.037421506],"study_design_scores_gemma":[0.000008358717,0.000031691747,0.0062191733,0.000026973523,0.000008865199,0.000153184,0.00030886938,0.00032136636,0.0008387033,0.00028802946,0.99177706,0.000017764223],"about_ca_topic_score_codex":0.6888237,"about_ca_topic_score_gemma":0.90347934,"teacher_disagreement_score":0.6888237,"about_ca_system_score_codex":0.014827002,"about_ca_system_score_gemma":0.016344573,"threshold_uncertainty_score":0.7571838},"labels":[],"label_agreement":null},{"id":"W4233663820","doi":"10.1177/0361198106198600113","title":"Who is Attracted to Carsharing?","year":2006,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":133,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Car sharing; Business; Descriptive statistics; Focus group; Car ownership; The Internet; Marketing; Advertising; Transport engineering; Engineering; Computer science; Public transport","score_opus":0.06880484622699579,"score_gpt":0.3595260622723869,"score_spread":0.29072121604539114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233663820","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90411395,0.006059135,0.00044865487,0.048643075,0.0010708593,0.000077838755,0.000367632,0.000036548874,0.039182175],"genre_scores_gemma":[0.97677976,0.0033846425,0.00014848981,0.00785132,0.0005145002,0.0000460894,0.00011785694,0.000013041512,0.0111441845],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988751,0.00030168213,0.000045637717,0.00012206695,0.00021089126,0.0004446874],"domain_scores_gemma":[0.996439,0.0006411488,0.0005114506,0.00007124297,0.0006698701,0.001667383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014840913,0.00013808373,0.0003892267,0.0013629852,0.0030908757,0.0035320763,0.00047009368,0.0018849443,0.014359304],"category_scores_gemma":[0.0053751143,0.00027386995,0.00029538825,0.0011545632,0.0009719168,0.0028460082,0.0009110369,0.0012695881,0.002770913],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022039494,0.000500106,0.6997412,0.0003591601,0.00009584515,0.0030945211,0.052413806,0.000049022758,0.0008618457,0.005472979,0.07332771,0.16386344],"study_design_scores_gemma":[0.00003245303,0.00031052617,0.3751625,0.0006703116,0.0001827292,0.00846687,0.4826569,0.00049261894,0.0006326288,0.0037313977,0.12755333,0.00010759237],"about_ca_topic_score_codex":0.010748287,"about_ca_topic_score_gemma":0.0104605295,"teacher_disagreement_score":0.014359304,"about_ca_system_score_codex":0.0008553194,"about_ca_system_score_gemma":0.0009906244,"threshold_uncertainty_score":0.048036635},"labels":[],"label_agreement":null},{"id":"W4234048259","doi":"10.32920/ryerson.14666370","title":"Shifting gears for the automated vehicle: findings from focus groups in the Greater Toronto and Hamilton area","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Planner; Focus group; Focus (optics); Key (lock); Public relations; Business; Public transport; Marketing; Computer science; Transport engineering; Political science; Engineering; Artificial intelligence; Computer security","score_opus":0.021261487538698037,"score_gpt":0.24096764909963098,"score_spread":0.21970616156093295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234048259","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99792045,0.0000786367,0.0002117834,0.0003172376,0.0000057915227,0.00009519162,0.00003402085,0.00000294439,0.0013338673],"genre_scores_gemma":[0.99725777,0.00018017611,0.00031880697,0.0002146143,0.000007137808,0.00012789469,0.000032199037,0.0000040907835,0.0018572683],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9971819,0.0016076408,0.00007676591,0.00023390957,0.00036828232,0.0005315653],"domain_scores_gemma":[0.9896889,0.007019641,0.0007346284,0.00022485193,0.0013067293,0.0010251907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003949646,0.00038681383,0.00030214727,0.0010811115,0.0074944785,0.0014548905,0.0011990372,0.0010156464,0.0025174303],"category_scores_gemma":[0.008843592,0.00035715496,0.00021019593,0.0014667627,0.0045552594,0.0010526783,0.0027623905,0.00081716664,0.00015909718],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049381313,0.00006922602,0.0140894065,0.00008570116,0.000005697471,0.0003427172,0.9781382,0.000047198726,0.0012812454,0.00019110745,0.0004621838,0.0052379705],"study_design_scores_gemma":[0.000009079807,0.00009772117,0.03659534,0.00006443077,0.000011165754,0.000055266824,0.95813084,0.00008985307,0.0004511504,0.00006402278,0.004416742,0.000014390303],"about_ca_topic_score_codex":0.6165445,"about_ca_topic_score_gemma":0.7605066,"teacher_disagreement_score":0.38345551,"about_ca_system_score_codex":0.010350436,"about_ca_system_score_gemma":0.010335315,"threshold_uncertainty_score":0.7714275},"labels":[],"label_agreement":null},{"id":"W4234323998","doi":"10.1002/atr.5670400201","title":"Masthead","year":2006,"lang":"en","type":"paratext","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Citation; Computer science; World Wide Web; Library science","score_opus":0.007846009920108992,"score_gpt":0.24118002641315225,"score_spread":0.23333401649304325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234323998","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00053258694,0.0005986862,0.00236613,0.00097506755,0.0019202902,0.00008424985,0.0021109197,0.0025537063,0.98885846],"genre_scores_gemma":[0.0006190361,0.00015076807,0.00030735723,0.00012798072,0.00009403045,0.000013456394,0.0004988267,0.0002579809,0.9979305],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99960834,0.000029942434,0.000018521105,0.00009044988,0.00020917816,0.00004374217],"domain_scores_gemma":[0.9987262,0.00018453029,0.00005112243,0.00021502646,0.0005716016,0.0002515384],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00050809595,0.0011083327,0.0007493068,0.0020067168,0.0016793311,0.003722858,0.0012991775,0.0017156001,0.8991296],"category_scores_gemma":[0.0021857054,0.0005649859,0.00054348,0.0016341468,0.00036077865,0.0027375657,0.0023056176,0.0016723784,0.82328933],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048419028,0.0000339725,0.00009026803,0.00006952115,0.0000014702631,0.000064058346,0.0000416037,0.000057136876,0.0006261778,0.0024151334,0.8578008,0.13875149],"study_design_scores_gemma":[0.000008037346,0.000017152226,0.00034753472,0.000037678423,0.0000020615328,0.00008828388,0.000045378303,0.00009044594,0.00025770665,0.000830544,0.998271,0.0000043011128],"about_ca_topic_score_codex":0.0015653028,"about_ca_topic_score_gemma":0.004358391,"teacher_disagreement_score":0.10087037,"about_ca_system_score_codex":0.00044836217,"about_ca_system_score_gemma":0.0009229502,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4234375276","doi":"10.1108/s2044-994120160000008032","title":"Index","year":2016,"lang":"en","type":"paratext","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Paratransit; Business; Public transport; Index (typography); Transport engineering; Service (business); Engineering; Marketing; Computer science; World Wide Web","score_opus":0.009877368555224267,"score_gpt":0.23159543141144934,"score_spread":0.22171806285622508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234375276","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005013258,0.00493534,0.0019509107,0.006170967,0.017185114,0.00027606354,0.017403115,0.002641074,0.94893605],"genre_scores_gemma":[0.0020044222,0.0037275902,0.0013820986,0.0021413101,0.002300646,0.00017208378,0.014027093,0.0010843158,0.97316045],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99813604,0.0001568471,0.00017570668,0.00039800434,0.000970854,0.00016248583],"domain_scores_gemma":[0.9976114,0.00018981157,0.00010332669,0.00040253878,0.0013445948,0.0003483719],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011475502,0.001714369,0.0014141041,0.004946805,0.002409204,0.011787309,0.0025194893,0.0026479128,0.72693014],"category_scores_gemma":[0.0061052307,0.0005762912,0.001138974,0.007866782,0.00089578674,0.008456575,0.0045588827,0.0024731737,0.7326382],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013919485,0.000019402465,0.00015445208,0.00022329343,0.0000042434144,0.000032324628,0.000060043272,0.000034752367,0.00014373499,0.005421709,0.91105986,0.082832225],"study_design_scores_gemma":[0.000002700232,0.0000065019112,0.00021242282,0.0001011619,0.0000017938463,0.000039167968,0.000049751074,0.000023198018,0.000049297298,0.001329636,0.99817955,0.0000048953766],"about_ca_topic_score_codex":0.0049107643,"about_ca_topic_score_gemma":0.005528035,"teacher_disagreement_score":0.72693014,"about_ca_system_score_codex":0.0025677409,"about_ca_system_score_gemma":0.0033550553,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4234406320","doi":"10.4018/9781605669885.ch024","title":"A Review of Recent Contribution in Agent-Based Health Care Modeling","year":2011,"lang":"en","type":"review","venue":"IGI Global eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Health care; Management science; Data science; Engineering; Political science","score_opus":0.06901787322622498,"score_gpt":0.33935734180571314,"score_spread":0.27033946857948815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234406320","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00043890742,0.96939284,0.018870963,0.0029872868,0.0007278791,0.000031294094,0.00008535408,0.00010207054,0.007363387],"genre_scores_gemma":[0.0057323487,0.98068327,0.010817891,0.00049147545,0.0007859277,0.00003041319,0.00014015974,0.00001993612,0.0012985362],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99929905,0.0002168205,0.000086844026,0.000102912505,0.00026055804,0.000033834014],"domain_scores_gemma":[0.99791604,0.0015078768,0.00009788533,0.000064476575,0.00035561481,0.00005816602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015342071,0.001015626,0.0013455522,0.002052447,0.00037803268,0.0019145418,0.0014715532,0.0015513728,0.0041582496],"category_scores_gemma":[0.003471431,0.0005775823,0.0009404818,0.00408104,0.0005274747,0.0019157823,0.000803768,0.001479406,0.0020876902],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004648531,0.000118266325,0.00095465116,0.012458202,0.00020728196,0.0002103816,0.00017431536,0.014898478,0.0005117021,0.03595381,0.047001366,0.88746506],"study_design_scores_gemma":[0.000020079042,0.00008042922,0.000884538,0.0054793493,0.00019183809,0.0006459752,0.00018456315,0.011183853,0.00047250235,0.021273753,0.95952135,0.000061611674],"about_ca_topic_score_codex":0.004858761,"about_ca_topic_score_gemma":0.0037425037,"teacher_disagreement_score":0.004858761,"about_ca_system_score_codex":0.0013489197,"about_ca_system_score_gemma":0.0020779695,"threshold_uncertainty_score":0.01391077},"labels":[],"label_agreement":null},{"id":"W4234681232","doi":"10.31219/osf.io/z9a4h","title":"Using Wait-time Thresholds to Improve Mobility: The Case of UberWAV Services in Toronto","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Downtown; TRIPS architecture; Service (business); Rush hour; Travel time; Transport engineering; Business; Geography; Marketing; Engineering","score_opus":0.023780867784430018,"score_gpt":0.28529916823546114,"score_spread":0.26151830045103114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234681232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97684413,0.0012113834,0.0015967524,0.0012464266,0.00005319159,0.0000320599,0.015284861,0.00018577714,0.0035453774],"genre_scores_gemma":[0.9881912,0.00024426237,0.001190454,0.000059903265,0.00001721045,0.000014434966,0.009520348,0.000027344102,0.0007348807],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991825,0.00013955057,0.00005126602,0.00017288541,0.00017372171,0.00028011113],"domain_scores_gemma":[0.99676573,0.001224753,0.000442008,0.00031173188,0.0007975459,0.00045817642],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010098501,0.00056830473,0.00045370162,0.0012919921,0.0010482565,0.0014098193,0.0009577104,0.0006311415,0.0016292451],"category_scores_gemma":[0.0082008075,0.00019563644,0.0004536367,0.003458432,0.0006107949,0.0013064686,0.00091476575,0.000779222,0.00043782766],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010769339,0.00017420368,0.862121,0.000431324,0.00033270445,0.0008054129,0.0034967363,0.06106339,0.002199206,0.0039592166,0.031487856,0.032852],"study_design_scores_gemma":[0.000059184615,0.00017380965,0.88492167,0.00012403433,0.00019395082,0.0002386685,0.0061496794,0.08944867,0.0012513185,0.0014600126,0.015882673,0.000096309384],"about_ca_topic_score_codex":0.8649164,"about_ca_topic_score_gemma":0.9181252,"teacher_disagreement_score":0.13508362,"about_ca_system_score_codex":0.007544092,"about_ca_system_score_gemma":0.0035735504,"threshold_uncertainty_score":0.27175826},"labels":[],"label_agreement":null},{"id":"W4235228763","doi":"10.32920/ryerson.14666373","title":"Impacts of autonomous vehicles on traffic volume: scenarios based on survey data for the City of Karlsruhe","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Transport engineering; Baseline (sea); Traffic volume; Mode (computer interface); Mode choice; Computer science; Survey data collection; Engineering; Statistics; Mathematics; Public transport","score_opus":0.06998933320892542,"score_gpt":0.2912266871800168,"score_spread":0.2212373539710914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235228763","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977755,0.000050195653,0.00027811457,0.000046062254,0.0000019506392,0.000014463035,0.0014623477,0.000012827477,0.0003585073],"genre_scores_gemma":[0.9978514,0.000079740734,0.00029263907,0.0000044827802,0.0000012445976,0.000016923193,0.0016467758,0.0000017999422,0.00010516236],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9991929,0.00035072438,0.000038625534,0.000101412654,0.00014027081,0.00017603635],"domain_scores_gemma":[0.9984931,0.00094802736,0.00018024916,0.00009734967,0.00020377802,0.0000775736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094294874,0.00043057205,0.0003524976,0.001267452,0.0002511468,0.00088037015,0.0004448536,0.00067707,0.0006918227],"category_scores_gemma":[0.001956084,0.00017512163,0.0007420573,0.0019590277,0.00040943574,0.0006756352,0.00054112374,0.00029452913,0.00014113089],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00082371064,0.00048223464,0.35811475,0.00027712155,0.00043920008,0.0015672973,0.00042876013,0.62082654,0.00130269,0.0019775738,0.002040821,0.011719256],"study_design_scores_gemma":[0.00010133825,0.00060435844,0.53616655,0.000056750378,0.0001885345,0.00040899919,0.0034344837,0.45261052,0.002619344,0.0012733273,0.0024042963,0.00013149521],"about_ca_topic_score_codex":0.045115177,"about_ca_topic_score_gemma":0.04129571,"teacher_disagreement_score":0.045115177,"about_ca_system_score_codex":0.0017826257,"about_ca_system_score_gemma":0.0005698511,"threshold_uncertainty_score":0.08970517},"labels":[],"label_agreement":null},{"id":"W4237320815","doi":"10.1002/atr.5670390301","title":"Masthead","year":2005,"lang":"en","type":"paratext","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Citation; Computer science; World Wide Web","score_opus":0.009196915609928047,"score_gpt":0.2518180302066815,"score_spread":0.24262111459675342,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237320815","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005463491,0.0005703008,0.0018987422,0.0009121962,0.0017353931,0.00007919197,0.002178652,0.0024350996,0.98964405],"genre_scores_gemma":[0.00062479865,0.00012833999,0.00023445259,0.00011870923,0.00007889811,0.000012197943,0.0005054752,0.00021207827,0.99808514],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996182,0.000030058947,0.00001841266,0.00008697472,0.00020075076,0.000045469842],"domain_scores_gemma":[0.99878126,0.00017355094,0.00004737674,0.00020197687,0.0005560297,0.00023979331],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000495574,0.0010865321,0.00072846335,0.0020906457,0.0017488078,0.004038304,0.0012780664,0.001711155,0.90249366],"category_scores_gemma":[0.0020943745,0.00055065495,0.0005216686,0.0017074626,0.00035885445,0.0027416316,0.0022084003,0.0015351768,0.82100993],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043814875,0.000030757637,0.000084648746,0.000062530824,0.0000013428566,0.000058878057,0.000041445404,0.00005021786,0.00049911527,0.0022634834,0.8777074,0.119156405],"study_design_scores_gemma":[0.000008277222,0.000017318122,0.00038313153,0.00003893164,0.0000021654848,0.00007458479,0.000053098018,0.00008850146,0.0002352491,0.00078168884,0.99831295,0.000004295158],"about_ca_topic_score_codex":0.0020078993,"about_ca_topic_score_gemma":0.005550825,"teacher_disagreement_score":0.097506344,"about_ca_system_score_codex":0.00050295045,"about_ca_system_score_gemma":0.0009737228,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4237483712","doi":"10.1007/978-981-15-8983-6_47","title":"Transportation Modeling","year":2021,"lang":"en","type":"book-chapter","venue":"The urban book series","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Scheduling (production processes); Intelligent transportation system; Informatics; Transport engineering; Engineering","score_opus":0.015918933723415123,"score_gpt":0.1920628035076362,"score_spread":0.17614386978422106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237483712","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007654024,0.0046917778,0.4348715,0.00695236,0.0015432481,0.0002689257,0.01299399,0.0021775246,0.5288467],"genre_scores_gemma":[0.26970178,0.010602316,0.100548655,0.0010799742,0.0007863605,0.00072364014,0.022757946,0.0010501369,0.5927492],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99958426,0.00012112189,0.000020602849,0.000112633046,0.00012323032,0.00003816871],"domain_scores_gemma":[0.99964166,0.00010216028,0.000024479845,0.00006155746,0.00014667022,0.000023441757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041792748,0.00087987276,0.00060619327,0.00092659716,0.0007402446,0.002859612,0.0014778376,0.0012451712,0.053514294],"category_scores_gemma":[0.0014027568,0.00033483675,0.0011185335,0.0018160145,0.00039874317,0.0016066373,0.001221068,0.0011318749,0.013276124],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023625787,0.00004243158,0.0012043039,0.00017352938,0.000053711232,0.00014355412,0.00012877604,0.39615896,0.00033829617,0.41513225,0.09791546,0.08868512],"study_design_scores_gemma":[0.000012030227,0.000020126827,0.0005085512,0.00014626773,0.000018494055,0.00008509521,0.00013292604,0.4599088,0.00025320827,0.15482894,0.38406137,0.000024133358],"about_ca_topic_score_codex":0.025533674,"about_ca_topic_score_gemma":0.01461006,"teacher_disagreement_score":0.053514294,"about_ca_system_score_codex":0.0020848599,"about_ca_system_score_gemma":0.0020704968,"threshold_uncertainty_score":0.17902315},"labels":[],"label_agreement":null},{"id":"W4238521111","doi":"10.32920/ryerson.14662929","title":"Design and Development of an Intelligent Agent-Based Supply Chain Simulation System","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Supply chain; Point of sale; Supply chain management; Computer science; Product (mathematics); Loan; Production (economics); Order (exchange); Business; Finance; Marketing; Economics; Microeconomics","score_opus":0.04549506273547051,"score_gpt":0.26278866660790723,"score_spread":0.21729360387243674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238521111","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015129665,0.00008582355,0.97103405,0.00014294565,0.00004801642,0.000512879,0.00015312826,0.008311256,0.0045821397],"genre_scores_gemma":[0.27249888,0.00029679705,0.72034127,0.00011872997,0.000023886154,0.0011669537,0.0007318018,0.0002600989,0.0045617362],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996191,0.00010901626,0.00004926586,0.00007775928,0.00011333747,0.000031539803],"domain_scores_gemma":[0.99949896,0.00016232039,0.000046207428,0.00006302221,0.00016647822,0.0000630551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007462601,0.0005867028,0.0008455697,0.0004701416,0.00056591316,0.001225425,0.0016816133,0.00082819874,0.004137615],"category_scores_gemma":[0.0012973351,0.00047940828,0.00051808194,0.00041574278,0.00031871127,0.0011032053,0.00078128895,0.00088899885,0.0011336084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041781826,0.0004909885,0.0041431407,0.0004877012,0.0001659255,0.0004945582,0.00048178682,0.77961326,0.030981766,0.028329471,0.005924212,0.14846945],"study_design_scores_gemma":[0.000040111336,0.00003606058,0.00013498502,0.000010075207,0.000020049367,0.00002793514,0.000015509522,0.99005365,0.0031830408,0.0009431272,0.0055243983,0.000011005872],"about_ca_topic_score_codex":0.0036513382,"about_ca_topic_score_gemma":0.0019276995,"teacher_disagreement_score":0.004137615,"about_ca_system_score_codex":0.0007786189,"about_ca_system_score_gemma":0.001516669,"threshold_uncertainty_score":0.013841689},"labels":[],"label_agreement":null},{"id":"W4238547960","doi":"10.1177/0361198106198600115","title":"Carsharing in North America","year":2006,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"University of California Transportation Center","keywords":"Popularity; Metropolitan area; Business; Car ownership; Market share; Growth management; Mainstreaming; Geography; Public transport; Transport engineering; Marketing; Political science; Engineering; Land use","score_opus":0.05533479788430298,"score_gpt":0.3369876678105173,"score_spread":0.2816528699262143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238547960","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21112114,0.033060063,0.0008204318,0.027525118,0.0018433955,0.00014281312,0.0030160495,0.00043820258,0.72203285],"genre_scores_gemma":[0.51992923,0.03252648,0.0015670216,0.008517617,0.0005915507,0.00015604324,0.0038838235,0.00014127641,0.43268695],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9996568,0.000028607146,0.000009607777,0.00006108145,0.00011497092,0.00012886991],"domain_scores_gemma":[0.99937516,0.000055132965,0.000053740834,0.000023195546,0.0002913487,0.00020137744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002663369,0.00023374168,0.0001262377,0.0008913072,0.003294728,0.001637836,0.0004101236,0.00064360275,0.031750083],"category_scores_gemma":[0.00048059697,0.00011932587,0.00014471203,0.0020069468,0.00045915993,0.000869186,0.0009394062,0.0006904211,0.002956099],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009098073,0.00025786026,0.058519825,0.00045120477,0.00002136054,0.0016023043,0.0064627817,0.0002376298,0.0023168016,0.026391871,0.55530673,0.34834057],"study_design_scores_gemma":[0.0000064259275,0.00003229565,0.10018135,0.00020452615,0.000008983416,0.00046958248,0.006808981,0.00011130407,0.0003316964,0.00077195093,0.89105886,0.000014137182],"about_ca_topic_score_codex":0.3760819,"about_ca_topic_score_gemma":0.596117,"teacher_disagreement_score":0.3760819,"about_ca_system_score_codex":0.004065986,"about_ca_system_score_gemma":0.007963795,"threshold_uncertainty_score":0.74778575},"labels":[],"label_agreement":null},{"id":"W4238908887","doi":"10.32920/ryerson.14647785.v1","title":"Smart Transit Dynamic Optimization and Informatics","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Dynamic pricing; Queue; Component (thermodynamics); Queueing theory; Operations research; Process (computing); Scheduling (production processes); Real-time computing; Mathematical optimization; Economics; Computer network; Engineering","score_opus":0.006371842414821381,"score_gpt":0.20301622465324595,"score_spread":0.19664438223842456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238908887","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18646345,0.0017085536,0.76461554,0.0041674683,0.0003414649,0.00013082617,0.0006721948,0.0006462317,0.041254226],"genre_scores_gemma":[0.96102035,0.00067697995,0.02913638,0.00024136003,0.000100272526,0.000073220246,0.00027331396,0.00009430311,0.008383898],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995472,0.00017226012,0.000015016708,0.00011089985,0.00007594498,0.0000787383],"domain_scores_gemma":[0.99913764,0.00049531856,0.00012839312,0.00009284182,0.00008872235,0.000057023462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007853777,0.00078943407,0.00090485794,0.00048413256,0.00041528075,0.0015318103,0.0006480085,0.0008274138,0.0046878634],"category_scores_gemma":[0.00221026,0.00043623187,0.0007085196,0.00073785527,0.0011888592,0.001762102,0.0011510759,0.0012524781,0.0002509534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027506241,0.000025972886,0.00044541777,0.00003606893,0.000023251656,0.000023891227,0.000018940565,0.9436738,0.00021192884,0.04754185,0.0011625102,0.0068089445],"study_design_scores_gemma":[0.0000063276216,0.00001592602,0.00022815833,0.0000055717755,0.000004351437,0.00000860765,0.000020488671,0.97059363,0.00010470554,0.027826067,0.0011816026,0.0000044528106],"about_ca_topic_score_codex":0.007771438,"about_ca_topic_score_gemma":0.004920285,"teacher_disagreement_score":0.007771438,"about_ca_system_score_codex":0.0021938037,"about_ca_system_score_gemma":0.0013099986,"threshold_uncertainty_score":0.015917242},"labels":[],"label_agreement":null},{"id":"W4240447694","doi":"10.1002/atr.5670360301","title":"Masthead","year":2002,"lang":"en","type":"paratext","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Citation; Computer science; World Wide Web; Library science","score_opus":0.011848281070214272,"score_gpt":0.24322515236990375,"score_spread":0.23137687129968948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240447694","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006377002,0.0007107875,0.0020470426,0.0009092247,0.0017507396,0.000071565795,0.0019864864,0.0022541815,0.98963237],"genre_scores_gemma":[0.0005833964,0.00013778669,0.00020358912,0.00010140365,0.000067070076,0.000010143793,0.000429412,0.0001974364,0.9982698],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996656,0.000027286413,0.000016522321,0.000085890686,0.00016522141,0.00003945389],"domain_scores_gemma":[0.99889827,0.000159814,0.00004306651,0.00018681995,0.0005038658,0.00020815925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043446876,0.0011468605,0.0007493764,0.0019652664,0.0017448699,0.003958501,0.0012122119,0.0017033329,0.8901924],"category_scores_gemma":[0.0017925517,0.0005735718,0.00049492606,0.0018503378,0.00033669497,0.0028148298,0.0020061075,0.0015036608,0.8116378],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051782266,0.000036559475,0.00010230708,0.000068372996,0.0000015639187,0.000070802336,0.000048643036,0.000060942195,0.00064657844,0.0024244762,0.8582222,0.13826588],"study_design_scores_gemma":[0.000008551373,0.00001772587,0.00041489876,0.000036980753,0.0000024070343,0.000084742365,0.00005459536,0.000103633625,0.00026049066,0.00078783755,0.9982236,0.000004439678],"about_ca_topic_score_codex":0.0019140361,"about_ca_topic_score_gemma":0.0051442436,"teacher_disagreement_score":0.8901924,"about_ca_system_score_codex":0.00043917634,"about_ca_system_score_gemma":0.0008005347,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4240553679","doi":"10.1079/tourismetc.2021.0014","title":"Exploring the Case: Parkbus – A Sustainable Transport Solution for Both Residents and Visitors","year":2021,"lang":"en","type":"article","venue":"Tourism Cases","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Sustainability; Tourism; Key (lock); Sustainable transport; Sustainable development; Sustainable tourism; Business; Environmental planning; Marketing; Public relations; Political science; Geography; Computer science","score_opus":0.04152291881385681,"score_gpt":0.2480546987249811,"score_spread":0.20653177991112429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240553679","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6256567,0.00071828574,0.0077631185,0.047332633,0.00045707013,0.0004601698,0.0001481235,0.0000844947,0.31737942],"genre_scores_gemma":[0.91788614,0.00068296405,0.004859191,0.0020031023,0.00008473333,0.00019525456,0.000045920457,0.000025933505,0.07421679],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9985171,0.0007344232,0.000017189079,0.00007021491,0.00018638995,0.00047475073],"domain_scores_gemma":[0.9993235,0.00021582788,0.00004092447,0.000025319192,0.000057665657,0.00033672558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001027667,0.00033317678,0.00022066274,0.00037240828,0.010170637,0.004236499,0.0012690538,0.004729204,0.014127892],"category_scores_gemma":[0.0014520357,0.00029347412,0.00035154936,0.00050663523,0.0042122644,0.0022940026,0.004442458,0.0032345394,0.0010798825],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031539737,0.00091556594,0.0136860395,0.0005647512,0.00002815392,0.09117039,0.37391487,0.006308738,0.005313641,0.34908506,0.10024078,0.05845664],"study_design_scores_gemma":[0.000022867745,0.00022050299,0.0022902994,0.00042347275,0.000012214976,0.00881837,0.5687016,0.0029802276,0.0009776213,0.009170856,0.40633908,0.000042819243],"about_ca_topic_score_codex":0.02016999,"about_ca_topic_score_gemma":0.050109483,"teacher_disagreement_score":0.02016999,"about_ca_system_score_codex":0.0038623947,"about_ca_system_score_gemma":0.00304326,"threshold_uncertainty_score":0.04726249},"labels":[],"label_agreement":null},{"id":"W4240633220","doi":"10.1126/science.358.6369.1375","title":"A matter of trust","year":2017,"lang":"en","type":"article","venue":"Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"World Federation of Science Journalists","funders":"Virginia Polytechnic Institute and State University; Ford Motor Company","keywords":"Business; Chemistry","score_opus":0.014017057686902876,"score_gpt":0.26058115074344795,"score_spread":0.2465640930565451,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240633220","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13813509,0.0067367647,0.03472727,0.42948887,0.0038906347,0.00012775515,0.00022504675,0.00021343016,0.38645524],"genre_scores_gemma":[0.9730865,0.0010835502,0.0010205337,0.013989723,0.0005265388,0.00003360998,0.000048525748,0.00008604179,0.010124979],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9680714,0.015359751,0.0013610958,0.0033745,0.008950075,0.0028831495],"domain_scores_gemma":[0.90195686,0.035936743,0.014615672,0.011716044,0.021641718,0.014133015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016387599,0.0003820387,0.0007733761,0.0011340561,0.008162902,0.013781561,0.0010831109,0.004580197,0.009513216],"category_scores_gemma":[0.09285171,0.00042380314,0.00038153864,0.0012085192,0.023713822,0.015594404,0.005554643,0.008102789,0.0022450886],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020650102,0.00012788881,0.024306208,0.00032756414,0.00025873972,0.0010022272,0.092356846,0.0004396738,0.001084794,0.7481391,0.071169816,0.060580738],"study_design_scores_gemma":[0.00006581501,0.00023585564,0.010287213,0.00065402646,0.00010292151,0.0008716129,0.06570467,0.0010183038,0.0007976204,0.48657277,0.4335538,0.0001353771],"about_ca_topic_score_codex":0.0102823265,"about_ca_topic_score_gemma":0.005389202,"teacher_disagreement_score":0.016387599,"about_ca_system_score_codex":0.0070184455,"about_ca_system_score_gemma":0.0076035806,"threshold_uncertainty_score":0.08666694},"labels":[],"label_agreement":null},{"id":"W4240824064","doi":"10.1016/s1359-6128(03)00807-3","title":"Abitibi-Consolidated rebuilds paper machine","year":2003,"lang":"en","type":"article","venue":"Pump Industry Analyst","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Newsprint; Engineering; Political science; Pulp and paper industry","score_opus":0.011694270057008151,"score_gpt":0.22669701112497226,"score_spread":0.2150027410679641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240824064","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0037834535,0.001268846,0.0056062867,0.0013639039,0.0024552974,0.0003316938,0.003734489,0.0073673576,0.9740888],"genre_scores_gemma":[0.007850892,0.00030707422,0.0024122584,0.00014973411,0.000088363355,0.000033568034,0.0021500594,0.0007194284,0.9862884],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979691,0.000042818014,0.000046812595,0.00018063352,0.0015880144,0.00017274776],"domain_scores_gemma":[0.99550205,0.00016232587,0.00007048489,0.00055718666,0.0032673345,0.0004405932],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013670354,0.0008108489,0.0006071754,0.0027508603,0.0033476732,0.0058746072,0.0014920734,0.0014141855,0.45487946],"category_scores_gemma":[0.0028528734,0.00081324915,0.00047299036,0.0019409455,0.00084364094,0.002211032,0.0012879402,0.0020923791,0.25719988],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010798762,0.000057655496,0.0004380246,0.00009480345,0.0000042713805,0.00011708717,0.00010556499,0.00015037102,0.0031604662,0.0048128064,0.84312713,0.14782386],"study_design_scores_gemma":[0.000017936061,0.000023696632,0.0011176333,0.000032370277,0.0000043213295,0.00012575138,0.00008643054,0.00034028062,0.0020453231,0.00041806226,0.9957769,0.000011237745],"about_ca_topic_score_codex":0.07164486,"about_ca_topic_score_gemma":0.17462076,"teacher_disagreement_score":0.45487946,"about_ca_system_score_codex":0.0028119548,"about_ca_system_score_gemma":0.0046731443,"threshold_uncertainty_score":0.7775483},"labels":[],"label_agreement":null},{"id":"W4240849242","doi":"10.1016/j.im.2009.11.001","title":"Situated DSS for personal finance management: Design and evaluation","year":2009,"lang":"en","type":"article","venue":"Information & Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Situated; Decision support system; Computer science; Systems engineering; Engineering; Engineering management; Knowledge management; Business; Human–computer interaction; Data mining; Artificial intelligence","score_opus":0.017680140752282865,"score_gpt":0.2416950863437537,"score_spread":0.22401494559147084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240849242","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9208241,0.00057193666,0.07165909,0.000204689,0.00009343316,0.0017325579,0.00036220904,0.00069430156,0.0038577481],"genre_scores_gemma":[0.8737003,0.0005357713,0.12271181,0.00010282154,0.000025973244,0.0010461131,0.00024054991,0.000043483476,0.0015932643],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974069,0.0016251819,0.00016068608,0.00022923524,0.00044481957,0.0001332302],"domain_scores_gemma":[0.977386,0.016995706,0.0007167325,0.0015326302,0.002421889,0.00094716036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005951665,0.0008645827,0.00092557044,0.0014786173,0.0006976534,0.0022492015,0.0017145167,0.002013402,0.0057612136],"category_scores_gemma":[0.016711073,0.0005583466,0.0005950221,0.0013763929,0.0006231195,0.0025244483,0.0012094394,0.0009708493,0.0005984694],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.021934668,0.02747841,0.046854317,0.0045326194,0.00078825414,0.0007008805,0.0056041656,0.16376287,0.021687368,0.015256222,0.0029058142,0.68849444],"study_design_scores_gemma":[0.009652989,0.06894521,0.032138918,0.001052866,0.0029900558,0.0005374422,0.008232568,0.78863746,0.051068317,0.01350573,0.022857435,0.00038105343],"about_ca_topic_score_codex":0.0039444515,"about_ca_topic_score_gemma":0.00394572,"teacher_disagreement_score":0.005951665,"about_ca_system_score_codex":0.0021266728,"about_ca_system_score_gemma":0.0020336108,"threshold_uncertainty_score":0.031475723},"labels":[],"label_agreement":null},{"id":"W4242636191","doi":"10.4095/300997","title":"Mode of Transportation to Work, 2006: All Other Modes (by census division)","year":2010,"lang":"en","type":"report","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Census; Mode (computer interface); Division (mathematics); Transport engineering; Geography; Computer science; Engineering; Demography; Mathematics; Sociology; Human–computer interaction; Population; Arithmetic","score_opus":0.026965325365482767,"score_gpt":0.2885345482700871,"score_spread":0.2615692229046044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242636191","genre_codex":"dataset","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019344533,0.00087774405,0.00024097436,0.00022578519,0.0001682614,0.00035042406,0.9441545,0.00018175843,0.034455962],"genre_scores_gemma":[0.048056737,0.004099887,0.0018107628,0.00031769637,0.00007695404,0.00079710846,0.8699471,0.00008605106,0.07480779],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.999546,0.00001331423,0.000058285867,0.000049147475,0.0002527808,0.00008052798],"domain_scores_gemma":[0.9990711,0.00001788999,0.00011503843,0.000024030878,0.0006776928,0.00009419153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002226107,0.0010268409,0.00029099526,0.0035885982,0.0005851148,0.0007619097,0.0010306175,0.00031124725,0.0155951725],"category_scores_gemma":[0.0008824932,0.00031671397,0.00050653814,0.0063423314,0.000114194234,0.0007573164,0.000558801,0.0005990723,0.010193248],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021558916,0.00021257692,0.11290561,0.0010474416,0.00006541337,0.00010378289,0.00037080725,0.00096938363,0.0007022727,0.0006013256,0.8342612,0.048544563],"study_design_scores_gemma":[0.000046316007,0.00005502906,0.702048,0.00028654057,0.000024107916,0.00012843063,0.00055440195,0.00035273875,0.00031532813,0.00008332248,0.2960805,0.000025314632],"about_ca_topic_score_codex":0.5808757,"about_ca_topic_score_gemma":0.7203924,"teacher_disagreement_score":0.4191243,"about_ca_system_score_codex":0.002784351,"about_ca_system_score_gemma":0.00461034,"threshold_uncertainty_score":0.8431852},"labels":[],"label_agreement":null},{"id":"W4242638375","doi":"10.4095/300995","title":"Mode of Transportation to Work, 2006: Car, Truck or Van as Driver (by census division)","year":2010,"lang":"en","type":"report","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Truck; Census; Division (mathematics); Mode (computer interface); Transport engineering; Work (physics); Engineering; Computer science; Automotive engineering; Sociology; Mathematics; Demography; Human–computer interaction","score_opus":0.018466323574628775,"score_gpt":0.28069801209987155,"score_spread":0.26223168852524276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242638375","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050244633,0.0011318646,0.000386005,0.00046318438,0.00023383826,0.0004319733,0.9110645,0.0001834903,0.03586053],"genre_scores_gemma":[0.090544425,0.0067425775,0.0025927897,0.00050411257,0.00013135983,0.0008801165,0.8133266,0.0000912846,0.085186765],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99954814,0.000015830296,0.000062598156,0.00005242841,0.0002515424,0.00006950122],"domain_scores_gemma":[0.998898,0.000030699415,0.00015198377,0.000022592008,0.0007885269,0.000108204345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029615272,0.00084220927,0.00025098858,0.0030133359,0.0005128349,0.0006787763,0.0009763183,0.0003125884,0.008609421],"category_scores_gemma":[0.0010754198,0.00032966209,0.00038590076,0.004013157,0.00011465578,0.0008729001,0.0005472523,0.0006431221,0.0055577597],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023955909,0.00036293437,0.22575144,0.0010400069,0.00007800037,0.00014444857,0.0005240736,0.0011137744,0.00081408105,0.00068118086,0.71978927,0.049461186],"study_design_scores_gemma":[0.00004867392,0.000079129684,0.79569745,0.0002331847,0.000032239095,0.00020183036,0.0009380699,0.0005087441,0.00045888624,0.000072977324,0.20170315,0.000025596597],"about_ca_topic_score_codex":0.5101439,"about_ca_topic_score_gemma":0.7156973,"teacher_disagreement_score":0.48985612,"about_ca_system_score_codex":0.0025588106,"about_ca_system_score_gemma":0.004487624,"threshold_uncertainty_score":0.985482},"labels":[],"label_agreement":null},{"id":"W4243033930","doi":"10.5383/jttm.01.01.001","title":"The matching problem of empty vehicle redistribution in autonomous taxi systems","year":2019,"lang":"en","type":"article","venue":"International Journal of Traffic and Transportation Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Bipartite graph; Queue; Redistribution (election); Computer science; Mathematical optimization; Matching (statistics); Graph; Operations research; Engineering; Mathematics; Computer network; Statistics; Theoretical computer science","score_opus":0.0045647536251294625,"score_gpt":0.21168392067843061,"score_spread":0.20711916705330116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243033930","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1687944,0.0003445579,0.82315564,0.0003911562,0.00005160449,0.00017231592,0.0002759489,0.00039616393,0.00641818],"genre_scores_gemma":[0.9240242,0.00021490431,0.06766066,0.000074128766,0.000037221926,0.00010764668,0.00025892563,0.000106321655,0.0075159925],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934596,0.00020514692,0.000024800262,0.00016279655,0.000085890824,0.00017545304],"domain_scores_gemma":[0.998938,0.00062665425,0.00015323014,0.00007547918,0.00010863116,0.00009792878],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011783297,0.0005787061,0.001218755,0.00077193556,0.0008732679,0.0012191737,0.0017234604,0.0014039631,0.003991012],"category_scores_gemma":[0.003270701,0.0005285779,0.0006627982,0.0013086885,0.00095300586,0.0022383013,0.0012934074,0.00069617387,0.00040324774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017694442,0.00005391952,0.0005851209,0.000081984675,0.000038988295,0.00010681086,0.000090260226,0.9532301,0.00135304,0.019251317,0.00097333355,0.024058186],"study_design_scores_gemma":[0.000025311836,0.00004959727,0.00030146696,0.0000045994047,0.000009882118,0.000046392797,0.00007187828,0.9806476,0.0006735712,0.017339518,0.0008203186,0.00000972114],"about_ca_topic_score_codex":0.0083756875,"about_ca_topic_score_gemma":0.0033894465,"teacher_disagreement_score":0.0083756875,"about_ca_system_score_codex":0.0014687811,"about_ca_system_score_gemma":0.0014278684,"threshold_uncertainty_score":0.016653836},"labels":[],"label_agreement":null},{"id":"W4243241224","doi":"10.22215/etd/2009-08968","title":"A suburban transportation hub prototype","year":2009,"lang":"en","type":"dissertation","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Library and Archives Canada","funders":"","keywords":"Computer science; Humanities; Art","score_opus":0.007916974343186568,"score_gpt":0.23138082670188143,"score_spread":0.22346385235869487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243241224","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41110858,0.00025138288,0.35795808,0.001020807,0.0007260775,0.0038451971,0.0063810567,0.082494736,0.13621399],"genre_scores_gemma":[0.625363,0.00020657167,0.16482195,0.00024083896,0.000038205217,0.0009768449,0.0056146304,0.0027905258,0.19994752],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996351,0.000037835198,0.000011810178,0.0000947971,0.00015803728,0.0000624678],"domain_scores_gemma":[0.99919575,0.00006586077,0.000020128087,0.00019161761,0.000348343,0.00017839056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000545333,0.00048883096,0.00032799022,0.00035504933,0.00043468623,0.0009357067,0.001979825,0.0006194991,0.056678],"category_scores_gemma":[0.00088740065,0.00036146495,0.000254241,0.0003474329,0.00018954546,0.0009805785,0.00059766026,0.00043073075,0.011751682],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026243837,0.0035417508,0.008021655,0.00084857806,0.00009848617,0.0015058729,0.0021441567,0.018862624,0.38821593,0.00796894,0.14442235,0.42174536],"study_design_scores_gemma":[0.0009326909,0.004216509,0.022722078,0.00012042845,0.0001512825,0.0010917424,0.0019408921,0.15391333,0.2221194,0.0017430611,0.5908933,0.00015527055],"about_ca_topic_score_codex":0.0064564417,"about_ca_topic_score_gemma":0.007925571,"teacher_disagreement_score":0.056678,"about_ca_system_score_codex":0.00045739984,"about_ca_system_score_gemma":0.0010857235,"threshold_uncertainty_score":0.18960679},"labels":[],"label_agreement":null},{"id":"W4243434034","doi":"10.4018/978-1-60566-056-1.ch040","title":"Developing an Online Fleet Management Service","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Business; Revenue; Profit (economics); The Internet; Service (business); Online business; Electronic business; Marketing; Engineering management; Knowledge management; Business model; Engineering; Finance; Computer science; Economics; World Wide Web","score_opus":0.03568537703194255,"score_gpt":0.25734779156618687,"score_spread":0.22166241453424432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243434034","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019357566,0.00048281657,0.028587647,0.0048635565,0.0006025224,0.00024474604,0.00019004411,0.00073185464,0.9449392],"genre_scores_gemma":[0.112661235,0.0012386905,0.036827836,0.0014630585,0.00016173367,0.00011593282,0.0005367478,0.00028535697,0.84670943],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99961865,0.00008064258,0.0000110774945,0.000042658725,0.00014675612,0.000100157275],"domain_scores_gemma":[0.9997757,0.000049182596,0.000013071149,0.000028917531,0.000050424653,0.00008268676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005080604,0.00035053733,0.00012138854,0.0008533201,0.002007368,0.002814253,0.0011384055,0.0023715498,0.07808768],"category_scores_gemma":[0.00075281714,0.00017015853,0.00036308556,0.0010670938,0.00060415664,0.00489162,0.0020705895,0.0015553619,0.021632014],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004115207,0.00058710383,0.0019115363,0.0002767079,0.000006444465,0.0060985275,0.007413924,0.0017482484,0.0061523495,0.28092417,0.24847294,0.44636685],"study_design_scores_gemma":[0.000004299123,0.000041941887,0.0004270116,0.00007761063,0.0000027375274,0.001199242,0.0018991918,0.0019937165,0.000891192,0.0039946777,0.989456,0.000012516478],"about_ca_topic_score_codex":0.006179642,"about_ca_topic_score_gemma":0.0113463625,"teacher_disagreement_score":0.07808768,"about_ca_system_score_codex":0.0015752404,"about_ca_system_score_gemma":0.0017038422,"threshold_uncertainty_score":0.26122934},"labels":[],"label_agreement":null},{"id":"W4243944704","doi":"10.5040/9781492596424.ch-006","title":"Active Transportation","year":2011,"lang":"en","type":"other","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.01177393903630744,"score_gpt":0.2008906540794199,"score_spread":0.18911671504311245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243944704","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001490438,0.00089568563,0.0043098885,0.0019279526,0.0010804269,0.00020012129,0.007129841,0.0007971264,0.9821684],"genre_scores_gemma":[0.034495942,0.0036282048,0.005344873,0.0018894639,0.00045654006,0.00033878192,0.01641897,0.0005099391,0.93691725],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99856025,0.00017099966,0.000076215925,0.00021139758,0.00075856515,0.00022265094],"domain_scores_gemma":[0.997523,0.00016965457,0.00011646285,0.00028061486,0.0014871149,0.00042309897],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008389545,0.00072495773,0.00033353688,0.0017137285,0.0021366775,0.0048178257,0.0013975218,0.0014118038,0.3347406],"category_scores_gemma":[0.0040278654,0.00020062315,0.0005722217,0.0022451496,0.00047818603,0.0031310637,0.0029752546,0.0012378201,0.16700685],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053876905,0.000088200635,0.0021325096,0.00030098137,0.000011157939,0.00007384311,0.00032176494,0.00035709218,0.0003548208,0.038376167,0.6628668,0.29506287],"study_design_scores_gemma":[0.000003488456,0.000011805066,0.0009934765,0.0001029525,0.0000033471997,0.000060190992,0.00014032138,0.00006448762,0.00008916018,0.001596329,0.99692935,0.000004945312],"about_ca_topic_score_codex":0.017023169,"about_ca_topic_score_gemma":0.01738319,"teacher_disagreement_score":0.3347406,"about_ca_system_score_codex":0.0022755198,"about_ca_system_score_gemma":0.0047303266,"threshold_uncertainty_score":0.9489118},"labels":[],"label_agreement":null},{"id":"W4244133199","doi":"10.31219/osf.io/6x5yg","title":"Measuring when Uber behaves as a substitute or complement to transit: An examination of travel-time differences in Toronto","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"TRIPS architecture; Transit (satellite); Public transport; Transport engineering; Business; Duration (music); Urban transit; Travel behavior; Sample (material); Kilometer; Demographic economics; Advertising; Geography; Economics; Engineering","score_opus":0.06980929996071908,"score_gpt":0.27875908420616274,"score_spread":0.20894978424544366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244133199","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99310416,0.00020367163,0.00015446145,0.00014720875,0.0000052096043,0.000023252634,0.00350676,0.000009561572,0.0028456745],"genre_scores_gemma":[0.9953484,0.00016914304,0.00020294492,0.00002576575,0.0000033680735,0.000019093888,0.0026651535,0.0000052659234,0.0015608445],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992849,0.0001223271,0.000058947062,0.00012931014,0.00022267955,0.00018184821],"domain_scores_gemma":[0.9970163,0.00038872362,0.00083944167,0.0001840537,0.0009831229,0.00058825384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063719705,0.00027929267,0.00029538825,0.0013940864,0.0014175855,0.0011154684,0.00075868453,0.00032287577,0.0029163738],"category_scores_gemma":[0.0030669111,0.00023212243,0.00053761376,0.004674287,0.00063141435,0.0005232475,0.0011600754,0.00037619402,0.00037758515],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000105058425,0.0000341094,0.98458916,0.000068007386,0.00009839225,0.00020382662,0.0065090023,0.00075373444,0.0006847819,0.0006256211,0.0019806914,0.004347613],"study_design_scores_gemma":[0.0000016960764,0.00001763877,0.9939136,0.000016483214,0.000016673506,0.000022879702,0.004161916,0.00054153666,0.00006884991,0.000014202035,0.0012156987,0.000008927816],"about_ca_topic_score_codex":0.9597025,"about_ca_topic_score_gemma":0.9830016,"teacher_disagreement_score":0.04029751,"about_ca_system_score_codex":0.015277705,"about_ca_system_score_gemma":0.0054006185,"threshold_uncertainty_score":0.11084801},"labels":[],"label_agreement":null},{"id":"W4244491616","doi":"10.32920/ryerson.14644365","title":"The future of emerging technologies in public transit in Greater Toronto Area","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Public transport; Transit (satellite); Business; Transit system; Emerging technologies; Transport engineering; Economic growth; Engineering; Economics; Computer science","score_opus":0.016471501786436252,"score_gpt":0.22643513634782564,"score_spread":0.2099636345613894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244491616","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07402039,0.36405024,0.0021371292,0.30193338,0.0062076147,0.00010552219,0.0017307256,0.0003975693,0.24941744],"genre_scores_gemma":[0.37816548,0.42159632,0.004981238,0.018750973,0.0029381877,0.000085521664,0.0014444863,0.000087760505,0.17195],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993318,0.00008732516,0.00003139556,0.000055593813,0.00027226325,0.00022163127],"domain_scores_gemma":[0.99769574,0.00026289487,0.00016445987,0.000037751997,0.0007569903,0.0010821432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011591121,0.00032671753,0.0001599226,0.0010342174,0.0016061678,0.004980686,0.0006988368,0.002234974,0.018285485],"category_scores_gemma":[0.0010923076,0.00012667807,0.00022410802,0.0018404663,0.0019248988,0.0025274302,0.0010983282,0.0012317137,0.0019700367],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002380712,0.00024811647,0.021508425,0.002717709,0.000026966854,0.0020252676,0.0052947393,0.002118032,0.004539299,0.09005137,0.37010145,0.5011305],"study_design_scores_gemma":[0.000010347609,0.00011145234,0.013795512,0.00060816336,0.000014619575,0.0003376049,0.0040781377,0.000703411,0.00036760914,0.0018384237,0.97810936,0.000025337229],"about_ca_topic_score_codex":0.48019674,"about_ca_topic_score_gemma":0.6104472,"teacher_disagreement_score":0.5198033,"about_ca_system_score_codex":0.017721029,"about_ca_system_score_gemma":0.017591454,"threshold_uncertainty_score":0.95480335},"labels":[],"label_agreement":null},{"id":"W4244767402","doi":"10.32920/ryerson.14644365.v1","title":"The future of emerging technologies in public transit in Greater Toronto Area","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Public transport; Transit (satellite); Business; Emerging technologies; Transit system; Transport engineering; Economic growth; Engineering; Economics; Computer science","score_opus":0.016471501786436252,"score_gpt":0.22643513634782564,"score_spread":0.2099636345613894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244767402","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07402039,0.36405024,0.0021371292,0.30193338,0.0062076147,0.00010552219,0.0017307256,0.0003975693,0.24941744],"genre_scores_gemma":[0.37816548,0.42159632,0.004981238,0.018750973,0.0029381877,0.000085521664,0.0014444863,0.000087760505,0.17195],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9993318,0.00008732516,0.00003139556,0.000055593813,0.00027226325,0.00022163127],"domain_scores_gemma":[0.99769574,0.00026289487,0.00016445987,0.000037751997,0.0007569903,0.0010821432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011591121,0.00032671753,0.0001599226,0.0010342174,0.0016061678,0.004980686,0.0006988368,0.002234974,0.018285485],"category_scores_gemma":[0.0010923076,0.00012667807,0.00022410802,0.0018404663,0.0019248988,0.0025274302,0.0010983282,0.0012317137,0.0019700367],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002380712,0.00024811647,0.021508425,0.002717709,0.000026966854,0.0020252676,0.0052947393,0.002118032,0.004539299,0.09005137,0.37010145,0.5011305],"study_design_scores_gemma":[0.000010347609,0.00011145234,0.013795512,0.00060816336,0.000014619575,0.0003376049,0.0040781377,0.000703411,0.00036760914,0.0018384237,0.97810936,0.000025337229],"about_ca_topic_score_codex":0.48019674,"about_ca_topic_score_gemma":0.6104472,"teacher_disagreement_score":0.5198033,"about_ca_system_score_codex":0.017721029,"about_ca_system_score_gemma":0.017591454,"threshold_uncertainty_score":0.95480335},"labels":[],"label_agreement":null},{"id":"W4244974331","doi":"10.1016/s1365-6937(14)70041-3","title":"BluMetric purchases Ottawa property","year":2014,"lang":"en","type":"article","venue":"Filtration Industry Analyst","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Property (philosophy); Business; Philosophy; Epistemology","score_opus":0.015018270975364114,"score_gpt":0.221755701648742,"score_spread":0.20673743067337788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244974331","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004005625,0.0011513007,0.00052426534,0.0036177933,0.0005203686,0.00014345266,0.0067287004,0.0023461897,0.98096234],"genre_scores_gemma":[0.010801855,0.00041203096,0.00036817213,0.00043521862,0.000050160783,0.000019308336,0.003135127,0.0002730928,0.98450506],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.996923,0.000058755933,0.00004554601,0.0004276131,0.002056727,0.0004883823],"domain_scores_gemma":[0.9949419,0.00018201074,0.00013655436,0.00056020956,0.0030029528,0.001176404],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007812756,0.0011819426,0.0008967817,0.003029413,0.009400637,0.0070032184,0.0018248821,0.0017892034,0.6022562],"category_scores_gemma":[0.0035565828,0.0011417478,0.00063099235,0.003084484,0.0017560506,0.0023821376,0.0023614315,0.002351664,0.26220134],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015289753,0.000082652754,0.0023209625,0.00008327495,0.000009801249,0.00018030962,0.00018703996,0.0000770553,0.00087958894,0.007897924,0.9169931,0.07113542],"study_design_scores_gemma":[0.000009921058,0.00002462638,0.0029495405,0.000030520096,0.000006309372,0.00007411891,0.0001986402,0.000092393544,0.00034791994,0.00021118317,0.99603695,0.00001792453],"about_ca_topic_score_codex":0.7783035,"about_ca_topic_score_gemma":0.9179505,"teacher_disagreement_score":0.7783035,"about_ca_system_score_codex":0.018127685,"about_ca_system_score_gemma":0.02302809,"threshold_uncertainty_score":0.5673333},"labels":[],"label_agreement":null},{"id":"W4245492649","doi":"10.1016/s1464-2859(20)30428-4","title":"Ballard sells UAV business to Honeywell","year":2020,"lang":"en","type":"article","venue":"Fuel Cells Bulletin","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Engineering; Engineering drawing; Manufacturing engineering; Computer science; Systems engineering","score_opus":0.01045695565776633,"score_gpt":0.1774625362048957,"score_spread":0.16700558054712936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245492649","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014363929,0.0026967872,0.00348152,0.007948822,0.0015299752,0.00023656426,0.0013647702,0.0045970073,0.9637805],"genre_scores_gemma":[0.027893145,0.000804908,0.0012718786,0.00053723255,0.00008311918,0.000016966429,0.000895073,0.00029912277,0.9681986],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990376,0.000024536832,0.000013004052,0.0001351606,0.0006485117,0.00014129443],"domain_scores_gemma":[0.99829954,0.000070499176,0.000048085934,0.00010344461,0.0010001668,0.00047831255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045478105,0.0007575499,0.00038815418,0.001354708,0.003224081,0.0028645466,0.0005817802,0.00085012696,0.21758363],"category_scores_gemma":[0.0014072969,0.00042054272,0.00031328684,0.00073009485,0.0007337833,0.0017439165,0.00083937077,0.0013781249,0.05346097],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001342663,0.00011678582,0.0025483703,0.0000627598,0.000010258317,0.00033702128,0.00018176003,0.00015832933,0.0042756363,0.008957795,0.8043792,0.17883779],"study_design_scores_gemma":[0.000012511461,0.000079449645,0.0020322017,0.000021349471,0.000006322,0.00019579321,0.00016655496,0.00055196555,0.001863726,0.00022901267,0.99482805,0.000013103024],"about_ca_topic_score_codex":0.23530383,"about_ca_topic_score_gemma":0.48003104,"teacher_disagreement_score":0.23530383,"about_ca_system_score_codex":0.0038146442,"about_ca_system_score_gemma":0.0047088303,"threshold_uncertainty_score":0.7278898},"labels":[],"label_agreement":null},{"id":"W4245689577","doi":"10.15760/etd.5662","title":"Issues in Urban Trip Generation","year":2000,"lang":"en","type":"report","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Trip generation; Engineering; Operations research","score_opus":0.0417321917234854,"score_gpt":0.2886425292965252,"score_spread":0.24691033757303976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245689577","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042325113,0.0549528,0.3763085,0.1078604,0.009287154,0.0016909625,0.018472476,0.0010825199,0.38802004],"genre_scores_gemma":[0.6495514,0.044883296,0.19858436,0.020209232,0.0046339883,0.0058168457,0.015160061,0.0020574762,0.059103306],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9561829,0.029165521,0.0024268394,0.0042892983,0.0071619386,0.0007734558],"domain_scores_gemma":[0.8854244,0.072662465,0.0058151884,0.013497567,0.021683766,0.00091665087],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04990282,0.00069336157,0.00081650156,0.0047853286,0.0023440912,0.009438862,0.0046895524,0.0013300552,0.020345703],"category_scores_gemma":[0.15784976,0.0008312149,0.00095265586,0.015627306,0.0041268934,0.009984838,0.0056246193,0.0036507675,0.005363955],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010687163,0.00005192221,0.015053559,0.0022498767,0.00011083626,0.000091011054,0.016791413,0.003899895,0.00009937289,0.47971362,0.084226824,0.39760485],"study_design_scores_gemma":[0.000030400859,0.00015834869,0.019741679,0.0048739887,0.00006663153,0.0003198887,0.024460392,0.0029655248,0.00048307094,0.186963,0.75981474,0.00012221263],"about_ca_topic_score_codex":0.016806254,"about_ca_topic_score_gemma":0.020082634,"teacher_disagreement_score":0.04990282,"about_ca_system_score_codex":0.0052720383,"about_ca_system_score_gemma":0.0063952645,"threshold_uncertainty_score":0.26391447},"labels":[],"label_agreement":null},{"id":"W4246733329","doi":"10.4018/978-1-60566-988-5.ch024","title":"A Review of Recent Contribution in Agent-Based Health Care Modeling","year":2011,"lang":"en","type":"review","venue":"IGI Global eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Health care; Computer science; Management science; Data science; Systems engineering; Engineering; Political science","score_opus":0.06901787322622498,"score_gpt":0.33935734180571314,"score_spread":0.27033946857948815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246733329","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00052927097,0.9650976,0.02404496,0.002335995,0.0007608836,0.000031241092,0.000084827145,0.000103179555,0.007012049],"genre_scores_gemma":[0.006356135,0.97906643,0.011854851,0.00045507346,0.0007843327,0.00003072717,0.00013936507,0.000020491249,0.0012926115],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993561,0.00020183982,0.00008526417,0.000097958546,0.0002279156,0.000030855674],"domain_scores_gemma":[0.99820006,0.001282935,0.00009058288,0.00005823303,0.00031404974,0.000054180375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013890159,0.0010242625,0.0014117715,0.0019278849,0.00036235683,0.0018697218,0.0014876178,0.001529943,0.0039834976],"category_scores_gemma":[0.0029298686,0.00057761144,0.0009145505,0.0040569515,0.00051370816,0.0018448636,0.00081424444,0.0014160865,0.002054681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005264765,0.00012521709,0.0009422794,0.014405743,0.00021547978,0.00022266441,0.0001974721,0.02027582,0.0007063215,0.04163038,0.041020494,0.88020545],"study_design_scores_gemma":[0.000021336687,0.00009725613,0.00091356144,0.005663508,0.00022534108,0.0006907613,0.00020120559,0.016794533,0.00059474393,0.026093008,0.9486325,0.00007231323],"about_ca_topic_score_codex":0.003987469,"about_ca_topic_score_gemma":0.0030385242,"teacher_disagreement_score":0.003987469,"about_ca_system_score_codex":0.0011925276,"about_ca_system_score_gemma":0.0018939656,"threshold_uncertainty_score":0.013326108},"labels":[],"label_agreement":null},{"id":"W4247085377","doi":"10.32920/ryerson.14647785","title":"Smart Transit Dynamic Optimization and Informatics","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Dynamic pricing; Queue; Component (thermodynamics); Queueing theory; Operations research; Process (computing); Scheduling (production processes); Real-time computing; Mathematical optimization; Economics; Computer network; Engineering","score_opus":0.006371842414821381,"score_gpt":0.20301622465324595,"score_spread":0.19664438223842456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247085377","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18646345,0.0017085536,0.76461554,0.0041674683,0.0003414649,0.00013082617,0.0006721948,0.0006462317,0.041254226],"genre_scores_gemma":[0.96102035,0.00067697995,0.02913638,0.00024136003,0.000100272526,0.000073220246,0.00027331396,0.00009430311,0.008383898],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995472,0.00017226012,0.000015016708,0.00011089985,0.00007594498,0.0000787383],"domain_scores_gemma":[0.99913764,0.00049531856,0.00012839312,0.00009284182,0.00008872235,0.000057023462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007853777,0.00078943407,0.00090485794,0.00048413256,0.00041528075,0.0015318103,0.0006480085,0.0008274138,0.0046878634],"category_scores_gemma":[0.00221026,0.00043623187,0.0007085196,0.00073785527,0.0011888592,0.001762102,0.0011510759,0.0012524781,0.0002509534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027506241,0.000025972886,0.00044541777,0.00003606893,0.000023251656,0.000023891227,0.000018940565,0.9436738,0.00021192884,0.04754185,0.0011625102,0.0068089445],"study_design_scores_gemma":[0.0000063276216,0.00001592602,0.00022815833,0.0000055717755,0.000004351437,0.00000860765,0.000020488671,0.97059363,0.00010470554,0.027826067,0.0011816026,0.0000044528106],"about_ca_topic_score_codex":0.007771438,"about_ca_topic_score_gemma":0.004920285,"teacher_disagreement_score":0.007771438,"about_ca_system_score_codex":0.0021938037,"about_ca_system_score_gemma":0.0013099986,"threshold_uncertainty_score":0.015917242},"labels":[],"label_agreement":null},{"id":"W4247140322","doi":"10.32920/ryerson.14654697","title":"Uber vs. Public Transit : friend or foe? An Empirical Study of Ridership Trends Across Uber Cities in the USA","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; McGill University","funders":"","keywords":"Public transport; Descriptive statistics; Transit (satellite); Business; Order (exchange); Service (business); Complement (music); Rail transit; Demographic economics; Marketing; Transport engineering; Economics; Finance; Engineering","score_opus":0.131734711918154,"score_gpt":0.3655757401839659,"score_spread":0.23384102826581188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247140322","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985815,0.00004859981,0.000038943486,0.00014443534,0.000002788725,0.000004516918,0.00024179005,0.0000021695987,0.0009352625],"genre_scores_gemma":[0.99845505,0.000104126695,0.000060574712,0.00008748509,0.000006400964,0.000007270556,0.00039858895,0.0000029530302,0.00087750726],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995003,0.00016545833,0.000033094348,0.000107970765,0.000099095516,0.00009405683],"domain_scores_gemma":[0.9933356,0.0024027466,0.0020569807,0.00024097374,0.001385097,0.0005785595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001077828,0.000081750375,0.00023489314,0.0010509328,0.000734589,0.0011720423,0.00033875008,0.00033224648,0.0024842538],"category_scores_gemma":[0.0055488483,0.00010880744,0.00016674052,0.0025124396,0.00041256522,0.0011983025,0.0006771023,0.0007893614,0.0003374073],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008671591,0.00011891495,0.98794425,0.000013128228,0.000032982844,0.00006525946,0.0038590555,0.000046746503,0.000082051905,0.00019052839,0.0012617754,0.0062985155],"study_design_scores_gemma":[0.0000020167922,0.000045926197,0.9880585,0.00001010839,0.000017299495,0.00002553057,0.010422767,0.00032008937,0.000056981207,0.000022421245,0.0010139195,0.0000044810895],"about_ca_topic_score_codex":0.07597613,"about_ca_topic_score_gemma":0.17356262,"teacher_disagreement_score":0.07597613,"about_ca_system_score_codex":0.00081271736,"about_ca_system_score_gemma":0.00040767514,"threshold_uncertainty_score":0.1510678},"labels":[],"label_agreement":null},{"id":"W4247592793","doi":"10.4095/300992","title":"Mode of Transportation to Work, 2006: Car, Truck or Van as Passenger (by census subdivision)","year":2010,"lang":"en","type":"report","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Truck; Census; Subdivision; Mode (computer interface); Transport engineering; Work (physics); Geography; Engineering; Computer science; Automotive engineering; Sociology; Archaeology; Demography; Human–computer interaction; Population; Mechanical engineering","score_opus":0.020813626645576205,"score_gpt":0.2867017899054362,"score_spread":0.26588816325986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247592793","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0562835,0.0010402593,0.00037371163,0.0004725516,0.0001955445,0.00037971657,0.90462995,0.00020880958,0.036415994],"genre_scores_gemma":[0.08234396,0.005177109,0.0022528444,0.00037961302,0.000104997795,0.00063795224,0.82135737,0.000085820284,0.087660335],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99949145,0.000018530458,0.0000664014,0.000059638536,0.00027944625,0.00008459935],"domain_scores_gemma":[0.9988385,0.000032515723,0.00015271422,0.000025993015,0.00083023624,0.00011995871],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033603326,0.0009192073,0.0002836753,0.0032368847,0.00058945734,0.000710168,0.0011760041,0.00035256226,0.009530999],"category_scores_gemma":[0.0011109832,0.00033932054,0.0003978357,0.0042912206,0.00012301312,0.0008716318,0.00061066507,0.00066795334,0.006277599],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027333372,0.0003880636,0.2336529,0.00099431,0.00007185047,0.00016576583,0.0006003197,0.0013574881,0.00086421886,0.00075504737,0.70990986,0.050966784],"study_design_scores_gemma":[0.000045235596,0.00008801305,0.8088473,0.00022170285,0.000030355324,0.00019015351,0.001013861,0.0005381192,0.00048560413,0.0000751629,0.18843833,0.000026127876],"about_ca_topic_score_codex":0.58174795,"about_ca_topic_score_gemma":0.76918197,"teacher_disagreement_score":0.58174795,"about_ca_system_score_codex":0.0030455566,"about_ca_system_score_gemma":0.0057371454,"threshold_uncertainty_score":0.8414304},"labels":[],"label_agreement":null},{"id":"W4247802446","doi":"10.1504/ijsom.2020.104333","title":"Carsharing customer demand forecasting using causal, time series and neural network methods: a case study","year":2020,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Exponential smoothing; Demand forecasting; Computer science; Time series; Autoregressive integrated moving average; Artificial neural network; Operations research; Service quality; Customer satisfaction; Service (business); Business; Marketing; Artificial intelligence; Machine learning","score_opus":0.036478361910206696,"score_gpt":0.30528396017292664,"score_spread":0.26880559826271994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247802446","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9801276,0.00027666084,0.016017346,0.0004243875,0.000026549475,0.00008513123,0.00037707415,0.000101813945,0.0025634868],"genre_scores_gemma":[0.99047416,0.00021301502,0.008105857,0.000016685422,0.000012299622,0.000036825128,0.0001988319,0.000008604775,0.0009337554],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946445,0.00022357248,0.000038812184,0.00006327779,0.00013058604,0.00007922989],"domain_scores_gemma":[0.9967204,0.002473474,0.00015721773,0.00014415763,0.00041184816,0.00009292031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015095185,0.0006395644,0.00045303084,0.0010440765,0.0006358281,0.0008342381,0.0008997683,0.0016371188,0.0016066043],"category_scores_gemma":[0.0030687645,0.00033327844,0.0006657179,0.0015931291,0.00042437518,0.0009154698,0.000481683,0.0008802385,0.0001582576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058335945,0.0013926639,0.042009134,0.00029368085,0.000129764,0.0027764447,0.00042211916,0.8912948,0.00236235,0.0040074764,0.0021492646,0.052579015],"study_design_scores_gemma":[0.000019462826,0.00014149782,0.0054189954,0.000006084674,0.000017576056,0.000077501434,0.00026424005,0.9920493,0.0010963158,0.00044727675,0.00044395155,0.000017762814],"about_ca_topic_score_codex":0.04089427,"about_ca_topic_score_gemma":0.034139574,"teacher_disagreement_score":0.04089427,"about_ca_system_score_codex":0.0014689406,"about_ca_system_score_gemma":0.0006565452,"threshold_uncertainty_score":0.08131248},"labels":[],"label_agreement":null},{"id":"W4248078225","doi":"10.1002/atr.5670360201","title":"Masthead","year":2002,"lang":"en","type":"paratext","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Citation; Computer science; World Wide Web; Library science","score_opus":0.011848281070214272,"score_gpt":0.24322515236990375,"score_spread":0.23137687129968948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248078225","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006377002,0.0007107875,0.0020470426,0.0009092247,0.0017507396,0.000071565795,0.0019864864,0.0022541815,0.98963237],"genre_scores_gemma":[0.0005833964,0.00013778669,0.00020358912,0.00010140365,0.000067070076,0.000010143793,0.000429412,0.0001974364,0.9982698],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996656,0.000027286413,0.000016522321,0.000085890686,0.00016522141,0.00003945389],"domain_scores_gemma":[0.99889827,0.000159814,0.00004306651,0.00018681995,0.0005038658,0.00020815925],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00043446876,0.0011468605,0.0007493764,0.0019652664,0.0017448699,0.003958501,0.0012122119,0.0017033329,0.8901924],"category_scores_gemma":[0.0017925517,0.0005735718,0.00049492606,0.0018503378,0.00033669497,0.0028148298,0.0020061075,0.0015036608,0.8116378],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051782266,0.000036559475,0.00010230708,0.000068372996,0.0000015639187,0.000070802336,0.000048643036,0.000060942195,0.00064657844,0.0024244762,0.8582222,0.13826588],"study_design_scores_gemma":[0.000008551373,0.00001772587,0.00041489876,0.000036980753,0.0000024070343,0.000084742365,0.00005459536,0.000103633625,0.00026049066,0.00078783755,0.9982236,0.000004439678],"about_ca_topic_score_codex":0.0019140361,"about_ca_topic_score_gemma":0.0051442436,"teacher_disagreement_score":0.10980761,"about_ca_system_score_codex":0.00043917634,"about_ca_system_score_gemma":0.0008005347,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4248387888","doi":"10.32920/ryerson.14664711","title":"What's Steering Consumer Preferences for Autonomous Vehicles in the Greater Toronto and Hamilton Area?","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Respondent; The Internet; Business; Public transport; Willingness to pay; Marketing; Advertising; Transport engineering; Economics; Engineering; Computer science; Political science; Microeconomics","score_opus":0.038808766103921616,"score_gpt":0.2557451725738443,"score_spread":0.2169364064699227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248387888","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99803954,0.000101990714,0.000035809106,0.00032589686,0.0000038867843,0.000009542281,0.00018737043,0.0000015108595,0.001294511],"genre_scores_gemma":[0.9992416,0.000097846496,0.000032111697,0.000041121846,0.0000026031976,0.0000037805496,0.00008652548,0.000001117215,0.00049326784],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99968505,0.000067792535,0.000011869971,0.000037965547,0.00009424015,0.00010306798],"domain_scores_gemma":[0.998863,0.00018344498,0.00030153437,0.000036995796,0.00027472174,0.00034037675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035915204,0.00011935034,0.00014493229,0.0004545219,0.00073271175,0.0011671147,0.00029452774,0.0003508792,0.003225704],"category_scores_gemma":[0.0013056826,0.0001744766,0.0003324185,0.0011638857,0.0007277109,0.00039704636,0.00032884185,0.00029118816,0.00023547884],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008765627,0.0000364644,0.985783,0.00002868124,0.00004203893,0.0001443271,0.00544333,0.00010081441,0.00035398267,0.00020690508,0.0013303615,0.00644242],"study_design_scores_gemma":[0.0000034372224,0.000022293827,0.9887664,0.000014431403,0.000012426098,0.000036928504,0.010030247,0.00019604102,0.000033557124,0.00003391825,0.00084354635,0.0000067461533],"about_ca_topic_score_codex":0.8060264,"about_ca_topic_score_gemma":0.918919,"teacher_disagreement_score":0.1939736,"about_ca_system_score_codex":0.004823382,"about_ca_system_score_gemma":0.0023711731,"threshold_uncertainty_score":0.39023185},"labels":[],"label_agreement":null},{"id":"W4248909097","doi":"10.31219/osf.io/hvbma","title":"Measuring when Uber behaves as a substitute or complement to transit: An examination of travel-time differences in Toronto","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"TRIPS architecture; Transit (satellite); Public transport; Business; Service (business); Duration (music); Travel behavior; Urban transit; Transport engineering; Sample (material); Vehicle miles of travel; Demographic economics; Advertising; Marketing; Economics; Engineering","score_opus":0.06980929996071908,"score_gpt":0.27875908420616274,"score_spread":0.20894978424544366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248909097","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99317306,0.00018773595,0.00014939193,0.0001476947,0.000004872422,0.000024951734,0.0033115472,0.000009651748,0.0029911348],"genre_scores_gemma":[0.9953734,0.00017283497,0.00021948652,0.000027467191,0.0000033235128,0.000020700525,0.0025610235,0.0000056985277,0.0016160578],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99928576,0.00012278816,0.000057277855,0.00012668515,0.0002249937,0.0001824842],"domain_scores_gemma":[0.99705184,0.0003865987,0.00078381866,0.00017846606,0.0010166191,0.00058259565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062427274,0.00028012443,0.0002941573,0.0013894876,0.0014822892,0.0011320248,0.0007734892,0.00032338253,0.0028605654],"category_scores_gemma":[0.0030463717,0.00023290367,0.00053542905,0.0045857592,0.0006483176,0.00050706445,0.0011603676,0.00038095238,0.0003747906],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001234225,0.00004081248,0.9829101,0.00007390636,0.00009898843,0.00021937552,0.0071855253,0.00081779243,0.0008319551,0.0006535193,0.002059911,0.004984759],"study_design_scores_gemma":[0.0000018057426,0.000020573641,0.9936386,0.000016653685,0.00001647152,0.000022804477,0.0044221194,0.0005475967,0.00007473052,0.000014498159,0.0012150703,0.000009099995],"about_ca_topic_score_codex":0.96289396,"about_ca_topic_score_gemma":0.98422295,"teacher_disagreement_score":0.037106037,"about_ca_system_score_codex":0.015892664,"about_ca_system_score_gemma":0.0059907218,"threshold_uncertainty_score":0.115309894},"labels":[],"label_agreement":null},{"id":"W4249669903","doi":"10.4095/301007","title":"Mode of Transportation to Work, 2001: All Other Modes (by census division)","year":2010,"lang":"en","type":"report","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Census; Division (mathematics); Mode (computer interface); Work (physics); Transport engineering; Geography; Computer science; Engineering; Sociology; Mathematics; Demography; Human–computer interaction; Arithmetic; Mechanical engineering","score_opus":0.035102312913360384,"score_gpt":0.29822693668617667,"score_spread":0.2631246237728163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249669903","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04110356,0.001542991,0.0002877789,0.00063494785,0.00019965522,0.0005225893,0.8909631,0.00028660888,0.06445867],"genre_scores_gemma":[0.11340252,0.0067756297,0.0016263521,0.0006903787,0.00009181815,0.0008770198,0.7394795,0.00011018798,0.1369466],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99943274,0.000008728582,0.000035766672,0.0000459474,0.0003376854,0.00013915528],"domain_scores_gemma":[0.99895716,0.000012364274,0.00007933427,0.000019841134,0.0008035147,0.00012779595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019370623,0.0010686396,0.0002561771,0.0040873303,0.0014518007,0.00094533217,0.0013298291,0.00043047074,0.01623977],"category_scores_gemma":[0.00093887514,0.00033049632,0.0005594467,0.007164851,0.00017185938,0.000590983,0.0006709373,0.000639023,0.005937739],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015668664,0.00013633401,0.15174146,0.0007844493,0.000076198565,0.00013160786,0.0006062812,0.0007097622,0.000780469,0.0006060078,0.78544694,0.058823705],"study_design_scores_gemma":[0.000029255307,0.00002545629,0.7878021,0.00020423916,0.00003231468,0.000098495824,0.0007696337,0.0002771265,0.00028495802,0.000051085262,0.21039674,0.000028593748],"about_ca_topic_score_codex":0.9774575,"about_ca_topic_score_gemma":0.9878907,"teacher_disagreement_score":0.9774575,"about_ca_system_score_codex":0.010270003,"about_ca_system_score_gemma":0.017684354,"threshold_uncertainty_score":0.07451439},"labels":[],"label_agreement":null},{"id":"W4250990792","doi":"10.4095/300996","title":"Mode of Transportation to Work, 2006: All Other Modes (by census subdivision)","year":2010,"lang":"en","type":"report","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Subdivision; Census; Mode (computer interface); Work (physics); Geography; Transport engineering; Computer science; Engineering; Sociology; Demography; Human–computer interaction; Archaeology; Mechanical engineering; Population","score_opus":0.02753936815050123,"score_gpt":0.28818288163394534,"score_spread":0.2606435134834441,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250990792","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026054777,0.0007806583,0.00023914389,0.00021964485,0.00013300273,0.0003123769,0.9365663,0.00019416411,0.03550002],"genre_scores_gemma":[0.0554088,0.0030958673,0.0015723123,0.0002362739,0.00005780569,0.00058453373,0.8634291,0.00007953127,0.07553573],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99952686,0.00001490938,0.00005468937,0.000049511735,0.00026130833,0.000092794595],"domain_scores_gemma":[0.99901974,0.000017758524,0.00011513721,0.000026917083,0.00071855285,0.00010180397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023364545,0.0009889563,0.00029741836,0.003540015,0.00064687,0.00072177214,0.001194235,0.00031283466,0.015931476],"category_scores_gemma":[0.00091751147,0.00030962654,0.00048449056,0.0058806366,0.00010862893,0.0007111656,0.000619044,0.0005621197,0.0095597105],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025616365,0.00023313359,0.15257023,0.00097147806,0.00007006672,0.00012553175,0.00048713046,0.0011354588,0.00073438406,0.0006699987,0.7927239,0.05002261],"study_design_scores_gemma":[0.000040385883,0.000056297213,0.7548791,0.00023414352,0.00002334279,0.00012087126,0.00064156455,0.0003610184,0.00031139338,0.000076586184,0.24323192,0.000023305798],"about_ca_topic_score_codex":0.65738094,"about_ca_topic_score_gemma":0.78550464,"teacher_disagreement_score":0.34261906,"about_ca_system_score_codex":0.0028894532,"about_ca_system_score_gemma":0.005266487,"threshold_uncertainty_score":0.6892736},"labels":[],"label_agreement":null},{"id":"W4251082716","doi":"10.32920/ryerson.14666370.v1","title":"Shifting gears for the automated vehicle: findings from focus groups in the Greater Toronto and Hamilton area","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Planner; Focus group; Focus (optics); Public relations; Key (lock); Business; Public transport; Marketing; Computer science; Transport engineering; Political science; Engineering; Artificial intelligence; Computer security","score_opus":0.021261487538698037,"score_gpt":0.24096764909963098,"score_spread":0.21970616156093295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251082716","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99792045,0.0000786367,0.0002117834,0.0003172376,0.0000057915227,0.00009519162,0.00003402085,0.00000294439,0.0013338673],"genre_scores_gemma":[0.99725777,0.00018017611,0.00031880697,0.0002146143,0.000007137808,0.00012789469,0.000032199037,0.0000040907835,0.0018572683],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9971819,0.0016076408,0.00007676591,0.00023390957,0.00036828232,0.0005315653],"domain_scores_gemma":[0.9896889,0.007019641,0.0007346284,0.00022485193,0.0013067293,0.0010251907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003949646,0.00038681383,0.00030214727,0.0010811115,0.0074944785,0.0014548905,0.0011990372,0.0010156464,0.0025174303],"category_scores_gemma":[0.008843592,0.00035715496,0.00021019593,0.0014667627,0.0045552594,0.0010526783,0.0027623905,0.00081716664,0.00015909718],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049381313,0.00006922602,0.0140894065,0.00008570116,0.000005697471,0.0003427172,0.9781382,0.000047198726,0.0012812454,0.00019110745,0.0004621838,0.0052379705],"study_design_scores_gemma":[0.000009079807,0.00009772117,0.03659534,0.00006443077,0.000011165754,0.000055266824,0.95813084,0.00008985307,0.0004511504,0.00006402278,0.004416742,0.000014390303],"about_ca_topic_score_codex":0.6165445,"about_ca_topic_score_gemma":0.7605066,"teacher_disagreement_score":0.38345551,"about_ca_system_score_codex":0.010350436,"about_ca_system_score_gemma":0.010335315,"threshold_uncertainty_score":0.7714275},"labels":[],"label_agreement":null},{"id":"W4251175326","doi":"10.1007/978-0-387-22458-9_5","title":"Trajectory Planning: Pick-and-Place Operations","year":2007,"lang":"en","type":"book-chapter","venue":"Mechanical engineering series","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Process (computing); Robot; Trajectory; Ideal (ethics); Object (grammar); Motion (physics); Simple (philosophy); Terrain; Artificial intelligence; Control engineering; Simulation; Engineering","score_opus":0.021191673564028263,"score_gpt":0.22518849070451027,"score_spread":0.203996817140482,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251175326","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00090789,0.007820656,0.885112,0.0006158606,0.0006219696,0.0000636283,0.00038603062,0.0014491833,0.1030228],"genre_scores_gemma":[0.04797315,0.038054604,0.6651063,0.00032702522,0.0005497112,0.0002976819,0.0022035418,0.001398524,0.24408948],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99976593,0.00002760951,0.000012621137,0.00006256756,0.00011096792,0.000020274314],"domain_scores_gemma":[0.9998988,0.000031949137,0.0000070717683,0.000021309179,0.00003173221,0.000009164666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022097013,0.0018682177,0.000894969,0.00074745005,0.00068658125,0.0023481338,0.0016276264,0.0011623584,0.020061126],"category_scores_gemma":[0.0005362524,0.0009283481,0.00068697624,0.0031504552,0.0011337764,0.0023335812,0.0010742643,0.001900579,0.008201559],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002834184,0.000042739022,0.00011670274,0.00037307318,0.000017062195,0.00006391057,0.000177099,0.10702221,0.001851577,0.22894675,0.08946758,0.5718929],"study_design_scores_gemma":[0.000011657977,0.000037985046,0.00026846226,0.00029100283,0.000024747955,0.00021473333,0.00016418798,0.14295761,0.0033730355,0.25362077,0.59898895,0.000046846977],"about_ca_topic_score_codex":0.011104222,"about_ca_topic_score_gemma":0.015089238,"teacher_disagreement_score":0.020061126,"about_ca_system_score_codex":0.0013522897,"about_ca_system_score_gemma":0.002116956,"threshold_uncertainty_score":0.067111194},"labels":[],"label_agreement":null},{"id":"W4251529353","doi":"10.1177/0361198106198500119","title":"Incorporating Within-Household Interactions into Mode Choice Model with Genetic Algorithm for Parameter Estimation","year":2006,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mode (computer interface); Computer science; Grid; Estimation; Genetic algorithm; Discrete choice; Algorithm; Estimation theory; Mode choice; Mathematical optimization; Machine learning; Mathematics; Engineering","score_opus":0.06912050632834542,"score_gpt":0.36038063307539236,"score_spread":0.29126012674704693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251529353","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011699132,0.00004460495,0.98713464,0.00005918219,0.000008509707,0.000039420866,0.000037805436,0.00014055468,0.000836267],"genre_scores_gemma":[0.37497422,0.00017622505,0.62148917,0.0000823325,0.000026721447,0.000511698,0.00023707726,0.000096340016,0.0024062106],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993932,0.00038074155,0.000014695682,0.00007248439,0.000083920895,0.000055063076],"domain_scores_gemma":[0.9980989,0.0015835476,0.000088500296,0.00006898572,0.00013561641,0.00002436173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016594676,0.00080231135,0.001304982,0.0008277821,0.0006218084,0.00088535604,0.0013727164,0.0012512511,0.0031709624],"category_scores_gemma":[0.006482745,0.0005625429,0.00091917085,0.001330491,0.0005529212,0.0010897736,0.0008361083,0.0014991745,0.00042104896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009811691,0.000017854763,0.00062884414,0.000008132324,0.000026041535,0.000031607564,0.000020414285,0.98337495,0.00012050098,0.0064128274,0.00018096417,0.009168024],"study_design_scores_gemma":[0.0000021310757,0.000003368829,0.000053153733,0.0000014377289,0.0000029042503,0.0000042303855,0.0000028640873,0.9976398,0.000029432656,0.0021887475,0.000068977926,0.0000029128187],"about_ca_topic_score_codex":0.023968142,"about_ca_topic_score_gemma":0.017651953,"teacher_disagreement_score":0.023968142,"about_ca_system_score_codex":0.0010024738,"about_ca_system_score_gemma":0.0015481985,"threshold_uncertainty_score":0.04765725},"labels":[],"label_agreement":null},{"id":"W4251669918","doi":"10.32920/ryerson.14648973","title":"Will autonomous vehicles undermine Ontario provincial policies to concentrate jobs and housing? Evidence from the Greater Toronto-Hamilton area","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Relocation; Work (physics); Pedestrian; Land use; Residence; Cycling; Journey to work; Business; Service (business); Transport engineering; Geography; Environmental planning; Public transport; Engineering; Demographic economics; Civil engineering; Economics; Computer science; Marketing","score_opus":0.03312357348549458,"score_gpt":0.2417685077624137,"score_spread":0.20864493427691913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251669918","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95472085,0.001242054,0.00027269297,0.0060325586,0.000043550266,0.000058272864,0.0021515281,0.00001245298,0.035466067],"genre_scores_gemma":[0.99447745,0.00058690953,0.000108960616,0.00025306744,0.0000089817095,0.000013335468,0.00026761435,0.0000052308474,0.004278554],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99825877,0.00023975589,0.00005741818,0.00015520188,0.000609736,0.00067919784],"domain_scores_gemma":[0.9941942,0.00076858775,0.0011317101,0.00030185096,0.00233774,0.0012658746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010973801,0.00015099268,0.0002132449,0.00065895834,0.0040459516,0.0022289867,0.0010454477,0.0004396187,0.0052799233],"category_scores_gemma":[0.005761672,0.00026180263,0.00030863276,0.002223537,0.0022820886,0.0010502433,0.0015528759,0.00054472237,0.000324715],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029084092,0.000081380356,0.8959725,0.00042286806,0.00010642776,0.0004149134,0.02994182,0.0006801637,0.0005985263,0.012369731,0.018075524,0.041045394],"study_design_scores_gemma":[0.000024138055,0.000052497187,0.933693,0.00021187965,0.000051224244,0.000044257304,0.035446707,0.00040866158,0.0001986729,0.00044976833,0.02939753,0.00002169811],"about_ca_topic_score_codex":0.99370956,"about_ca_topic_score_gemma":0.9981346,"teacher_disagreement_score":0.049867485,"about_ca_system_score_codex":0.049867485,"about_ca_system_score_gemma":0.061834358,"threshold_uncertainty_score":0.36181557},"labels":[],"label_agreement":null},{"id":"W4251694648","doi":"10.1093/geront/gnv537.05","title":"TRAVEL TRAINING FOR OLDER ADULTS: PROMOTING A HEALTHY TRANSITION FROM DRIVING","year":2015,"lang":"en","type":"article","venue":"The Gerontologist","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Joseph's Care Group; University of Manitoba; Western University; University of Ottawa; Lakehead University","funders":"","keywords":"Training (meteorology); Transition (genetics); Gerontology; Psychology; Physical medicine and rehabilitation; Medicine; Geography","score_opus":0.06153634867840181,"score_gpt":0.2842463937996038,"score_spread":0.22271004512120202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251694648","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45502317,0.06535195,0.012042036,0.34228495,0.010807643,0.0011769675,0.00033648356,0.000739534,0.11223725],"genre_scores_gemma":[0.82756954,0.0630483,0.036035564,0.033510316,0.0029041169,0.000745873,0.00026861185,0.00008475987,0.035833005],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99946207,0.00026425923,0.000042789743,0.00003954198,0.00008719914,0.000104101775],"domain_scores_gemma":[0.99899894,0.00015349926,0.00009426704,0.000023171871,0.00015152238,0.0005786502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001609951,0.0002636417,0.00019830895,0.00042131677,0.0012588965,0.0014602572,0.00045350354,0.0017831459,0.005314975],"category_scores_gemma":[0.0026396774,0.00014113694,0.00033236528,0.00018981477,0.0005499479,0.0010708235,0.0022827717,0.0018138057,0.0008515944],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001246576,0.001886878,0.012915906,0.0024156945,0.00004698733,0.00025187913,0.0070515187,0.0003007873,0.0022551897,0.0030887423,0.0760816,0.8935801],"study_design_scores_gemma":[0.00024345126,0.0041710595,0.2660046,0.007702627,0.00026304412,0.0016390702,0.040746287,0.0012461054,0.0025678927,0.008284726,0.66699994,0.00013126622],"about_ca_topic_score_codex":0.0030447445,"about_ca_topic_score_gemma":0.010514168,"teacher_disagreement_score":0.005314975,"about_ca_system_score_codex":0.0006827781,"about_ca_system_score_gemma":0.00268017,"threshold_uncertainty_score":0.017780364},"labels":[],"label_agreement":null},{"id":"W4252135256","doi":"10.4018/978-1-60566-054-7.ch142","title":"Mobile Virtual Communities of Commuters","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Taxis; Public transport; Global Positioning System; Computer science; Telephony; Telecommunications; The Internet; Passenger information; Software; Mobile telephony; Transport engineering; Computer security; Engineering; Mobile radio; World Wide Web","score_opus":0.015817238681852846,"score_gpt":0.2290390644634867,"score_spread":0.21322182578163387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252135256","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07617158,0.0073209773,0.06861339,0.005437117,0.0011981294,0.00035586022,0.00038193454,0.0016412104,0.83887976],"genre_scores_gemma":[0.48163164,0.005015209,0.0348304,0.00091590575,0.0005169383,0.0004686951,0.0006885694,0.00030224374,0.47563043],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99959606,0.00017619727,0.000015397576,0.00007257034,0.00008071739,0.000059147726],"domain_scores_gemma":[0.99922526,0.00020090606,0.000046744208,0.0001401403,0.00008334041,0.00030366183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005960606,0.00037728905,0.00021180214,0.0009934357,0.002579753,0.005337559,0.0010813279,0.001162189,0.037004724],"category_scores_gemma":[0.0016004872,0.00021236268,0.00025481833,0.0010328469,0.0011506216,0.0061693657,0.0048242426,0.0007006617,0.005593483],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012495938,0.00017357862,0.0016427897,0.00052469416,0.000020228115,0.0011220692,0.025617894,0.0016683136,0.0026361737,0.4211341,0.10614728,0.4391879],"study_design_scores_gemma":[0.000017794895,0.000045996145,0.00053396064,0.00012976278,0.000008593485,0.00066026364,0.004899663,0.0016076196,0.00036950398,0.03408358,0.9576298,0.000013515558],"about_ca_topic_score_codex":0.0010999176,"about_ca_topic_score_gemma":0.002015368,"teacher_disagreement_score":0.037004724,"about_ca_system_score_codex":0.0007016463,"about_ca_system_score_gemma":0.00066327624,"threshold_uncertainty_score":0.123793185},"labels":[],"label_agreement":null},{"id":"W4252361803","doi":"10.5383/jttm.03.01.004","title":"Modeling framework for supporting taxi policy making","year":2019,"lang":"en","type":"article","venue":"International Journal of Traffic and Transportation Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Order (exchange); Business; Econometric model; Mode (computer interface); Fleet management; Supply and demand; Distribution (mathematics); Transport engineering; Operations research; Computer science; Industrial organization; Economics; Finance; Engineering; Microeconomics","score_opus":0.011268370391382027,"score_gpt":0.2926964490448884,"score_spread":0.2814280786535064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252361803","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021438585,0.00035076286,0.9667771,0.0020116384,0.00017212355,0.00024646817,0.0009482581,0.0007818159,0.026567915],"genre_scores_gemma":[0.17364897,0.0024012749,0.79529285,0.00059835654,0.000382104,0.0017776138,0.0025645911,0.00043694634,0.02289731],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987746,0.00048287236,0.0001081592,0.00018091161,0.0003439279,0.00010950138],"domain_scores_gemma":[0.99816835,0.0007706959,0.00019128043,0.0001824511,0.00057505723,0.0001121112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030497855,0.0012152432,0.0011277721,0.0016391253,0.001386598,0.004018961,0.004091043,0.0032759053,0.011137673],"category_scores_gemma":[0.005370976,0.00073068857,0.0019157395,0.001777828,0.0010182991,0.0037142073,0.002517453,0.0029479617,0.0026547508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010659782,0.00005032192,0.0003066456,0.00008147974,0.00003562945,0.00011621629,0.00017149858,0.42074183,0.00033257602,0.56411177,0.0044251285,0.0096162325],"study_design_scores_gemma":[0.000016519189,0.000017055532,0.00009197906,0.000073822994,0.000022075877,0.00004491593,0.000110573776,0.76894134,0.00021124166,0.18644147,0.044001967,0.000026980431],"about_ca_topic_score_codex":0.02555696,"about_ca_topic_score_gemma":0.0152323255,"teacher_disagreement_score":0.02555696,"about_ca_system_score_codex":0.002814071,"about_ca_system_score_gemma":0.0051241736,"threshold_uncertainty_score":0.050816417},"labels":[],"label_agreement":null},{"id":"W4252451967","doi":"10.5383/jttm.02.02.003","title":"The effects of autonomous buses to vehicle scheduling system","year":2020,"lang":"en","type":"article","venue":"International Journal of Traffic and Transportation Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Crew; Public transport; Crew scheduling; Scheduling (production processes); Computer science; Population; Transport engineering; Operations research; Business; Engineering; Aeronautics; Operations management","score_opus":0.0057761575401743485,"score_gpt":0.2098955778032294,"score_spread":0.20411942026305505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252451967","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9683156,0.0006130731,0.017529732,0.00047609475,0.00024404301,0.00011013127,0.00028306083,0.00079045055,0.011637824],"genre_scores_gemma":[0.9978229,0.00007972516,0.0010265161,0.000027683045,0.000016993352,0.000008573396,0.00008067601,0.000017547465,0.000919407],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994804,0.00022876955,0.000018738227,0.00006274428,0.00007594115,0.00013342674],"domain_scores_gemma":[0.99836653,0.0009032818,0.00013121826,0.00010524094,0.00031850406,0.00017519118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007335033,0.0006219812,0.00044430434,0.0004381231,0.0005053277,0.00067322224,0.00062232715,0.00040119563,0.0052279485],"category_scores_gemma":[0.0022688187,0.00013974156,0.0003481084,0.0004172432,0.0003492997,0.0005119001,0.00052768533,0.00033912683,0.00032926066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018122386,0.0003479415,0.005961218,0.00022198833,0.00009214926,0.00029970068,0.00012925333,0.94220525,0.0079484265,0.0025725153,0.0025988892,0.035810396],"study_design_scores_gemma":[0.000111638095,0.0009740526,0.005925756,0.000012504989,0.00011156913,0.00005552086,0.00033444478,0.98423564,0.00446004,0.0016741611,0.0020839265,0.000020641008],"about_ca_topic_score_codex":0.016377302,"about_ca_topic_score_gemma":0.006807454,"teacher_disagreement_score":0.016377302,"about_ca_system_score_codex":0.0008703048,"about_ca_system_score_gemma":0.00058231445,"threshold_uncertainty_score":0.032563925},"labels":[],"label_agreement":null},{"id":"W4253771444","doi":"10.1109/glocom.2014.7417469","title":"A Public Vehicle System with Multiple Origin-Destination Pairs on Traffic Networks","year":2014,"lang":"en","type":"article","venue":"2015 IEEE Global Communications Conference (GLOBECOM)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Taxis; Public transport; Computer science; Traffic congestion; Scheduling (production processes); Travelling salesman problem; Key (lock); Path (computing); Energy consumption; Traffic system; Transport engineering; Real-time computing; Computer network; Mathematical optimization; Engineering; Computer security","score_opus":0.05761607196773316,"score_gpt":0.2602072905555159,"score_spread":0.20259121858778273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253771444","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7491322,0.0005993374,0.2161126,0.0018768363,0.0003466764,0.00037533915,0.0015101274,0.001052741,0.028994132],"genre_scores_gemma":[0.9855192,0.00017995975,0.0055285897,0.000051531704,0.00004634708,0.00010101433,0.00029566625,0.000018127495,0.00825948],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992078,0.00018337448,0.00002701072,0.00021388901,0.000109242355,0.00025872033],"domain_scores_gemma":[0.99934727,0.00024659367,0.00009138954,0.00006338639,0.00013310827,0.00011826775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047787573,0.0009930842,0.0013060351,0.0006650713,0.0022589024,0.0017130637,0.0021023024,0.0018814094,0.009586281],"category_scores_gemma":[0.0011974062,0.0004224046,0.0006487531,0.001549334,0.00095044286,0.0020897435,0.0021634323,0.00087472895,0.0008723335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005511308,0.00016666079,0.0031392933,0.00012494356,0.00008282606,0.0013923843,0.00015690681,0.94484866,0.0030336413,0.028432937,0.0039068074,0.014163952],"study_design_scores_gemma":[0.000043125037,0.00009079731,0.00036464166,0.000004548407,0.00002407691,0.0001164586,0.00008396529,0.99141884,0.00040993484,0.0057981964,0.0016286422,0.000016821861],"about_ca_topic_score_codex":0.015429809,"about_ca_topic_score_gemma":0.011428835,"teacher_disagreement_score":0.015429809,"about_ca_system_score_codex":0.0025672342,"about_ca_system_score_gemma":0.0014177543,"threshold_uncertainty_score":0.032069266},"labels":[],"label_agreement":null},{"id":"W4254066904","doi":"10.21203/rs.3.rs-362419/v1","title":"Differential Impacts of Ridesharing on Alcohol-related Crashes by Socioeconomic Municipalities: Rate of Technology Adoption Matters","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Socioeconomic status; Geography; Demography; Confidence interval; Demographic economics; Socioeconomics; Environmental health; Medicine; Economics; Sociology; Population","score_opus":0.03504915248086762,"score_gpt":0.33652258179825245,"score_spread":0.30147342931738486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254066904","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9972957,0.0004891038,0.00031081264,0.00021573037,0.000009745849,0.0000143735015,0.00035425677,0.0000075951425,0.0013028068],"genre_scores_gemma":[0.9995592,0.000101477606,0.000049603135,0.000015299247,0.0000069052494,0.000005008306,0.00010622142,0.0000026834693,0.00015349952],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974955,0.0010122692,0.00018521474,0.0005176327,0.00032682103,0.00046251144],"domain_scores_gemma":[0.9862294,0.005122305,0.005816578,0.0011895215,0.00077778427,0.0008643551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023855371,0.00026895554,0.00043652116,0.0011991218,0.0003476524,0.0013375048,0.0007225829,0.0004942434,0.0052900184],"category_scores_gemma":[0.015930414,0.00017620265,0.0013706035,0.0016373886,0.0007122868,0.0007665049,0.0014672972,0.00055400416,0.00030669218],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000079683145,0.000020850877,0.9974511,0.000026825144,0.00015602361,0.000068917485,0.00020711348,0.0000771948,0.00012846055,0.000081162514,0.00006564002,0.0016369617],"study_design_scores_gemma":[0.0000015073076,0.000048062408,0.9985726,0.000018249359,0.00007536139,0.000040492603,0.0008238561,0.00017394034,0.00006391619,0.00004533936,0.00013379168,0.0000028474228],"about_ca_topic_score_codex":0.02433276,"about_ca_topic_score_gemma":0.014301716,"teacher_disagreement_score":0.02433276,"about_ca_system_score_codex":0.0004820466,"about_ca_system_score_gemma":0.0006945404,"threshold_uncertainty_score":0.048382282},"labels":[],"label_agreement":null},{"id":"W4254072778","doi":"10.1108/s2044-994120150000007009","title":"Index","year":2015,"lang":"en","type":"paratext","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Index (typography); Mathematics; Computer science; World Wide Web","score_opus":0.020516111482758826,"score_gpt":0.2527939647166392,"score_spread":0.23227785323388034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254072778","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004898289,0.0058265277,0.0018240357,0.0065242224,0.016149068,0.00031817344,0.021462115,0.002589873,0.9448163],"genre_scores_gemma":[0.0020410123,0.004763106,0.0014536873,0.002396733,0.002319162,0.00021931955,0.018076023,0.0009805061,0.9677503],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99817693,0.00015470109,0.00016680165,0.00035198033,0.0009857398,0.00016380395],"domain_scores_gemma":[0.9975625,0.0001844493,0.00010100685,0.0003618495,0.0014492765,0.00034092608],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0012434502,0.0017354459,0.0014093844,0.005510424,0.0025171752,0.0116697615,0.002605417,0.0025584847,0.70255244],"category_scores_gemma":[0.006194789,0.00057813997,0.0011283101,0.008192039,0.0008293529,0.008468715,0.004423753,0.0022755307,0.7258396],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011401424,0.00001681958,0.00012781606,0.00019496611,0.0000034663183,0.000024833795,0.000050206858,0.000029215493,0.000116087525,0.004671754,0.9231823,0.07157112],"study_design_scores_gemma":[0.0000023547166,0.0000061097257,0.00018963873,0.00009544804,0.0000017257993,0.000033032236,0.000045923305,0.00002116631,0.00004368538,0.0011220886,0.99843436,0.0000044752555],"about_ca_topic_score_codex":0.005255752,"about_ca_topic_score_gemma":0.005906641,"teacher_disagreement_score":0.29744756,"about_ca_system_score_codex":0.0026306354,"about_ca_system_score_gemma":0.0035626967,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4255241136","doi":"10.1177/0361198106198600114","title":"Carsharing and Station Cars in Asia","year":2006,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"University of California, Davis; National University of Singapore","keywords":"Kuala lumpur; Public transport; Business; Car ownership; Transport engineering; Geography; Engineering; Economic growth; Marketing; Economics","score_opus":0.055293694918341366,"score_gpt":0.34467087627663784,"score_spread":0.2893771813582965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255241136","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08754138,0.37200087,0.0019835408,0.0073164525,0.0031749867,0.00008058377,0.0025762843,0.00023860729,0.52508736],"genre_scores_gemma":[0.37028793,0.46388608,0.0020054355,0.0034399435,0.0014259774,0.00006263897,0.0039446615,0.00013323253,0.15481412],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99947983,0.000046546524,0.000063857166,0.00010558944,0.00019711228,0.00010718638],"domain_scores_gemma":[0.9982912,0.00017977961,0.0003601078,0.00010490493,0.0008198013,0.00024420198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006413476,0.00046590445,0.0002832629,0.0017600533,0.00094196823,0.0040857526,0.0005513921,0.00063965423,0.017760623],"category_scores_gemma":[0.000945093,0.00017682301,0.00035538204,0.0075991424,0.0006315429,0.0035804845,0.0019883164,0.000960303,0.003526135],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015879425,0.00014141231,0.052580796,0.0060814624,0.000090159796,0.0018745498,0.008405934,0.00058491813,0.0028766252,0.040472806,0.11554228,0.7711903],"study_design_scores_gemma":[0.0000039320053,0.00012344836,0.044909723,0.0010974898,0.00005706929,0.0016814718,0.006609259,0.000112855574,0.0012708572,0.0014232513,0.9426831,0.000027514337],"about_ca_topic_score_codex":0.013190887,"about_ca_topic_score_gemma":0.016357942,"teacher_disagreement_score":0.017760623,"about_ca_system_score_codex":0.001346681,"about_ca_system_score_gemma":0.0033925634,"threshold_uncertainty_score":0.05941522},"labels":[],"label_agreement":null},{"id":"W4256531722","doi":"10.1007/978-0-387-39940-9_2980","title":"Location Services","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Geography; Computer science; Business","score_opus":0.009302821148771205,"score_gpt":0.20909501436815026,"score_spread":0.19979219321937905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4256531722","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014694168,0.0033357588,0.056143865,0.001745131,0.0008057001,0.00017212683,0.009663755,0.020188281,0.9064759],"genre_scores_gemma":[0.013189764,0.004675789,0.019505853,0.0010517803,0.00031758225,0.000095302115,0.013770275,0.001883511,0.9455102],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996107,0.000035732948,0.000023774825,0.00007772445,0.00019829413,0.000053749656],"domain_scores_gemma":[0.9996388,0.00004965901,0.000015713007,0.0001262876,0.0001226225,0.00004695007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032078783,0.0008913743,0.0005161453,0.001973732,0.0007551976,0.0037224777,0.0015374369,0.0013386908,0.2429432],"category_scores_gemma":[0.0011682393,0.00043498032,0.0004850564,0.003690098,0.00028146568,0.004036881,0.0021327436,0.0009812593,0.28157336],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004084691,0.00004355722,0.00018385904,0.00018987217,0.0000080740365,0.000090578586,0.00015425874,0.00034350017,0.002135089,0.04286936,0.6001629,0.35377815],"study_design_scores_gemma":[0.000004073135,0.0000046256764,0.00011195964,0.0000364106,0.0000036143288,0.0001186309,0.00003666182,0.00036736229,0.00056900457,0.0033665535,0.995375,0.0000061167807],"about_ca_topic_score_codex":0.0039072,"about_ca_topic_score_gemma":0.005565582,"teacher_disagreement_score":0.2429432,"about_ca_system_score_codex":0.00080628257,"about_ca_system_score_gemma":0.0008204733,"threshold_uncertainty_score":0.81272596},"labels":[],"label_agreement":null},{"id":"W4256599980","doi":"10.32920/ryerson.14657100.v1","title":"The Rise of Uber and the [Re]construction of the North American Dream","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Narrative; Dream; Meaning (existential); Aesthetics; Sociology; History; Political science; Psychology; Epistemology; Art; Philosophy; Literature","score_opus":0.00562730752729227,"score_gpt":0.1994357040645466,"score_spread":0.19380839653725435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4256599980","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1384298,0.0043045734,0.0060295803,0.04687588,0.0010279635,0.000024426321,0.00006392642,0.00011199488,0.8031319],"genre_scores_gemma":[0.86028993,0.0019645493,0.0019410766,0.003197564,0.00009933777,0.000040915333,0.000037586717,0.00010217382,0.13232674],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9978569,0.0012775179,0.000029231005,0.000264481,0.00025099513,0.00032085046],"domain_scores_gemma":[0.99896836,0.00034756065,0.00006255074,0.00019990922,0.00018403736,0.00023767172],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033889152,0.00032787112,0.00030520893,0.00075436186,0.017135784,0.008278207,0.0007913954,0.0018132629,0.007848801],"category_scores_gemma":[0.0022054361,0.00024752747,0.00020402973,0.000988871,0.024817908,0.010640743,0.006042537,0.005218026,0.0008670928],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017250084,0.000017699489,0.00041015627,0.000030274958,0.0000019693557,0.00013351621,0.22144143,0.00006891019,0.00009970079,0.7502178,0.014992656,0.012568648],"study_design_scores_gemma":[0.0000039050396,0.000012728441,0.0008646393,0.00015431577,0.0000038314456,0.00016474584,0.262489,0.00028662424,0.00017035991,0.062074915,0.6737496,0.000025387579],"about_ca_topic_score_codex":0.060281932,"about_ca_topic_score_gemma":0.13904582,"teacher_disagreement_score":0.060281932,"about_ca_system_score_codex":0.0076411897,"about_ca_system_score_gemma":0.0047652572,"threshold_uncertainty_score":0.11986208},"labels":[],"label_agreement":null},{"id":"W4280650648","doi":"10.18280/jesa.550215","title":"Joint Scheduling of Charging and Service Operation of Electric Taxi Based on Reinforcement Learning","year":2022,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Xiamen University; Xiamen University of Technology","keywords":"Taxis; Scheduling (production processes); Reinforcement learning; Computer science; Charging station; Electricity; Grid; Computer network; Real-time computing; Electric vehicle; Automotive engineering; Transport engineering; Engineering; Power (physics); Electrical engineering; Operations management","score_opus":0.01676037080870544,"score_gpt":0.22555800407041593,"score_spread":0.2087976332617105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280650648","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14521584,0.0001942817,0.8493112,0.00018943183,0.00006516478,0.00011690306,0.000030685995,0.00064246,0.0042341566],"genre_scores_gemma":[0.98687184,0.00003644443,0.012224767,0.000024573143,0.000010799132,0.000046456833,0.000019691595,0.000007906656,0.0007575138],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996575,0.00006927038,0.000019002637,0.00009305842,0.0000753008,0.00008590867],"domain_scores_gemma":[0.9994338,0.0001931851,0.00010838387,0.000038058693,0.00014480368,0.00008176595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005803558,0.00050910626,0.0006661926,0.00023736083,0.00037245496,0.0004978001,0.0008041606,0.00043529953,0.0009917666],"category_scores_gemma":[0.0013567319,0.00021482956,0.00028866314,0.00021978316,0.00052094314,0.0004213752,0.00049788645,0.0005942443,0.00013730592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001265423,0.0001268418,0.0019586044,0.000033554556,0.000033427048,0.000077991375,0.00005637333,0.94727385,0.0036855808,0.0019611735,0.0005398123,0.044126313],"study_design_scores_gemma":[0.000010160377,0.000028656463,0.00016633852,0.0000011108011,0.000004480458,0.0000064154747,0.000003906978,0.9989974,0.00037481872,0.00032165123,0.000082169,0.0000029345222],"about_ca_topic_score_codex":0.010918887,"about_ca_topic_score_gemma":0.007086897,"teacher_disagreement_score":0.010918887,"about_ca_system_score_codex":0.0007233543,"about_ca_system_score_gemma":0.0014260175,"threshold_uncertainty_score":0.021710634},"labels":[],"label_agreement":null},{"id":"W4281250146","doi":"10.48550/arxiv.2205.09679","title":"Dynamic Pricing Provides Robust Equilibria in Stochastic Ridesharing Networks","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Air Force Office of Scientific Research; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Robustness (evolution); Flexibility (engineering); Computer science; Stochastic modelling; Mathematical optimization; Dynamic pricing; Stochastic process; Economics; Microeconomics; Mathematics","score_opus":0.04577244190526565,"score_gpt":0.17893478037452426,"score_spread":0.13316233846925862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281250146","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1784605,0.00014797697,0.81233317,0.00055129203,0.00003093214,0.00010201481,0.00018468655,0.00032060628,0.0078688525],"genre_scores_gemma":[0.9730102,0.00015103986,0.02445975,0.00007920207,0.000015491929,0.000091313035,0.000083005594,0.000064792956,0.0020451385],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985998,0.0005388112,0.00008807401,0.00030273266,0.00022686369,0.0002437002],"domain_scores_gemma":[0.9935628,0.004018089,0.000973612,0.00064910686,0.00046911297,0.00032723512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022847708,0.00096986606,0.0014083345,0.0007511725,0.00088178087,0.0020950513,0.0018785748,0.0017084351,0.003738653],"category_scores_gemma":[0.018345656,0.0006857547,0.001187664,0.00073335407,0.0020235395,0.0031412214,0.0029723395,0.001646599,0.00042258142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000114827424,0.000066657405,0.0010816461,0.00007273014,0.00007156139,0.00017808088,0.0001642327,0.7333729,0.0027220664,0.25204885,0.0008169089,0.009289543],"study_design_scores_gemma":[0.000021367227,0.000033011496,0.00014588307,0.000009026485,0.000012104705,0.000043194403,0.000034996978,0.8600473,0.00046332896,0.13872054,0.00045569896,0.000013501083],"about_ca_topic_score_codex":0.002987576,"about_ca_topic_score_gemma":0.0015203427,"teacher_disagreement_score":0.003738653,"about_ca_system_score_codex":0.0016335252,"about_ca_system_score_gemma":0.0012176249,"threshold_uncertainty_score":0.012507021},"labels":[],"label_agreement":null},{"id":"W4281396565","doi":"10.1155/2022/9693949","title":"A Slack Departure Strategy for Demand Responsive Transit Based on Bounded Rationality","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Beijing Municipal Natural Science Foundation; National Natural Science Foundation of China","keywords":"Incentive; Bounded rationality; Operations research; Profit (economics); Computer science; Operator (biology); Heuristic; Mathematical optimization; Economics; Microeconomics; Engineering; Mathematics; Artificial intelligence","score_opus":0.01634211478315035,"score_gpt":0.26855175480709376,"score_spread":0.2522096400239434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281396565","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22185016,0.00027627242,0.7587711,0.00059991307,0.00007277112,0.00020010714,0.000077645884,0.00019147128,0.017960494],"genre_scores_gemma":[0.97227883,0.00014927742,0.024758596,0.000057990892,0.000010731433,0.00008477445,0.000039005936,0.000020686915,0.002600112],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992613,0.00028271938,0.00003191556,0.00013434849,0.00013439298,0.00015535286],"domain_scores_gemma":[0.9992366,0.00034757558,0.00011964073,0.00003796057,0.0001350195,0.00012339452],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089608814,0.0009309053,0.0007600684,0.00046208443,0.00067631097,0.0012673277,0.0010354848,0.00075727055,0.0029782169],"category_scores_gemma":[0.0015937386,0.00031011872,0.00089826796,0.00039476127,0.00090885634,0.0013183872,0.0010698405,0.0009693635,0.00020823104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037389732,0.0002974418,0.0025823554,0.00023649582,0.000109492765,0.00074916333,0.00064874854,0.82133573,0.014140267,0.12608764,0.0021616756,0.0312772],"study_design_scores_gemma":[0.000026722864,0.0001253457,0.00023595791,0.000010035036,0.00002477736,0.000042857682,0.00011760203,0.98542374,0.0006127463,0.01280804,0.00055199186,0.00002016461],"about_ca_topic_score_codex":0.00585702,"about_ca_topic_score_gemma":0.0038369277,"teacher_disagreement_score":0.00585702,"about_ca_system_score_codex":0.001715792,"about_ca_system_score_gemma":0.0018109583,"threshold_uncertainty_score":0.012449026},"labels":[],"label_agreement":null},{"id":"W4281633910","doi":"10.1016/j.trd.2022.103353","title":"Exploring “automobility engagement”: A predictor of shared, automated, and electric mobility interest?","year":2022,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Sample (material); Electric cars; Marketing; Exploratory research; Identity (music); Business; Exploratory factor analysis; Consumer behaviour; Psychology; Sociology; Engineering; Social science","score_opus":0.14963041698455304,"score_gpt":0.296729389058101,"score_spread":0.14709897207354794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281633910","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976622,0.00005847962,0.00023878271,0.00012202947,0.0000017684629,0.0000126834375,0.00009591375,0.0000021554388,0.0018060122],"genre_scores_gemma":[0.99944836,0.000042621326,0.00014926142,0.00001614782,0.0000016736935,0.000009866531,0.000103009486,6.5955874e-7,0.00022842693],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994168,0.00015999321,0.000038042403,0.00007949857,0.0001554728,0.00015021318],"domain_scores_gemma":[0.9955258,0.0015780664,0.0014279359,0.00016815243,0.0007028651,0.00059711654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013789219,0.00019560511,0.00020959473,0.0011326424,0.0006973991,0.0014098999,0.00052905694,0.00063321204,0.0027955223],"category_scores_gemma":[0.0058263475,0.0001224112,0.00051170035,0.0017149878,0.0009042852,0.0010284367,0.0010668895,0.00061351515,0.00019620884],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025050995,0.000063545,0.99234843,0.0000259554,0.000035701614,0.00003784164,0.0023599565,0.000112475886,0.00018445842,0.00037341306,0.000105812775,0.0043275035],"study_design_scores_gemma":[0.0000031245306,0.000038706323,0.9898157,0.000022825996,0.000032302672,0.000034017317,0.008002102,0.0009112018,0.00014542675,0.00019535517,0.00079042563,0.000008811139],"about_ca_topic_score_codex":0.18512347,"about_ca_topic_score_gemma":0.24814896,"teacher_disagreement_score":0.18512347,"about_ca_system_score_codex":0.0018238235,"about_ca_system_score_gemma":0.0023744158,"threshold_uncertainty_score":0.36809188},"labels":[],"label_agreement":null},{"id":"W4281659465","doi":"10.3233/shti220126","title":"Use of Robots to Support Those Living with Dementia and Their Caregivers","year":2022,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Michael Smith Health Research BC; University of Victoria","funders":"Michael Smith Health Research BC","keywords":"Dementia; Robot; Health care; Assisted living; Robotics; Intersection (aeronautics); Assisted Living Facility; Independent living; Cognitive impairment; Psychology; Cognition; Medicine; Gerontology; Computer science; Artificial intelligence; Psychiatry; Engineering; Pathology; Political science","score_opus":0.04116877317295272,"score_gpt":0.2927583140577026,"score_spread":0.2515895408847499,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281659465","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.041212738,0.91225034,0.0030591558,0.008581787,0.0011772099,0.0008152421,0.00053386827,0.000049966784,0.032319654],"genre_scores_gemma":[0.25866547,0.7242311,0.009466477,0.0030334916,0.0002514722,0.0015226103,0.00043045852,0.00001982503,0.002379072],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99123305,0.005939436,0.0011291893,0.00032518417,0.0011377685,0.00023532273],"domain_scores_gemma":[0.98221856,0.013855146,0.0019029953,0.00032334833,0.0014682702,0.00023172949],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008050152,0.00053063245,0.0010331111,0.0033204106,0.0010456757,0.002855961,0.0010012148,0.0012505691,0.003431221],"category_scores_gemma":[0.030756429,0.00030137625,0.0019701247,0.0019890545,0.0010851723,0.0022509529,0.0019563707,0.000901817,0.00048381495],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035939566,0.00022818778,0.007210175,0.18832034,0.0015055059,0.0005682633,0.0077254213,0.000540873,0.00044137085,0.005612546,0.013220804,0.7742671],"study_design_scores_gemma":[0.00038601804,0.0014873374,0.025722029,0.5931081,0.004370932,0.002085766,0.021176506,0.0003160123,0.0014271769,0.0055657863,0.34422016,0.00013418181],"about_ca_topic_score_codex":0.0045920433,"about_ca_topic_score_gemma":0.009783413,"teacher_disagreement_score":0.008050152,"about_ca_system_score_codex":0.0019069258,"about_ca_system_score_gemma":0.0050264867,"threshold_uncertainty_score":0.04257381},"labels":[],"label_agreement":null},{"id":"W4281660006","doi":"10.1155/2022/1108272","title":"Modal Choice for the Driverless City: Scenario Simulation Based on a Stated Preference Survey","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"European Regional Development Fund; Ministerio de Ciencia e Innovación","keywords":"Discrete choice; Public transport; Mode choice; Revealed preference; Travel survey; Modal; Preference; Mode (computer interface); Mixed logit; Terrain; Travel behavior; Environmental economics; Choice modelling; Economics; Survey data collection; Transport engineering; Business; Public economics; Computer science; Microeconomics; Econometrics; Marketing; Logistic regression; Geography; Engineering","score_opus":0.043834723196604794,"score_gpt":0.28109897474340334,"score_spread":0.23726425154679853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281660006","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9925156,0.000023058888,0.0054411558,0.00009243482,0.000010023525,0.00009978512,0.00055796927,0.000024498819,0.0012353668],"genre_scores_gemma":[0.99390656,0.000036597958,0.0045568054,0.000022147393,0.0000040455634,0.00015607946,0.0005874568,0.000004073586,0.0007262249],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984963,0.0011084756,0.000038619,0.0001091781,0.00005556535,0.00019185657],"domain_scores_gemma":[0.9918532,0.006569135,0.00038634602,0.00032426344,0.00049374887,0.00037323454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026101177,0.0008167314,0.00071771815,0.0008424232,0.00050253334,0.0010407423,0.0015094142,0.0019278381,0.0054011433],"category_scores_gemma":[0.0045609195,0.0004213736,0.0018993331,0.0011225989,0.00052453484,0.0010002614,0.00084533356,0.0015355714,0.0004434194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007178654,0.0011197223,0.033009436,0.00010118926,0.00020598774,0.00044644708,0.000511604,0.9541566,0.00056796987,0.004994118,0.00057229947,0.0035967564],"study_design_scores_gemma":[0.000076696204,0.0003997632,0.0039128126,0.000007523167,0.000031875043,0.000023606923,0.0004903629,0.993848,0.00018847511,0.00076773966,0.00023121056,0.000021819407],"about_ca_topic_score_codex":0.03270127,"about_ca_topic_score_gemma":0.022268742,"teacher_disagreement_score":0.03270127,"about_ca_system_score_codex":0.0018392805,"about_ca_system_score_gemma":0.00088597456,"threshold_uncertainty_score":0.06502181},"labels":[],"label_agreement":null},{"id":"W4281714222","doi":"10.1177/03611981221093998","title":"Exploring Agent-Based Modelling for Car-Based Volunteer Driver Program Planning","year":2022,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"NetLogo; TRIPS architecture; Replicate; Service (business); Transport engineering; Agent-based model; Computer science; Sustainability; Engineering; Simulation; Operations research; Business; Marketing","score_opus":0.2920115648237464,"score_gpt":0.39340933234470943,"score_spread":0.10139776752096302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281714222","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20180497,0.00074671267,0.7650434,0.0014005423,0.00013270474,0.00045759187,0.0010876475,0.00077613286,0.028550327],"genre_scores_gemma":[0.8676931,0.00042630598,0.12469789,0.0001140426,0.000029589157,0.00043748066,0.0005093984,0.00010936537,0.005982775],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995433,0.00025286764,0.00002196618,0.00005656301,0.000059247406,0.00006620124],"domain_scores_gemma":[0.9980666,0.0014710331,0.00012151605,0.00005080967,0.00017814938,0.00011202764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010453161,0.0008346809,0.0009373967,0.00055152667,0.000753811,0.00217415,0.0015070058,0.0014129599,0.0035870092],"category_scores_gemma":[0.0032234262,0.00076536194,0.0010088524,0.0006275725,0.0006794465,0.0011409927,0.001332607,0.0011720619,0.00035421073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010384548,0.000015303289,0.00033044373,0.000012753214,0.000010784411,0.000018973677,0.00003201309,0.9961732,0.00005129576,0.0023512025,0.00009479269,0.0008988454],"study_design_scores_gemma":[0.00000446959,0.000004069185,0.00003898098,0.0000029849741,0.000002463359,0.0000017258644,0.0000151594695,0.99855775,0.000018603285,0.0010554115,0.0002961657,0.0000022110696],"about_ca_topic_score_codex":0.06450598,"about_ca_topic_score_gemma":0.054392,"teacher_disagreement_score":0.06450598,"about_ca_system_score_codex":0.0020328842,"about_ca_system_score_gemma":0.0024164566,"threshold_uncertainty_score":0.12826103},"labels":[],"label_agreement":null},{"id":"W4281775318","doi":"10.1155/2022/1052221","title":"Shared Clean Mobility Operations for First-Mile and Last-Mile Public Transit Connections: A Case Study of Doha, Qatar","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Qatar National Library","keywords":"Public transport; Transport engineering; Service (business); Last mile (transportation); Relocation; Component (thermodynamics); Transit (satellite); Paratransit; Computer science; Mile; Business; Engineering; Marketing","score_opus":0.020967714522790424,"score_gpt":0.2588717524613337,"score_spread":0.23790403793854328,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281775318","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9953962,0.00006645986,0.0017491591,0.00017634135,0.000008462028,0.000045242316,0.00019231091,0.000024065806,0.002341808],"genre_scores_gemma":[0.99698156,0.000074600204,0.0015321105,0.000022322123,0.00000444534,0.000026556458,0.00016727821,0.0000067676187,0.0011842801],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99957913,0.00015573147,0.000011841748,0.000056414574,0.00004016486,0.00015675362],"domain_scores_gemma":[0.99907863,0.0004752563,0.00010946683,0.000060321217,0.00011504455,0.00016132036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062642875,0.00064421433,0.00038855252,0.00063479756,0.001907466,0.0010776746,0.0012126133,0.0017670636,0.002813916],"category_scores_gemma":[0.0010891887,0.00028891533,0.0007555075,0.0009816927,0.00092354964,0.0010983993,0.00076462526,0.000891545,0.00025687538],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007968057,0.0029483093,0.14808384,0.00031940188,0.00028703752,0.03260026,0.0062328894,0.738814,0.005865164,0.032000124,0.008347976,0.02370421],"study_design_scores_gemma":[0.00021322646,0.00068832247,0.054998074,0.00006404192,0.0001804394,0.0015281066,0.019770365,0.9086738,0.0023663333,0.0036794792,0.007753619,0.00008413681],"about_ca_topic_score_codex":0.10266764,"about_ca_topic_score_gemma":0.12887408,"teacher_disagreement_score":0.10266764,"about_ca_system_score_codex":0.0030162742,"about_ca_system_score_gemma":0.0017271899,"threshold_uncertainty_score":0.20414007},"labels":[],"label_agreement":null},{"id":"W4281882079","doi":"10.1155/2022/1679469","title":"An Improved Adaptive Large Neighborhood Search Algorithm for the Heterogeneous Customized Bus Service with Multiple Pickup and Delivery Candidate Locations","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Pickup; Computer science; Service (business); Algorithm; Artificial intelligence","score_opus":0.008374631592161388,"score_gpt":0.22937010746232248,"score_spread":0.22099547587016108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281882079","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020500237,0.00042085143,0.973513,0.00017377415,0.00006271615,0.0000875295,0.00009814458,0.00046656255,0.0046772105],"genre_scores_gemma":[0.4433478,0.0003667148,0.5457935,0.00019288085,0.000060130442,0.0004105439,0.0007260338,0.00017490005,0.00892749],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995981,0.000099580524,0.000018901794,0.000107883236,0.00009108372,0.0000844805],"domain_scores_gemma":[0.9997774,0.00008121591,0.000027324124,0.000018868242,0.00006761787,0.00002771292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045856702,0.0008893802,0.0013155106,0.0006173006,0.0007082475,0.00067689194,0.0014395617,0.00093198713,0.003799939],"category_scores_gemma":[0.00093822327,0.00046068407,0.0008235858,0.0010033016,0.00031471538,0.0011387304,0.00093614054,0.0008511381,0.00057616597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013838458,0.00009170761,0.0005474214,0.00008726343,0.000044324494,0.00010634983,0.00007556061,0.8958237,0.0022043688,0.011332336,0.0055905576,0.08395807],"study_design_scores_gemma":[0.000013473475,0.000015819485,0.00003934251,0.0000021320552,0.000004606232,0.000013272496,0.000009904322,0.9981705,0.00017087556,0.00097247073,0.0005842851,0.0000033594213],"about_ca_topic_score_codex":0.018050276,"about_ca_topic_score_gemma":0.018656686,"teacher_disagreement_score":0.018050276,"about_ca_system_score_codex":0.0009489219,"about_ca_system_score_gemma":0.0018618965,"threshold_uncertainty_score":0.03589046},"labels":[],"label_agreement":null},{"id":"W4281966321","doi":"10.1007/978-3-031-18158-0_37","title":"Investigating End-User Acceptance of Last-Mile Delivery by Autonomous Vehicles in the United States","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"York University","keywords":"Mile; Perception; Last mile (transportation); Technology acceptance model; Computer science; Structural equation modeling; Partial least squares regression; Gauge (firearms); Applied psychology; Psychology; Human–computer interaction; Usability; Geography; Machine learning","score_opus":0.013898979775973062,"score_gpt":0.22083282500905188,"score_spread":0.2069338452330788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281966321","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986092,0.00003385741,0.00014811415,0.0000483033,0.0000020719933,0.000007699785,0.000021104624,0.0000031346196,0.001126641],"genre_scores_gemma":[0.9994209,0.00003840215,0.00012331716,0.000017650716,0.0000015630952,0.0000085196825,0.000030191764,0.0000011252176,0.00035853987],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99898404,0.00054047833,0.000044984976,0.000056809207,0.00029572277,0.00007795802],"domain_scores_gemma":[0.9915769,0.0047507524,0.0012923789,0.00018742781,0.0016994822,0.00049312244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019341625,0.00012510217,0.0001685579,0.00047957033,0.00027411003,0.0009115796,0.000306117,0.00028569,0.0018765973],"category_scores_gemma":[0.006487845,0.00007433112,0.0001757429,0.0003674648,0.00021417488,0.00049048156,0.0004403785,0.00038918792,0.000261895],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018667316,0.0003568036,0.9398055,0.0000917829,0.00004496464,0.0002330579,0.0148653565,0.00039493467,0.00203892,0.00025834853,0.0004541136,0.04126954],"study_design_scores_gemma":[0.000005256115,0.0008051196,0.9548541,0.000060461614,0.000022323296,0.000166803,0.038772527,0.0021290497,0.0008897875,0.000075923635,0.0022013327,0.000017415037],"about_ca_topic_score_codex":0.0058383197,"about_ca_topic_score_gemma":0.0058870907,"teacher_disagreement_score":0.0058383197,"about_ca_system_score_codex":0.00036664898,"about_ca_system_score_gemma":0.00027158723,"threshold_uncertainty_score":0.01160872},"labels":[],"label_agreement":null},{"id":"W4282036030","doi":"10.1155/2022/5300088","title":"The Car-Purchasing Intention of the Youth in the Context of Online Car-Hailing: The Extended Theory of Planned Behavior","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Purchasing; Business; Theory of planned behavior; Advertising; Context (archaeology); Marketing; Worry; Quality (philosophy); Public transport; Service (business); Service quality; Control (management); Psychology; Transport engineering; Engineering; Economics","score_opus":0.0176996380840903,"score_gpt":0.25624732686764334,"score_spread":0.23854768878355304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282036030","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9973719,0.0001074147,0.00096120505,0.0001662558,0.000012027519,0.00002678033,0.00005703631,0.0000050613385,0.001292335],"genre_scores_gemma":[0.99927646,0.00007253435,0.00032017942,0.000022387017,0.0000034623577,0.000016368122,0.000051215564,0.0000010006446,0.00023632134],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995436,0.0001841969,0.00003421478,0.00006482194,0.00007970803,0.000093433286],"domain_scores_gemma":[0.99862325,0.00048960076,0.0003487931,0.00005865308,0.0002229125,0.00025669823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009919108,0.00026314147,0.00028312518,0.00049412047,0.0004093838,0.0009307203,0.00022227963,0.00041611056,0.0014122919],"category_scores_gemma":[0.0027600704,0.00019064039,0.0008764317,0.00042569014,0.00037105137,0.0006151168,0.0004556359,0.0010144738,0.00012567596],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007036239,0.00057294243,0.9837933,0.00004403741,0.00009946581,0.00019443025,0.0039053552,0.00047499166,0.0003217527,0.0008601849,0.00020253536,0.009460586],"study_design_scores_gemma":[0.000010661545,0.00028051456,0.987298,0.000046551686,0.0001246364,0.00010667571,0.0038533458,0.0065409616,0.00020515762,0.0009968198,0.0005190758,0.000017637914],"about_ca_topic_score_codex":0.013832549,"about_ca_topic_score_gemma":0.014283289,"teacher_disagreement_score":0.013832549,"about_ca_system_score_codex":0.0006111882,"about_ca_system_score_gemma":0.00094167254,"threshold_uncertainty_score":0.027504027},"labels":[],"label_agreement":null},{"id":"W4282596060","doi":"10.1111/poms.13775","title":"Smart urban transport and logistics: A business analytics perspective","year":2022,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Key Research and Development Program of China; Ministry of Education - Singapore","keywords":"Perspective (graphical); Computer science; Big data; Analytics; Sustainability; Business analytics; Software; Process management; Data analysis; Data science; Engineering management; Business model; Knowledge management; Business; Business analysis; Marketing; Engineering; Artificial intelligence","score_opus":0.013141020658262543,"score_gpt":0.21764770124832222,"score_spread":0.2045066805900597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282596060","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033347882,0.19021323,0.36959338,0.18942907,0.0018847425,0.00022446201,0.0013295593,0.0006822486,0.21329549],"genre_scores_gemma":[0.5864854,0.2282446,0.15551329,0.009920138,0.0054580593,0.0002512592,0.0012686405,0.00016104284,0.012697552],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99788886,0.0009937566,0.000121112884,0.00019657963,0.000633299,0.0001664099],"domain_scores_gemma":[0.9956067,0.003193075,0.0002857864,0.00018738273,0.0004520851,0.00027499776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002910736,0.0011400525,0.0006436381,0.0077781444,0.0010370456,0.013226475,0.0012086096,0.0026309094,0.0024257542],"category_scores_gemma":[0.0034672506,0.00045408323,0.000583628,0.01064378,0.00437589,0.014606883,0.0024873232,0.0034714607,0.00068365806],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020208978,0.00008352561,0.0024502005,0.00068231876,0.000048220187,0.0002694232,0.0009558994,0.00580853,0.00044204938,0.90524083,0.0098944465,0.074104264],"study_design_scores_gemma":[0.000009233098,0.00005986504,0.0019861895,0.0014783284,0.000038701495,0.00044297703,0.0060977438,0.040292185,0.0013596056,0.663526,0.28464386,0.00006538665],"about_ca_topic_score_codex":0.003241089,"about_ca_topic_score_gemma":0.0024552133,"teacher_disagreement_score":0.013226475,"about_ca_system_score_codex":0.0032714724,"about_ca_system_score_gemma":0.0029619597,"threshold_uncertainty_score":0.023736298},"labels":[],"label_agreement":null},{"id":"W4282938567","doi":"10.1155/2022/1905526","title":"A Long-Term Shared Autonomous Vehicle System Design Problem considering Relocation and Pricing","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Relocation; Computer science; Mathematical optimization; Solver; Particle swarm optimization; Operations research; Optimization problem; Engineering; Mathematics","score_opus":0.014323622236480881,"score_gpt":0.2259328703512414,"score_spread":0.21160924811476053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282938567","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14175488,0.0012635421,0.8390235,0.0009703632,0.00018477297,0.00043621563,0.00062820205,0.00029498042,0.015443569],"genre_scores_gemma":[0.96113074,0.00031804954,0.031430647,0.00009203467,0.00004356009,0.00048014245,0.00030679133,0.000052746534,0.006145231],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99830097,0.0006108968,0.00006401658,0.00044085886,0.00023799362,0.0003452828],"domain_scores_gemma":[0.9976043,0.0013654851,0.0002939241,0.00007740756,0.00039033502,0.00026854745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021350118,0.0021785041,0.00266269,0.0009516303,0.0010646568,0.0029103083,0.0022821971,0.0033633215,0.005091435],"category_scores_gemma":[0.0032601478,0.001219198,0.0014336044,0.001284392,0.0014189848,0.0016100415,0.002096264,0.0018483925,0.00037440602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048470574,0.00002646502,0.00038128733,0.000074185766,0.000034165296,0.00019395849,0.000033926,0.9918429,0.00039775576,0.0032588877,0.0003260381,0.0033818916],"study_design_scores_gemma":[0.000018672225,0.000055732107,0.00012279734,0.0000050560297,0.000017470815,0.000022537377,0.000032989457,0.9974286,0.00009494691,0.0018929427,0.00030159077,0.0000067714086],"about_ca_topic_score_codex":0.014101066,"about_ca_topic_score_gemma":0.0084066745,"teacher_disagreement_score":0.014101066,"about_ca_system_score_codex":0.0021045853,"about_ca_system_score_gemma":0.002903866,"threshold_uncertainty_score":0.028037965},"labels":[],"label_agreement":null},{"id":"W4283450948","doi":"10.1155/2022/7418127","title":"Investigating Evaluation Indicators of Intelligent Vehicle Sharing Based on Operation Efficiency: A Case Study in Xiong’an New Area, China","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Public transport; Computer science; Transport engineering; Service (business); Index (typography); Mode (computer interface); Performance indicator; Intelligent transportation system; Level of service; Operations research; Environmental economics; Engineering; Business","score_opus":0.02761360171991384,"score_gpt":0.3009871227142969,"score_spread":0.27337352099438306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283450948","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986852,0.00002273224,0.0005585806,0.000028243932,0.0000016413527,0.000025049094,0.00004573399,0.000005602652,0.0006271478],"genre_scores_gemma":[0.998706,0.000046152538,0.00070608105,0.0000044120598,0.0000017424481,0.00001689898,0.00009155668,0.0000025564818,0.00042457323],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99909854,0.00026307977,0.00007612513,0.00013356784,0.00024266876,0.00018609181],"domain_scores_gemma":[0.9987721,0.00041773674,0.00023166201,0.00010714921,0.00034918328,0.00012213028],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013831102,0.00042507704,0.0003401152,0.001833381,0.00076849107,0.0009822779,0.0008570174,0.00047512006,0.00063960126],"category_scores_gemma":[0.0018418815,0.00021897012,0.00047103042,0.0027913142,0.0007012429,0.0011463588,0.0006161019,0.00034837634,0.00005900034],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003565671,0.0011487241,0.8184594,0.0003562938,0.00023659674,0.008711084,0.0087313475,0.080122784,0.009142197,0.0054099434,0.0017948531,0.06553026],"study_design_scores_gemma":[0.00003238462,0.0007413055,0.752401,0.000041953524,0.00014141326,0.0005288271,0.024527362,0.21228941,0.0053364914,0.0009596771,0.0029090832,0.000091117814],"about_ca_topic_score_codex":0.09378206,"about_ca_topic_score_gemma":0.09373946,"teacher_disagreement_score":0.09378206,"about_ca_system_score_codex":0.003552904,"about_ca_system_score_gemma":0.0015191929,"threshold_uncertainty_score":0.18647242},"labels":[],"label_agreement":null},{"id":"W4283822457","doi":"10.3390/su14138159","title":"A Decision Model for Free-Floating Car-Sharing Providers for Sustainable and Resilient Supply Chains","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"Natural Sciences and Engineering Research Council of Canada; Wilfrid Laurier University","keywords":"Resilience (materials science); Supply chain; Business; Investment (military); Industrial organization; Business model; Environmental economics; Operations management; Marketing; Engineering; Economics","score_opus":0.01062520142999109,"score_gpt":0.25344237004230386,"score_spread":0.24281716861231276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283822457","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.055735573,0.0006654726,0.9094537,0.0026596712,0.00024597504,0.00047591233,0.0013366156,0.0004368696,0.028990181],"genre_scores_gemma":[0.88912886,0.0007862672,0.07953595,0.00041068278,0.00013067487,0.0010501178,0.0008363627,0.00010483952,0.028016245],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863714,0.00041315646,0.00006256871,0.00034547123,0.00016456044,0.00037712936],"domain_scores_gemma":[0.9976179,0.0015113532,0.0002035571,0.000044797678,0.00038442796,0.0002378884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029099486,0.0014950316,0.0022904954,0.0012965025,0.0015798445,0.0043814234,0.002869822,0.0048409672,0.021574423],"category_scores_gemma":[0.0041629793,0.00120187,0.00197712,0.0012842623,0.0013138815,0.0027242792,0.0024986106,0.003653717,0.0016381221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007093458,0.0000556843,0.00045252457,0.000065085405,0.00002878471,0.0001715279,0.0000749247,0.9711934,0.0003981637,0.023261538,0.0009908037,0.003236752],"study_design_scores_gemma":[0.000014116421,0.00001766489,0.000060467093,0.000010013602,0.0000113724545,0.000010669605,0.00003641817,0.9951833,0.000050405004,0.0041418066,0.00045510734,0.000008666316],"about_ca_topic_score_codex":0.030147726,"about_ca_topic_score_gemma":0.019668592,"teacher_disagreement_score":0.030147726,"about_ca_system_score_codex":0.0045011267,"about_ca_system_score_gemma":0.00465505,"threshold_uncertainty_score":0.072173595},"labels":[],"label_agreement":null},{"id":"W4284960966","doi":"10.1016/j.scs.2022.104045","title":"Can shared micromobility programs reduce greenhouse gas emissions: Evidence from urban transportation big data","year":2022,"lang":"en","type":"article","venue":"Sustainable Cities and Society","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Greenhouse gas; Sustainability; Business; Environmental economics; Natural resource economics; Environmental planning; Environmental science; Economics","score_opus":0.04167017423537557,"score_gpt":0.2472012923825968,"score_spread":0.20553111814722125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4284960966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9063647,0.0068392796,0.0034939216,0.045017656,0.0008305066,0.00039103933,0.01794219,0.00030938565,0.018811338],"genre_scores_gemma":[0.9903923,0.0017665687,0.0009354247,0.0022838837,0.00022587174,0.00018217211,0.003363084,0.000023609437,0.00082719786],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9952632,0.0028938653,0.00016216889,0.0005115734,0.0005596585,0.0006095095],"domain_scores_gemma":[0.97166526,0.016530408,0.004472825,0.0028452598,0.0028748852,0.0016112863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056681074,0.0005907707,0.0005204796,0.001118784,0.00073255325,0.0015423533,0.0021292383,0.0014722267,0.0047799153],"category_scores_gemma":[0.030026017,0.00037044467,0.001495906,0.0026853574,0.0013852892,0.00362575,0.003077363,0.0018170893,0.000721634],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0082698455,0.005724431,0.59991413,0.0044445726,0.010073399,0.00023821038,0.0026812435,0.019422185,0.0008144631,0.014185276,0.06283906,0.27139324],"study_design_scores_gemma":[0.0041805753,0.003391979,0.8366624,0.0035914148,0.0086249625,0.0001313279,0.00814492,0.01633884,0.003462913,0.037912186,0.077346526,0.0002119716],"about_ca_topic_score_codex":0.053946447,"about_ca_topic_score_gemma":0.053294543,"teacher_disagreement_score":0.053946447,"about_ca_system_score_codex":0.0013811061,"about_ca_system_score_gemma":0.00374036,"threshold_uncertainty_score":0.10726488},"labels":[],"label_agreement":null},{"id":"W4285044155","doi":"10.22215/etd/2022-15052","title":"Planned Inefficiency: Defining and Defending the Public Realm in the Age of Autonomous Vehicles","year":2022,"lang":"en","type":"dissertation","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Realm; Architecture; Inefficiency; Monetization; Corporate governance; Public space; Democracy; Political science; Public relations; Public administration; Engineering; Business; Architectural engineering; Law; Geography; Politics; Economics","score_opus":0.016517099762241437,"score_gpt":0.24535605380716888,"score_spread":0.22883895404492743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285044155","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.087076426,0.013071296,0.05439253,0.06369199,0.00082554255,0.000095094016,0.000060082788,0.00007924071,0.78070784],"genre_scores_gemma":[0.95493734,0.004945209,0.0046913577,0.0024254182,0.00022919397,0.00008957271,0.00003430081,0.0000761608,0.032571446],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979761,0.0011633389,0.000043053187,0.00022853463,0.00026920537,0.00031976064],"domain_scores_gemma":[0.9980634,0.0010092115,0.00017352912,0.00023503981,0.00028482298,0.00023411233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004432902,0.00038522022,0.00022597605,0.0011379084,0.00583225,0.012355369,0.0011112341,0.0033008044,0.0034011041],"category_scores_gemma":[0.0039902725,0.00023918826,0.0003048963,0.0009084975,0.043043744,0.012857028,0.0059854086,0.004493697,0.0005832098],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000042340084,0.0000049143,0.00016620908,0.000012264403,9.809291e-7,0.00002854468,0.010685515,0.00021823865,0.00002877418,0.98276746,0.0014450436,0.004637795],"study_design_scores_gemma":[0.000007139086,0.000025833491,0.00058598927,0.0002453353,0.0000062328045,0.00008162977,0.027308986,0.00082413823,0.00026965907,0.71857715,0.2520513,0.000016523803],"about_ca_topic_score_codex":0.0072225505,"about_ca_topic_score_gemma":0.010825396,"teacher_disagreement_score":0.012355369,"about_ca_system_score_codex":0.009398418,"about_ca_system_score_gemma":0.008536595,"threshold_uncertainty_score":0.068190575},"labels":[],"label_agreement":null},{"id":"W4285081856","doi":"10.1016/j.cor.2022.105933","title":"The dial-a-ride problem with private fleet and common carrier","year":2022,"lang":"en","type":"article","venue":"Computers & Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo; Compute Canada","keywords":"Computer science; Key (lock); Mathematical optimization; Metaheuristic; Taxis; Vehicle routing problem; Service provider; Service (business); Genetic algorithm; Outsourcing; Operations research; Routing (electronic design automation); Algorithm; Computer network; Transport engineering; Mathematics","score_opus":0.025853680611030033,"score_gpt":0.2956066425456766,"score_spread":0.26975296193464654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285081856","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43455985,0.00486111,0.24344586,0.064665124,0.00080651126,0.00045272103,0.003651952,0.00054906367,0.24700777],"genre_scores_gemma":[0.9058603,0.0020194217,0.021045364,0.0012351113,0.00046459518,0.00014410727,0.0006337024,0.00019047866,0.068406925],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975331,0.00091833126,0.00011302752,0.0005226666,0.0002461972,0.0006667356],"domain_scores_gemma":[0.98463213,0.011204019,0.0009218459,0.001117512,0.0006867709,0.0014376972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036277266,0.00097392825,0.0043925927,0.0016076441,0.0045982352,0.006445039,0.0045081167,0.013117377,0.03776745],"category_scores_gemma":[0.026215449,0.0016273778,0.0019765734,0.0037766781,0.004917986,0.017166803,0.0048265024,0.0060027307,0.0016145725],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003752011,0.00025017606,0.0017266922,0.00024775995,0.00010797747,0.0012232539,0.0006359213,0.07260137,0.00019820927,0.8583237,0.046958826,0.017350893],"study_design_scores_gemma":[0.00022027982,0.000062545965,0.0004957693,0.00006636018,0.00005958078,0.0005812779,0.0010375921,0.11280882,0.00018857497,0.87400454,0.0104082,0.000066481494],"about_ca_topic_score_codex":0.0243433,"about_ca_topic_score_gemma":0.014493168,"teacher_disagreement_score":0.03776745,"about_ca_system_score_codex":0.0024301382,"about_ca_system_score_gemma":0.002350446,"threshold_uncertainty_score":0.12634468},"labels":[],"label_agreement":null},{"id":"W4285202605","doi":"10.7202/1088298ar","title":"Développement et architecture d’une application web pour localiser les entreprises près de vous selon le mode de transport : le géolocalisateur d’entreprises de Lanaudière","year":2022,"lang":"fr","type":"article","venue":"Canadian Journal of Regional Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Architecture; Mode (computer interface); Business; Computer science; World Wide Web; Engineering; Transport engineering; Human–computer interaction; Art; Visual arts","score_opus":0.017181718318053884,"score_gpt":0.25269418817632994,"score_spread":0.23551246985827606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285202605","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07907743,0.00076393795,0.8891038,0.00088244834,0.000106311854,0.00057883,0.00029509785,0.009016735,0.020175418],"genre_scores_gemma":[0.30452117,0.0010744823,0.6510488,0.00027211587,0.000037536698,0.00049827504,0.00096031144,0.00096860237,0.04061871],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99910563,0.00022936348,0.000052061587,0.00016882471,0.00034213864,0.000101974416],"domain_scores_gemma":[0.9987696,0.00026747194,0.000049966744,0.00023007115,0.00058324554,0.00009950444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013747422,0.00061953836,0.00039671396,0.00087488187,0.0011960679,0.0033858775,0.0011627355,0.001346286,0.0032327534],"category_scores_gemma":[0.0019895136,0.00059551204,0.00087606016,0.00082723727,0.0007297679,0.001825088,0.0015167356,0.0012661611,0.001838653],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004439635,0.00059360295,0.015435644,0.0015008161,0.00019779264,0.0026478728,0.0074473596,0.062930375,0.19999234,0.045859654,0.016218998,0.6467316],"study_design_scores_gemma":[0.00014258639,0.000490999,0.014507081,0.00035002182,0.00026661673,0.0017690021,0.002837196,0.46809056,0.18201785,0.012871324,0.31644654,0.00021021016],"about_ca_topic_score_codex":0.038204864,"about_ca_topic_score_gemma":0.035394967,"teacher_disagreement_score":0.038204864,"about_ca_system_score_codex":0.0012037805,"about_ca_system_score_gemma":0.0037505697,"threshold_uncertainty_score":0.07596493},"labels":[],"label_agreement":null},{"id":"W4285252157","doi":"10.5267/j.ijiec.2022.3.002","title":"Nash-stackelberg game perspective on pricing strategies for ride-hailing and aggregation platforms under bundle mode","year":2022,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Stackelberg competition; Bundle; Pricing strategies; Nash equilibrium; Service (business); Key (lock); Popularity; Business; Computer science; Microeconomics; Industrial organization; Marketing; Economics; Computer security","score_opus":0.029391190782041377,"score_gpt":0.28313311123009316,"score_spread":0.25374192044805177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285252157","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1878696,0.00063293515,0.7637915,0.0013665102,0.00015151306,0.00020624904,0.00020008937,0.00011277968,0.045668922],"genre_scores_gemma":[0.977801,0.0003681503,0.014531287,0.00007169411,0.000047075937,0.00008651425,0.000039123915,0.000016338885,0.007038804],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989485,0.00044728402,0.000028102831,0.00017076184,0.00017363664,0.00023174933],"domain_scores_gemma":[0.9990096,0.0004588968,0.00018408938,0.000051410472,0.00017865677,0.00011731948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012363301,0.0011084619,0.0008761378,0.00083052454,0.0010334353,0.0022162,0.0016235776,0.0016273329,0.006916574],"category_scores_gemma":[0.0040082447,0.00041795996,0.0012183993,0.0007191138,0.0015145636,0.0044647222,0.0011031448,0.0014859205,0.0004310374],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010940091,0.00008658353,0.0023226454,0.00009327922,0.000055196422,0.00065849087,0.0004185102,0.37911648,0.0025514574,0.60192645,0.0021840823,0.010477323],"study_design_scores_gemma":[0.000018089559,0.00007477705,0.00067744945,0.000014101387,0.000028124761,0.0001302627,0.00026253707,0.864574,0.00030116676,0.13252813,0.0013567299,0.000034509827],"about_ca_topic_score_codex":0.0065139737,"about_ca_topic_score_gemma":0.0037678457,"teacher_disagreement_score":0.006916574,"about_ca_system_score_codex":0.00193867,"about_ca_system_score_gemma":0.0011284712,"threshold_uncertainty_score":0.023138285},"labels":[],"label_agreement":null},{"id":"W4285286727","doi":"10.1007/978-3-031-09593-1_8","title":"Toward a Trip Planner Adapted to Older Adults Context: Mobilaînés Project","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Planner; Computer science; Socialization; Context (archaeology); Public transport; Human–computer interaction; Transport engineering; Artificial intelligence; Psychology; Engineering; Social psychology","score_opus":0.02146200136001295,"score_gpt":0.24099766287103624,"score_spread":0.2195356615110233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285286727","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1889319,0.0011942014,0.6699666,0.0020641193,0.0007381054,0.0028194473,0.0034965759,0.0618505,0.06893864],"genre_scores_gemma":[0.21412455,0.0010315157,0.68330926,0.0005243694,0.00009434118,0.001780709,0.00818057,0.0052435715,0.0857111],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999603,0.00013646542,0.000025291998,0.000076428485,0.00011973472,0.000039149225],"domain_scores_gemma":[0.9993807,0.00016246039,0.000025353263,0.000082801474,0.0001528783,0.00019581013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011478493,0.0006129716,0.0002590651,0.0005542939,0.00038051812,0.0012178319,0.0010641798,0.00087555987,0.0103170015],"category_scores_gemma":[0.0018945147,0.0003197561,0.00038006966,0.00030110453,0.00031147047,0.0014484022,0.0025536765,0.0010022531,0.0041527483],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000742227,0.0022560782,0.0076836315,0.0010882482,0.00009777907,0.002118397,0.008533485,0.013535447,0.059245493,0.024855321,0.1479718,0.7318721],"study_design_scores_gemma":[0.00033099065,0.001250468,0.0055675395,0.0005044536,0.00012817515,0.0018124816,0.0029032647,0.09820101,0.02840938,0.0101304725,0.8506407,0.000120978955],"about_ca_topic_score_codex":0.0017630871,"about_ca_topic_score_gemma":0.001721459,"teacher_disagreement_score":0.0103170015,"about_ca_system_score_codex":0.00033696726,"about_ca_system_score_gemma":0.0009580344,"threshold_uncertainty_score":0.03451377},"labels":[],"label_agreement":null},{"id":"W4285531520","doi":"10.2139/ssrn.4095275","title":"Driving Ambitions: The Implications of Decarbonizing the Transportation Sector by 2030","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ontario Museum; Queen's University; University of Toronto; University of Calgary","funders":"","keywords":"Business; Transport engineering; Environmental planning; Natural resource economics; Economics; Engineering; Environmental science","score_opus":0.007246154791743008,"score_gpt":0.21370592214648956,"score_spread":0.20645976735474655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285531520","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4298089,0.006968118,0.0032366447,0.1978429,0.003214228,0.000087181375,0.006636361,0.00017978546,0.35202596],"genre_scores_gemma":[0.9808503,0.0031688134,0.0005128246,0.0050294455,0.00024788696,0.000035877234,0.0008384612,0.000025034025,0.009291326],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99909747,0.00016137757,0.000021712256,0.00006628034,0.00015740418,0.00049579825],"domain_scores_gemma":[0.9990081,0.00012024461,0.00015255077,0.000021812753,0.000327884,0.0003694439],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087303563,0.00040398032,0.00021045179,0.000621296,0.0011018777,0.0048754085,0.0006323689,0.0020397245,0.011783655],"category_scores_gemma":[0.0025482338,0.00011775874,0.000624938,0.001313979,0.0009939257,0.0023746386,0.0020825537,0.0025555075,0.001052896],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000785065,0.00052112644,0.06153882,0.00074782874,0.0001641268,0.0015954517,0.0032947802,0.020654315,0.0027740595,0.639903,0.14996357,0.11805787],"study_design_scores_gemma":[0.00009635265,0.0005714771,0.1846938,0.0012981131,0.0001812191,0.00045577902,0.04909171,0.016278518,0.0020657016,0.23814616,0.50692666,0.00019451746],"about_ca_topic_score_codex":0.046929426,"about_ca_topic_score_gemma":0.07415461,"teacher_disagreement_score":0.046929426,"about_ca_system_score_codex":0.0039049736,"about_ca_system_score_gemma":0.0058364156,"threshold_uncertainty_score":0.0933125},"labels":[],"label_agreement":null},{"id":"W4285784781","doi":"10.1016/j.trpro.2024.12.233","title":"Inclusion persons with disabilities to a public transport system: An integrative decision-aiding approach","year":2025,"lang":"en","type":"article","venue":"Transportation research procedia","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Université Polytechnique Hauts-de-France","keywords":"Inclusion (mineral); Public transport; Psychology; Decision system; Applied psychology; Gerontology; Medicine; Transport engineering; Engineering; Operations research; Social psychology","score_opus":0.04660411831827204,"score_gpt":0.34289699638023396,"score_spread":0.2962928780619619,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285784781","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06901965,0.0032497854,0.7710693,0.016213508,0.00036250328,0.0008483897,0.00019066573,0.0001775108,0.1388687],"genre_scores_gemma":[0.7160114,0.0032455134,0.27437887,0.00055325974,0.00016995611,0.0006325949,0.00015093335,0.00004272621,0.0048148376],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9904841,0.006606155,0.00043451812,0.00064891484,0.0011401994,0.00068608066],"domain_scores_gemma":[0.99167913,0.0061116433,0.00046979313,0.00025681115,0.0008789774,0.00060369703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01196957,0.0020010264,0.0014528641,0.0055138087,0.0045565697,0.01695083,0.004203763,0.0036786995,0.004502332],"category_scores_gemma":[0.009256794,0.000793396,0.0018929671,0.004203078,0.0092014065,0.009632628,0.011076886,0.004307614,0.00046104516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037974263,0.00028140622,0.001830722,0.0005593125,0.000103758706,0.0008143799,0.012187889,0.04895742,0.00060009566,0.88646173,0.0016231397,0.046542164],"study_design_scores_gemma":[0.00003114594,0.00016385586,0.0010104638,0.0013116102,0.00015599058,0.00025754186,0.036940914,0.12552893,0.0009902632,0.7794508,0.0540551,0.000103453225],"about_ca_topic_score_codex":0.0053267553,"about_ca_topic_score_gemma":0.0068322914,"teacher_disagreement_score":0.01695083,"about_ca_system_score_codex":0.009554371,"about_ca_system_score_gemma":0.012264214,"threshold_uncertainty_score":0.06932217},"labels":[],"label_agreement":null},{"id":"W4285802675","doi":"10.1155/2022/7293909","title":"Impact of New Mobility Solutions on Travel Behaviour and Its Incorporation into Travel Demand Models","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Personal mobility; Context (archaeology); Transport engineering; Electrification; Computer science; Travel behavior; Investment (military); Software deployment; Operations research; Risk analysis (engineering); Business; Engineering; Telecommunications","score_opus":0.024763317037698778,"score_gpt":0.2723380753077266,"score_spread":0.2475747582700278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285802675","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40119788,0.2256374,0.16835347,0.011907794,0.001165248,0.000707817,0.016170012,0.00037627685,0.17448409],"genre_scores_gemma":[0.8606697,0.10526119,0.020805692,0.00055672356,0.00013637646,0.00038698135,0.0040243366,0.000102275284,0.008056736],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986625,0.0006832788,0.00008789728,0.00014616913,0.00032310712,0.00009716306],"domain_scores_gemma":[0.9976737,0.0015576798,0.00018800613,0.000085487365,0.0004546181,0.00004048112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015386268,0.0006888883,0.00053047616,0.0015999653,0.0002590419,0.0023993638,0.0009889242,0.0009449966,0.0035156705],"category_scores_gemma":[0.0043186187,0.0003818115,0.0015946849,0.0027871986,0.00039469395,0.0018852968,0.0010586663,0.0010124886,0.0007485118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031589333,0.00033474673,0.059169803,0.017427446,0.0014254183,0.00075934234,0.0042791246,0.4045769,0.0027667736,0.18446179,0.018618207,0.30586457],"study_design_scores_gemma":[0.00004465701,0.0005854709,0.0721773,0.009833893,0.0016923642,0.000655315,0.009105105,0.44688714,0.0032227878,0.06603879,0.3893793,0.00037781993],"about_ca_topic_score_codex":0.020535128,"about_ca_topic_score_gemma":0.020512264,"teacher_disagreement_score":0.020535128,"about_ca_system_score_codex":0.0024844501,"about_ca_system_score_gemma":0.0014315745,"threshold_uncertainty_score":0.04083121},"labels":[],"label_agreement":null},{"id":"W4285819854","doi":"10.1109/tvt.2022.3191490","title":"Dual Dynamic Programming for the Mean Standard Deviation Canadian Traveller Problem","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Agency for Science, Technology and Research","keywords":"Standard deviation; Computer science; Benchmark (surveying); Linear programming; Dynamic programming; Mathematics; Mathematical optimization; Statistics; Algorithm","score_opus":0.007403918407990373,"score_gpt":0.21347775847024203,"score_spread":0.20607384006225166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285819854","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021836085,0.00085816596,0.9601587,0.0015158954,0.00018445567,0.00013780604,0.00045158967,0.00020294481,0.014654457],"genre_scores_gemma":[0.6700927,0.001569858,0.29121783,0.00078937825,0.00026392908,0.0006408405,0.0010702169,0.0003651646,0.03399007],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998681,0.0005019018,0.000036717203,0.0002663626,0.00024964675,0.000264377],"domain_scores_gemma":[0.9975503,0.0016065992,0.00018122223,0.00007107317,0.0003651003,0.00022571869],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002343218,0.0016127601,0.0017815289,0.0011312659,0.00091268984,0.0022542838,0.0020267998,0.0019863585,0.007824028],"category_scores_gemma":[0.0068584657,0.00072584534,0.001034757,0.0013555308,0.001676873,0.0018834333,0.0018715122,0.0032334756,0.0004937899],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013483301,0.00006990777,0.0005237433,0.00014007812,0.000051322535,0.000098262295,0.00008149711,0.85436124,0.00032827962,0.12128519,0.0057340334,0.017191555],"study_design_scores_gemma":[0.000019528627,0.000021761629,0.00008643536,0.0000113396145,0.000008055336,0.000016835178,0.000021649144,0.96474475,0.000113794325,0.033505443,0.0014379184,0.0000125165225],"about_ca_topic_score_codex":0.04062813,"about_ca_topic_score_gemma":0.028756293,"teacher_disagreement_score":0.04062813,"about_ca_system_score_codex":0.0050265985,"about_ca_system_score_gemma":0.0070686503,"threshold_uncertainty_score":0.08078331},"labels":[],"label_agreement":null},{"id":"W4286492688","doi":"10.1155/2022/1005979","title":"Assessing the Potential of the Strategic Formation of Urban Platoons for Shared Automated Vehicle Fleets","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Platoon; Transport engineering; TRIPS architecture; Energy consumption; Computer science; Automotive engineering; Engineering; Control (management)","score_opus":0.017134792006240233,"score_gpt":0.2676368795408601,"score_spread":0.25050208753461983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286492688","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9867056,0.000080330734,0.011025934,0.00006842365,0.000008950339,0.00003592414,0.00008252932,0.000026618227,0.0019657633],"genre_scores_gemma":[0.9986632,0.000024227136,0.0011567543,0.000002679584,0.0000012583209,0.000007824192,0.000032917967,0.0000022539346,0.00010885978],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995264,0.0002128103,0.000014572445,0.000050111063,0.000088334404,0.00010783466],"domain_scores_gemma":[0.99573994,0.0030725985,0.0004002779,0.0002606964,0.00029479648,0.00023167036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010908336,0.0005211994,0.00027333832,0.0004366119,0.0003372578,0.00070170284,0.00057174166,0.00059466047,0.000914],"category_scores_gemma":[0.00527537,0.00027803308,0.0004661759,0.00043645527,0.00051898963,0.0014762664,0.0009943898,0.00046478177,0.000070485854],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007824943,0.00003767084,0.006002643,0.000020783886,0.000018615103,0.00004690077,0.000022367542,0.9898962,0.00059263845,0.0010865154,0.000044973713,0.002152505],"study_design_scores_gemma":[0.0000099280405,0.00028373196,0.0026125803,0.00000371005,0.00001542398,0.000019291672,0.000099118304,0.9952676,0.00072965963,0.00078836497,0.00016176722,0.000008793659],"about_ca_topic_score_codex":0.01191948,"about_ca_topic_score_gemma":0.008814737,"teacher_disagreement_score":0.01191948,"about_ca_system_score_codex":0.0009910233,"about_ca_system_score_gemma":0.0007764199,"threshold_uncertainty_score":0.023700178},"labels":[],"label_agreement":null},{"id":"W4286744221","doi":"10.2139/ssrn.4168512","title":"An Sp-Off-Rp Survey to Understand the Impacts of Autonomous Vehicles on Travel Mode Choices","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hudbay Minerals (Canada); University of Toronto; Carleton University","funders":"","keywords":"Mode choice; Mode (computer interface); Transport engineering; Business; Computer science; Geography; Engineering; Human–computer interaction; Public transport","score_opus":0.01658400570110702,"score_gpt":0.262689235514247,"score_spread":0.24610522981313998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286744221","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99131525,0.000041348165,0.00044749214,0.00012747689,0.0000075880334,0.00006176212,0.0035580178,0.000009854929,0.0044312184],"genre_scores_gemma":[0.9898421,0.00012881341,0.0008160381,0.0001903886,0.000009447772,0.00021479707,0.004388263,0.000011335304,0.004398706],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993463,0.00029298247,0.00003075384,0.000064675914,0.00012304916,0.00014224475],"domain_scores_gemma":[0.9975089,0.00063905737,0.00055384793,0.0001714818,0.00067497033,0.0004516893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087171694,0.0001741037,0.00017141817,0.0009075172,0.00050603,0.0005360186,0.0003761196,0.00051039265,0.0046826913],"category_scores_gemma":[0.0027940392,0.00019549063,0.00031276248,0.0018393367,0.00017816476,0.00091663067,0.00084108167,0.00089944556,0.0018459177],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002057938,0.0007040766,0.968825,0.000093816685,0.000051151434,0.00015168554,0.0027338138,0.0005288716,0.00075248105,0.0004886188,0.00452257,0.020942064],"study_design_scores_gemma":[0.000004952437,0.0003543187,0.98670226,0.00001879171,0.000010562629,0.00006798366,0.006861325,0.0007277709,0.00012084311,0.00010694821,0.0050168443,0.0000073441324],"about_ca_topic_score_codex":0.032418728,"about_ca_topic_score_gemma":0.047219764,"teacher_disagreement_score":0.032418728,"about_ca_system_score_codex":0.0004553235,"about_ca_system_score_gemma":0.0010927604,"threshold_uncertainty_score":0.06446004},"labels":[],"label_agreement":null},{"id":"W4287266431","doi":"10.48550/arxiv.2103.09951","title":"Demand for shared mobility to replace private mobility using connected\\n and automated vehicles","year":2021,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Downtown; Transport engineering; Traffic congestion; Duration (music); Mode (computer interface); Process (computing); Computer science; Engineering; Geography","score_opus":0.07034482937638467,"score_gpt":0.2180217469991957,"score_spread":0.14767691762281102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287266431","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9890771,0.00004187975,0.006626153,0.00015548467,0.000022856084,0.00002282032,0.00017422193,0.00012252177,0.0037569348],"genre_scores_gemma":[0.99852186,0.000011514652,0.0008430111,0.000008470969,0.0000025144711,0.0000063610087,0.000078759535,0.00000477563,0.00052274135],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997454,0.00006301094,0.000009170316,0.0000621539,0.000061336,0.000058792844],"domain_scores_gemma":[0.9994444,0.00019545115,0.00011331496,0.00008525382,0.00010095449,0.000060633116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034184943,0.0003059947,0.00022569355,0.00023553745,0.00025517814,0.0005335059,0.00067502464,0.00032318558,0.003913987],"category_scores_gemma":[0.0016146471,0.000109498564,0.00027590262,0.00045271704,0.00031393144,0.000860245,0.00061589817,0.00023434218,0.0002740016],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001227597,0.0006506469,0.11261681,0.00025995143,0.00019183756,0.0007055166,0.00043033157,0.6934512,0.034948688,0.011734022,0.0059720958,0.13781127],"study_design_scores_gemma":[0.000084026826,0.00073482376,0.051696457,0.000021739546,0.0000918112,0.00019908001,0.00089106074,0.9277925,0.008873605,0.0032527028,0.0063271206,0.000035074587],"about_ca_topic_score_codex":0.015890038,"about_ca_topic_score_gemma":0.0259591,"teacher_disagreement_score":0.015890038,"about_ca_system_score_codex":0.0011535034,"about_ca_system_score_gemma":0.0006279052,"threshold_uncertainty_score":0.03159511},"labels":[],"label_agreement":null},{"id":"W4287334168","doi":"","title":"Stochastic Modelling of Free-Floating Car-Sharing Systems","year":2021,"lang":"en","type":"preprint","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Car sharing; Engineering; Transport engineering","score_opus":0.02189052396592245,"score_gpt":0.22272032732927066,"score_spread":0.2008298033633482,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287334168","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1888014,0.00058497436,0.7903541,0.0009689873,0.00012405824,0.00013269659,0.0009832113,0.00039246757,0.01765811],"genre_scores_gemma":[0.978207,0.0003855792,0.007952143,0.00006595362,0.000055846842,0.00011463782,0.0002909586,0.00004828557,0.012879561],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991277,0.00024611995,0.00004012743,0.00016810448,0.00020469996,0.0002132399],"domain_scores_gemma":[0.9981931,0.0009053954,0.0003796643,0.00007921427,0.0002731372,0.00016949611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009855584,0.0009979915,0.00095911435,0.00084882905,0.0006069992,0.0017756501,0.0017684055,0.00141799,0.0032456594],"category_scores_gemma":[0.0032543298,0.0004576683,0.0009864584,0.0007479638,0.0012619356,0.0013904592,0.000990901,0.0011146733,0.00035701387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022346421,0.000020562962,0.00065181626,0.000025679252,0.000021052647,0.00011876944,0.00007520306,0.9298384,0.000851839,0.066687174,0.00045437567,0.0012327358],"study_design_scores_gemma":[0.000003243947,0.0000074036475,0.00013638141,0.0000023699388,0.0000035018409,0.000009549177,0.000012836325,0.9928899,0.00004785169,0.006646154,0.0002350877,0.0000058469395],"about_ca_topic_score_codex":0.029601064,"about_ca_topic_score_gemma":0.011900312,"teacher_disagreement_score":0.029601064,"about_ca_system_score_codex":0.0019809287,"about_ca_system_score_gemma":0.001155187,"threshold_uncertainty_score":0.05885756},"labels":[],"label_agreement":null},{"id":"W4287631640","doi":"","title":"The location and routing models applicable to the transport of persons with disabilities","year":2020,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Routing (electronic design automation); Computer network","score_opus":0.01815350234226587,"score_gpt":0.2108352201004417,"score_spread":0.19268171775817583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287631640","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.121634714,0.001851171,0.8455686,0.0049713217,0.0005133777,0.00017856779,0.0029401472,0.00040294617,0.021939144],"genre_scores_gemma":[0.90550965,0.0030959032,0.04166754,0.00031830982,0.00036547618,0.00031288335,0.0015902837,0.0001623863,0.046977554],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994863,0.00018569647,0.000023925339,0.00012372222,0.000069776834,0.00011048837],"domain_scores_gemma":[0.99879223,0.00062105124,0.00016896403,0.000062360625,0.00027237795,0.000083063926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010216736,0.0009952248,0.0012744841,0.0009399564,0.00084595976,0.001976424,0.0020440037,0.0024558848,0.0041791275],"category_scores_gemma":[0.00576324,0.00076284294,0.0016552623,0.001869203,0.0008256009,0.0018416308,0.0013109142,0.0017458053,0.00091066275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011676259,0.000009136613,0.0004343597,0.000013939832,0.000007750808,0.000077794044,0.000028369348,0.9860621,0.00008126717,0.009818178,0.0008283452,0.002626997],"study_design_scores_gemma":[0.000004393165,0.00000692758,0.00018570568,0.000008722883,0.000010141772,0.000026410426,0.00003450714,0.99362624,0.000036115885,0.005436237,0.0006163134,0.000008339721],"about_ca_topic_score_codex":0.10950576,"about_ca_topic_score_gemma":0.044527978,"teacher_disagreement_score":0.10950576,"about_ca_system_score_codex":0.0024730042,"about_ca_system_score_gemma":0.0025922735,"threshold_uncertainty_score":0.21773678},"labels":[],"label_agreement":null},{"id":"W4287639741","doi":"10.1287/mnsc.2023.4925","title":"Privacy-Preserving Personalized Revenue Management","year":2023,"lang":"en","type":"article","venue":"Management Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Agence Nationale de la Recherche","keywords":"Revenue; Differential privacy; Revenue management; Computer science; Set (abstract data type); Categorical variable; Agency (philosophy); Operations research; Business; Data mining; Finance; Mathematics; Machine learning","score_opus":0.018824277413542874,"score_gpt":0.2579498909950312,"score_spread":0.23912561358148832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287639741","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.073131084,0.00054015755,0.9184725,0.0013892154,0.000066960245,0.00016515702,0.00048123638,0.0006681643,0.005085512],"genre_scores_gemma":[0.9079611,0.000333809,0.08851899,0.00026855568,0.00009381648,0.00009168991,0.00035857435,0.00012362795,0.0022498153],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9925581,0.0030841783,0.00035888806,0.0017013326,0.0014658197,0.00083172973],"domain_scores_gemma":[0.982199,0.008803224,0.0014715128,0.0062769637,0.0008283554,0.0004208497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007628405,0.001081791,0.0020027834,0.000988151,0.0009729809,0.0036823717,0.0038491113,0.0017627933,0.0030251155],"category_scores_gemma":[0.02606419,0.0008378832,0.0011659341,0.0022751887,0.0018026334,0.008328395,0.0034610017,0.0034451804,0.0009445817],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063906563,0.0005463351,0.0058095325,0.00019675343,0.00021178128,0.0005304835,0.0005488371,0.6043036,0.005149192,0.18570289,0.007201346,0.18916011],"study_design_scores_gemma":[0.000057405916,0.00011047145,0.0006321671,0.000017601298,0.000035385652,0.00026555418,0.000097479926,0.8288288,0.0032437206,0.16415559,0.002521978,0.000033745622],"about_ca_topic_score_codex":0.0012079426,"about_ca_topic_score_gemma":0.00084526115,"teacher_disagreement_score":0.007628405,"about_ca_system_score_codex":0.0017198487,"about_ca_system_score_gemma":0.001954633,"threshold_uncertainty_score":0.040343404},"labels":[],"label_agreement":null},{"id":"W4287905040","doi":"","title":"May autonomous vehicles transform freight and logistics","year":2020,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Traffic management; Transport engineering; Computer science; Automotive engineering; Engineering","score_opus":0.019023162970943672,"score_gpt":0.21925048287468385,"score_spread":0.20022731990374018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287905040","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047967713,0.0034459862,0.12102482,0.05059976,0.008254978,0.0000730538,0.0008655078,0.0010279631,0.7667402],"genre_scores_gemma":[0.6963734,0.0028264483,0.01358457,0.0026448697,0.0011513606,0.0000596857,0.00038802304,0.00024090323,0.28273076],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995969,0.00008297948,0.00001224398,0.00011516946,0.00011393206,0.000078817946],"domain_scores_gemma":[0.99950325,0.00010807803,0.000046880225,0.00013876568,0.00013446258,0.00006850309],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006306881,0.0005654279,0.00025450534,0.0004934554,0.0010742034,0.005153168,0.0006841684,0.0020974532,0.022707542],"category_scores_gemma":[0.0030125326,0.00027050675,0.00042938814,0.0007047864,0.0022714096,0.0068081343,0.0015532626,0.0018114574,0.005767332],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031432108,0.000011022517,0.00016393482,0.000013265562,0.000005018075,0.000043161694,0.0001321893,0.0024486089,0.00026199807,0.97163117,0.011609952,0.013648201],"study_design_scores_gemma":[0.000010686655,0.000019905754,0.00024831426,0.000013206341,0.0000066922457,0.00007074399,0.0002766149,0.0077954107,0.0007183729,0.8024469,0.18838151,0.000011604712],"about_ca_topic_score_codex":0.011427617,"about_ca_topic_score_gemma":0.0056451196,"teacher_disagreement_score":0.022707542,"about_ca_system_score_codex":0.0021746815,"about_ca_system_score_gemma":0.0014899763,"threshold_uncertainty_score":0.07596433},"labels":[],"label_agreement":null},{"id":"W4288089682","doi":"","title":"Les normes sociales du déplacement piéton : un enjeu pour le véhicule autonome","year":2019,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Political science; Humanities; Philosophy","score_opus":0.023155461273410505,"score_gpt":0.23074829021619275,"score_spread":0.20759282894278225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4288089682","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.65360135,0.012661335,0.03637885,0.09794479,0.0009299142,0.00008157146,0.0016414241,0.00017924454,0.19658151],"genre_scores_gemma":[0.972548,0.0020507565,0.0039099655,0.00048732912,0.00009922915,0.0000616397,0.00015174308,0.000046707162,0.020644495],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9948218,0.0022784043,0.00013094353,0.00053437956,0.0017719456,0.00046248967],"domain_scores_gemma":[0.99073386,0.0030381787,0.0010590395,0.00043372335,0.0040188017,0.00071649137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005169842,0.0005108738,0.00054776686,0.0017171646,0.0039737094,0.009985734,0.0010860561,0.0013367025,0.004581308],"category_scores_gemma":[0.011982328,0.00028829294,0.0003624128,0.0025525715,0.009286407,0.004716144,0.0020556678,0.0019237971,0.0002763262],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038833023,0.00012211455,0.08467712,0.0004729263,0.00020261762,0.00040434694,0.07785315,0.008589866,0.0020900343,0.6645399,0.026806602,0.13385305],"study_design_scores_gemma":[0.00006326426,0.0002114877,0.34546044,0.0010877535,0.00013520014,0.00033588614,0.1384051,0.015652733,0.001916109,0.07269032,0.42368925,0.0003524884],"about_ca_topic_score_codex":0.8680198,"about_ca_topic_score_gemma":0.82385933,"teacher_disagreement_score":0.8680198,"about_ca_system_score_codex":0.033715732,"about_ca_system_score_gemma":0.026238933,"threshold_uncertainty_score":0.26551485},"labels":[],"label_agreement":null},{"id":"W4288111734","doi":"10.48550/arxiv.1909.04615","title":"On Re-Balancing Self-Interested Agents in Ride-Sourcing Transportation\\n Networks","year":2019,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Control (management); Operations research; Profit (economics); Set (abstract data type); Engineering; Microeconomics; Economics; Artificial intelligence","score_opus":0.05281631097310019,"score_gpt":0.1917246421643071,"score_spread":0.1389083311912069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4288111734","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14597216,0.0012170932,0.84225357,0.0011908874,0.00019905806,0.00021635075,0.000095785945,0.00045069485,0.008404429],"genre_scores_gemma":[0.9419557,0.0004417289,0.052467365,0.00028519833,0.0001028892,0.00012024322,0.00007798949,0.000102962615,0.0044460255],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991999,0.00032467168,0.000032728258,0.00018068908,0.00010987896,0.00015218346],"domain_scores_gemma":[0.99637526,0.0024134847,0.00043491038,0.00022117651,0.00033548154,0.0002196542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024273298,0.0013883006,0.0012446198,0.0006708899,0.00086429354,0.0013186906,0.001906866,0.0013870464,0.003201316],"category_scores_gemma":[0.0059438916,0.00043001666,0.00048611613,0.000647356,0.0013675719,0.002322305,0.0015849598,0.0010243215,0.0003957651],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001456833,0.00010951916,0.0006744738,0.00007140242,0.00003675278,0.000052155192,0.00013073283,0.9632138,0.0017420325,0.008855462,0.001259981,0.023707984],"study_design_scores_gemma":[0.000015986223,0.000050648436,0.0001098199,0.0000046169193,0.0000062807285,0.000009949282,0.000049682025,0.9945475,0.00027196945,0.0043226327,0.00060573715,0.0000052722294],"about_ca_topic_score_codex":0.007933594,"about_ca_topic_score_gemma":0.0054927324,"teacher_disagreement_score":0.007933594,"about_ca_system_score_codex":0.001270516,"about_ca_system_score_gemma":0.0009869759,"threshold_uncertainty_score":0.015774846},"labels":[],"label_agreement":null},{"id":"W4289107433","doi":"10.48550/arxiv.1812.07636","title":"Distributed Algorithms for Internet-of-Things-enabled Prosumer Markets: A Control Theoretic Perspective","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Prosumer; Computer science; Resource (disambiguation); Shared resource; Context (archaeology); The Internet; Probabilistic logic; Distributed computing; Computer security; Computer network; World Wide Web; Renewable energy; Engineering","score_opus":0.028780473099187798,"score_gpt":0.1917094456271226,"score_spread":0.1629289725279348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289107433","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010932648,0.0004402568,0.98167634,0.00065677793,0.00007100995,0.00008467526,0.00003773123,0.00007732759,0.0060231867],"genre_scores_gemma":[0.75672626,0.0013084859,0.2327991,0.00038130587,0.00018659284,0.00052303285,0.00012756992,0.000109450564,0.007838213],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987962,0.0004895688,0.00005307845,0.00024406213,0.00025953286,0.00015745353],"domain_scores_gemma":[0.9957705,0.0032226979,0.00030799126,0.00019677388,0.0003537616,0.00014816785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002784728,0.0013070237,0.0014006722,0.0006945298,0.0008874962,0.0021283377,0.0018419789,0.0018519148,0.003221844],"category_scores_gemma":[0.008455471,0.000500031,0.0008745864,0.0008718358,0.0020026022,0.0021104168,0.0017246512,0.002314186,0.00035567555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000065066524,0.00006209609,0.0003225707,0.000098170814,0.000044742308,0.000055986962,0.00008039947,0.8137888,0.00086472044,0.16914944,0.0010901073,0.014377942],"study_design_scores_gemma":[0.000027872073,0.000026235655,0.00004019121,0.000010073564,0.000008133925,0.000018238432,0.000023324976,0.9298405,0.0002475836,0.0690315,0.000718966,0.0000073084684],"about_ca_topic_score_codex":0.0022862137,"about_ca_topic_score_gemma":0.0016338876,"teacher_disagreement_score":0.003221844,"about_ca_system_score_codex":0.001977378,"about_ca_system_score_gemma":0.0018646732,"threshold_uncertainty_score":0.014727235},"labels":[],"label_agreement":null},{"id":"W4289654090","doi":"10.1155/2022/6940850","title":"Analysis of the Impact of Ride-Hailing on Urban Road Network Traffic by Using Vehicle Trajectory Data","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Foundation of Anhui Province; Hefei University","keywords":"Transport engineering; Traffic congestion; Computer science; License; Work (physics); Floating car data; Vehicle miles of travel; Engineering","score_opus":0.018499043260563265,"score_gpt":0.2749799431732979,"score_spread":0.2564808999127346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289654090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958182,0.00005316208,0.001738416,0.000035707402,0.0000060239295,0.000022022326,0.001699569,0.000032819684,0.0005939726],"genre_scores_gemma":[0.9952093,0.00007538031,0.0011400997,0.0000035558935,0.0000039676574,0.000017268545,0.003304399,0.00000493533,0.0002410342],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992878,0.00020431203,0.00006577883,0.00015456928,0.0001763004,0.0001113532],"domain_scores_gemma":[0.99819463,0.00062827015,0.00039797305,0.00018261537,0.0004765245,0.00011999004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008585001,0.00045412194,0.00023262894,0.0027266068,0.00027734076,0.0006855727,0.0004400675,0.00025766864,0.0007578528],"category_scores_gemma":[0.0032185428,0.00015540338,0.0005448125,0.0034588187,0.00017644206,0.00095877907,0.000616126,0.00033037408,0.00017642388],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000079422374,0.00008527825,0.95699054,0.000061308274,0.00012401654,0.00020531226,0.00024418897,0.022629295,0.00089006923,0.0004386118,0.00037179902,0.017880186],"study_design_scores_gemma":[0.0000043801556,0.00012722849,0.83387905,0.000026002363,0.0000930481,0.000112432506,0.0015816358,0.16086799,0.0015534519,0.00024107304,0.0014838991,0.000029796964],"about_ca_topic_score_codex":0.039589614,"about_ca_topic_score_gemma":0.04060747,"teacher_disagreement_score":0.039589614,"about_ca_system_score_codex":0.0007267735,"about_ca_system_score_gemma":0.0006282087,"threshold_uncertainty_score":0.078718364},"labels":[],"label_agreement":null},{"id":"W4289913123","doi":"10.1109/access.2022.3196684","title":"A Pricing Mechanism for Ride-Hailing Systems in the Presence of Driver Acceptance Uncertainty","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mechanism (biology); Computer science; Business; Environmental economics; Economics","score_opus":0.029994923721493552,"score_gpt":0.28471364953133327,"score_spread":0.25471872580983973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289913123","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26083484,0.0004372454,0.7320721,0.0008939461,0.00018601672,0.00037583974,0.00018204171,0.0007799688,0.0042379503],"genre_scores_gemma":[0.9848733,0.00006787751,0.013810863,0.00004377798,0.00003362264,0.00006406369,0.000033629505,0.000013911027,0.0010589958],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967152,0.0014165441,0.00014707682,0.0006105165,0.0005428623,0.00056779897],"domain_scores_gemma":[0.9940468,0.0030608997,0.00081929663,0.0006633006,0.00083588454,0.0005737698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056007737,0.0008438102,0.0015023457,0.0008965104,0.0011085179,0.002373227,0.0043910355,0.0023011893,0.004284581],"category_scores_gemma":[0.013103075,0.0006881148,0.00096306734,0.0009801297,0.0009995846,0.0034683563,0.0016518553,0.0021401308,0.0005242487],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004278809,0.00040963312,0.004880413,0.000112383445,0.00011732325,0.00031615395,0.00021470746,0.87403214,0.0050209886,0.045229025,0.0026860647,0.06655322],"study_design_scores_gemma":[0.000021651937,0.0000968274,0.00056856195,0.0000037618033,0.00002165117,0.000049509857,0.000025215952,0.9942431,0.00029641448,0.004259618,0.00039280002,0.000020930493],"about_ca_topic_score_codex":0.0039569084,"about_ca_topic_score_gemma":0.0018925248,"teacher_disagreement_score":0.0056007737,"about_ca_system_score_codex":0.0017247449,"about_ca_system_score_gemma":0.001659515,"threshold_uncertainty_score":0.029620111},"labels":[],"label_agreement":null},{"id":"W4290879673","doi":"10.1155/2022/3866042","title":"Characteristics Analysis and Equilibrium Optimization of Mixed Traffic Flow considering Connected Automated and Human-Driven Vehicles","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Foundation of Hunan Province; Hunan Provincial Innovation Foundation for Postgraduate; Ministry of Education of the People's Republic of China; Scientific Research Foundation of Hunan Provincial Education Department; National Natural Science Foundation of China","keywords":"Bilevel optimization; Simulated annealing; Mathematical optimization; Computer science; Programming paradigm; Maximization; Flow network; Simulation; Optimization problem; Mathematics","score_opus":0.00864119469189897,"score_gpt":0.2310471877871211,"score_spread":0.22240599309522213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4290879673","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35071123,0.00035617492,0.6336448,0.00044880662,0.000053562624,0.00010095645,0.00027245638,0.00021380492,0.014198167],"genre_scores_gemma":[0.9850366,0.00014966006,0.011481667,0.000026746038,0.000010670399,0.00007207574,0.00014232533,0.000035807636,0.003044469],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999642,0.0000958287,0.000012137919,0.00007191722,0.000060227467,0.00011785423],"domain_scores_gemma":[0.99936336,0.00027285874,0.000095387455,0.000016724847,0.00019967077,0.000051934465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007613414,0.0007981182,0.0007200642,0.0012514759,0.00076842366,0.0015980279,0.00085399894,0.00078472914,0.0026059973],"category_scores_gemma":[0.0019089181,0.00049472466,0.0009802034,0.0009659349,0.0007253641,0.0016329599,0.0007213369,0.00053243176,0.00013594997],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042748467,0.000023956676,0.001713593,0.00003832043,0.00002043109,0.00010630453,0.00005557296,0.9813091,0.00071284623,0.012438758,0.00040171377,0.003136682],"study_design_scores_gemma":[0.000002029932,0.000009915573,0.0001779303,0.0000017804808,0.0000036016506,0.000006679195,0.00002531702,0.9980007,0.00009692769,0.0015777535,0.00009391213,0.0000034455109],"about_ca_topic_score_codex":0.02592871,"about_ca_topic_score_gemma":0.010151424,"teacher_disagreement_score":0.02592871,"about_ca_system_score_codex":0.0016689418,"about_ca_system_score_gemma":0.0015506299,"threshold_uncertainty_score":0.051555574},"labels":[],"label_agreement":null},{"id":"W4291929696","doi":"","title":"A quarter of service users can't use services because they can't afford the transport to get there.","year":2004,"lang":"en","type":"article","venue":"PubMed","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Service (business); Business; Marketing; Geography","score_opus":0.016326562183371855,"score_gpt":0.19714813086270314,"score_spread":0.18082156867933127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4291929696","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47126502,0.03225257,0.0045199865,0.08414258,0.007148312,0.00031739884,0.01276095,0.0019080824,0.38568506],"genre_scores_gemma":[0.50775236,0.040684134,0.0016311571,0.024014767,0.0014785624,0.00020309353,0.0074298345,0.0003073202,0.41649875],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99925095,0.00010298009,0.000033778935,0.000042397216,0.000273904,0.00029594035],"domain_scores_gemma":[0.9985531,0.00026824232,0.00018915025,0.00011375883,0.00045497197,0.0004208381],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046211525,0.00036023665,0.00035858515,0.0010447835,0.0011751362,0.0016897435,0.00056761235,0.0011908001,0.10268663],"category_scores_gemma":[0.002893688,0.00014072306,0.0004450027,0.0020787714,0.0004299134,0.0011597449,0.0011385271,0.0010172306,0.02332417],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021270441,0.00015787146,0.042098634,0.0005398587,0.000030669555,0.0004914432,0.0013535875,0.00007011331,0.00172188,0.005124077,0.49852777,0.44967145],"study_design_scores_gemma":[0.000036503778,0.00018422445,0.059605565,0.00057177694,0.00005477499,0.0021721378,0.009474371,0.00039214132,0.0011493897,0.002077955,0.9242511,0.00003023111],"about_ca_topic_score_codex":0.02025364,"about_ca_topic_score_gemma":0.0232789,"teacher_disagreement_score":0.10268663,"about_ca_system_score_codex":0.0006572689,"about_ca_system_score_gemma":0.0020401,"threshold_uncertainty_score":0.343521},"labels":[],"label_agreement":null},{"id":"W4292066131","doi":"10.1080/23249935.2022.2107729","title":"Planning delivery-by-drone micro-fulfilment centres","year":2022,"lang":"en","type":"article","venue":"Transportmetrica A Transport Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Advanced Education, Government of Alberta","keywords":"Drone; Urban sprawl; Knapsack problem; Benchmark (surveying); Computer science; Delivery system; Operations research; Environmental economics; Transport engineering; Simulation; Land use; Engineering; Economics; Civil engineering; Geography","score_opus":0.011596319906353444,"score_gpt":0.21827132865193152,"score_spread":0.2066750087455781,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292066131","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41606984,0.00048564066,0.5540268,0.000826916,0.000081431135,0.00048520177,0.0010779959,0.00041005798,0.026536025],"genre_scores_gemma":[0.9415574,0.00016525568,0.05140477,0.00004313004,0.0000067995684,0.00013972256,0.00024634087,0.000042905718,0.006393586],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968386,0.0001067115,0.000009453606,0.00007137866,0.000041608524,0.00008704888],"domain_scores_gemma":[0.99931633,0.00036924434,0.000076079086,0.000034545916,0.00008378418,0.0001200161],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005704193,0.00048158105,0.00062835,0.00039689915,0.00051717216,0.0012465216,0.0012506114,0.0011786097,0.00840842],"category_scores_gemma":[0.0015157488,0.00053508184,0.0005546781,0.0006936815,0.00065836916,0.0012100673,0.0009754002,0.00094087975,0.0004724181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002948581,0.000015428073,0.0003331951,0.000015586267,0.0000046458945,0.00003227077,0.000015329295,0.9940574,0.00017883339,0.0030404332,0.00022168054,0.0020556997],"study_design_scores_gemma":[0.000009379515,0.000029819324,0.00013237097,0.0000037762316,0.000003243669,0.000009738393,0.000057753256,0.9977043,0.0001813408,0.0012799241,0.00058433204,0.0000040994823],"about_ca_topic_score_codex":0.032225896,"about_ca_topic_score_gemma":0.03314711,"teacher_disagreement_score":0.032225896,"about_ca_system_score_codex":0.0021025743,"about_ca_system_score_gemma":0.0024990267,"threshold_uncertainty_score":0.06407666},"labels":[],"label_agreement":null},{"id":"W4292314484","doi":"10.1016/j.tre.2022.102835","title":"A machine learning-driven two-phase metaheuristic for autonomous ridesharing operations","year":2022,"lang":"en","type":"article","venue":"Transportation Research Part E Logistics and Transportation Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"École Polytechnique Fédérale de Lausanne","keywords":"Metaheuristic; Computer science; Context (archaeology); Intersection (aeronautics); Benchmark (surveying); Vehicle routing problem; Heuristic; Artificial intelligence; Machine learning; Mathematical optimization; Routing (electronic design automation); Engineering; Mathematics; Transport engineering","score_opus":0.11009495229305144,"score_gpt":0.3908383848599684,"score_spread":0.280743432566917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292314484","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05507267,0.0013503497,0.9302251,0.0005771859,0.0002947215,0.00030823136,0.00019402348,0.000671497,0.011306189],"genre_scores_gemma":[0.60923874,0.00047260206,0.3836635,0.0004099128,0.00011497709,0.00055338285,0.00025308089,0.00019038317,0.0051034037],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995459,0.0001773386,0.00002312736,0.00007570279,0.000084088344,0.000093779774],"domain_scores_gemma":[0.99903655,0.00067563506,0.00007405659,0.00003928374,0.000114751965,0.000059659735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013627768,0.0012563039,0.0019221196,0.0012369102,0.0005949272,0.0012667321,0.002331585,0.0028025364,0.0030757352],"category_scores_gemma":[0.0020585437,0.0008348305,0.0016458663,0.0011813916,0.00082834234,0.0011757911,0.0014027455,0.0018055007,0.00034757968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055500015,0.00007105292,0.00013579705,0.00004225775,0.00003678553,0.000022536586,0.000018475364,0.9798079,0.0003236517,0.002475456,0.00049062906,0.01651997],"study_design_scores_gemma":[0.00002853308,0.000043883963,0.00003846836,0.000007140614,0.000009721186,0.000005143809,0.0000069122134,0.9986436,0.00007876591,0.0008912967,0.0002432133,0.0000033889123],"about_ca_topic_score_codex":0.010743804,"about_ca_topic_score_gemma":0.0072314315,"teacher_disagreement_score":0.010743804,"about_ca_system_score_codex":0.001457519,"about_ca_system_score_gemma":0.002147088,"threshold_uncertainty_score":0.021362543},"labels":[],"label_agreement":null},{"id":"W4292870487","doi":"10.5194/iag-comm4-2022-55","title":"Navigation Technologies for Future Autonomous Vehicles","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"GNSS applications; Navigation system; Computer science; Drone; Real-time computing; Embedded system; Telecommunications; Global Positioning System","score_opus":0.01369784393816983,"score_gpt":0.24930824843867425,"score_spread":0.2356104045005044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292870487","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017286316,0.033752754,0.09120521,0.027505064,0.011766707,0.00029944195,0.0015414606,0.00434773,0.827853],"genre_scores_gemma":[0.029707666,0.034754615,0.07835508,0.006858521,0.0028614872,0.00056704663,0.004392177,0.00084024254,0.84166306],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991375,0.00013712497,0.000048711157,0.000117636584,0.00046177485,0.00009721938],"domain_scores_gemma":[0.99909043,0.00008195993,0.00005657482,0.000119202676,0.0005356192,0.00011627622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094682345,0.0009716215,0.0003856518,0.0008548004,0.00096214376,0.0033369814,0.0012446181,0.002492373,0.10368094],"category_scores_gemma":[0.0019352131,0.00028358417,0.00033694637,0.00083781977,0.00074355793,0.004627844,0.0024684984,0.0026762956,0.08460747],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029320132,0.00003222638,0.00027531356,0.000339467,0.000009893549,0.00013754284,0.00025205017,0.0014302763,0.0024483409,0.17957963,0.36702934,0.44843662],"study_design_scores_gemma":[0.0000024954675,0.000013660602,0.00006877193,0.00009496074,0.0000018208717,0.000055801233,0.000046279114,0.00042764138,0.00018660305,0.011254071,0.9878427,0.000005243368],"about_ca_topic_score_codex":0.0026573807,"about_ca_topic_score_gemma":0.002451444,"teacher_disagreement_score":0.10368094,"about_ca_system_score_codex":0.001543065,"about_ca_system_score_gemma":0.0018925392,"threshold_uncertainty_score":0.3468473},"labels":[],"label_agreement":null},{"id":"W4293224569","doi":"10.1155/2022/1960488","title":"Acceptance of Electric Car Sharing in Rural Areas","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Bundesministerium für Bildung und Forschung","keywords":"Expectancy theory; Rural area; Service (business); Business; Electric cars; Car sharing; Early adopter; Sharing economy; Marketing; Electric vehicle; Transport engineering; Environmental economics; Computer science; Engineering; Psychology; Economics","score_opus":0.007033486606474608,"score_gpt":0.23176932866180103,"score_spread":0.22473584205532643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293224569","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99852115,0.000028899814,0.000083265804,0.0001463303,0.0000019416807,0.0000083921705,0.0000070458395,0.0000015044754,0.0012014994],"genre_scores_gemma":[0.999522,0.00004011942,0.00005440414,0.00002467463,0.0000015649658,0.0000064079018,0.00000689236,7.8644e-7,0.00034323914],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99868804,0.0006818128,0.000044689135,0.00010851722,0.00021783287,0.00025910442],"domain_scores_gemma":[0.99706715,0.0012027193,0.00062985264,0.00012023207,0.00047858528,0.0005015902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001969028,0.00014896996,0.00019713445,0.00037514485,0.0007868449,0.00078699406,0.00028807178,0.00046728193,0.003779819],"category_scores_gemma":[0.004191035,0.00012379422,0.0002021464,0.00038463037,0.00088938104,0.0005702614,0.001048745,0.00044904373,0.00018482334],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035369824,0.00083365705,0.73713857,0.00033604374,0.000060153157,0.003250663,0.16202721,0.000666145,0.00937044,0.0031511374,0.0014448109,0.081367515],"study_design_scores_gemma":[0.00002708872,0.00088202994,0.7515718,0.0000943621,0.000031254305,0.00083486136,0.2347317,0.0010334185,0.0007185516,0.0006771825,0.009359127,0.00003869881],"about_ca_topic_score_codex":0.005417691,"about_ca_topic_score_gemma":0.0080571845,"teacher_disagreement_score":0.005417691,"about_ca_system_score_codex":0.00059464824,"about_ca_system_score_gemma":0.000588657,"threshold_uncertainty_score":0.012644768},"labels":[],"label_agreement":null},{"id":"W4293248877","doi":"10.1080/07352166.2022.2053332","title":"Moving ideas? The news media’s impact on ridehailing regulation in Canadian cities","year":2022,"lang":"en","type":"article","venue":"Journal of Urban Affairs","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"York University","funders":"","keywords":"Newspaper; Jurisdiction; Consolidation (business); News media; Politics; Ideology; Political science; Public relations; Advertising; Public administration; Business; Law","score_opus":0.00980642680318478,"score_gpt":0.2188334025356206,"score_spread":0.20902697573243584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293248877","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6290151,0.006446475,0.0008537989,0.05472534,0.00048924796,0.00013021429,0.0018303678,0.00009089911,0.3064186],"genre_scores_gemma":[0.98654306,0.0021640493,0.00026681813,0.0012536553,0.00008131969,0.00002352187,0.0002646708,0.0000305661,0.009372398],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9898671,0.0018861588,0.00030885605,0.0006788071,0.004552804,0.0027062993],"domain_scores_gemma":[0.9544123,0.013255604,0.005936227,0.0013703132,0.018492933,0.006532672],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008030042,0.00038306948,0.00039788047,0.0063252705,0.017683392,0.02220404,0.0022625248,0.0016457802,0.012446793],"category_scores_gemma":[0.034576524,0.0004153894,0.00044083563,0.014504636,0.009884773,0.004110542,0.0056731594,0.0027552892,0.0005173407],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004959805,0.0002077395,0.23265181,0.0011577386,0.00017087373,0.002099542,0.38809213,0.0013778538,0.001443341,0.17267868,0.084365755,0.11525862],"study_design_scores_gemma":[0.00005213701,0.000044541168,0.24663119,0.000977432,0.0001328443,0.00009900293,0.40271387,0.00085429783,0.0008418693,0.0045131864,0.34296298,0.00017655738],"about_ca_topic_score_codex":0.9818782,"about_ca_topic_score_gemma":0.98722494,"teacher_disagreement_score":0.15266098,"about_ca_system_score_codex":0.15266098,"about_ca_system_score_gemma":0.13296682,"threshold_uncertainty_score":0.98279315},"labels":[],"label_agreement":null},{"id":"W4293570076","doi":"10.1016/j.tranpol.2022.08.015","title":"Is access enough? A spatial and demographic analysis of one-way carsharing policies and practice","year":2022,"lang":"en","type":"article","venue":"Transport Policy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Demographics; Equity (law); Business; Descriptive statistics; Service (business); Household income; Car ownership; Sample (material); Low income; Marketing; Transport engineering; Geography; Demographic economics; Public transport; Economics; Engineering","score_opus":0.034583910477880814,"score_gpt":0.31121790818227746,"score_spread":0.2766339977043967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293570076","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99399453,0.00026836002,0.0004334066,0.0010575042,0.000005795836,0.000035359113,0.000614236,0.000004642695,0.0035862098],"genre_scores_gemma":[0.9988255,0.00025440013,0.0002704452,0.000078225654,0.000007785075,0.0000392496,0.0002584909,0.0000036497863,0.00026227324],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998013,0.00074811996,0.00019565895,0.00024756143,0.00048797487,0.0003074858],"domain_scores_gemma":[0.9891973,0.0030681212,0.004699585,0.0004606228,0.0016110805,0.0009631906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022288966,0.00010564574,0.00019833732,0.0017332935,0.00094379456,0.0017222886,0.0005628059,0.00044703262,0.003952095],"category_scores_gemma":[0.012746665,0.00019327177,0.00030594395,0.002879157,0.0012028986,0.0035385925,0.0013999989,0.0006995421,0.0004162425],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031090538,0.00007524984,0.97562736,0.000050384184,0.00002631696,0.00007795889,0.009106499,0.00013186231,0.000097398624,0.0013006334,0.00084172003,0.012633636],"study_design_scores_gemma":[0.0000030739066,0.00009540216,0.9490979,0.00009917645,0.00001901609,0.00016621352,0.045540813,0.00061476696,0.00009109704,0.0005155113,0.0037420609,0.000015028711],"about_ca_topic_score_codex":0.025971469,"about_ca_topic_score_gemma":0.027765144,"teacher_disagreement_score":0.025971469,"about_ca_system_score_codex":0.0015049737,"about_ca_system_score_gemma":0.0014255308,"threshold_uncertainty_score":0.05164063},"labels":[],"label_agreement":null},{"id":"W4293863347","doi":"10.1109/siu55565.2022.9864959","title":"Collective Success Measure and Analysis in Gamification","year":2022,"lang":"en","type":"article","venue":"2022 30th Signal Processing and Communications Applications Conference (SIU)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Stantec (Canada)","funders":"","keywords":"Measure (data warehouse); Cluster analysis; Term (time); Hierarchical clustering; Computer science; Statistics; Econometrics; Mathematics; Data mining; Physics","score_opus":0.02598629477845124,"score_gpt":0.25921515830474084,"score_spread":0.2332288635262896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293863347","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8930863,0.00091889134,0.09334228,0.00019759448,0.00006744312,0.0003503189,0.0003674477,0.00028086838,0.0113888355],"genre_scores_gemma":[0.9811559,0.00012854599,0.016726086,0.000011989672,0.000017275306,0.00028208992,0.0002129751,0.000017021417,0.0014481186],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99652976,0.0015057992,0.00019391342,0.00048792435,0.0009729841,0.00030972],"domain_scores_gemma":[0.99340606,0.003850782,0.0010767519,0.00043464772,0.00071839953,0.0005134072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038545413,0.0009983116,0.0007454345,0.0065075364,0.00077606476,0.0017536484,0.00071480655,0.0006527163,0.0025897243],"category_scores_gemma":[0.013953939,0.0001882275,0.0008693318,0.0046231044,0.0012363879,0.0013477247,0.0016037539,0.00082719076,0.0004176853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012283553,0.0010394108,0.4951288,0.0007002136,0.00073500327,0.0009012365,0.009141926,0.040628996,0.004593341,0.0327919,0.0021200844,0.41099077],"study_design_scores_gemma":[0.00006160049,0.001953944,0.6870506,0.0003095691,0.00039080207,0.000671839,0.009490283,0.2553817,0.0042548445,0.031090206,0.009092691,0.0002519692],"about_ca_topic_score_codex":0.002755503,"about_ca_topic_score_gemma":0.0018926798,"teacher_disagreement_score":0.0065075364,"about_ca_system_score_codex":0.00093624624,"about_ca_system_score_gemma":0.00066921464,"threshold_uncertainty_score":0.020385027},"labels":[],"label_agreement":null},{"id":"W4296211873","doi":"10.1109/tits.2022.3202111","title":"Autonomous Bus Operation Alternatives in Urban Areas Using Fuzzy Dombi-Bonferroni Operator Based Decision Making Model","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Fuzzy logic; Operator (biology); Autonomous system (mathematics); Computer science; Transport engineering; Bonferroni correction; Operations research; Engineering; Artificial intelligence; Mathematics","score_opus":0.03322803963380815,"score_gpt":0.27596509979787637,"score_spread":0.2427370601640682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296211873","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20825072,0.00055974285,0.7802098,0.00044262884,0.00007830556,0.00039353617,0.00020778444,0.000094093746,0.009763388],"genre_scores_gemma":[0.92310786,0.00033409795,0.07302253,0.000055222194,0.000019647388,0.0003750467,0.000111753354,0.000009467354,0.002964286],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980702,0.0010851381,0.00007682762,0.00018992965,0.0003451661,0.00023274751],"domain_scores_gemma":[0.9979215,0.0013595895,0.0001995324,0.00002708122,0.00036252313,0.00012979971],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035469786,0.0011407982,0.0013805558,0.0014806702,0.00086398236,0.0021304474,0.0015322099,0.0012144899,0.0044583706],"category_scores_gemma":[0.004344964,0.00048853795,0.0010571354,0.0013741311,0.00077246496,0.0013937943,0.0010187707,0.0012034269,0.00019489229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010828108,0.00008445059,0.0011130519,0.00009365934,0.00006989999,0.00009831256,0.00011502949,0.97686964,0.00043549575,0.011319733,0.0003080546,0.009384308],"study_design_scores_gemma":[0.000011627927,0.000052753247,0.00015282983,0.0000075652024,0.0000111267045,0.000006516408,0.000033168755,0.99691087,0.00007669208,0.00261887,0.000110791356,0.0000073140986],"about_ca_topic_score_codex":0.01408831,"about_ca_topic_score_gemma":0.013355996,"teacher_disagreement_score":0.01408831,"about_ca_system_score_codex":0.0025575783,"about_ca_system_score_gemma":0.002209649,"threshold_uncertainty_score":0.028012574},"labels":[],"label_agreement":null},{"id":"W4296436259","doi":"10.2139/ssrn.4219437","title":"The Liquidity Premium of Digital Payment Vehicle","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Market liquidity; Treasury; Payment; Business; Context (archaeology); Liquidity premium; Exploit; Payment system; Cash; Monetary economics; Liquidity risk; Finance; Economics; Computer science; Computer security","score_opus":0.005727970017811789,"score_gpt":0.2011830474721667,"score_spread":0.19545507745435492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296436259","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93588585,0.0029168408,0.005788502,0.009626063,0.0002452709,0.000021773809,0.000688407,0.00020212798,0.04462525],"genre_scores_gemma":[0.99479634,0.00023723277,0.000096827156,0.00013473809,0.00012120224,0.0000022434074,0.00008394633,0.000010179282,0.004517389],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993073,0.00013689058,0.0000343223,0.00010684876,0.00016018146,0.00025444955],"domain_scores_gemma":[0.99097604,0.0046023717,0.0023831122,0.00033044783,0.0007358817,0.0009721557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013553842,0.00028759261,0.0005615288,0.00135471,0.0006685004,0.0046999604,0.0006428316,0.002421446,0.017424932],"category_scores_gemma":[0.012894809,0.00033197165,0.00033858718,0.00096179865,0.0012460314,0.0040800967,0.0009897065,0.0027908045,0.0013038476],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004128183,0.00070324243,0.109152816,0.00034350768,0.00014968941,0.002698215,0.0012613175,0.023867145,0.009136937,0.72775126,0.035381522,0.08542625],"study_design_scores_gemma":[0.00054495985,0.0007746417,0.12058472,0.0002847411,0.00031791834,0.001985967,0.003744692,0.12765056,0.0058859764,0.7141526,0.02380492,0.0002683342],"about_ca_topic_score_codex":0.003612536,"about_ca_topic_score_gemma":0.0029519193,"teacher_disagreement_score":0.017424932,"about_ca_system_score_codex":0.0017002383,"about_ca_system_score_gemma":0.0008224107,"threshold_uncertainty_score":0.05829221},"labels":[],"label_agreement":null},{"id":"W4300287132","doi":"10.48550/arxiv.1303.3522","title":"Rebalancing the Rebalancers: Optimally Routing Vehicles and Drivers in\\n Mobility-on-Demand Systems","year":2013,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Destinations; TRIPS architecture; Computer science; Service (business); Routing (electronic design automation); Transport engineering; Stability (learning theory); Operations research; Business; Computer network; Marketing; Engineering; Tourism","score_opus":0.037507276440947625,"score_gpt":0.1724824212209014,"score_spread":0.1349751447799538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4300287132","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2987697,0.00097313564,0.69107217,0.00097208715,0.00012037118,0.00027660365,0.00022423855,0.00021297159,0.0073786196],"genre_scores_gemma":[0.96818227,0.00033403758,0.027298696,0.00010636889,0.000046955276,0.00006669752,0.00008176082,0.000050476985,0.003832797],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919146,0.00030297096,0.000030102274,0.00017313298,0.000064776745,0.00023744497],"domain_scores_gemma":[0.9987482,0.0006427318,0.00024746446,0.00006565146,0.00012387952,0.0001721569],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009526019,0.0019308084,0.0014452876,0.00052960444,0.00084264396,0.0016464901,0.002096564,0.0016179889,0.0031820056],"category_scores_gemma":[0.0028565042,0.00090760156,0.00060975313,0.0006132518,0.0011427745,0.0025688685,0.0016564714,0.0012336283,0.00034593718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019890028,0.00006710788,0.00080376276,0.00006537733,0.000049518643,0.00010998352,0.00010176024,0.9773392,0.0021394126,0.008457987,0.00050697225,0.010159909],"study_design_scores_gemma":[0.000020729694,0.000099639554,0.00020287793,0.00000667616,0.000015254378,0.000028797214,0.00014064542,0.99426854,0.0005494533,0.0040022824,0.00065431616,0.000010693612],"about_ca_topic_score_codex":0.009149248,"about_ca_topic_score_gemma":0.0065733916,"teacher_disagreement_score":0.009149248,"about_ca_system_score_codex":0.0015874745,"about_ca_system_score_gemma":0.00082064304,"threshold_uncertainty_score":0.018191993},"labels":[],"label_agreement":null},{"id":"W4301291847","doi":"10.1108/mscra-01-2022-0002","title":"On-demand service platform operations management: a literature review and research agendas","year":2022,"lang":"en","type":"review","venue":"Modern Supply Chain Research and Applications","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Originality; Context (archaeology); Computer science; Service (business); Empirical research; Management science; Data science; Field (mathematics); Systematic review; Knowledge management; Operations research; Engineering; Marketing; Business; Qualitative research; Sociology","score_opus":0.11793716799268371,"score_gpt":0.4020655330570356,"score_spread":0.28412836506435185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4301291847","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0037319134,0.9791803,0.0019405597,0.0057436028,0.0006842477,0.00009285024,0.00011370761,0.000023441316,0.008489503],"genre_scores_gemma":[0.02703967,0.96797013,0.00212807,0.00095236656,0.00056503393,0.00008151583,0.00014720586,0.000010312297,0.001105709],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99686414,0.0011731576,0.00044526233,0.0002965716,0.0009818322,0.00023896036],"domain_scores_gemma":[0.9819594,0.0119532645,0.0016898661,0.00029596518,0.0037704483,0.0003310492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004908507,0.0010457918,0.0015174433,0.014863237,0.0014537203,0.005439071,0.0015510692,0.0023861933,0.0051686526],"category_scores_gemma":[0.013814893,0.00059240864,0.0014480174,0.018053573,0.0013569896,0.0059122597,0.0016376605,0.0018042019,0.0010639501],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015247488,0.00027131833,0.0026363027,0.10509265,0.00037102366,0.0008380138,0.002426907,0.0024305226,0.0010940221,0.06695204,0.035735436,0.7819993],"study_design_scores_gemma":[0.00005729363,0.00044800495,0.01426135,0.23421273,0.0017237368,0.0022825636,0.016182037,0.0046129767,0.0016605022,0.038440447,0.68594533,0.00017309397],"about_ca_topic_score_codex":0.006090919,"about_ca_topic_score_gemma":0.008769823,"teacher_disagreement_score":0.014863237,"about_ca_system_score_codex":0.004343345,"about_ca_system_score_gemma":0.011987381,"threshold_uncertainty_score":0.031513333},"labels":[],"label_agreement":null},{"id":"W4302774336","doi":"10.1155/2022/4614848","title":"Exploring Users’ Preferences for Automated Minibuses and Their Service Type: A Stated Choice Experiment in the Netherlands","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Technische Universiteit Delft","keywords":"Transport engineering; Mode choice; TRIPS architecture; Public transport; Service (business); Schedule; Level of service; Preference; Perception; Mixed logit; Travel behavior; Value of time; Computer science; Travel time; Engineering; Statistics; Logistic regression; Business; Marketing; Mathematics; Psychology","score_opus":0.06795066614647291,"score_gpt":0.28558210803495554,"score_spread":0.21763144188848263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4302774336","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986118,0.0000149724965,0.00052233366,0.000026894242,0.0000043022696,0.00017347022,0.00007814241,0.0000027633594,0.0005652952],"genre_scores_gemma":[0.99328506,0.000063025436,0.003657382,0.000072852075,0.0000071221793,0.00087388605,0.00020511309,0.000009153793,0.0018264218],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9952976,0.00308817,0.00037789662,0.00049859885,0.00046394544,0.00027378526],"domain_scores_gemma":[0.98464984,0.012362169,0.0011611932,0.0006786392,0.0006909958,0.00045715936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052596047,0.0006275438,0.00089070614,0.00027662827,0.00070984085,0.002452243,0.0008149003,0.0016767613,0.0045280014],"category_scores_gemma":[0.013836796,0.00064629724,0.0007857876,0.00037675118,0.00088220864,0.0019667186,0.00088305725,0.0009187554,0.00069486914],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0456179,0.12828574,0.3055783,0.0051090266,0.0011148731,0.005014547,0.20717697,0.028687442,0.17058736,0.012999417,0.0054698125,0.08435871],"study_design_scores_gemma":[0.01678984,0.12348734,0.4415858,0.00066295936,0.0013391317,0.001286936,0.1536216,0.14231034,0.064682245,0.010817354,0.041372806,0.002043509],"about_ca_topic_score_codex":0.0077144294,"about_ca_topic_score_gemma":0.0058718426,"teacher_disagreement_score":0.0077144294,"about_ca_system_score_codex":0.00082999014,"about_ca_system_score_gemma":0.000676981,"threshold_uncertainty_score":0.02781576},"labels":[],"label_agreement":null},{"id":"W4306194565","doi":"10.1371/journal.pone.0275714","title":"The impact of COVID-19 pandemic on ridesourcing services differed between small towns and large cities","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); TRIPS architecture; Population; 2019-20 coronavirus outbreak; Demography; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Vaccination; Environmental health; Geography; Socioeconomics; Medicine; Outbreak; Virology; Infectious disease (medical specialty); Economics; Disease; Engineering","score_opus":0.06791492717836786,"score_gpt":0.25987930442735857,"score_spread":0.1919643772489907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306194565","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978975,0.000057524976,0.00006901351,0.000067462475,0.000002898423,0.000015996884,0.00075486617,0.0000038345684,0.0011309059],"genre_scores_gemma":[0.99879056,0.000038475086,0.00005155074,0.00002085989,0.0000030865,0.000012052416,0.0005797659,0.0000041426156,0.0004996253],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989668,0.00023293128,0.00007084484,0.00021154255,0.0001819799,0.0003358738],"domain_scores_gemma":[0.998185,0.0003713477,0.00050728663,0.00013628977,0.00039544542,0.00040462895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046381785,0.00031094917,0.00030803133,0.0012871039,0.0005548661,0.0009736824,0.0004451743,0.000349965,0.002730315],"category_scores_gemma":[0.0023014785,0.00016506057,0.0006638419,0.0020592746,0.0006767126,0.0006142878,0.0010300992,0.00039029215,0.00030200498],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000695881,0.00002920021,0.99732107,0.000014553889,0.000050715385,0.00006205086,0.00036514294,0.00032234925,0.0002670787,0.00006273812,0.00016937742,0.0012662238],"study_design_scores_gemma":[0.0000013023263,0.00002231009,0.9980381,0.0000052183445,0.000009416644,0.000020638343,0.0013227852,0.0003126637,0.000048822567,0.0000133712865,0.00020158036,0.0000038757294],"about_ca_topic_score_codex":0.24955305,"about_ca_topic_score_gemma":0.4302297,"teacher_disagreement_score":0.24955305,"about_ca_system_score_codex":0.0021912928,"about_ca_system_score_gemma":0.0015237232,"threshold_uncertainty_score":0.49620098},"labels":[],"label_agreement":null},{"id":"W4306318354","doi":"10.1155/2022/3316535","title":"What Affects Safety Perception of Female Ride-Hailing Passengers? An Empirical Study in China Context","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Humanities and Social Science Fund of Ministry of Education of China; Chongqing Jiaotong University; Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Perception; Structural equation modeling; Confirmatory factor analysis; Context (archaeology); Mobile phone; Risk perception; Phone; Applied psychology; China; Transport engineering; Marketing; Psychology; Engineering; Business; Computer science; Telecommunications","score_opus":0.014780457762672332,"score_gpt":0.29365229181457336,"score_spread":0.278871834051901,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306318354","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996903,0.00002659148,0.000027740383,0.000034912235,0.0000015009601,0.0000053702715,0.00002533897,3.9804416e-7,0.00018788557],"genre_scores_gemma":[0.9995098,0.00006831239,0.000045498222,0.000026782147,0.0000027253907,0.000009499891,0.00004291456,5.4949885e-7,0.00029393026],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99946946,0.000120338,0.000045786757,0.00010285498,0.00011399807,0.00014756723],"domain_scores_gemma":[0.9987909,0.00027996127,0.00036795865,0.000051021605,0.00026688934,0.00024332551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010174284,0.000356119,0.00028429588,0.00072291284,0.001114081,0.0007047548,0.00031488133,0.00043701957,0.0021205693],"category_scores_gemma":[0.0021322628,0.00024433807,0.00045449848,0.0006823878,0.00064360275,0.0006400888,0.000499017,0.0005154381,0.00019715005],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055775807,0.00017664074,0.964024,0.00007115761,0.000024730358,0.00042459264,0.027876996,0.00007338937,0.0007877601,0.00011643194,0.0002251934,0.00614339],"study_design_scores_gemma":[0.0000035137814,0.00017822252,0.9626882,0.000021431017,0.0000175259,0.00012540213,0.035868272,0.00033120706,0.00014975671,0.000029387833,0.000573058,0.000014086324],"about_ca_topic_score_codex":0.060164098,"about_ca_topic_score_gemma":0.061077688,"teacher_disagreement_score":0.060164098,"about_ca_system_score_codex":0.0011054334,"about_ca_system_score_gemma":0.0013343799,"threshold_uncertainty_score":0.119627774},"labels":[],"label_agreement":null},{"id":"W4306726345","doi":"10.1155/2022/7256505","title":"Analysis of Individuals’ Acceptance and Influencing Factors for Young Users of Autonomous Vehicles Using the Hybrid Choice Model","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Jiangxi Provincial Department of Science and Technology; Natural Science Foundation of Jiangxi Province; National Natural Science Foundation of China","keywords":"Latent variable; Popularity; Structural equation modeling; Descriptive statistics; Psychology; Goodness of fit; Matching (statistics); Government (linguistics); Statistics; Applied psychology; Social psychology; Computer science; Mathematics","score_opus":0.020151097978804575,"score_gpt":0.266421072710656,"score_spread":0.24626997473185144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306726345","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99914217,0.000016659387,0.00054573227,0.000018621471,0.0000016472453,0.000015647476,0.000022548125,0.0000018458866,0.00023509203],"genre_scores_gemma":[0.999432,0.000019337784,0.00032458702,0.000004675814,0.0000016908951,0.000025826199,0.000043747303,8.933279e-7,0.0001471647],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99840003,0.0007514891,0.00016536136,0.0001523893,0.0003363679,0.00019444604],"domain_scores_gemma":[0.98995763,0.0064308196,0.0016783075,0.00040960402,0.0007966735,0.00072699104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033404122,0.00035886283,0.00033646278,0.001176989,0.0005499945,0.0012304971,0.00033172677,0.0006139761,0.003051506],"category_scores_gemma":[0.010292983,0.00019953193,0.0015860337,0.0007946169,0.0005128828,0.00068472547,0.0007974086,0.0007668607,0.00023977143],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006173943,0.00012262719,0.99194384,0.000015129395,0.00005205049,0.00010937989,0.0023105585,0.00047351286,0.00020124816,0.00022709172,0.000038751386,0.0044440087],"study_design_scores_gemma":[0.000006990229,0.00036614484,0.97190946,0.000029241013,0.00007911051,0.00018016626,0.009268886,0.01699612,0.00028827935,0.00045992152,0.00038821666,0.000027523722],"about_ca_topic_score_codex":0.005248684,"about_ca_topic_score_gemma":0.004305183,"teacher_disagreement_score":0.005248684,"about_ca_system_score_codex":0.0005326188,"about_ca_system_score_gemma":0.0006129544,"threshold_uncertainty_score":0.017665982},"labels":[],"label_agreement":null},{"id":"W4307533359","doi":"","title":"Etudes d'impact d'infrastructures routières - volets \"air et santé\" : état initial et recueil des données","year":2008,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Center for Northern Studies","funders":"","keywords":"Computer science; Medicine; Humanities; Physics; Philosophy","score_opus":0.02300284612888271,"score_gpt":0.2686222646314979,"score_spread":0.2456194185026152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307533359","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3313627,0.07314781,0.18855993,0.018031912,0.0021558548,0.0035434603,0.08987907,0.0021271529,0.29119205],"genre_scores_gemma":[0.65601254,0.07869682,0.15089193,0.003400559,0.0005376408,0.0043069124,0.03909452,0.0010777019,0.06598138],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.98109597,0.006154874,0.0015280821,0.0016858524,0.00891344,0.0006218761],"domain_scores_gemma":[0.94322944,0.03582021,0.0030217003,0.0029474932,0.014411431,0.00056984613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013109144,0.0013534345,0.0012004788,0.006700162,0.0014967332,0.008736646,0.002155052,0.0019210149,0.0124088805],"category_scores_gemma":[0.04057421,0.0009079151,0.002571006,0.010758564,0.0015949521,0.006090105,0.0032786028,0.0026733326,0.0020866184],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066793105,0.00042807916,0.1168773,0.029047502,0.0020334788,0.0014059688,0.028610297,0.057558738,0.0076303105,0.08360404,0.04850995,0.6236264],"study_design_scores_gemma":[0.000085027175,0.0008895518,0.19484347,0.021235578,0.0014001089,0.00091579923,0.03802743,0.01811175,0.013401463,0.027067,0.6835998,0.00042301908],"about_ca_topic_score_codex":0.08122874,"about_ca_topic_score_gemma":0.08541921,"teacher_disagreement_score":0.08122874,"about_ca_system_score_codex":0.00833726,"about_ca_system_score_gemma":0.010155675,"threshold_uncertainty_score":0.16151184},"labels":[],"label_agreement":null},{"id":"W4307641870","doi":"10.1155/2022/2999162","title":"An Auction-Based Multiagent Simulation for the Matching Problem in Dynamic Vehicle Routing Problem with Occasional Drivers","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Ministry of Science and Technology, Taiwan","keywords":"Common value auction; Computer science; Matching (statistics); Time horizon; Compensation (psychology); Interval (graph theory); Mathematical optimization; Routing (electronic design automation); Simple (philosophy); Vehicle routing problem; Operations research; Simulation; Distributed computing; Real-time computing; Engineering; Microeconomics; Computer network; Economics; Mathematics","score_opus":0.007588048445034803,"score_gpt":0.24987661935582817,"score_spread":0.24228857091079337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307641870","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5664128,0.0002804191,0.4140671,0.00051179784,0.00010547223,0.00025686275,0.00031815062,0.00037939905,0.017667983],"genre_scores_gemma":[0.9461759,0.00007744587,0.052065928,0.00003128836,0.000008701873,0.000119479446,0.00008238615,0.000019741623,0.0014191045],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996705,0.00019001079,0.000014842797,0.00003753328,0.000045030833,0.000042043543],"domain_scores_gemma":[0.99814975,0.0013569462,0.00012939134,0.00009020196,0.00016243586,0.00011140835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010515061,0.00043472165,0.0006438356,0.00041995285,0.0005171576,0.0007088684,0.0009915569,0.001067377,0.0021457074],"category_scores_gemma":[0.0022229278,0.00036010568,0.00064792234,0.00034830996,0.00047551288,0.0006736683,0.000617108,0.00084254757,0.0001274099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022822762,0.000030478604,0.00030710959,0.000009926929,0.0000077623135,0.000019190999,0.000012031981,0.9965628,0.00018193646,0.0019401965,0.00004531919,0.00086044316],"study_design_scores_gemma":[0.0000063460648,0.000008890028,0.00003029583,7.717807e-7,0.0000014538808,0.0000018051336,0.000004120958,0.9995086,0.000053749547,0.00032187265,0.000060996546,0.000001133433],"about_ca_topic_score_codex":0.014151461,"about_ca_topic_score_gemma":0.009363357,"teacher_disagreement_score":0.014151461,"about_ca_system_score_codex":0.0009137435,"about_ca_system_score_gemma":0.0012428417,"threshold_uncertainty_score":0.02813816},"labels":[],"label_agreement":null},{"id":"W4307820550","doi":"10.1007/s11116-022-10344-2","title":"Facing the future of transit ridership: shifting attitudes towards public transit and auto ownership among transit riders during COVID-19","year":2022,"lang":"en","type":"article","venue":"Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; Public Health Ontario; University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; University of Toronto; Government of Ontario; School of Cities, University of Toronto","keywords":"Transit (satellite); Public transport; Transport engineering; Coronavirus disease 2019 (COVID-19); Business; Urban transit; 2019-20 coronavirus outbreak; Engineering; Medicine","score_opus":0.02328112678753736,"score_gpt":0.2365698056715451,"score_spread":0.21328867888400774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307820550","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970421,0.00009774683,0.000027319182,0.0013687897,0.000020570062,0.000006591562,0.00005690853,8.9909497e-7,0.0013789734],"genre_scores_gemma":[0.9982224,0.00010822464,0.000028146917,0.00020886563,0.000009018302,0.000008532641,0.00005226917,0.0000013335706,0.0013611388],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992649,0.00017582472,0.000031947253,0.00005726453,0.00008774053,0.00038223655],"domain_scores_gemma":[0.998456,0.00015262517,0.00035279128,0.000037307007,0.0003025993,0.0006987417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014470216,0.00014938148,0.00017096568,0.0006075838,0.0028205786,0.0032429318,0.0005231174,0.0014718468,0.004451667],"category_scores_gemma":[0.0017850285,0.000267965,0.00038737143,0.00059404183,0.0013471222,0.0025711725,0.002086688,0.0023019984,0.00043507674],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011923551,0.00027190894,0.8690054,0.000031425596,0.000029543018,0.00041132997,0.11936568,0.00006723976,0.0005097661,0.0011309083,0.001573719,0.007483874],"study_design_scores_gemma":[0.0000032752114,0.00008114359,0.5705307,0.000043810356,0.000009704344,0.000094646246,0.42548433,0.00013875157,0.00009913678,0.00013531833,0.0033629672,0.000016240021],"about_ca_topic_score_codex":0.1270538,"about_ca_topic_score_gemma":0.24668093,"teacher_disagreement_score":0.1270538,"about_ca_system_score_codex":0.0021981732,"about_ca_system_score_gemma":0.0025176923,"threshold_uncertainty_score":0.2526285},"labels":[],"label_agreement":null},{"id":"W4308148970","doi":"10.1016/j.trb.2022.10.005","title":"Supply regulation under the exclusion policy in a ride-sourcing market","year":2022,"lang":"en","type":"article","venue":"Transportation Research Part B Methodological","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Fundamental Research Funds for the Central Universities; Singapore Management University; National Natural Science Foundation of China; Shanghai Municipal Education Commission; National University's Basic Research Foundation of China; Science and Technology Commission of Shanghai Municipality; Shanghai Education Development Foundation","keywords":"Profit (economics); Welfare; Service provider; Service quality; Quality (philosophy); Business; Economics; Economic surplus; Industrial organization; Social Welfare; Public policy; Microeconomics; Service (business); Public economics; Marketing; Market economy; Economic growth","score_opus":0.27662342395682704,"score_gpt":0.437612799659619,"score_spread":0.16098937570279198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308148970","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39966857,0.0010761303,0.28894112,0.026877806,0.0006403273,0.00041784876,0.00070821383,0.00042931607,0.2812406],"genre_scores_gemma":[0.97198176,0.000255311,0.005168668,0.0012169838,0.00036517016,0.00017828136,0.000057852554,0.00005478519,0.020721147],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9922854,0.003054695,0.00030205163,0.0013514382,0.00089671364,0.0021097173],"domain_scores_gemma":[0.98049957,0.013353568,0.0019284158,0.001723042,0.0015887044,0.00090676046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010347506,0.0006855524,0.003352894,0.00122657,0.0038231467,0.008292191,0.0031112214,0.0073161335,0.018669484],"category_scores_gemma":[0.02257937,0.00093481515,0.0032736112,0.0011665934,0.007897751,0.008448199,0.0053257095,0.007915727,0.00095933134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019846941,0.00013685398,0.00065506273,0.000082126375,0.000034236607,0.0002269529,0.00023231855,0.009743331,0.0008113247,0.9831033,0.0020224687,0.0027534796],"study_design_scores_gemma":[0.00027201153,0.00012382257,0.00095023296,0.000050094673,0.00010137523,0.00007749838,0.0005414138,0.044039976,0.0007215673,0.94868654,0.0043769693,0.00005857515],"about_ca_topic_score_codex":0.010687459,"about_ca_topic_score_gemma":0.0064575677,"teacher_disagreement_score":0.018669484,"about_ca_system_score_codex":0.0051159374,"about_ca_system_score_gemma":0.007191438,"threshold_uncertainty_score":0.062455654},"labels":[],"label_agreement":null},{"id":"W4308717894","doi":"10.3917/rindu1.224.0086","title":"La mobilité décarbonée : le premier projet de rétrofit d’autocar, l’expérience normande avec Nomad","year":2022,"lang":"fr","type":"article","venue":"Annales des Mines - Réalités industrielles","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Intégré de Santé et Services Sociaux de Chaudière-Appalache","funders":"","keywords":"Humanities; Political science; Art","score_opus":0.02876683433003979,"score_gpt":0.2550855738873355,"score_spread":0.2263187395572957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308717894","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7422716,0.004146639,0.013952405,0.012027867,0.0005051939,0.00014181076,0.000400497,0.00030871222,0.2262453],"genre_scores_gemma":[0.8980417,0.0032715984,0.008841748,0.0008599525,0.00008073988,0.00008893262,0.0003663976,0.00013122885,0.08831779],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988477,0.00028162464,0.000034254143,0.00020647886,0.00039911515,0.00023075608],"domain_scores_gemma":[0.9989008,0.00021532345,0.00012113654,0.000077393524,0.0003543457,0.0003309733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018042593,0.00046731756,0.00017248059,0.00062022393,0.0019060822,0.0039472696,0.00070333946,0.00088675955,0.0068363403],"category_scores_gemma":[0.0011744525,0.0001829832,0.00029965834,0.00076217187,0.0019308535,0.002233544,0.0030164977,0.0013445952,0.00071910385],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009364438,0.0010594836,0.05594458,0.0017099427,0.000118014796,0.003317421,0.10218591,0.01203943,0.047847986,0.13815789,0.03391131,0.60277164],"study_design_scores_gemma":[0.00003368891,0.0007707994,0.033867553,0.00039602013,0.000031941254,0.0006572484,0.049314454,0.0016767388,0.013302125,0.005616889,0.89425105,0.00008144188],"about_ca_topic_score_codex":0.03222145,"about_ca_topic_score_gemma":0.075491376,"teacher_disagreement_score":0.03222145,"about_ca_system_score_codex":0.004933126,"about_ca_system_score_gemma":0.007538011,"threshold_uncertainty_score":0.06406778},"labels":[],"label_agreement":null},{"id":"W4309345280","doi":"10.1109/smc53654.2022.9945274","title":"A Deep Averaged Reinforcement Learning Approach for the Traveling Salesman Problem","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Reinforcement learning; Travelling salesman problem; Heuristics; Forgetting; Computer science; Artificial intelligence; Convergence (economics); Generalization; Mathematical optimization; Process (computing); Machine learning; Mathematics; Algorithm","score_opus":0.04134696800989715,"score_gpt":0.2538691343529126,"score_spread":0.21252216634301543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309345280","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022346046,0.00030221968,0.97405213,0.00016324222,0.000051675594,0.000039665094,0.000031146585,0.0005895241,0.0024244231],"genre_scores_gemma":[0.792967,0.00019767771,0.2031843,0.0001734384,0.00005123247,0.000101326485,0.00009215022,0.00007747692,0.0031554212],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969256,0.00008629121,0.000017928829,0.00007059378,0.00007815904,0.000054571254],"domain_scores_gemma":[0.9995908,0.00016571843,0.000052722167,0.00003486833,0.00011479647,0.00004116899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075555715,0.0006889123,0.0008162666,0.0003752865,0.00028880048,0.00045961683,0.0011515148,0.00071511755,0.0019530971],"category_scores_gemma":[0.0015877836,0.00032294256,0.00042726065,0.00030345327,0.0004774345,0.00074263767,0.0006505942,0.0011858913,0.0002067528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036092377,0.000051255065,0.00042210572,0.000034553876,0.000029724079,0.000038909257,0.00002954941,0.93523896,0.0012529471,0.0054336647,0.0006352498,0.05679695],"study_design_scores_gemma":[0.0000028040886,0.0000147985875,0.000027747194,0.000001305376,0.0000022947368,0.000004243782,0.0000011381502,0.9988558,0.00014738525,0.00080509373,0.00013606399,0.0000013458977],"about_ca_topic_score_codex":0.008205516,"about_ca_topic_score_gemma":0.0069736717,"teacher_disagreement_score":0.008205516,"about_ca_system_score_codex":0.00077026675,"about_ca_system_score_gemma":0.0013053679,"threshold_uncertainty_score":0.01631546},"labels":[],"label_agreement":null},{"id":"W4310051786","doi":"10.1155/2022/8281988","title":"Automated Mobility-on-Demand Service Improvement Strategy through Latent Class Analysis of Stated Preference Survey","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Korea Agency for Infrastructure Technology Advancement; Ministry of Land, Infrastructure and Transport","keywords":"Reservation; Preference; Transport engineering; Service (business); Public transport; Revealed preference; Computer science; Business; Marketing; Engineering; Economics","score_opus":0.030201023306016102,"score_gpt":0.27428811246388907,"score_spread":0.24408708915787297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310051786","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9633654,0.00007640275,0.033513855,0.00023207416,0.00001555681,0.0003413477,0.0014044184,0.00009878119,0.00095217617],"genre_scores_gemma":[0.9900455,0.000037022044,0.008021348,0.00002515815,0.0000071479376,0.00021607507,0.0013606375,0.000005533695,0.00028144493],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9945427,0.0036603843,0.00028947656,0.0004893706,0.0006414204,0.0003766332],"domain_scores_gemma":[0.9908703,0.004997734,0.0013141057,0.00073541317,0.0016478483,0.00043454452],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059947777,0.0004872467,0.00064869435,0.0020121043,0.00046506737,0.0012835714,0.0007609588,0.00046587738,0.0026641453],"category_scores_gemma":[0.011360086,0.00020732371,0.0013736129,0.0022755957,0.00025913698,0.0009853321,0.0009277624,0.0010250664,0.0006155358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010275501,0.0026388636,0.84369993,0.00025620306,0.00060191733,0.00014112357,0.0016530982,0.016140264,0.0015075657,0.002362628,0.0028456002,0.12712532],"study_design_scores_gemma":[0.00009747641,0.0011270001,0.33739156,0.00006137309,0.00027530573,0.00007305241,0.004635835,0.6511325,0.0011675286,0.0022949837,0.0016545162,0.00008887779],"about_ca_topic_score_codex":0.00925968,"about_ca_topic_score_gemma":0.008782379,"teacher_disagreement_score":0.00925968,"about_ca_system_score_codex":0.0011159063,"about_ca_system_score_gemma":0.0012834081,"threshold_uncertainty_score":0.03170383},"labels":[],"label_agreement":null},{"id":"W4311529210","doi":"10.1111/caje.12630","title":"Do ridesharing services cause traffic congestion?","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Metropolitan area; Transport engineering; Traffic congestion; Travel time; Statistical analysis; Vehicle miles of travel; Event (particle physics); Geography; Advertising; Computer science; Statistics; Business; Engineering; Mathematics; Archaeology","score_opus":0.08492301353942051,"score_gpt":0.1787698168325104,"score_spread":0.09384680329308988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311529210","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9925155,0.0007316105,0.00043099394,0.0011493622,0.000061389226,0.00004108171,0.0008811326,0.00002413409,0.004164725],"genre_scores_gemma":[0.99901736,0.00016071484,0.00007011717,0.000078283745,0.000037271704,0.000009249558,0.0001896872,0.0000034606314,0.0004337435],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99607724,0.0017961845,0.00023976136,0.00048800753,0.00057355163,0.0008252884],"domain_scores_gemma":[0.9810022,0.008633048,0.0069243577,0.0006421833,0.0014558936,0.0013423185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025019501,0.00025095505,0.0006791115,0.001214199,0.0006367414,0.0023609228,0.0009653961,0.0009773229,0.008146202],"category_scores_gemma":[0.021120192,0.00021130875,0.0014536226,0.0019557246,0.0010357009,0.0015323216,0.0013842738,0.0012360563,0.0004990843],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012072908,0.00089547574,0.9528138,0.00026107527,0.00093649834,0.00040851723,0.0007046764,0.0050625564,0.00031078796,0.002916149,0.0030367936,0.03144642],"study_design_scores_gemma":[0.00007086803,0.00072994694,0.97852576,0.00009797899,0.0005091557,0.00014757481,0.00516713,0.0083067175,0.0006291846,0.0021205535,0.0036602982,0.00003486087],"about_ca_topic_score_codex":0.04489373,"about_ca_topic_score_gemma":0.035956115,"teacher_disagreement_score":0.04489373,"about_ca_system_score_codex":0.0017156769,"about_ca_system_score_gemma":0.0012625728,"threshold_uncertainty_score":0.08926487},"labels":[],"label_agreement":null},{"id":"W4311651489","doi":"10.1155/2022/6816851","title":"Estimating the Potential Modal Split of Any Future Mode Using Revealed Preference Data","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Mode choice; Multinomial logistic regression; Discrete choice; Mode (computer interface); Modal; Revealed preference; Preference; Mixed logit; Econometrics; Function (biology); Basis (linear algebra); Constant (computer programming); Multinomial distribution; Choice set; Mathematics; Statistics; Computer science; Logistic regression; Engineering; Geometry; Public transport","score_opus":0.02781760049798916,"score_gpt":0.27496934164221437,"score_spread":0.24715174114422522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311651489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83824074,0.00046753263,0.13910727,0.00039252042,0.000045449433,0.00016604051,0.016535597,0.00030099676,0.004743837],"genre_scores_gemma":[0.94297993,0.00017766295,0.040149115,0.000039910534,0.0000110402525,0.00018126729,0.01444197,0.000039574654,0.0019796246],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99807763,0.00092001364,0.000109190005,0.00047316126,0.00026314677,0.0001567258],"domain_scores_gemma":[0.9924154,0.0049790703,0.0006906629,0.0010388541,0.00068363635,0.00019224953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051396918,0.0006571668,0.0008153652,0.0021677702,0.00036352564,0.0016616131,0.0012633229,0.001035322,0.0036995008],"category_scores_gemma":[0.019397609,0.0003776273,0.0015678051,0.0023248817,0.00044174684,0.0022003946,0.0011372329,0.0014403571,0.0014066075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011515686,0.0004531759,0.5445935,0.00053857296,0.0006319111,0.0004980472,0.0014090084,0.3150179,0.0022535343,0.020261927,0.009680811,0.10350996],"study_design_scores_gemma":[0.00005996214,0.00020554228,0.11636114,0.00015793656,0.00012728327,0.00021799405,0.0012501434,0.8495878,0.0017039452,0.020706097,0.009518166,0.000104088096],"about_ca_topic_score_codex":0.020517172,"about_ca_topic_score_gemma":0.024273662,"teacher_disagreement_score":0.020517172,"about_ca_system_score_codex":0.0010564785,"about_ca_system_score_gemma":0.00070555316,"threshold_uncertainty_score":0.040795505},"labels":[],"label_agreement":null},{"id":"W4311874458","doi":"10.1177/03611981221140369","title":"Wheelchair Users’ Perspective on Transportation Service Hailed Through Uber and Lyft Apps","year":2022,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Wheelchair; Descriptive statistics; Service (business); Perspective (graphical); Applied psychology; Sample (material); Perception; Internet privacy; Psychology; Computer security; Transport engineering; Engineering; Advertising; Computer science; Business; Marketing; World Wide Web; Artificial intelligence","score_opus":0.07488246156418628,"score_gpt":0.35880395073424187,"score_spread":0.2839214891700556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311874458","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.982025,0.00087002333,0.0007148823,0.003915788,0.000041598367,0.00000885845,0.00009608327,0.000018857269,0.012308931],"genre_scores_gemma":[0.9960277,0.0010739118,0.00021071188,0.0005948996,0.000016746397,0.0000075282214,0.000030272433,0.000009506106,0.0020287205],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9978806,0.0012755328,0.000101741236,0.00009503824,0.00035064542,0.0002965257],"domain_scores_gemma":[0.99730647,0.00132394,0.00043551452,0.00008034403,0.0004382184,0.0004155443],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015676164,0.0001977923,0.00024172528,0.0007953956,0.0027544298,0.0041391104,0.00035718203,0.0009112409,0.005227354],"category_scores_gemma":[0.0049849083,0.0001704622,0.0003139874,0.0008788158,0.0017215523,0.004200829,0.0020323086,0.00090181053,0.0006050357],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010926104,0.0001074414,0.13729191,0.00031949958,0.000048121987,0.003544799,0.7988261,0.00017047927,0.0023846389,0.004730511,0.0063422127,0.04612502],"study_design_scores_gemma":[0.0000021583742,0.00013205812,0.055360857,0.00026612697,0.000033558907,0.001665565,0.9102081,0.0002065249,0.0003974463,0.00039871447,0.03128295,0.000045902674],"about_ca_topic_score_codex":0.0139873875,"about_ca_topic_score_gemma":0.027672196,"teacher_disagreement_score":0.0139873875,"about_ca_system_score_codex":0.00094294874,"about_ca_system_score_gemma":0.0008897836,"threshold_uncertainty_score":0.027811944},"labels":[],"label_agreement":null},{"id":"W4312235499","doi":"10.1109/iscc55528.2022.9912963","title":"Adaptive Q-leaming-supported Resource Allocation Model in Vehicular Fogs","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Symposium on Computers and Communications (ISCC)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Computer science; Reinforcement learning; Distributed computing; Resource allocation; Cloud computing; Cloudlet; Resource management (computing); Vehicular ad hoc network; Quality of service; Resource (disambiguation); Fog; Compromise; Computer network; Wireless; Wireless ad hoc network; Artificial intelligence; Telecommunications","score_opus":0.018492349625111603,"score_gpt":0.2237186982422464,"score_spread":0.20522634861713482,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312235499","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09594462,0.0014024556,0.88339627,0.001367266,0.00034081232,0.0001287105,0.0003742827,0.00029639984,0.01674921],"genre_scores_gemma":[0.98466927,0.00034889815,0.009398606,0.0001277538,0.00004772655,0.00006367853,0.000068270594,0.000019285826,0.005256534],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993074,0.00014484336,0.000027014727,0.00016463791,0.000121355624,0.00023468575],"domain_scores_gemma":[0.99932003,0.00025471018,0.00009336073,0.000029349674,0.00021690736,0.00008557553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009846039,0.0007837629,0.0011702909,0.0005054368,0.00071412773,0.0013942396,0.0023769813,0.001382889,0.0024067196],"category_scores_gemma":[0.0016676346,0.00044806054,0.00070602866,0.0006275654,0.0010930487,0.0012790565,0.0011106778,0.0011747831,0.0002896302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000769252,0.000036977817,0.0006348563,0.000051842722,0.00003664365,0.00028373286,0.00011500779,0.94774246,0.0016297651,0.043450207,0.0015968821,0.004344594],"study_design_scores_gemma":[0.000005639755,0.000009761375,0.00007049045,0.0000025928166,0.000005267624,0.000012579681,0.0000111439385,0.9970962,0.000047689042,0.0025348582,0.00019931681,0.000004427446],"about_ca_topic_score_codex":0.019435167,"about_ca_topic_score_gemma":0.01079025,"teacher_disagreement_score":0.019435167,"about_ca_system_score_codex":0.0018202775,"about_ca_system_score_gemma":0.0013230634,"threshold_uncertainty_score":0.038644075},"labels":[],"label_agreement":null},{"id":"W4312366087","doi":"10.1109/tits.2022.3215512","title":"Optimization Framework for Crowd-Sourced Delivery Services With the Consideration of Shippers’ Acceptance Uncertainties","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Matching (statistics); Compensation (psychology); Order (exchange); Computer science; Operations research; Scheme (mathematics); Bipartite graph; Work (physics); Stochastic optimization; Mathematical optimization; Business; Engineering; Mathematics; Statistics","score_opus":0.018423970296775484,"score_gpt":0.2300580051545757,"score_spread":0.21163403485780022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312366087","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014754952,0.00047981663,0.97987354,0.00042016956,0.00006953069,0.000121616904,0.00012961272,0.00017677141,0.0039739525],"genre_scores_gemma":[0.8064971,0.0007611596,0.18292262,0.0003984994,0.00014037683,0.000508733,0.00032972344,0.00019106,0.0082507385],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986292,0.0005127539,0.000048721584,0.00025382696,0.00027196805,0.00028350117],"domain_scores_gemma":[0.9984847,0.00090156106,0.00016035578,0.000057963254,0.00024575499,0.00014969756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002932497,0.0016820799,0.002058876,0.0008857741,0.0006519526,0.0018243307,0.0020632688,0.0020050034,0.005438207],"category_scores_gemma":[0.0036892726,0.00095388014,0.0013780495,0.0010247608,0.0008788259,0.0012626324,0.0018168949,0.0018384454,0.00048060613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028508508,0.000029708232,0.00021262366,0.000047164005,0.00002465512,0.000047228776,0.00002608437,0.9871263,0.0002709402,0.006516332,0.0006404256,0.0050300723],"study_design_scores_gemma":[0.000006858663,0.000015951462,0.00006148843,0.000004694576,0.000006074683,0.0000067124324,0.000011838936,0.997154,0.000053856165,0.002418501,0.0002562128,0.0000038100852],"about_ca_topic_score_codex":0.013444822,"about_ca_topic_score_gemma":0.006321534,"teacher_disagreement_score":0.013444822,"about_ca_system_score_codex":0.0020441222,"about_ca_system_score_gemma":0.0030469599,"threshold_uncertainty_score":0.0267331},"labels":[],"label_agreement":null},{"id":"W4312703873","doi":"10.2139/ssrn.4285203","title":"The Passenger's Willingness to Wait with Sunk Waiting Time: An Empirical Study in Ride-Sourcing Market","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina; Western University","funders":"","keywords":"Sunk costs; Queueing theory; Queue; Order (exchange); Metropolitan area; Business; Microeconomics; Economics; Econometrics; Advertising; Computer science; Computer network; Finance","score_opus":0.0073076931820102685,"score_gpt":0.24274958916500788,"score_spread":0.2354418959829976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312703873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99834466,0.000054540254,0.00013652701,0.00008577826,0.0000041861495,0.000011414544,0.00006959817,0.0000032814498,0.001289976],"genre_scores_gemma":[0.99861276,0.000036386587,0.00004956784,0.00001879977,0.000007098644,0.000006854444,0.000113159134,0.0000029206803,0.00115236],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99935657,0.00017858762,0.000042016392,0.00011233922,0.000110847395,0.0001996877],"domain_scores_gemma":[0.98199856,0.01158166,0.0031640278,0.00044947266,0.0008375892,0.0019686548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002664149,0.000332506,0.00039767157,0.0008243784,0.00087350333,0.0024829202,0.0009680073,0.001911107,0.012673687],"category_scores_gemma":[0.010021316,0.00026435274,0.000851859,0.0012716491,0.0008238751,0.0031899621,0.00057221955,0.002820713,0.0010382032],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023070653,0.0050325817,0.9495193,0.00021849823,0.00029906663,0.0015040548,0.0069868146,0.007817797,0.0031503725,0.008543573,0.0018222022,0.012798689],"study_design_scores_gemma":[0.00014208385,0.0019212645,0.9288189,0.00004990324,0.00031593887,0.00040119057,0.029752025,0.03196135,0.0009397543,0.0028168592,0.0027473338,0.00013345708],"about_ca_topic_score_codex":0.012272436,"about_ca_topic_score_gemma":0.009941604,"teacher_disagreement_score":0.012673687,"about_ca_system_score_codex":0.0011564207,"about_ca_system_score_gemma":0.0011076428,"threshold_uncertainty_score":0.042397678},"labels":[],"label_agreement":null},{"id":"W4312808061","doi":"10.1007/978-3-030-72322-4_126-1","title":"Energy-Smart Transportation Systems","year":2022,"lang":"en","type":"book-chapter","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Electrification; Transport engineering; Sustainable transport; Greenhouse gas; Environmental economics; Engineering; Business; Sustainability; Electricity; Economics","score_opus":0.012398450470008876,"score_gpt":0.1839838540266793,"score_spread":0.17158540355667043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312808061","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00048299783,0.007211142,0.006119098,0.0016935603,0.0010886798,0.000021297614,0.00008874159,0.0000902873,0.9832041],"genre_scores_gemma":[0.009477003,0.008320938,0.0018747428,0.00072667893,0.00032678043,0.00003311706,0.000119821394,0.0000864575,0.9790344],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9998776,0.000027364025,0.000003487346,0.000020346739,0.00005759131,0.000013720003],"domain_scores_gemma":[0.999962,0.00001193947,0.0000022143502,0.0000086410955,0.000011584034,0.000003667072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013358703,0.0009003588,0.00028496073,0.0006340593,0.00079463306,0.0023193527,0.0004823996,0.0010509854,0.05313693],"category_scores_gemma":[0.0002595289,0.0002598218,0.00023144356,0.0010469217,0.0008183019,0.0030738802,0.0011520353,0.0015116847,0.017410275],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000057559673,0.000024167426,0.00004798408,0.00010228981,0.0000036590432,0.000038752478,0.00015309826,0.0013628007,0.00047619315,0.6523353,0.23934749,0.10610247],"study_design_scores_gemma":[8.9634403e-7,0.0000048204065,0.000067884204,0.000052618085,0.0000012817612,0.00002778236,0.000061202656,0.0005491774,0.00014043081,0.06179151,0.93729997,0.0000023378534],"about_ca_topic_score_codex":0.0034042913,"about_ca_topic_score_gemma":0.007838393,"teacher_disagreement_score":0.05313693,"about_ca_system_score_codex":0.0015772802,"about_ca_system_score_gemma":0.0008269393,"threshold_uncertainty_score":0.17776072},"labels":[],"label_agreement":null},{"id":"W4312939575","doi":"10.2139/ssrn.4274781","title":"Fuzzy Guided Evolutionary Optimisation of Multi-Objective 3-Echelon Demand-Responsive Public Transit Systems","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; RTDS Technologies (Canada)","funders":"Economic and Social Research Council","keywords":"Fuzzy logic; Public transport; Transit (satellite); Computer science; Business; Engineering; Artificial intelligence; Transport engineering","score_opus":0.017687886505027457,"score_gpt":0.23871237443159338,"score_spread":0.22102448792656593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312939575","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5801427,0.0005223221,0.388516,0.0006098724,0.00015060444,0.00016935352,0.00037090457,0.0002792407,0.029238978],"genre_scores_gemma":[0.9823484,0.00007040613,0.013724093,0.000042341388,0.000013047907,0.00008375707,0.00007602619,0.000026602476,0.0036153565],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961084,0.0001607309,0.000012503197,0.00004988008,0.0000580542,0.00010798765],"domain_scores_gemma":[0.99923325,0.00047328597,0.0000812435,0.00003169062,0.00011154481,0.000069029615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010304698,0.00087546563,0.0016439517,0.0008137666,0.0007033156,0.0017572932,0.001015391,0.0021385306,0.003562807],"category_scores_gemma":[0.0017910489,0.0005786866,0.0010711923,0.00090576406,0.0006397637,0.00057993585,0.0009670463,0.00088458863,0.00022055126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002648852,0.000015579923,0.000100885285,0.000010823777,0.000011691402,0.000027869972,0.000011448094,0.99751043,0.00022890905,0.00047864305,0.00006853741,0.0015086215],"study_design_scores_gemma":[0.0000049287296,0.000019089432,0.000075751,0.000001634001,0.0000025858496,0.0000031131565,0.000010827773,0.9995016,0.000059972288,0.00025619587,0.00006237552,0.0000018079379],"about_ca_topic_score_codex":0.013409935,"about_ca_topic_score_gemma":0.00834337,"teacher_disagreement_score":0.013409935,"about_ca_system_score_codex":0.0015404556,"about_ca_system_score_gemma":0.0011016033,"threshold_uncertainty_score":0.02666378},"labels":[],"label_agreement":null},{"id":"W4313225615","doi":"10.3390/su15010460","title":"Moving toward a More Sustainable Autonomous Mobility, Case of Heterogeneity in Preferences","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"University Canada West","keywords":"Taxis; Preference; Modal shift; Mixed logit; Sustainable transport; Travel behavior; Modal; Logit; Business; Revealed preference; Computer science; Transport engineering; Marketing; Environmental economics; Econometrics; Logistic regression; Economics; Sustainability; Microeconomics; Public transport; Engineering; Ecology","score_opus":0.01387183587673322,"score_gpt":0.2685293153857197,"score_spread":0.2546574795089865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313225615","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9406114,0.00030707856,0.04654649,0.0022318924,0.000042382766,0.00013630636,0.00052561157,0.000027962154,0.009570776],"genre_scores_gemma":[0.99750745,0.00004914585,0.0013446765,0.000065445456,0.0000135214905,0.000036447076,0.00007506213,0.0000017761743,0.00090650615],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967481,0.0015673592,0.00018458012,0.00058951037,0.0002942137,0.000616256],"domain_scores_gemma":[0.99260736,0.0038070977,0.00196422,0.0009634566,0.00038919502,0.0002687318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003553551,0.0003944199,0.0007380969,0.0008666401,0.00090947875,0.00197576,0.00087172363,0.0012372785,0.006533054],"category_scores_gemma":[0.010077321,0.00027413538,0.0012493863,0.0012695694,0.0010369547,0.0017666909,0.0012923854,0.0013294695,0.00039644496],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008182263,0.00081112096,0.68758416,0.0006288528,0.0011252539,0.010507177,0.0051140515,0.060978476,0.0038696378,0.15562636,0.003533693,0.06940298],"study_design_scores_gemma":[0.00029353212,0.0010611911,0.41465613,0.00031195773,0.00066561706,0.005534115,0.028253432,0.2661399,0.0027350967,0.266556,0.013516668,0.0002762994],"about_ca_topic_score_codex":0.0059508714,"about_ca_topic_score_gemma":0.006245345,"teacher_disagreement_score":0.006533054,"about_ca_system_score_codex":0.0011920496,"about_ca_system_score_gemma":0.00067104184,"threshold_uncertainty_score":0.021855235},"labels":[],"label_agreement":null},{"id":"W4313250949","doi":"10.1111/mice.12958","title":"Modeling, equilibrium, and demand management for mobility and delivery services in Mobility‐as‐a‐Service ecosystems","year":2022,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Regina","funders":"","keywords":"Computer science; Service (business); Incentive; Service delivery framework; Multimodal transport; Environmental economics; Operations research; Business; Microeconomics; Economics; Marketing; Engineering","score_opus":0.005097845602064915,"score_gpt":0.18423138523198124,"score_spread":0.17913353962991632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313250949","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3192645,0.00083114684,0.6431561,0.005136051,0.00020303964,0.00017073422,0.0011253908,0.00033347931,0.029779498],"genre_scores_gemma":[0.9699574,0.00043425176,0.019972796,0.000114558425,0.000062043524,0.00013463569,0.0002399042,0.000072213064,0.009012132],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990356,0.0003885139,0.00004500176,0.00017863313,0.00010421655,0.0002481031],"domain_scores_gemma":[0.9984705,0.00093323947,0.00017359428,0.000056760462,0.00021796973,0.0001479822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017489544,0.00090216857,0.0011138312,0.0012815612,0.0011881737,0.00336572,0.0022442343,0.0021603936,0.0045502954],"category_scores_gemma":[0.0045622448,0.00087880826,0.0012390339,0.0012993743,0.0016770805,0.0039447662,0.002127146,0.0015301869,0.00039466645],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035719575,0.000069328315,0.0019370178,0.000033243352,0.000032112333,0.000065304375,0.00013095081,0.8872211,0.0003472898,0.10524288,0.0010311311,0.0038539434],"study_design_scores_gemma":[0.0000051578004,0.0000075181233,0.00020945577,0.0000042489673,0.0000064747323,0.000008542092,0.00009250947,0.9775237,0.000052588297,0.021607744,0.00047436994,0.000007743899],"about_ca_topic_score_codex":0.06533936,"about_ca_topic_score_gemma":0.043827727,"teacher_disagreement_score":0.06533936,"about_ca_system_score_codex":0.0052178777,"about_ca_system_score_gemma":0.0037602906,"threshold_uncertainty_score":0.1299181},"labels":[],"label_agreement":null},{"id":"W4313429600","doi":"10.1155/2022/2000835","title":"A Travel Demand Response Model in MaaS Based on Spatiotemporal Preference Clustering","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Foundation of Gansu Province; National Natural Science Foundation of China","keywords":"Reservation; Cluster analysis; Computer science; Preference; DBSCAN; Hierarchical clustering; Mathematical optimization; Data mining; Fuzzy clustering; Mathematics; Statistics; Machine learning; CURE data clustering algorithm","score_opus":0.022344204113706755,"score_gpt":0.24520620776953805,"score_spread":0.2228620036558313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313429600","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10452963,0.0003178964,0.8824577,0.0006938779,0.00010365752,0.00017100883,0.0006720317,0.0006433864,0.010410974],"genre_scores_gemma":[0.95133656,0.0002512207,0.03871275,0.0000923459,0.00003010863,0.00018164444,0.0005190513,0.000068280235,0.008808107],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992238,0.00014993115,0.00004812513,0.00025165797,0.00016324552,0.0001632273],"domain_scores_gemma":[0.9993973,0.000118588345,0.000075118696,0.000051452742,0.00029119264,0.000066337925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007301804,0.000872203,0.0007270724,0.00063857215,0.00083755434,0.001349636,0.002420779,0.0010648018,0.0039395383],"category_scores_gemma":[0.0015335353,0.0004164973,0.0010167132,0.0014406445,0.00048919057,0.0017957952,0.0010807712,0.0009848985,0.000688995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006002388,0.000026050902,0.0014236664,0.000036908048,0.000026713786,0.00007826977,0.0000802614,0.97766817,0.0012002452,0.010462991,0.0010981235,0.007838482],"study_design_scores_gemma":[0.0000026787973,0.000009035708,0.00016442918,0.0000013709267,0.0000046424184,0.000012257955,0.000028084438,0.9980082,0.00011492962,0.001287866,0.00036186652,0.0000047363706],"about_ca_topic_score_codex":0.0529248,"about_ca_topic_score_gemma":0.025834998,"teacher_disagreement_score":0.0529248,"about_ca_system_score_codex":0.0020504156,"about_ca_system_score_gemma":0.0014103069,"threshold_uncertainty_score":0.10523349},"labels":[],"label_agreement":null},{"id":"W4313680449","doi":"10.2139/ssrn.4319324","title":"Integrated Strategic and Tactical Design of Multi-Echelon City Distribution Systems with Vehicles Synchronization: Case of the Greater Montréal Area","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Synchronization (alternating current); Distribution (mathematics); Operations management; Computer science; Operations research; Engineering; Business; Telecommunications; Mathematics","score_opus":0.025327218800743477,"score_gpt":0.22193820385717158,"score_spread":0.1966109850564281,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313680449","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7659152,0.00031992357,0.16349992,0.00084116624,0.000046977686,0.00032290464,0.00024364791,0.00035197265,0.068458214],"genre_scores_gemma":[0.9912587,0.00003745413,0.0050877826,0.000016391297,0.00000410344,0.000021604492,0.000023231702,0.00001317692,0.0035375282],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940884,0.00017800335,0.000012302101,0.00007080802,0.000109198925,0.00022084848],"domain_scores_gemma":[0.9995598,0.00011424793,0.00005200465,0.000027976976,0.00015482986,0.000091165384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007155314,0.0005241907,0.0004225828,0.00052499655,0.001171448,0.0027250526,0.0010362427,0.0008826492,0.004184862],"category_scores_gemma":[0.0009853875,0.00036819157,0.0004135303,0.00069228205,0.0010024245,0.00077410525,0.00092365174,0.00043674803,0.00027693968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000074571544,0.00004236419,0.0010988866,0.0000190303,0.000015694855,0.00025347443,0.00009143075,0.9798881,0.002380653,0.008068252,0.0003081909,0.0077594137],"study_design_scores_gemma":[0.00004944533,0.00014339993,0.0019515944,0.0000072318912,0.000027893779,0.000037427944,0.000448906,0.9918636,0.0010944465,0.0024962535,0.0018572741,0.000022563492],"about_ca_topic_score_codex":0.20265381,"about_ca_topic_score_gemma":0.26210797,"teacher_disagreement_score":0.7973462,"about_ca_system_score_codex":0.005831064,"about_ca_system_score_gemma":0.004527731,"threshold_uncertainty_score":0.4029485},"labels":[],"label_agreement":null},{"id":"W4315486068","doi":"10.1080/03081060.2022.2162518","title":"Who will adopt private automated vehicles and automated shuttle buses? Testing the roles of past experience and performance expectancy","year":2023,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; Toronto Metropolitan University","funders":"Federation for the Humanities and Social Sciences","keywords":"Expectancy theory; Public transport; Transport engineering; Unified theory of acceptance and use of technology; Engineering; Plan (archaeology); Master plan; Operations management; Business; Psychology; Engineering management; Geography; Social psychology","score_opus":0.01567148060598169,"score_gpt":0.24061779469822003,"score_spread":0.22494631409223834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4315486068","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988771,0.00005431167,0.00005651421,0.00009717189,0.000002153707,0.0000049451737,0.00003136506,7.8784024e-7,0.00087572],"genre_scores_gemma":[0.999746,0.000024972702,0.000017848324,0.000011644227,0.0000013574981,0.0000023746213,0.000029428009,4.76245e-7,0.00016588965],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99813557,0.0007449932,0.000089510344,0.00021501367,0.00033714678,0.00047778495],"domain_scores_gemma":[0.97461104,0.013982282,0.0055184644,0.00087301544,0.001795702,0.0032195242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036638076,0.0001489319,0.00025920916,0.0005248056,0.0005628097,0.0016047407,0.0005905877,0.0005161778,0.002879918],"category_scores_gemma":[0.017456751,0.00021515672,0.0004888002,0.00057188096,0.0013796681,0.0011644119,0.0006701998,0.0008391,0.00024528924],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010347623,0.00011793602,0.9934772,0.000008148899,0.000041452928,0.00003723777,0.002929021,0.00007997046,0.0000578703,0.0001517988,0.00005186026,0.0029439963],"study_design_scores_gemma":[0.000005360835,0.0001337562,0.9923712,0.000014056409,0.000019332836,0.000033185057,0.006482057,0.00050767546,0.000053641004,0.00008096832,0.0002917923,0.00000698078],"about_ca_topic_score_codex":0.16389082,"about_ca_topic_score_gemma":0.18429124,"teacher_disagreement_score":0.16389082,"about_ca_system_score_codex":0.0015574583,"about_ca_system_score_gemma":0.0017433795,"threshold_uncertainty_score":0.3258738},"labels":[],"label_agreement":null},{"id":"W4316011108","doi":"10.2172/1908698","title":"Fort Erie On-Demand Transit Case Study","year":2023,"lang":"en","type":"report","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Office of Energy Efficiency; Office of Energy Efficiency and Renewable Energy; National Renewable Energy Laboratory; U.S. Department of Energy","keywords":"Kilometer; Public transport; Transport engineering; Per capita; Population; Service (business); Transit (satellite); Mile; Square (algebra); Quarter (Canadian coin); Business; Geography; Agricultural economics; Engineering; Economics","score_opus":0.13344016098403752,"score_gpt":0.35767116265297877,"score_spread":0.22423100166894125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4316011108","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90559363,0.00035836868,0.0025319485,0.0016903407,0.00008125642,0.0004642419,0.0039898986,0.00014066951,0.085149504],"genre_scores_gemma":[0.9604895,0.00048636558,0.0037341672,0.00031506148,0.00003179812,0.00017675135,0.0033405665,0.00004941809,0.031376347],"study_design_codex":"not_applicable","study_design_gemma":"qualitative","domain_scores_codex":[0.9995395,0.0000967507,0.000018865192,0.000056952682,0.000103997314,0.00018394248],"domain_scores_gemma":[0.99929917,0.00015365978,0.0000538473,0.00006185268,0.0002805272,0.00015092173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003656812,0.00049190776,0.00021845818,0.0006612852,0.0027166372,0.00096218276,0.0011390764,0.0013442265,0.0076466524],"category_scores_gemma":[0.0010003042,0.00015671256,0.00030171202,0.0016040762,0.0004680447,0.0007869079,0.00074703636,0.0006303501,0.0009202137],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020417445,0.004842352,0.20583105,0.0015201091,0.0002590566,0.13547404,0.020711007,0.13771777,0.011267485,0.05652046,0.30700463,0.116810374],"study_design_scores_gemma":[0.00048564165,0.0015537955,0.15877044,0.0004840003,0.0001817393,0.018740548,0.113130204,0.12094047,0.006131708,0.0060834396,0.5732776,0.00022039755],"about_ca_topic_score_codex":0.37493673,"about_ca_topic_score_gemma":0.63638395,"teacher_disagreement_score":0.6250633,"about_ca_system_score_codex":0.004919307,"about_ca_system_score_gemma":0.0019642846,"threshold_uncertainty_score":0.7455087},"labels":[],"label_agreement":null},{"id":"W4316464395","doi":"10.3390/su15021649","title":"Usage Intention of Shared Autonomous Vehicles with Dynamic Ride Sharing on Long-Distance Trips","year":2023,"lang":"en","type":"article","venue":"Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"TRIPS architecture; Travel behavior; License; Business; Sustainable transport; Order (exchange); Key (lock); Marketing; Sample (material); Transport engineering; Computer science; Sustainability; Engineering; Computer security","score_opus":0.009387473812597249,"score_gpt":0.24857183401223187,"score_spread":0.23918436019963463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4316464395","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987311,0.0000214796,0.00023620049,0.000038069164,0.0000023780046,0.000008423591,0.000055579952,0.000003063522,0.0009036982],"genre_scores_gemma":[0.99928075,0.000028703736,0.00019690864,0.000009990894,0.0000019461363,0.000010014074,0.000082374514,0.0000011063221,0.00038832263],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99939716,0.00025926242,0.00006143146,0.00007613815,0.00012022537,0.000085802625],"domain_scores_gemma":[0.9946079,0.0024618483,0.0014523407,0.00032627827,0.0006403882,0.00051122275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010153136,0.0001473581,0.00014861143,0.00040600952,0.00021513805,0.00089278526,0.00025840968,0.00038933987,0.0035624346],"category_scores_gemma":[0.005774766,0.00009423769,0.00063245895,0.00045099584,0.00025857627,0.0006540957,0.00047725593,0.00043475608,0.00039329298],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000087706074,0.0003645867,0.98220545,0.000045937933,0.000075016695,0.00008372851,0.0016466082,0.0011704966,0.00052549026,0.00035637364,0.00019173491,0.013246786],"study_design_scores_gemma":[0.0000035657156,0.00035788282,0.9876824,0.000029969135,0.000059059712,0.000116670555,0.0052940613,0.0049969833,0.00035367627,0.00020458167,0.00088215584,0.00001896934],"about_ca_topic_score_codex":0.006496248,"about_ca_topic_score_gemma":0.008924124,"teacher_disagreement_score":0.006496248,"about_ca_system_score_codex":0.0003107127,"about_ca_system_score_gemma":0.00032661634,"threshold_uncertainty_score":0.012916863},"labels":[],"label_agreement":null},{"id":"W4316591786","doi":"10.1016/j.trpro.2024.12.194","title":"A new stochastic model for carsharing suited to free-floating","year":2025,"lang":"en","type":"article","venue":"Transportation research procedia","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","score_opus":0.06839634382848984,"score_gpt":0.37386009929446984,"score_spread":0.30546375546598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4316591786","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029119957,0.00053331885,0.9621752,0.0006390641,0.00015635585,0.00006667308,0.00049588375,0.00019481045,0.006618819],"genre_scores_gemma":[0.8994062,0.001329556,0.05494565,0.0003779353,0.00026945578,0.0004037456,0.00093731517,0.00017605098,0.042154104],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915826,0.00019186038,0.000042190248,0.00024513283,0.00017605007,0.0001865157],"domain_scores_gemma":[0.99889624,0.0005525455,0.00019135696,0.000066378314,0.00016725584,0.00012612378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010443925,0.0012213611,0.0015021798,0.00061873667,0.00070330524,0.0022091633,0.0027694628,0.0021990414,0.004933184],"category_scores_gemma":[0.0021495218,0.00065141753,0.0017336005,0.00085585006,0.0014659802,0.0021190504,0.001481068,0.002156406,0.00077486766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033417495,0.000038426053,0.00042961305,0.000054377757,0.000028046288,0.00013642746,0.000054187352,0.9107379,0.0018772156,0.08282399,0.0011215643,0.0026649577],"study_design_scores_gemma":[0.0000075186513,0.000015418533,0.00007455109,0.0000036259273,0.0000079774245,0.000019749306,0.000008818398,0.99016917,0.00010643873,0.008930081,0.0006469987,0.000009653081],"about_ca_topic_score_codex":0.014249969,"about_ca_topic_score_gemma":0.008801041,"teacher_disagreement_score":0.014249969,"about_ca_system_score_codex":0.0017220613,"about_ca_system_score_gemma":0.00145913,"threshold_uncertainty_score":0.028334081},"labels":[],"label_agreement":null},{"id":"W4318572180","doi":"10.1155/2023/3187654","title":"Planning Flexible Bus Service as an Alternative to Suspended Bicycle-Sharing Service: A Data-Driven Approach","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Heilongjiang Provincial Postdoctoral Science Foundation; Natural Science Foundation of Heilongjiang Province; National Natural Science Foundation of China","keywords":"Cluster analysis; Service (business); Computer science; Matching (statistics); Key (lock); Path (computing); Transport engineering; Operations research; Trajectory; Data mining; Real-time computing; Engineering; Computer network; Artificial intelligence","score_opus":0.06112843680893426,"score_gpt":0.3336288979062747,"score_spread":0.27250046109734044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318572180","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.103854515,0.00036585177,0.8884945,0.0005775624,0.000045973,0.00027262158,0.0021461882,0.0007939042,0.0034487878],"genre_scores_gemma":[0.72771627,0.0003253226,0.26697475,0.00005196484,0.000022303977,0.00025805508,0.0031887502,0.00009874548,0.001363887],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942833,0.000117588366,0.000042637017,0.00018163062,0.00014071136,0.0000890454],"domain_scores_gemma":[0.9989355,0.00042162125,0.0001503281,0.000096086005,0.00028131492,0.00011526636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083709473,0.00089645106,0.0008506443,0.0019677775,0.00060161337,0.00158674,0.0016040785,0.00085241476,0.0015914917],"category_scores_gemma":[0.002131002,0.0008922733,0.0011667296,0.0022495193,0.0005033464,0.0018407817,0.0008955427,0.0008340966,0.00024017296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038397102,0.00004755529,0.0032166415,0.00009314044,0.000036718455,0.00011397786,0.000069650545,0.96450084,0.00071428483,0.003621608,0.00061925594,0.026927937],"study_design_scores_gemma":[0.0000027434733,0.000010988167,0.00040307952,0.0000051714196,0.000008031099,0.0000118552125,0.000070209775,0.9973448,0.00038545308,0.0012541349,0.00049674563,0.0000067208916],"about_ca_topic_score_codex":0.037847105,"about_ca_topic_score_gemma":0.03815271,"teacher_disagreement_score":0.037847105,"about_ca_system_score_codex":0.0017329439,"about_ca_system_score_gemma":0.0026991705,"threshold_uncertainty_score":0.075253606},"labels":[],"label_agreement":null},{"id":"W4318603638","doi":"10.1109/ssci51031.2022.10022259","title":"A Data-Driven Forecasting and Solution Approach for the Dial-A-Ride Problem with Time Windows","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Symposium Series on Computational Intelligence (SSCI)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Tabu search; Artificial neural network; Benchmark (surveying); Mathematical optimization; Gradient descent; Simulated annealing; Travelling salesman problem; Operations research; Artificial intelligence; Machine learning; Algorithm; Engineering; Mathematics","score_opus":0.04255682157573455,"score_gpt":0.2447510428787917,"score_spread":0.20219422130305714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318603638","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028272055,0.0007485235,0.96677935,0.0006095071,0.00009670207,0.000098631164,0.00029525324,0.0002481016,0.0028518531],"genre_scores_gemma":[0.67564166,0.0011957613,0.3175107,0.00017118943,0.00017037216,0.00055747764,0.0010042276,0.000091636604,0.0036569485],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996791,0.00008245876,0.000023300212,0.00009856615,0.00006688932,0.000049705362],"domain_scores_gemma":[0.9990175,0.00062684366,0.00010287585,0.000029520814,0.00017047227,0.000052875916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010423786,0.001150523,0.0011670269,0.0007854058,0.00045069604,0.0012587563,0.0015059807,0.0014958391,0.0016961173],"category_scores_gemma":[0.0025439458,0.00070170517,0.00093247386,0.0010370461,0.00041579633,0.0011427271,0.0008145083,0.0019484079,0.0001881819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012491427,0.00001603446,0.0002379143,0.000028339413,0.000013556587,0.000020278892,0.000012814131,0.98980916,0.00013022947,0.0015326682,0.00028449018,0.00790203],"study_design_scores_gemma":[0.0000014292209,0.000005441169,0.000026207308,0.0000022835882,0.0000016465048,0.0000019291033,0.0000043348773,0.9992323,0.000047638358,0.0005651196,0.000110456276,0.0000012919005],"about_ca_topic_score_codex":0.018614644,"about_ca_topic_score_gemma":0.013367054,"teacher_disagreement_score":0.018614644,"about_ca_system_score_codex":0.0011488829,"about_ca_system_score_gemma":0.0018738946,"threshold_uncertainty_score":0.037012577},"labels":[],"label_agreement":null},{"id":"W4318823778","doi":"10.2139/ssrn.3610517","title":"Real-Time Spatial-Intertemporal Pricing and Relocation in a Ride-Hailing Network: Near-Optimal Policies and The Value of Dynamic Pricing","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Relocation; Dynamic pricing; Value of time; Value (mathematics); Economics; Microeconomics; Hedonic pricing; Business; Econometrics; Travel time; Computer science; Engineering; Transport engineering","score_opus":0.004375197540327816,"score_gpt":0.21093422308502724,"score_spread":0.20655902554469943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318823778","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53757906,0.001644067,0.4300752,0.0047503905,0.00024332227,0.00016721127,0.0005471849,0.00023691107,0.024756666],"genre_scores_gemma":[0.9851806,0.00058490626,0.008671072,0.000078117984,0.00004959263,0.000033733773,0.000069478316,0.000045677978,0.005286801],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985404,0.0008383554,0.00004575288,0.00020549337,0.000084690386,0.0002853831],"domain_scores_gemma":[0.9897556,0.0077208364,0.000954465,0.00034135586,0.0005481436,0.00067950814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031344008,0.0009684542,0.0021224266,0.001348352,0.0010897513,0.004377232,0.0028817921,0.0032051087,0.0076598804],"category_scores_gemma":[0.019237056,0.0011647596,0.0009110516,0.002011297,0.0024916679,0.007428995,0.0018326001,0.0024547263,0.00039740893],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002817303,0.00012123438,0.0009770326,0.00007469995,0.000046585774,0.0001517786,0.000093555536,0.8765912,0.00041220532,0.11298326,0.0012123744,0.007054356],"study_design_scores_gemma":[0.000023536202,0.000045269495,0.0003031228,0.00001652837,0.000021787593,0.000041698488,0.00014871154,0.9123907,0.00013430713,0.086404495,0.0004474395,0.000022279228],"about_ca_topic_score_codex":0.009005049,"about_ca_topic_score_gemma":0.0064763934,"teacher_disagreement_score":0.009005049,"about_ca_system_score_codex":0.0033641318,"about_ca_system_score_gemma":0.0019300441,"threshold_uncertainty_score":0.025624871},"labels":[],"label_agreement":null},{"id":"W4318824227","doi":"10.2139/ssrn.4330372","title":"E-Scooters as a Last-Mile Transit Solution? Travel Behavior Insights from Los Angeles and Washington D.C","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mile; Transit (satellite); Transport engineering; Travel behavior; Last mile (transportation); Aeronautics; Engineering; Geography; Public transport; Geodesy","score_opus":0.008260464419287985,"score_gpt":0.2228753456211126,"score_spread":0.21461488120182462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318824227","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8358076,0.0019586727,0.00077636255,0.029327493,0.00009569447,0.000040425028,0.0017091832,0.000053598604,0.13023111],"genre_scores_gemma":[0.98458314,0.0012694899,0.00043327973,0.00088147464,0.000024419132,0.000017700797,0.00045860908,0.000021685544,0.012310145],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997714,0.000070436945,0.0000056671424,0.000026492511,0.00003648687,0.000089418885],"domain_scores_gemma":[0.9991986,0.0001533675,0.00011732881,0.000026654376,0.00026831898,0.00023571728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039246544,0.00012391787,0.00013842556,0.00056902395,0.0011478651,0.0029886246,0.00048611083,0.0005942842,0.011935147],"category_scores_gemma":[0.0018231518,0.00009596157,0.00013936778,0.0014635614,0.00043199456,0.0024008045,0.00053592277,0.00092854677,0.0010171899],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010239047,0.0017474649,0.34276018,0.000444323,0.00016045696,0.0007950642,0.017384375,0.005947057,0.0013287775,0.10473216,0.24133857,0.28233764],"study_design_scores_gemma":[0.00015098517,0.00046250375,0.42851186,0.00079919194,0.00017643801,0.00025069603,0.19547766,0.016007034,0.00082621793,0.01143335,0.3458121,0.000091970156],"about_ca_topic_score_codex":0.23315196,"about_ca_topic_score_gemma":0.57563233,"teacher_disagreement_score":0.23315196,"about_ca_system_score_codex":0.002815558,"about_ca_system_score_gemma":0.0024413595,"threshold_uncertainty_score":0.46358973},"labels":[],"label_agreement":null},{"id":"W4319071864","doi":"10.1016/j.spc.2023.02.001","title":"Global warming potential, water footprint, and energy demand of shared autonomous electric vehicles incorporating circular economy practices","year":2023,"lang":"en","type":"article","venue":"Sustainable Production and Consumption","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"American University of Sharjah","keywords":"Ecological footprint; Footprint; Life-cycle assessment; Work (physics); Water use; Environmental science; Environmental economics; Circular economy; Energy mix; Environmental engineering; Energy (signal processing); Carbon footprint; Natural resource economics; Engineering; Production (economics); Greenhouse gas; Economics; Sustainability; Electricity generation; Ecology; Geography; Mechanical engineering","score_opus":0.012257584379700643,"score_gpt":0.2317185354232758,"score_spread":0.21946095104357516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319071864","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99738485,0.000016064567,0.00054192817,0.000023107508,0.00000211744,0.0000034470743,0.000050899656,0.0000056642243,0.0019719528],"genre_scores_gemma":[0.99934727,0.000010546993,0.000136239,0.000001976855,4.3705685e-7,0.0000023173109,0.000040721206,0.0000018961904,0.0004586533],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998272,0.000055644883,0.0000055241476,0.000035607183,0.000031779993,0.000044238186],"domain_scores_gemma":[0.99926966,0.00036452268,0.0000657113,0.00006839746,0.00019054422,0.000041060848],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004686056,0.00021306198,0.0002060968,0.0002998447,0.00023767902,0.00072579866,0.0003522421,0.00033414314,0.0031371864],"category_scores_gemma":[0.0011674556,0.00012627731,0.00035424146,0.0006899504,0.00039445848,0.0013044322,0.00044712145,0.0002471365,0.00017602934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026353758,0.00087668176,0.13336436,0.00015558062,0.00023966302,0.00043645274,0.0007742417,0.7737145,0.016188787,0.019384922,0.00080342114,0.051426068],"study_design_scores_gemma":[0.00009821329,0.002097021,0.141495,0.000030442268,0.00035347446,0.00012558988,0.006057781,0.8075248,0.020076497,0.01651946,0.005502509,0.00011911245],"about_ca_topic_score_codex":0.014731944,"about_ca_topic_score_gemma":0.02212969,"teacher_disagreement_score":0.014731944,"about_ca_system_score_codex":0.0012207307,"about_ca_system_score_gemma":0.000709135,"threshold_uncertainty_score":0.029292405},"labels":[],"label_agreement":null},{"id":"W4319299244","doi":"10.1155/2023/9283130","title":"An Optimization Model for Structuring a Car-Sharing Fleet Considering Traffic Congestion Intensity","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Horizon 2020; Foundation for Science and Technology; MIT Portugal","keywords":"Purchasing; Traffic congestion; Energy consumption; Diesel fuel; Traffic intensity; Transport engineering; Total cost; Environmental economics; Computer science; Business; Automotive engineering; Engineering; Economics; Telecommunications; Marketing","score_opus":0.02331497278363183,"score_gpt":0.2668955200127332,"score_spread":0.24358054722910139,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319299244","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17684065,0.0011122235,0.78798884,0.000960616,0.00012045106,0.0002896805,0.0011195012,0.00027290022,0.031295028],"genre_scores_gemma":[0.94095254,0.0006258062,0.041348398,0.00009964127,0.00003717032,0.00039882536,0.0004993606,0.00008075332,0.015957536],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947053,0.0001947206,0.000016149581,0.00010812273,0.00006782389,0.00014270378],"domain_scores_gemma":[0.99946445,0.00027505553,0.000081105594,0.000015724881,0.00008726216,0.00007644282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010934481,0.0012492227,0.0013884077,0.00081284903,0.0006700714,0.0018219097,0.0015723708,0.0022646678,0.005848796],"category_scores_gemma":[0.0014468444,0.0008462467,0.0012794196,0.0011834719,0.00077881746,0.0013623864,0.0010584651,0.0013407079,0.00044916492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012576248,0.000008341593,0.00012350534,0.00001189297,0.0000076040205,0.000030910658,0.000006979925,0.9970798,0.00015844007,0.001768171,0.00013572832,0.0006560752],"study_design_scores_gemma":[0.0000057251877,0.00001584349,0.000104199105,0.000003898591,0.000006619165,0.000006716609,0.000014787627,0.99866927,0.00005007611,0.0009156475,0.00020332146,0.0000038145902],"about_ca_topic_score_codex":0.026284471,"about_ca_topic_score_gemma":0.013708232,"teacher_disagreement_score":0.026284471,"about_ca_system_score_codex":0.0024233276,"about_ca_system_score_gemma":0.0022769785,"threshold_uncertainty_score":0.052262902},"labels":[],"label_agreement":null},{"id":"W4319985834","doi":"10.1088/978-0-7503-5306-9","title":"Transportation Technologies for a Sustainable Future","year":2023,"lang":"en","type":"book","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Business; Environmental planning; Environmental science","score_opus":0.008437744852077194,"score_gpt":0.21674759567399818,"score_spread":0.208309850821921,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319985834","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00065523095,0.034296434,0.007304674,0.013177073,0.0071724467,0.0000560985,0.00043058346,0.0005737046,0.9363338],"genre_scores_gemma":[0.0049110204,0.023190325,0.004076476,0.0023017423,0.00091503386,0.00005460502,0.0004427664,0.00027421842,0.9638338],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99943143,0.000057982375,0.000014995264,0.00006918416,0.00036588925,0.00006046389],"domain_scores_gemma":[0.9998286,0.00003530528,0.00001169633,0.00002458473,0.000070842354,0.00002899423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028767792,0.0010787828,0.00043352944,0.00080470066,0.0014216575,0.005598883,0.0007828048,0.0017674757,0.07404235],"category_scores_gemma":[0.0008498755,0.0003175218,0.0005411253,0.0013575926,0.0010462148,0.0058737104,0.002076642,0.0033338952,0.06599484],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059038252,0.000014666724,0.000053478034,0.00018939801,0.000005204917,0.000051822848,0.00023744373,0.00051380077,0.00040977917,0.15257703,0.74558264,0.10035884],"study_design_scores_gemma":[4.920218e-7,0.000002233319,0.000026019727,0.000070617476,8.1642935e-7,0.000031023737,0.000043006108,0.00007981986,0.000041590076,0.007192322,0.99250984,0.000002225586],"about_ca_topic_score_codex":0.004231515,"about_ca_topic_score_gemma":0.0063225646,"teacher_disagreement_score":0.07404235,"about_ca_system_score_codex":0.0024976162,"about_ca_system_score_gemma":0.002702853,"threshold_uncertainty_score":0.24769634},"labels":[],"label_agreement":null},{"id":"W4320012278","doi":"10.2139/ssrn.4324581","title":"Enhancing Equitable Access to Taxis in NYC Through Search Friction Reduction and Spatial Pricing","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Taxis; Reduction (mathematics); Transport engineering; Business; Economics; Engineering; Mathematics","score_opus":0.02061299791044472,"score_gpt":0.29137394880114836,"score_spread":0.2707609508907036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320012278","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81470317,0.00101513,0.06329862,0.005957557,0.00011947992,0.00032512718,0.0008920965,0.00093977107,0.11274915],"genre_scores_gemma":[0.9893489,0.00011970755,0.0035809,0.00011434214,0.00002540322,0.000030486859,0.00010981295,0.00003823136,0.006632337],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880135,0.00039079032,0.000037046084,0.00014172032,0.00026738967,0.00036171646],"domain_scores_gemma":[0.9956012,0.0020105708,0.00059278315,0.0005288321,0.00071322545,0.0005533958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019552007,0.00030744512,0.00073710957,0.0012512131,0.00081755494,0.0027971114,0.0011907745,0.0010834608,0.0346252],"category_scores_gemma":[0.01666814,0.0002545888,0.0003770244,0.001587965,0.0007341358,0.004163254,0.0023272575,0.0011851195,0.0015002155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014539178,0.002539177,0.04725074,0.00023476327,0.00016388852,0.00050237007,0.00090118666,0.31787208,0.00398804,0.23958845,0.038820807,0.34668463],"study_design_scores_gemma":[0.00046027405,0.00062075397,0.028890504,0.00010030167,0.00019151156,0.00022593328,0.0021900819,0.7802644,0.0032300244,0.15627283,0.027458414,0.000094987445],"about_ca_topic_score_codex":0.033410285,"about_ca_topic_score_gemma":0.044973888,"teacher_disagreement_score":0.0346252,"about_ca_system_score_codex":0.0024484152,"about_ca_system_score_gemma":0.0035979967,"threshold_uncertainty_score":0.115832865},"labels":[],"label_agreement":null},{"id":"W4320896034","doi":"10.1155/2023/7593649","title":"Optimization of a Semiflexible Demand-Responsive Feeder System in Suburban Areas Using a Memetic Algorithm","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"KU Leuven","keywords":"Memetic algorithm; Service (business); Computer science; Public transport; Service level; Operations research; Order (exchange); Bus network; Level of service; Transport engineering; On demand; Mathematical optimization; Local search (optimization); Algorithm; Engineering; Business; Marketing; Mathematics","score_opus":0.01341835708543639,"score_gpt":0.2537409551722381,"score_spread":0.2403225980868017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320896034","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38909608,0.00046154694,0.59754145,0.0004365238,0.00006679884,0.00014337279,0.00013747442,0.0004696088,0.011647122],"genre_scores_gemma":[0.96178985,0.00011834356,0.034381565,0.000068350986,0.000009693816,0.00011902528,0.000060922048,0.000021244012,0.0034308927],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982554,0.000065034685,0.0000070784695,0.000032552856,0.000026417272,0.000043452823],"domain_scores_gemma":[0.9995634,0.00025121012,0.00007354421,0.000016283191,0.000062487445,0.00003316266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064255996,0.0008010707,0.0009292769,0.0005339035,0.00041207115,0.00088228687,0.0007603521,0.0011010536,0.001562836],"category_scores_gemma":[0.000867137,0.0004929655,0.00053201674,0.0005287618,0.0005096758,0.00037331096,0.0005723701,0.00042785818,0.00013366093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000227091,0.000017039634,0.00015529618,0.000014262531,0.00001610654,0.000038919534,0.0000133371,0.9957533,0.00051385723,0.0004538372,0.000120220415,0.0028811698],"study_design_scores_gemma":[0.000006768191,0.000019181633,0.000065869346,0.0000014046108,0.0000037621396,0.0000039831043,0.000007415327,0.9994973,0.00009344518,0.00022333156,0.00007602548,0.0000014999849],"about_ca_topic_score_codex":0.0062888586,"about_ca_topic_score_gemma":0.0034105836,"teacher_disagreement_score":0.0062888586,"about_ca_system_score_codex":0.0007701556,"about_ca_system_score_gemma":0.0007952376,"threshold_uncertainty_score":0.012504518},"labels":[],"label_agreement":null},{"id":"W4321327092","doi":"10.1155/2023/5725009","title":"Hierarchical Vehicle Scheduling Research on Tide Bicycle-Sharing Traffic of Autonomous Transportation Systems","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Beijing; Public transport; Scheduling (production processes); Computer science; Transport engineering; Operations research; Real-time computing; Engineering","score_opus":0.04360663119657123,"score_gpt":0.3238466036265323,"score_spread":0.28023997242996107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321327092","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2614257,0.0009959877,0.7286404,0.0003397455,0.00007651436,0.00008275984,0.00012904074,0.0001374389,0.008172416],"genre_scores_gemma":[0.9795885,0.00039583686,0.018661678,0.00002489124,0.000023534703,0.000025300444,0.000064094565,0.000015530766,0.0012005327],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995535,0.00011974661,0.000018724002,0.00011191647,0.00009372273,0.0001022738],"domain_scores_gemma":[0.9995654,0.00017114192,0.00008174359,0.000033498873,0.000094654526,0.000053553562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046360656,0.00047894832,0.00045081612,0.00066718186,0.00054329075,0.0007079425,0.0007889851,0.00030965873,0.0011228246],"category_scores_gemma":[0.001260047,0.0002557181,0.00049857155,0.0009924173,0.0005311043,0.000963539,0.0004196991,0.0004135433,0.00008830301],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023895667,0.000023666784,0.001589955,0.000038812355,0.000019160227,0.000035728415,0.00008638625,0.9703513,0.0011965324,0.015080621,0.00030060663,0.011253366],"study_design_scores_gemma":[0.0000015465487,0.000014026902,0.00030541318,0.000001375075,0.0000046413124,0.0000054677694,0.000026069405,0.9966738,0.00010982288,0.0026149096,0.00024033044,0.0000025111513],"about_ca_topic_score_codex":0.03481581,"about_ca_topic_score_gemma":0.016012874,"teacher_disagreement_score":0.03481581,"about_ca_system_score_codex":0.001706274,"about_ca_system_score_gemma":0.0016609258,"threshold_uncertainty_score":0.069226325},"labels":[],"label_agreement":null},{"id":"W4321507443","doi":"10.1016/j.rser.2023.113212","title":"Low carbon future of vehicle sharing, automation, and electrification: A review of modeling mobility behavior and demand","year":2023,"lang":"en","type":"review","venue":"Renewable and Sustainable Energy Reviews","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Electrification; Urban sprawl; Environmental economics; Emerging technologies; Sustainability; Automation; Travel behavior; Transport engineering; Engineering; Computer science; Electricity; Economics; Urban planning","score_opus":0.02369176434802056,"score_gpt":0.28092333961633026,"score_spread":0.2572315752683097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321507443","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016999594,0.99777204,0.00050816115,0.00056379946,0.00014918113,0.0000027545736,0.000025455012,0.000006474758,0.0008021815],"genre_scores_gemma":[0.0011854395,0.9979772,0.0003023045,0.00014342678,0.00014911678,0.0000037291938,0.00002321135,0.000001592451,0.00021405854],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997316,0.000064295746,0.00002891405,0.000048286347,0.00010662179,0.000020158386],"domain_scores_gemma":[0.99903595,0.000624139,0.00009296332,0.000021160591,0.0001995458,0.000026208407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008639037,0.0010222732,0.0013684579,0.0015918253,0.00021947866,0.0012637796,0.0010012825,0.0013433895,0.0028806468],"category_scores_gemma":[0.0014228128,0.00031435225,0.00065166154,0.002791001,0.0004509077,0.0026964648,0.0006245337,0.0011435138,0.0009379314],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057241672,0.00008582608,0.00041115764,0.030132022,0.00015957553,0.000092095775,0.000077735014,0.005259975,0.0012274132,0.037073407,0.03193695,0.8934866],"study_design_scores_gemma":[0.000013353023,0.00011939264,0.0011149477,0.012983324,0.00029402913,0.00034320363,0.00014557289,0.0029022915,0.0005690339,0.021473924,0.95998585,0.000055019773],"about_ca_topic_score_codex":0.00421866,"about_ca_topic_score_gemma":0.0076945224,"teacher_disagreement_score":0.00421866,"about_ca_system_score_codex":0.00096403214,"about_ca_system_score_gemma":0.0023033612,"threshold_uncertainty_score":0.0096367},"labels":[],"label_agreement":null},{"id":"W4322775743","doi":"10.1287/msom.2023.1191","title":"The Impact of Behavioral and Economic Drivers on Gig Economy Workers","year":2023,"lang":"en","type":"article","venue":"Manufacturing & Service Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":99,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Incentive; Endogeneity; Flexibility (engineering); Economics; Work (physics); Microeconomics; Labour economics; Price elasticity of demand; Business; Econometrics","score_opus":0.012962344254916046,"score_gpt":0.2552357739844124,"score_spread":0.24227342972949634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4322775743","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99009156,0.00015888675,0.0043501123,0.0014641591,0.000021559903,0.000058416503,0.00042660307,0.000023003402,0.0034056571],"genre_scores_gemma":[0.9974934,0.000089024674,0.00083522504,0.00012899119,0.000014092292,0.000041302595,0.00015968319,0.0000053939552,0.001232852],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991685,0.00036761607,0.000037876875,0.00015179746,0.000092296286,0.00018190005],"domain_scores_gemma":[0.98937523,0.006544607,0.002394822,0.00047695244,0.00035554494,0.0008527397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022814178,0.00029658023,0.0003881858,0.00037062803,0.0005501332,0.0013780646,0.0005715164,0.0009502219,0.0074479356],"category_scores_gemma":[0.009505519,0.00023449575,0.00045504645,0.00054801936,0.00070590153,0.0007664491,0.0007534013,0.0010007094,0.00092087017],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038036826,0.00066363066,0.9327672,0.00012954955,0.00009966774,0.00025608798,0.00067059544,0.023631312,0.0011115958,0.0062738447,0.0020735017,0.031942524],"study_design_scores_gemma":[0.000059908056,0.00037474438,0.9042218,0.000082350416,0.00009750485,0.00013492946,0.003986348,0.07336425,0.00082300836,0.012703369,0.0040838886,0.000067932],"about_ca_topic_score_codex":0.006841445,"about_ca_topic_score_gemma":0.009635664,"teacher_disagreement_score":0.0074479356,"about_ca_system_score_codex":0.0009936118,"about_ca_system_score_gemma":0.00096031534,"threshold_uncertainty_score":0.024915814},"labels":[],"label_agreement":null},{"id":"W4323240735","doi":"10.5220/0011620400003396","title":"Workforce Modelling with Experience Accumulation","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Department of National Defence; Defence Research and Development Canada","funders":"","keywords":"Workforce; Computer science; Economics","score_opus":0.09205138164687,"score_gpt":0.29526290709456404,"score_spread":0.20321152544769405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323240735","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053693093,0.0005648149,0.92099947,0.0013659275,0.0002602461,0.00011637127,0.00079061475,0.00037133266,0.021838032],"genre_scores_gemma":[0.8877509,0.00057659385,0.07381788,0.00021334738,0.00018802719,0.00034202755,0.0007243141,0.0001988601,0.03618809],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991627,0.00032379685,0.00004121341,0.00018961098,0.00010305736,0.00017971089],"domain_scores_gemma":[0.9965347,0.0024344416,0.00025415316,0.00021549485,0.00028012542,0.00028113063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015652656,0.001062098,0.001366412,0.0010807238,0.0006646598,0.001920887,0.0023350338,0.0025291557,0.012886905],"category_scores_gemma":[0.008962241,0.001182647,0.0018223285,0.0012746159,0.0009955917,0.0022536737,0.0027902168,0.0018584331,0.0014551468],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037134174,0.000037869904,0.00074856944,0.000040506835,0.00002501847,0.00008205064,0.00009309391,0.9669516,0.0001231302,0.0236488,0.0008485093,0.007363752],"study_design_scores_gemma":[0.000007225965,0.000011199663,0.000112499925,0.000012706975,0.0000060019956,0.0000112126045,0.000020045134,0.98226625,0.000052932355,0.016844159,0.0006503158,0.0000054014995],"about_ca_topic_score_codex":0.02265727,"about_ca_topic_score_gemma":0.01207053,"teacher_disagreement_score":0.02265727,"about_ca_system_score_codex":0.0011281869,"about_ca_system_score_gemma":0.0015595515,"threshold_uncertainty_score":0.0450508},"labels":[],"label_agreement":null},{"id":"W4323241016","doi":"10.5220/0011783100003396","title":"Multi-Objective Task Assignment Solution for Parked Vehicular Computing","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Task (project management); Engineering; Systems engineering","score_opus":0.025879777812082214,"score_gpt":0.2639662625599769,"score_spread":0.23808648474789468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323241016","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13447404,0.0006059768,0.8528079,0.00044771584,0.00020510146,0.00019500234,0.0003996429,0.0005265433,0.010338153],"genre_scores_gemma":[0.8446769,0.00020130073,0.14719127,0.000076188095,0.000040092404,0.00016151139,0.0003519918,0.000088263245,0.0072125904],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996111,0.00009886266,0.000016579901,0.00008874763,0.00005958808,0.00012522993],"domain_scores_gemma":[0.99962544,0.00015351703,0.000042268548,0.00002929985,0.000084928724,0.00006440514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055167696,0.0009553659,0.0010337717,0.00065795175,0.00075893616,0.0010822425,0.0013187809,0.0009450232,0.00474275],"category_scores_gemma":[0.0012476852,0.0003815119,0.0006795485,0.0008300201,0.0003279549,0.0008190926,0.0010399459,0.0007618564,0.000402155],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008511762,0.000065251676,0.00034765215,0.00007574194,0.000030499601,0.000076567405,0.000038176386,0.9666207,0.0011376074,0.0022275706,0.0013224244,0.027972607],"study_design_scores_gemma":[0.00000877605,0.00003944282,0.000096791955,0.000004476319,0.0000063343314,0.000013667054,0.000038895363,0.9976815,0.00020398672,0.0014949031,0.00040794682,0.00000320184],"about_ca_topic_score_codex":0.008917323,"about_ca_topic_score_gemma":0.010613038,"teacher_disagreement_score":0.008917323,"about_ca_system_score_codex":0.0007159973,"about_ca_system_score_gemma":0.0015138137,"threshold_uncertainty_score":0.017730832},"labels":[],"label_agreement":null},{"id":"W4323343774","doi":"10.14778/3579075.3579091","title":"A Hierarchical Grouping Algorithm for the Multi-Vehicle Dial-a-Ride Problem","year":2023,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Latency (audio); Set (abstract data type); State (computer science); Destinations; Algorithm; Point (geometry); Mathematical optimization; Mathematics; Telecommunications","score_opus":0.021500584599856626,"score_gpt":0.24308542913708225,"score_spread":0.22158484453722563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323343774","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017246494,0.00021633519,0.9783044,0.00017383302,0.00004299412,0.00021357798,0.00015543938,0.0010319278,0.0026150048],"genre_scores_gemma":[0.14016749,0.00015523002,0.85539657,0.000092218244,0.000028052062,0.0002179329,0.0008051477,0.00020002386,0.0029373479],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991885,0.00018167951,0.000045051806,0.00026984853,0.00016371963,0.00015129596],"domain_scores_gemma":[0.99909854,0.00028144405,0.00011856261,0.000264993,0.00015121685,0.00008530913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009054457,0.0010748033,0.0012105862,0.0010815442,0.0011611372,0.0008146379,0.0021787393,0.0013070368,0.0043500126],"category_scores_gemma":[0.002348824,0.0005434979,0.0011143087,0.0016660294,0.00054102193,0.0022623828,0.0018440965,0.0013988147,0.0015568954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002182667,0.0003115666,0.0012560338,0.0002604791,0.000075477394,0.00013430724,0.00039497463,0.61491114,0.008378772,0.023223326,0.0128179705,0.33801764],"study_design_scores_gemma":[0.000055638844,0.00013439219,0.00034546535,0.000016554874,0.000023702183,0.0000905873,0.00013685672,0.974573,0.0019653654,0.017218279,0.005420569,0.000019541076],"about_ca_topic_score_codex":0.0063790055,"about_ca_topic_score_gemma":0.0064499234,"teacher_disagreement_score":0.0063790055,"about_ca_system_score_codex":0.0010312196,"about_ca_system_score_gemma":0.0017158035,"threshold_uncertainty_score":0.014552236},"labels":[],"label_agreement":null},{"id":"W4323537538","doi":"10.1155/2023/3440691","title":"Customer’s Adoption Intentions toward Autonomous Delivery Vehicle Services: Extending DOI Theory with Social Awkwardness and Use Experience","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Business; Marketing; Context (archaeology); Technology acceptance model; Usability; Computer science","score_opus":0.017844963864631327,"score_gpt":0.2552857675974543,"score_spread":0.23744080373282297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323537538","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9890893,0.00011846091,0.0051549925,0.00038159176,0.000011788429,0.000099676196,0.000029942295,0.00000824879,0.0051060845],"genre_scores_gemma":[0.9986424,0.000104678365,0.0009659568,0.00003398422,0.00000442398,0.00006179594,0.0000192491,0.0000010894796,0.00016642378],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972345,0.0014000718,0.00022882456,0.00025819908,0.0006161312,0.00026226335],"domain_scores_gemma":[0.9830103,0.011476644,0.0025349553,0.00053762743,0.001540947,0.0008995604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037617215,0.00042373547,0.00037725415,0.0022524912,0.00064583606,0.0024220704,0.0005246371,0.0008968171,0.0019022233],"category_scores_gemma":[0.012162452,0.00033263123,0.0012271344,0.0010508577,0.001490698,0.0024827856,0.0021105623,0.0013133597,0.00018439646],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001230263,0.0013813737,0.87651443,0.00031222738,0.00020537309,0.0006271814,0.04211343,0.0018646837,0.001106255,0.016835146,0.00032360762,0.058593325],"study_design_scores_gemma":[0.00007027668,0.0020521057,0.8141036,0.0007006311,0.0004724254,0.00084423955,0.09070521,0.061466046,0.0013987315,0.021592807,0.006392379,0.0002015198],"about_ca_topic_score_codex":0.0040575354,"about_ca_topic_score_gemma":0.0026990396,"teacher_disagreement_score":0.0040575354,"about_ca_system_score_codex":0.0013815659,"about_ca_system_score_gemma":0.0014873035,"threshold_uncertainty_score":0.019894123},"labels":[],"label_agreement":null},{"id":"W4323773115","doi":"10.2139/ssrn.4383042","title":"Implications of Three Autonomous Mobility Scenarios: A Comparison between Lyon, France and Montreal, Canada","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Regional science; Geography; Political science","score_opus":0.010916106847513107,"score_gpt":0.23454342603612124,"score_spread":0.22362731918860815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323773115","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9060482,0.0013068019,0.0011563597,0.0059619974,0.000088896675,0.00024846572,0.0051969984,0.00010026675,0.07989208],"genre_scores_gemma":[0.9926686,0.00046598836,0.000397281,0.0002238242,0.000009238751,0.000032411415,0.001142202,0.000014764102,0.0050456617],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99825674,0.0004006369,0.000033317177,0.00012861361,0.00033910954,0.0008414878],"domain_scores_gemma":[0.9978878,0.00043009204,0.00014594212,0.000057775396,0.0010094506,0.00046891152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012397298,0.0006413002,0.00051841635,0.0017544876,0.0046989745,0.005852826,0.0020042316,0.0015891145,0.006205275],"category_scores_gemma":[0.0042912327,0.0002987757,0.00073186844,0.0036824553,0.0018382303,0.0015974888,0.001606566,0.0009868052,0.00030960765],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035270867,0.0011797945,0.29156888,0.00064055104,0.0008650252,0.006822618,0.00592605,0.42181432,0.0024154198,0.13361134,0.06883691,0.06279198],"study_design_scores_gemma":[0.0011184455,0.0010720124,0.6497516,0.0005200657,0.00071978057,0.0005856637,0.07628988,0.16231157,0.0017668421,0.0154230865,0.089869246,0.00057177397],"about_ca_topic_score_codex":0.9899322,"about_ca_topic_score_gemma":0.99395144,"teacher_disagreement_score":0.043894753,"about_ca_system_score_codex":0.043894753,"about_ca_system_score_gemma":0.030226914,"threshold_uncertainty_score":0.3184802},"labels":[],"label_agreement":null},{"id":"W4323906542","doi":"10.1007/978-3-031-23721-8_86","title":"Transit Fare Equity: Understanding the Factors Affecting Different Groups of Users’ Payment Method","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in intelligent transportation and infrastructure","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Payment; Equity (law); Business; Transit (satellite); Actuarial science; Transport engineering; Finance; Public transport; Engineering; Political science","score_opus":0.04476488772380729,"score_gpt":0.2770349213092458,"score_spread":0.2322700335854385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323906542","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97247845,0.00017656945,0.003015673,0.00078690966,0.000010040022,0.000029862267,0.00020721722,0.000010273371,0.023284955],"genre_scores_gemma":[0.99781173,0.000030380555,0.00023428288,0.000015701155,0.000004465458,0.000004605362,0.000050418457,0.0000030426845,0.0018453082],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99958104,0.00011426387,0.000013735071,0.000070878865,0.000074072086,0.00014603246],"domain_scores_gemma":[0.9965192,0.0020136738,0.00063680793,0.00012289723,0.00040594063,0.0003014308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009904942,0.0001785658,0.00023170584,0.0008745419,0.00053449563,0.002297399,0.00046073805,0.00043645754,0.014004351],"category_scores_gemma":[0.0072046868,0.00013524685,0.00022750231,0.0009842095,0.0007100394,0.0025579373,0.0008414756,0.00080066506,0.00068344997],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027814554,0.00029632452,0.8763156,0.000038986145,0.000072315226,0.0001738016,0.006451524,0.0036693423,0.0011652879,0.05104879,0.0019690415,0.058520734],"study_design_scores_gemma":[0.000014273998,0.00009060607,0.9499621,0.000035399913,0.000054712295,0.0000959535,0.012566661,0.009355749,0.00047119745,0.023361385,0.003974089,0.000017948394],"about_ca_topic_score_codex":0.019682875,"about_ca_topic_score_gemma":0.018658651,"teacher_disagreement_score":0.019682875,"about_ca_system_score_codex":0.0014223915,"about_ca_system_score_gemma":0.00084801856,"threshold_uncertainty_score":0.04684919},"labels":[],"label_agreement":null},{"id":"W4323927905","doi":"10.1016/j.trc.2023.104082","title":"Optimizing first-mile ridesharing services to intercity transit hubs","year":2023,"lang":"en","type":"article","venue":"Transportation Research Part C Emerging Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"National Key Research and Development Program of China; China Scholarship Council; National Natural Science Foundation of China","keywords":"Transport engineering; Mile; Transit (satellite); Last mile (transportation); Public transport; Engineering; Transit system; Computer science; Business; Geography","score_opus":0.06750005512630407,"score_gpt":0.34135038546137764,"score_spread":0.27385033033507356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323927905","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85132974,0.0006159858,0.10682547,0.0007206148,0.00015508514,0.00040350246,0.0014684799,0.0016334837,0.036847714],"genre_scores_gemma":[0.98227304,0.000106204556,0.011032369,0.00004033616,0.000012033238,0.000031730884,0.0003460543,0.000117627045,0.006040488],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992305,0.00015544247,0.000012979178,0.0001401488,0.00006123453,0.00039966125],"domain_scores_gemma":[0.99934703,0.00019882347,0.000056939218,0.000058456444,0.00017329391,0.00016545349],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006200215,0.0018277612,0.0016316505,0.0010640449,0.0014867398,0.0026422685,0.0015675797,0.0015052861,0.016404932],"category_scores_gemma":[0.0020683547,0.0006932717,0.00085767836,0.0015783753,0.00054956926,0.0014594364,0.0012574566,0.0011007818,0.002007646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046711665,0.00024425433,0.0025536509,0.00007975092,0.000059306672,0.000112302194,0.0000788472,0.94351393,0.0054772035,0.0024164445,0.00467863,0.04031855],"study_design_scores_gemma":[0.000030890427,0.0002943244,0.0019558852,0.000011548458,0.00005928623,0.000027805241,0.00040807243,0.99158126,0.0024669978,0.0016364943,0.0015134601,0.000013839765],"about_ca_topic_score_codex":0.03839673,"about_ca_topic_score_gemma":0.047695775,"teacher_disagreement_score":0.03839673,"about_ca_system_score_codex":0.0030981575,"about_ca_system_score_gemma":0.003285688,"threshold_uncertainty_score":0.07634646},"labels":[],"label_agreement":null},{"id":"W4324132502","doi":"10.1016/j.trd.2023.103687","title":"A large-scale empirical study on impacting factors of taxi charging station utilization","year":2023,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Alberta","funders":"China Scholarship Council","keywords":"Taxis; Electrification; Transport engineering; Charging station; Public transport; Scale (ratio); Electric vehicle; Population; Environmental science; Geography; Engineering; Electricity; Electrical engineering","score_opus":0.14593085971274333,"score_gpt":0.374246452980905,"score_spread":0.22831559326816164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4324132502","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986532,0.00006040995,0.00013186708,0.000051834242,0.000002245249,0.000014892144,0.000403424,0.0000036056108,0.00067859906],"genre_scores_gemma":[0.9989532,0.00005852275,0.00010295335,0.000020654841,0.0000044262097,0.000013352172,0.0005702724,0.0000026611194,0.00027404208],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986312,0.00064110995,0.000117316544,0.00017838585,0.0002143531,0.0002176639],"domain_scores_gemma":[0.9796215,0.011630479,0.004356801,0.001195107,0.001843768,0.0013523003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021809787,0.00026461072,0.00035125253,0.0012158649,0.0010373871,0.0012966038,0.00079174916,0.00059739285,0.0035290094],"category_scores_gemma":[0.012705285,0.00030162805,0.00071741996,0.0033394725,0.0007330739,0.0013450903,0.0006991286,0.0012825088,0.00070495234],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000450352,0.00022271188,0.9966479,0.000012951918,0.00006812088,0.000052331354,0.00036477315,0.00014587885,0.000060954244,0.000120765166,0.0001985264,0.002060143],"study_design_scores_gemma":[0.0000035571059,0.00005630919,0.9972676,0.0000067830088,0.000028917839,0.00004060815,0.0017346577,0.00048640632,0.000039686798,0.000033119202,0.00029754144,0.000004840973],"about_ca_topic_score_codex":0.049383357,"about_ca_topic_score_gemma":0.05970818,"teacher_disagreement_score":0.049383357,"about_ca_system_score_codex":0.0013474263,"about_ca_system_score_gemma":0.002114716,"threshold_uncertainty_score":0.0981918},"labels":[],"label_agreement":null},{"id":"W4328007271","doi":"10.1109/tvt.2023.3258841","title":"Computation Resource Optimization for Large-Scale Intelligent Urban Rail Transit: A Mean-Field Game Approach","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Science Foundation of Beijing Municipality; National Natural Science Foundation of China","keywords":"Computation offloading; Computer science; Computation; Resource allocation; Mathematical optimization; Quality of service; Optimization problem; Distributed computing; Resource management (computing); Resource (disambiguation); Enhanced Data Rates for GSM Evolution; Artificial intelligence; Edge computing; Computer network; Algorithm; Mathematics","score_opus":0.013489626194321196,"score_gpt":0.23441640041291478,"score_spread":0.22092677421859358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4328007271","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0461631,0.00033311197,0.9433719,0.0007697366,0.000086197935,0.00010400173,0.000073328956,0.00008567301,0.009013043],"genre_scores_gemma":[0.9576661,0.00031811243,0.03679463,0.00017904595,0.000035410227,0.00017463668,0.000043259344,0.000026984348,0.0047618104],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994406,0.00021185493,0.000017005552,0.000112121335,0.000106884734,0.00011154689],"domain_scores_gemma":[0.99935323,0.00041790307,0.00006676862,0.0000158228,0.00008016713,0.00006615886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009610266,0.0010121973,0.00104321,0.000472644,0.00065255683,0.0011330994,0.0012457957,0.0012362065,0.0023164682],"category_scores_gemma":[0.0015012658,0.00042583872,0.0007849315,0.00043704684,0.0013027112,0.0013610694,0.0011968263,0.0011264387,0.00013805478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005460795,0.000040779116,0.00032892445,0.00004564345,0.0000275605,0.00011240453,0.00005387615,0.96367323,0.001240316,0.029155118,0.00075481285,0.00451258],"study_design_scores_gemma":[0.00000969278,0.000013683787,0.000043800188,0.0000021209523,0.0000044966428,0.0000071589525,0.000010601113,0.9955611,0.00007077367,0.0040833238,0.00018973714,0.000003504732],"about_ca_topic_score_codex":0.010200987,"about_ca_topic_score_gemma":0.0067148963,"teacher_disagreement_score":0.010200987,"about_ca_system_score_codex":0.0017667599,"about_ca_system_score_gemma":0.001619345,"threshold_uncertainty_score":0.020283222},"labels":[],"label_agreement":null},{"id":"W4360618583","doi":"10.31219/osf.io/pesjk","title":"Ride-hailing and transit accessibility considering the trade-off between time and money","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"TRIPS architecture; Subsidy; Business; Mile; Service (business); Transit (satellite); Transport engineering; Last mile (transportation); Pareto principle; Finance; Economics; Public transport; Marketing; Geography; Operations management; Engineering","score_opus":0.04021557936567586,"score_gpt":0.267358324842417,"score_spread":0.22714274547674115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360618583","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95477605,0.00042548653,0.024002457,0.00031985212,0.000013024321,0.000033934542,0.00031978928,0.000030771185,0.020078616],"genre_scores_gemma":[0.9979219,0.00006900829,0.0012486959,0.0000044397502,0.0000030284782,0.0000055064315,0.000039065053,0.0000044435624,0.00070396974],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996557,0.00011131551,0.000013053847,0.00004351544,0.00006228789,0.000113989954],"domain_scores_gemma":[0.9989968,0.00053003134,0.00019131634,0.00006701779,0.0001206478,0.000094312876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046551364,0.0003150561,0.00024007498,0.0008430937,0.00028287992,0.0015954017,0.00039002413,0.00033003028,0.004773455],"category_scores_gemma":[0.0025557724,0.0001361865,0.00061585003,0.0010563008,0.0007697454,0.0015448572,0.0009261413,0.00045718363,0.00018909237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033950867,0.00024689597,0.17920701,0.00031458735,0.00028852676,0.00071865856,0.00077460834,0.6627376,0.0047074477,0.071680196,0.0010860304,0.07789889],"study_design_scores_gemma":[0.00003706126,0.0005999975,0.32101732,0.00014191502,0.00025875584,0.00063605845,0.0047436696,0.5933466,0.0027073747,0.06327738,0.01314218,0.00009179812],"about_ca_topic_score_codex":0.009026112,"about_ca_topic_score_gemma":0.015502076,"teacher_disagreement_score":0.009026112,"about_ca_system_score_codex":0.0009589265,"about_ca_system_score_gemma":0.00044421983,"threshold_uncertainty_score":0.017947137},"labels":[],"label_agreement":null},{"id":"W4360778039","doi":"10.5267/j.ijdns.2023.1.001","title":"Vehicle service reservation system and crowd-prediction feature using ARIMA method","year":2023,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Respondent; Reservation; Autoregressive integrated moving average; Computer science; Service (business); Machine learning; Marketing; Computer network; Time series; Business","score_opus":0.057477202249141095,"score_gpt":0.34213481687498754,"score_spread":0.28465761462584643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360778039","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33446112,0.0010752078,0.6547365,0.00044451517,0.00021049558,0.00022698051,0.00058553246,0.0022517107,0.0060079866],"genre_scores_gemma":[0.9311204,0.0003237944,0.065398134,0.0000512894,0.00007810517,0.00014099535,0.0004306869,0.00004297873,0.0024135741],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998423,0.0004799308,0.00012133996,0.000410341,0.0004253237,0.00014008014],"domain_scores_gemma":[0.9975689,0.0013474828,0.00025452755,0.00014617862,0.0006093089,0.00007354502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002418553,0.00065560633,0.00069399155,0.0018282597,0.00052123045,0.0010193596,0.0009515316,0.00060780015,0.0018310638],"category_scores_gemma":[0.0060773953,0.00032871333,0.001104987,0.0013691632,0.00024031018,0.0011252086,0.0005959055,0.0008513757,0.0004727095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010633728,0.0007041709,0.1435721,0.00070933823,0.0006744116,0.0007278986,0.0014918356,0.36864978,0.020262985,0.007674706,0.004411787,0.45005763],"study_design_scores_gemma":[0.000016900192,0.00019952156,0.015802808,0.00002558903,0.00013496906,0.00011915941,0.00025979048,0.97710365,0.0026245718,0.0013063193,0.0023489206,0.000057855366],"about_ca_topic_score_codex":0.017531078,"about_ca_topic_score_gemma":0.010664876,"teacher_disagreement_score":0.017531078,"about_ca_system_score_codex":0.00069996493,"about_ca_system_score_gemma":0.00092589064,"threshold_uncertainty_score":0.034858048},"labels":[],"label_agreement":null},{"id":"W4362581711","doi":"10.1016/j.trd.2023.103675","title":"Function, symbolism or society? Exploring consumer interest in electric and shared mobility","year":2023,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Perception; Early adopter; The Symbolic; Function (biology); Marketing; Business; Sample (material); Psychology; Sociology","score_opus":0.16857680445215062,"score_gpt":0.30027641956847195,"score_spread":0.13169961511632133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362581711","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9760774,0.00007622001,0.0003305634,0.0005839177,0.0000068201725,0.0000062776653,0.000013651361,0.0000015272384,0.02290371],"genre_scores_gemma":[0.9991435,0.000035980036,0.0000582334,0.000049780887,0.000003889121,0.0000059044905,0.000008634401,0.0000029559258,0.0006911824],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.9986312,0.0007568829,0.000031165342,0.000110419736,0.00020973817,0.00026054558],"domain_scores_gemma":[0.99269825,0.005171385,0.0008570133,0.0002864266,0.0005121574,0.0004747646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025627632,0.00022704032,0.00025747073,0.0011645112,0.0018940793,0.007299218,0.0007032282,0.0014668823,0.007115184],"category_scores_gemma":[0.009684853,0.00024046833,0.00034358128,0.0013678077,0.005123177,0.0066887825,0.0038341717,0.0014980421,0.00027042473],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007231721,0.0004882818,0.19676343,0.00015201833,0.00007298331,0.0005663771,0.6988641,0.00029473656,0.0019023644,0.0700979,0.00074174744,0.029332848],"study_design_scores_gemma":[0.00002968456,0.00013838655,0.14614141,0.000076539116,0.000052892963,0.00021376488,0.8312239,0.00086074945,0.00047495862,0.0134481415,0.0073055215,0.000033962537],"about_ca_topic_score_codex":0.0062404545,"about_ca_topic_score_gemma":0.007646051,"teacher_disagreement_score":0.007299218,"about_ca_system_score_codex":0.0022828411,"about_ca_system_score_gemma":0.0009965517,"threshold_uncertainty_score":0.023802638},"labels":[],"label_agreement":null},{"id":"W4362584456","doi":"10.1287/opre.2022.2425","title":"Real-Time Spatial–Intertemporal Pricing and Relocation in a Ride-Hailing Network: Near-Optimal Policies and the Value of Dynamic Pricing","year":2023,"lang":"en","type":"article","venue":"Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Dynamic pricing; Computer science; Server; Relocation; Randomness; Service (business); Queueing theory; Value (mathematics); Operations research; Microeconomics; Mathematical optimization; Economics; Computer network; Business; Marketing; Mathematics","score_opus":0.022540938760126552,"score_gpt":0.32545741681071,"score_spread":0.30291647805058347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362584456","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17920847,0.0018378552,0.80617815,0.0025060968,0.00018667027,0.00013916414,0.00011856334,0.00018476578,0.0096402215],"genre_scores_gemma":[0.96404105,0.00087013555,0.032757,0.00015937698,0.000087361026,0.000048039474,0.000051908788,0.000047355526,0.0019378039],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982564,0.0008954128,0.000055157234,0.00024025932,0.00020570586,0.00034700538],"domain_scores_gemma":[0.9866175,0.010679578,0.00083148247,0.00050848763,0.00092477916,0.00043802196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037451873,0.0013364264,0.0019427089,0.0010480962,0.0011481226,0.0029634417,0.0026337297,0.002369397,0.003112757],"category_scores_gemma":[0.019923918,0.0009895217,0.0008419822,0.0015990379,0.002034636,0.0050120056,0.0016801106,0.0024767264,0.00022090547],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016725021,0.000117184936,0.0006410353,0.000056755034,0.00005102444,0.00007708436,0.000065765074,0.9395516,0.0006688675,0.048437886,0.0009415687,0.009223931],"study_design_scores_gemma":[0.0000115896755,0.000035802084,0.00010727272,0.000006565919,0.000010574925,0.000021075923,0.00004143588,0.9795783,0.00021841037,0.019704983,0.00025152095,0.000012520209],"about_ca_topic_score_codex":0.006396789,"about_ca_topic_score_gemma":0.003482456,"teacher_disagreement_score":0.006396789,"about_ca_system_score_codex":0.0031193618,"about_ca_system_score_gemma":0.0017304817,"threshold_uncertainty_score":0.022632658},"labels":[],"label_agreement":null},{"id":"W4362622293","doi":"10.1080/21650020.2023.2197979","title":"Analysis of millennials and older adults’ automobility behavior in Hamilton, Ontario","year":2023,"lang":"en","type":"article","venue":"Urban Planning and Transport Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Gerontology; Sociology; Psychology; Medicine","score_opus":0.04511466306610308,"score_gpt":0.32562601990139434,"score_spread":0.28051135683529127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362622293","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99738437,0.00014489643,0.0000631908,0.00008049073,0.0000027810258,0.00002435488,0.0011905967,0.0000021583494,0.0011071942],"genre_scores_gemma":[0.9971835,0.0002259518,0.00014719939,0.000041263625,0.0000027018089,0.000030683303,0.0011738384,0.000001907674,0.0011929112],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996902,0.000036254467,0.000026833206,0.000045466528,0.00009679815,0.00010452141],"domain_scores_gemma":[0.99880457,0.00008493055,0.00033619223,0.00005366115,0.00043155323,0.00028908282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043601505,0.00016187964,0.00020957993,0.00081863964,0.0012812878,0.00056352443,0.0005088232,0.00018395165,0.0014830007],"category_scores_gemma":[0.0013363142,0.00019023096,0.0003649237,0.0019623095,0.00029354714,0.000294122,0.0008438022,0.0002202455,0.00020423859],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017383873,0.000010509991,0.9950324,0.000012873781,0.000013853593,0.000045676265,0.0016772405,0.000026941341,0.000110719884,0.000039274782,0.00031961474,0.0026934098],"study_design_scores_gemma":[0.0000010531274,0.000006750729,0.9982849,0.0000061734504,0.0000033479653,0.00000943485,0.0011422503,0.000034658016,0.000013080405,0.0000038594244,0.0004930913,0.0000015207366],"about_ca_topic_score_codex":0.9635382,"about_ca_topic_score_gemma":0.989484,"teacher_disagreement_score":0.03646177,"about_ca_system_score_codex":0.00847423,"about_ca_system_score_gemma":0.006904793,"threshold_uncertainty_score":0.07335293},"labels":[],"label_agreement":null},{"id":"W4362685181","doi":"10.2139/ssrn.4411441","title":"A Novel and Failsafe Blockchain Framework for Secure Ota Updates in Connected Autonomous Vehicles","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Blockchain; Computer science; Computer security; Computer network","score_opus":0.01662430149374138,"score_gpt":0.25539722500827955,"score_spread":0.23877292351453816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362685181","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023262158,0.0002557876,0.96861035,0.00040150667,0.00015162533,0.0002358917,0.0002363824,0.0014903115,0.005356014],"genre_scores_gemma":[0.85077167,0.00026778132,0.13952407,0.00012110737,0.0001209031,0.00027841583,0.00029445763,0.00017839696,0.008443146],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99760276,0.00059083005,0.00014750402,0.0003784393,0.0009207746,0.00035970847],"domain_scores_gemma":[0.9955206,0.0016820986,0.00026516948,0.001448998,0.0006922939,0.00039082835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002269881,0.0005594706,0.0011652053,0.0006494475,0.0015019953,0.0025762843,0.0025777195,0.0017350231,0.008357671],"category_scores_gemma":[0.0065679383,0.00042137786,0.0005190171,0.00075955945,0.001475834,0.003768914,0.004196788,0.0021765903,0.0014275931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010322398,0.00030423308,0.0014822423,0.00031750934,0.00011003135,0.00081288675,0.0005785375,0.4617002,0.014987012,0.3109498,0.008998392,0.19872689],"study_design_scores_gemma":[0.00005279543,0.00007267379,0.00008675895,0.000019911025,0.000016818907,0.00009036193,0.000053419903,0.9163127,0.002825479,0.07533255,0.005116728,0.000019901305],"about_ca_topic_score_codex":0.0033472644,"about_ca_topic_score_gemma":0.005699356,"teacher_disagreement_score":0.008357671,"about_ca_system_score_codex":0.00092967896,"about_ca_system_score_gemma":0.0030088425,"threshold_uncertainty_score":0.027959228},"labels":[],"label_agreement":null},{"id":"W4364365580","doi":"10.1016/j.tranpol.2023.04.001","title":"Ride-matching for the ride-hailing platform with heterogeneous drivers","year":2023,"lang":"en","type":"article","venue":"Transport Policy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Fundamental Research Funds for the Central Universities; National University's Basic Research Foundation of China; Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China","keywords":"Matching (statistics); Subsidy; Revenue; Computer science; Operations research; Transport engineering; Business; Engineering; Economics; Finance; Mathematics; Statistics","score_opus":0.020043269419011286,"score_gpt":0.2532851911837767,"score_spread":0.23324192176476538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4364365580","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5539896,0.00022214423,0.405317,0.0024011536,0.00024244977,0.00055074453,0.0012853934,0.0009077797,0.035083733],"genre_scores_gemma":[0.9722669,0.00006714372,0.015291485,0.00007663353,0.000037494447,0.000069658396,0.0002768114,0.00005706386,0.011856856],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979798,0.00051973446,0.00007804241,0.000496217,0.00017214622,0.0007540279],"domain_scores_gemma":[0.9962657,0.001668917,0.00028514062,0.00076444156,0.00041864897,0.0005971092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033249347,0.0008301242,0.0018045986,0.0009934328,0.0016454888,0.0032004837,0.0024358346,0.0028105367,0.02569129],"category_scores_gemma":[0.0113856,0.0006252513,0.0014984338,0.0010378956,0.0012322166,0.0049067955,0.0041282224,0.0020238506,0.0018843416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017059181,0.000610563,0.0064799166,0.00013569767,0.00014137669,0.0006115367,0.00034348576,0.7031792,0.0027173515,0.22406417,0.008576035,0.05143478],"study_design_scores_gemma":[0.000058915688,0.000110060806,0.0007259222,0.00001047962,0.00003453323,0.000042890824,0.00020483347,0.9428198,0.00064582156,0.05392925,0.0013938808,0.000023550872],"about_ca_topic_score_codex":0.013121234,"about_ca_topic_score_gemma":0.007071686,"teacher_disagreement_score":0.02569129,"about_ca_system_score_codex":0.0019543588,"about_ca_system_score_gemma":0.0026991912,"threshold_uncertainty_score":0.085945964},"labels":[],"label_agreement":null},{"id":"W4365139972","doi":"10.1155/2023/8953109","title":"Willingness to Pay for Conditional Automated Driving among Segments of Potential Buyers in Europe","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"European Commission","keywords":"Willingness to pay; Software deployment; Willingness to accept; Population; Business; Driving factors; Marketing; Economics; Environmental health; Computer science; Microeconomics; Geography; Medicine","score_opus":0.007271739085709225,"score_gpt":0.2539328709246461,"score_spread":0.2466611318389369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4365139972","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994159,0.00003802862,0.000056090586,0.000022534821,0.0000014983731,0.000002189139,0.000045568722,6.293655e-7,0.00041761788],"genre_scores_gemma":[0.9996942,0.000026549296,0.000023960072,0.000012100077,0.000001132967,0.0000015699969,0.00007393021,4.1529307e-7,0.00016616588],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99967563,0.000087382454,0.000029329614,0.00006200274,0.00006743801,0.00007824998],"domain_scores_gemma":[0.9988096,0.00036162476,0.0004230385,0.00005581044,0.00013333108,0.0002166308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000909085,0.00014860477,0.00019070477,0.0005973049,0.00024826228,0.0010594169,0.00023280267,0.0004743899,0.0026205746],"category_scores_gemma":[0.0016680975,0.00012457874,0.0003376199,0.0005802363,0.00033898346,0.0007520682,0.00045472904,0.0004337884,0.00028618018],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006501653,0.00006160022,0.99395233,0.000010340954,0.00002978494,0.00009779882,0.0011390996,0.00015234342,0.0001668156,0.00018960585,0.00015077305,0.003984453],"study_design_scores_gemma":[0.000003022369,0.00006934254,0.99395233,0.000010326142,0.000010171422,0.00014476848,0.004754528,0.00042321696,0.00007091299,0.00007413935,0.00048062095,0.0000066108164],"about_ca_topic_score_codex":0.0046804715,"about_ca_topic_score_gemma":0.0033917606,"teacher_disagreement_score":0.0046804715,"about_ca_system_score_codex":0.0002178076,"about_ca_system_score_gemma":0.00014497859,"threshold_uncertainty_score":0.00930649},"labels":[],"label_agreement":null},{"id":"W4365503648","doi":"10.1155/2023/7291712","title":"Resilience-Oriented Scheduling of Shared Autonomous Electric Vehicles: A Cooperation Framework for Electrical Distribution Networks and Transportation Sector","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Villum Fonden","keywords":"News aggregator; Scheduling (production processes); Computer science; Grid; Operations research; Schedule; Electric power system; Time horizon; Distributed computing; Engineering; Power (physics); Operations management; Mathematical optimization","score_opus":0.009137577675801986,"score_gpt":0.24947939790241136,"score_spread":0.24034182022660938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4365503648","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012317407,0.0001894166,0.98249507,0.00023268574,0.00005610005,0.000075323165,0.00003194412,0.00014791336,0.004454078],"genre_scores_gemma":[0.8094889,0.00043812912,0.1846918,0.00007564048,0.00009760657,0.00022865486,0.00010142307,0.000060976516,0.004816804],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990835,0.00036927187,0.0000381991,0.000190338,0.00016110101,0.00015753772],"domain_scores_gemma":[0.9993443,0.0002086649,0.00010797214,0.00007367352,0.00013654398,0.00012886159],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018725137,0.00076860713,0.00047343172,0.0005699364,0.00079315633,0.0010485067,0.0016182762,0.00070618984,0.0025871622],"category_scores_gemma":[0.0017533363,0.00024375567,0.0007489506,0.0006652736,0.0008963968,0.001336963,0.0017202982,0.0008973633,0.000309525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000101345235,0.00005931089,0.00065027835,0.00007004424,0.000038996688,0.00022727431,0.00030667186,0.8026089,0.0034349926,0.15506864,0.0019512648,0.035482332],"study_design_scores_gemma":[0.000009674524,0.00004249478,0.00008558718,0.0000068301833,0.000010665508,0.00002567341,0.000069442736,0.9792867,0.0002954677,0.017687205,0.0024734528,0.00000688311],"about_ca_topic_score_codex":0.00538538,"about_ca_topic_score_gemma":0.0041396394,"teacher_disagreement_score":0.00538538,"about_ca_system_score_codex":0.0013561996,"about_ca_system_score_gemma":0.0022419132,"threshold_uncertainty_score":0.010708034},"labels":[],"label_agreement":null},{"id":"W4367016616","doi":"10.2139/ssrn.4425845","title":"Shipment Consolidation in Hub Location Modeling with Time-Definite Transportation","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Consolidation (business); Computer science; Operations research; Mathematics; Business; Finance","score_opus":0.017503877518341402,"score_gpt":0.2318448954189497,"score_spread":0.2143410179006083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367016616","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0730492,0.00053172116,0.91944367,0.0005551867,0.000097741606,0.000067723,0.00029244553,0.00016581976,0.0057964525],"genre_scores_gemma":[0.9409633,0.00061603234,0.04346333,0.00012729627,0.00008749387,0.00016017012,0.00046857362,0.00014192802,0.013971885],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99895763,0.00044491506,0.00006465026,0.0002674912,0.00011600913,0.00014925232],"domain_scores_gemma":[0.9972927,0.0015089518,0.00038395735,0.00019334919,0.00038046745,0.00024056752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023561441,0.0011426248,0.0020447664,0.0008884942,0.0007190035,0.0024457425,0.003230061,0.0022836374,0.003778383],"category_scores_gemma":[0.0070712036,0.0017846709,0.0017033872,0.0015454221,0.0019857925,0.0034950136,0.002278799,0.0022405228,0.0004941904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017604936,0.000012825783,0.00025120995,0.000014859663,0.000010958407,0.000025696532,0.000014549755,0.99027085,0.00006298092,0.008183673,0.00014383806,0.000991002],"study_design_scores_gemma":[0.0000013753696,0.0000033046306,0.000020524683,0.0000014108593,0.00000258692,0.000001908576,0.0000036823653,0.9978928,0.000024045768,0.0019821792,0.000064792395,0.0000013009536],"about_ca_topic_score_codex":0.03548779,"about_ca_topic_score_gemma":0.016387062,"teacher_disagreement_score":0.03548779,"about_ca_system_score_codex":0.0019671286,"about_ca_system_score_gemma":0.0021778645,"threshold_uncertainty_score":0.07056248},"labels":[],"label_agreement":null},{"id":"W4367158461","doi":"10.1021/cen-09943-buscon18","title":"Business Roundup","year":2021,"lang":"en","type":"article","venue":"C&EN Global Enterprise","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Commerce","score_opus":0.005058223050982897,"score_gpt":0.2186615157666056,"score_spread":0.21360329271562273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367158461","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00035325534,0.0010379787,0.0011937062,0.02063656,0.041824766,0.00038229517,0.003298046,0.003439848,0.92783356],"genre_scores_gemma":[0.0009583213,0.00035183938,0.0003394228,0.004409355,0.0024402053,0.00009081268,0.0013108441,0.0005898756,0.98950934],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978156,0.00021992644,0.00009735509,0.00033684957,0.0012264635,0.00030382947],"domain_scores_gemma":[0.99132794,0.00065209053,0.00028443802,0.0008250341,0.0033915613,0.0035190042],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0018859367,0.0013416378,0.00077786326,0.0015835334,0.002513714,0.010154889,0.0020609363,0.0045771543,0.8049203],"category_scores_gemma":[0.009189039,0.0005549999,0.0007509374,0.0013737057,0.00082426064,0.0049223425,0.003921767,0.0044170907,0.8113798],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012042251,0.000012401098,0.000021635571,0.000027353264,7.2224844e-7,0.000019986173,0.000008675966,0.000009631761,0.000070666836,0.00089161965,0.97955453,0.019370902],"study_design_scores_gemma":[0.0000033281162,0.000005154426,0.000059423208,0.000014563811,3.204367e-7,0.000011983806,0.000017188175,0.000010297068,0.0000257711,0.0002337907,0.99961555,0.0000025855873],"about_ca_topic_score_codex":0.002262583,"about_ca_topic_score_gemma":0.0034850235,"teacher_disagreement_score":0.8049203,"about_ca_system_score_codex":0.001527738,"about_ca_system_score_gemma":0.0037537636,"threshold_uncertainty_score":0.27825743},"labels":[],"label_agreement":null},{"id":"W4367838518","doi":"10.1109/sm57895.2023.10112562","title":"Smart Mobility for Sustainable Development Goals: Enablers and Barriers","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"General Motors (Canada)","funders":"","keywords":"Enabling; Sustainability; Sustainable development; Key (lock); Reliability (semiconductor); Computer science; Smart city; Business; Computer security; Telecommunications; Risk analysis (engineering); Internet of Things","score_opus":0.013607548826520561,"score_gpt":0.23231830355616243,"score_spread":0.21871075472964185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367838518","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033479415,0.051747385,0.054341882,0.41618502,0.0036118939,0.00036635096,0.00050436036,0.00027373494,0.43949],"genre_scores_gemma":[0.8009651,0.070470236,0.044186857,0.035732087,0.0018009377,0.0009117977,0.0004890985,0.00017450824,0.04526951],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9935486,0.0020104942,0.0003577567,0.0004927849,0.0024934905,0.0010968497],"domain_scores_gemma":[0.9961914,0.0017236508,0.00042272563,0.00027230784,0.00090695464,0.00048294023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006222592,0.00091777806,0.00063592236,0.0011183023,0.0030159801,0.009670846,0.0013844491,0.0044112504,0.0043660267],"category_scores_gemma":[0.00718781,0.00029813862,0.00048604293,0.0011638219,0.007944632,0.013851215,0.009778921,0.0065055857,0.0009212387],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000101200485,0.00003271515,0.0005174729,0.00036804125,0.000006662802,0.000083777544,0.001455,0.0007912795,0.00028320964,0.96433175,0.011517617,0.020602318],"study_design_scores_gemma":[0.0000065923055,0.000058364923,0.0011300867,0.002062555,0.000014232945,0.0002619296,0.008254556,0.0013596022,0.00056651415,0.5267168,0.45951965,0.000049049344],"about_ca_topic_score_codex":0.004888121,"about_ca_topic_score_gemma":0.0050543197,"teacher_disagreement_score":0.009670846,"about_ca_system_score_codex":0.0037576158,"about_ca_system_score_gemma":0.008912677,"threshold_uncertainty_score":0.03290862},"labels":[],"label_agreement":null},{"id":"W4367838523","doi":"10.1109/sm57895.2023.10112307","title":"Scalable Planning of Garbage Collection in a Smart City","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Truck; Garbage collection; Garbage; Computer science; Scalability; Integer programming; Linear programming; Real-time computing; Operations research; Database; Engineering; Automotive engineering","score_opus":0.026282938736215632,"score_gpt":0.2533001656494789,"score_spread":0.22701722691326326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367838523","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2202588,0.0007017521,0.75993556,0.00067021255,0.00008856037,0.00019019877,0.0008943393,0.002207442,0.015053149],"genre_scores_gemma":[0.887801,0.00034478676,0.10747102,0.00006841759,0.00001547222,0.00018925828,0.0005764702,0.00015997478,0.0033736557],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99970067,0.000070013,0.00001081616,0.00007287243,0.00005354421,0.00009216296],"domain_scores_gemma":[0.9997137,0.00015087985,0.000033503842,0.000021685326,0.00003827766,0.000041959636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045855655,0.0008922036,0.0010328586,0.00045187672,0.0006645312,0.0010532637,0.00083795947,0.0008430989,0.0029500017],"category_scores_gemma":[0.00089859887,0.000816141,0.000757071,0.00096441986,0.0008259868,0.0010442656,0.0013129271,0.0007574152,0.00028647418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023480543,0.000008792968,0.000121883255,0.00001937227,0.0000069102816,0.00003083955,0.000017326252,0.9940341,0.0005018825,0.0015278353,0.00023822063,0.0034693242],"study_design_scores_gemma":[0.0000052993823,0.000011446024,0.00008807391,0.0000028070558,0.0000041826725,0.000005254749,0.000027247464,0.99736136,0.00028974543,0.0017601675,0.00044077545,0.000003642921],"about_ca_topic_score_codex":0.024795618,"about_ca_topic_score_gemma":0.020956436,"teacher_disagreement_score":0.024795618,"about_ca_system_score_codex":0.0013392187,"about_ca_system_score_gemma":0.0018279682,"threshold_uncertainty_score":0.049302578},"labels":[],"label_agreement":null},{"id":"W4371784804","doi":"10.25300/misq/2022/15707","title":"Impact of Ride-Hailing Services on Transportation Mode Choices: Evidence from Traffic and Transit Ridership","year":2022,"lang":"en","type":"article","venue":"MIS Quarterly","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Public transport; Leverage (statistics); Mode choice; Transport engineering; Traffic congestion; Business; Mode (computer interface); Travel behavior; Computer science; Engineering","score_opus":0.017203495531151643,"score_gpt":0.2559409969982914,"score_spread":0.2387375014671398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4371784804","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99766797,0.00024684815,0.00019180473,0.0001402967,0.000005616981,0.000008348862,0.0008899297,0.000004199501,0.0008450503],"genre_scores_gemma":[0.9983912,0.0001956101,0.00009454649,0.00003407958,0.000010719832,0.00001057556,0.00092494144,0.000004174647,0.0003340527],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982089,0.0008194609,0.00013061901,0.00033046375,0.00024771158,0.0002628347],"domain_scores_gemma":[0.985313,0.005416167,0.00539543,0.0011817773,0.001220321,0.0014732992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018344895,0.00030354122,0.00043342696,0.0012012802,0.0005442231,0.0010107668,0.0008603033,0.00062644127,0.00415655],"category_scores_gemma":[0.012129004,0.00027698535,0.0012249063,0.0023710898,0.00086858746,0.0013518429,0.0016451824,0.001035219,0.00055757735],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017505919,0.00014220341,0.99373925,0.000044341363,0.00027596598,0.000059500937,0.0006088452,0.00040693747,0.00008585115,0.00026727852,0.0004426449,0.0037520258],"study_design_scores_gemma":[0.00000634828,0.00007764125,0.9972416,0.00002372291,0.000073307834,0.000030487558,0.0010254085,0.0007116039,0.000057170062,0.00011199761,0.0006337574,0.0000068295726],"about_ca_topic_score_codex":0.041162375,"about_ca_topic_score_gemma":0.047245003,"teacher_disagreement_score":0.041162375,"about_ca_system_score_codex":0.000535718,"about_ca_system_score_gemma":0.00039831176,"threshold_uncertainty_score":0.08184558},"labels":[],"label_agreement":null},{"id":"W4376639351","doi":"10.18280/isi.280229","title":"Data Export and Optimization Technique in Connected Vehicle","year":2023,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Business","score_opus":0.027440612966080802,"score_gpt":0.2510381604726928,"score_spread":0.22359754750661198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376639351","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024632355,0.0004599432,0.96009034,0.00023704652,0.00008834396,0.00006273092,0.00013183965,0.001254567,0.013042821],"genre_scores_gemma":[0.717741,0.00081016676,0.2592442,0.00015445663,0.00010132072,0.00019803386,0.0007074652,0.00048495864,0.020558387],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99979323,0.00003230492,0.000012521231,0.00004151287,0.00009481625,0.000025525022],"domain_scores_gemma":[0.99984837,0.000040730632,0.00001681328,0.000026691505,0.00005895167,0.000008349197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028075758,0.00056963146,0.0005077692,0.00085389835,0.00046203376,0.00079691445,0.0006054995,0.00046265824,0.0061363326],"category_scores_gemma":[0.00071928755,0.0002567057,0.00061191065,0.0009122069,0.00033109612,0.00076650316,0.0006552212,0.00049882865,0.00102941],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022624883,0.00014709984,0.00224341,0.00028442094,0.00006846064,0.00030090354,0.00021235875,0.5851943,0.018011713,0.045611147,0.008595516,0.33910444],"study_design_scores_gemma":[0.000013188531,0.000058855796,0.00039817352,0.000013309398,0.000012939251,0.00007792324,0.000047887363,0.98267406,0.0036631052,0.0064279726,0.0066028335,0.0000097275615],"about_ca_topic_score_codex":0.0043144054,"about_ca_topic_score_gemma":0.002338569,"teacher_disagreement_score":0.0061363326,"about_ca_system_score_codex":0.00042717127,"about_ca_system_score_gemma":0.000586179,"threshold_uncertainty_score":0.020528078},"labels":[],"label_agreement":null},{"id":"W4378469237","doi":"10.1155/2023/6597844","title":"NCG-TSM: A Noncooperative Game for the Taxi Sharing Model in Urban Road Networks","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Foundation of Jiangxi Province; National Natural Science Foundation of China","keywords":"Traffic congestion; Computer science; Transport engineering; Travel time; Fuel efficiency; Resource (disambiguation); Nash equilibrium; Operations research; Simulation; Mathematical optimization; Computer network; Engineering; Automotive engineering; Mathematics","score_opus":0.01832241313562547,"score_gpt":0.2667108822273101,"score_spread":0.24838846909168463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378469237","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03407402,0.00014362224,0.95947725,0.00026522475,0.000056629287,0.00008376876,0.0001008185,0.0001059784,0.0056927893],"genre_scores_gemma":[0.957256,0.00023194628,0.036962543,0.00009553069,0.000024927349,0.0002030186,0.00007031877,0.000022470085,0.0051331287],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993175,0.00025219744,0.000024673887,0.00014242798,0.00013964692,0.00012363034],"domain_scores_gemma":[0.99943894,0.0002587081,0.000095453914,0.000032649594,0.00010097299,0.00007332454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008413984,0.0009789369,0.00088428525,0.0004172983,0.0005922012,0.00092933537,0.0014138516,0.0009797749,0.0019987188],"category_scores_gemma":[0.0015271956,0.00029202973,0.0006606461,0.00060932094,0.0014053266,0.0011984674,0.0012072962,0.0011814417,0.00020505792],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004113304,0.000026242877,0.00033688053,0.000037499092,0.000018538134,0.00014023944,0.000053343025,0.9460344,0.0010104966,0.04658578,0.0007196356,0.004995799],"study_design_scores_gemma":[0.00000529658,0.000016654267,0.000037917715,0.0000016504274,0.000003831296,0.000013263107,0.000012215738,0.9946374,0.00007517373,0.0049677254,0.00022483389,0.000004001177],"about_ca_topic_score_codex":0.013829647,"about_ca_topic_score_gemma":0.008079976,"teacher_disagreement_score":0.013829647,"about_ca_system_score_codex":0.0015494616,"about_ca_system_score_gemma":0.0018090457,"threshold_uncertainty_score":0.027498305},"labels":[],"label_agreement":null},{"id":"W4379527327","doi":"10.2139/ssrn.4471026","title":"Compensation Guarantees in Crowdsourced Delivery: Impact on Platform and Driver Welfare","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Toronto Metropolitan University","funders":"","keywords":"Compensation (psychology); Welfare; Business; Crowdsourcing; Computer science; Economics; World Wide Web; Psychology; Market economy; Social psychology","score_opus":0.014924461841508318,"score_gpt":0.25039880368010414,"score_spread":0.23547434183859584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379527327","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77022666,0.0023917633,0.16807473,0.007906326,0.0012638889,0.00049576873,0.0021207668,0.0015469225,0.045973185],"genre_scores_gemma":[0.9914799,0.00012730341,0.0027330974,0.00013435549,0.00011010102,0.000056203004,0.00015534107,0.00003869759,0.00516492],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955753,0.0015560543,0.00014277504,0.0006807938,0.001188103,0.0008569415],"domain_scores_gemma":[0.97029155,0.017951196,0.0032948481,0.0030941004,0.0033333579,0.0020350674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008851851,0.0010388849,0.0014765426,0.0010010173,0.0016505632,0.0035139734,0.002919898,0.003574158,0.017465651],"category_scores_gemma":[0.037004746,0.0005799411,0.00086262636,0.0011548547,0.0012777306,0.0036186306,0.0038446651,0.0030172076,0.0020239884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.01250768,0.0027181858,0.036628224,0.001044587,0.00044458808,0.00093303365,0.0016020619,0.4534873,0.0073716715,0.14179899,0.036614016,0.30484965],"study_design_scores_gemma":[0.0013456261,0.0030936005,0.040264513,0.00048532506,0.00050081784,0.0004834341,0.0037196488,0.72230625,0.005573036,0.20290698,0.019056676,0.0002640222],"about_ca_topic_score_codex":0.007634598,"about_ca_topic_score_gemma":0.0047158683,"teacher_disagreement_score":0.017465651,"about_ca_system_score_codex":0.0023903002,"about_ca_system_score_gemma":0.0043897703,"threshold_uncertainty_score":0.058428407},"labels":[],"label_agreement":null},{"id":"W4379660562","doi":"10.2139/ssrn.4471292","title":"Machine Learning-enhanced Column Generation Approach for Express Shipments with Autonomous Robots and Public Transportation","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; University of Waterloo","funders":"","keywords":"Column (typography); Robot; Column generation; Business; Computer science; Artificial intelligence; Computer network; Mathematics","score_opus":0.015738972376624773,"score_gpt":0.21884188675515132,"score_spread":0.20310291437852654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379660562","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0330869,0.0004978638,0.9611411,0.0002525716,0.00014274733,0.00010450343,0.00039031947,0.0017196912,0.002664234],"genre_scores_gemma":[0.53557247,0.0003583218,0.44946474,0.00021289289,0.00021156053,0.00021748719,0.0018506416,0.00027357816,0.01183831],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99970716,0.00006914163,0.000013579174,0.00008828241,0.000060415427,0.00006137105],"domain_scores_gemma":[0.99925286,0.00037891147,0.00005898127,0.00006967663,0.00019447261,0.000045016397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004508703,0.0007737354,0.001063862,0.00096569065,0.000559899,0.00093741424,0.0014357516,0.0009764591,0.0061429194],"category_scores_gemma":[0.0011907757,0.00050279923,0.0011559889,0.0011076065,0.00036768365,0.00075056707,0.0006582942,0.0010372343,0.0010045182],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023247363,0.00018983718,0.0009909199,0.00017623248,0.000077816876,0.00024103682,0.00007219329,0.71163374,0.004364463,0.005237878,0.0072887265,0.2694947],"study_design_scores_gemma":[0.0000048420616,0.000016709517,0.00009039362,0.0000023221055,0.0000069483863,0.00001129422,0.000008755841,0.997959,0.00043039376,0.0010869917,0.00037883068,0.000003516921],"about_ca_topic_score_codex":0.016584232,"about_ca_topic_score_gemma":0.01750695,"teacher_disagreement_score":0.016584232,"about_ca_system_score_codex":0.00061211106,"about_ca_system_score_gemma":0.0013000588,"threshold_uncertainty_score":0.032975376},"labels":[],"label_agreement":null},{"id":"W4379911948","doi":"10.54254/2754-1169/6/20220207","title":"Human-Computer Interaction Applied in Rental Market","year":2023,"lang":"en","type":"article","venue":"Advances in Economics Management and Political Sciences","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Renting; Computer science; Human–computer interaction; Business; Engineering","score_opus":0.01201765968259174,"score_gpt":0.2714726363515068,"score_spread":0.2594549766689151,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379911948","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34736523,0.02129678,0.11234058,0.00815762,0.0012191127,0.0005248316,0.00025069984,0.0006740449,0.5081711],"genre_scores_gemma":[0.9750377,0.0024686605,0.008004825,0.0003778205,0.0001258797,0.000109919434,0.000037668087,0.000027898683,0.013809574],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991035,0.00045539255,0.000035396886,0.0000993886,0.0002259171,0.00008043716],"domain_scores_gemma":[0.9991498,0.00058556546,0.00003957089,0.000042045052,0.00013266027,0.000050302337],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087492523,0.00033943783,0.0001977772,0.0011427467,0.0010702168,0.002831198,0.00044749735,0.0010807491,0.010365402],"category_scores_gemma":[0.002737788,0.00011697799,0.00029779627,0.00092948496,0.0012900954,0.0019746441,0.0010889544,0.00046223728,0.00078814494],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004977921,0.00050136255,0.018092515,0.0023492672,0.00010985674,0.0037784083,0.019900894,0.017322062,0.017223567,0.41514364,0.027889356,0.47719124],"study_design_scores_gemma":[0.00011699335,0.0013713742,0.08942826,0.0013680949,0.00018726024,0.00544582,0.034927797,0.22236912,0.015097186,0.24226725,0.3871581,0.0002628154],"about_ca_topic_score_codex":0.0050185993,"about_ca_topic_score_gemma":0.0025032405,"teacher_disagreement_score":0.010365402,"about_ca_system_score_codex":0.0011679506,"about_ca_system_score_gemma":0.00085136236,"threshold_uncertainty_score":0.034675717},"labels":[],"label_agreement":null},{"id":"W4380203506","doi":"10.1007/s10489-023-04603-7","title":"Linear programming-based solution methods for constrained partially observable Markov decision processes","year":2023,"lang":"en","type":"article","venue":"Applied Intelligence","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Mathematical optimization; Markov decision process; Flexibility (engineering); Time horizon; Linear programming; Partially observable Markov decision process; Observable; Dynamic programming; Linear approximation; Markov chain; Markov process; Algorithm; Markov model; Mathematics; Nonlinear system","score_opus":0.05473292348790335,"score_gpt":0.35094116424215926,"score_spread":0.2962082407542559,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380203506","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025965266,0.000317438,0.99506015,0.00022404527,0.000040434148,0.00004508592,0.00006180324,0.00008616932,0.0015683839],"genre_scores_gemma":[0.40317154,0.0014008643,0.5801587,0.00041695024,0.00026001548,0.0011902917,0.0006876789,0.0003653817,0.0123485215],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985909,0.0007353269,0.0000633177,0.0002350533,0.00021340275,0.00016197478],"domain_scores_gemma":[0.9889348,0.009833099,0.00035672693,0.00011557727,0.00059430825,0.00016543227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032946733,0.0016981848,0.0026399926,0.0014302739,0.0007839268,0.0019005582,0.002311601,0.0024623054,0.0073047243],"category_scores_gemma":[0.010862759,0.0019269234,0.0015947288,0.0018672826,0.0016732033,0.0018485833,0.0025754634,0.00343249,0.00061257975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027764605,0.00004057727,0.00009945505,0.00008774165,0.00003344703,0.000021057373,0.000029685774,0.9729556,0.00009756285,0.01649338,0.00059421227,0.009519487],"study_design_scores_gemma":[0.0000070418027,0.000004904858,0.000012120564,0.000007297276,0.000003209058,0.0000015369972,0.000004631438,0.9923005,0.000030416513,0.0074976734,0.00012789815,0.0000025935353],"about_ca_topic_score_codex":0.02109995,"about_ca_topic_score_gemma":0.015553217,"teacher_disagreement_score":0.02109995,"about_ca_system_score_codex":0.0021515551,"about_ca_system_score_gemma":0.004468009,"threshold_uncertainty_score":0.04195428},"labels":[],"label_agreement":null},{"id":"W4380367053","doi":"10.17118/11143/20076","title":"Réduire les émissions par l’adoption de modes de transport durable et par l’aménagement viable du territoire : une solution en parallèle de la CCNUCC?","year":2011,"lang":"fr","type":"article","venue":"Cahiers de recherche en politique appliquée","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Political science","score_opus":0.059122619262145314,"score_gpt":0.3159510768764264,"score_spread":0.2568284576142811,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380367053","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29127252,0.017638763,0.32383922,0.09771558,0.0014036801,0.0007525531,0.0006815589,0.00046689308,0.26622924],"genre_scores_gemma":[0.8757817,0.0062604565,0.07000565,0.0020599347,0.00023982995,0.00045231773,0.00017781055,0.00016879875,0.04485337],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.996741,0.0012421634,0.000089823996,0.00057775324,0.0008068163,0.00054246583],"domain_scores_gemma":[0.99729854,0.0007022514,0.000370657,0.0002647548,0.0011752683,0.00018843921],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004122085,0.00089882786,0.0006607163,0.0012557039,0.0014207616,0.0053789755,0.0020721832,0.0039431495,0.007488157],"category_scores_gemma":[0.005558289,0.00040187832,0.0010771937,0.0018403523,0.0022861464,0.0032812592,0.0035732617,0.0027047587,0.00059102214],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002143019,0.0003195605,0.022677692,0.0012495858,0.00020914822,0.00040783366,0.0031445909,0.06558307,0.012408031,0.5680012,0.0079687685,0.31781617],"study_design_scores_gemma":[0.00010282711,0.00095090317,0.06355683,0.0023456474,0.00030130387,0.00049048534,0.018609801,0.10628977,0.016550124,0.25729126,0.5332083,0.00030273915],"about_ca_topic_score_codex":0.06112763,"about_ca_topic_score_gemma":0.088437214,"teacher_disagreement_score":0.06112763,"about_ca_system_score_codex":0.008468302,"about_ca_system_score_gemma":0.01344147,"threshold_uncertainty_score":0.121543646},"labels":[],"label_agreement":null},{"id":"W4381800917","doi":"10.1061/jtepbs.teeng-7301","title":"Investigating Changes in Ride-Sourcing Use during the COVID-19 Pandemic: Evidence from a Two-Cycle Survey of the Greater Toronto Area","year":2023,"lang":"en","type":"article","venue":"Journal of Transportation Engineering Part A Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Survey research; Geography; Virology; Medicine; Psychology; Applied psychology; Outbreak","score_opus":0.09685130316863517,"score_gpt":0.2795416085118336,"score_spread":0.1826903053431984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381800917","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99825615,0.00008172422,0.000043789358,0.0000973121,0.0000028037418,0.000034866007,0.0008963824,0.0000016678179,0.00058530737],"genre_scores_gemma":[0.9985201,0.00017068029,0.00008264437,0.000068852256,0.000004166062,0.00003871226,0.0007091575,0.0000015079917,0.00040425363],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990791,0.00025447298,0.00007301363,0.00013068302,0.0002325659,0.00023015671],"domain_scores_gemma":[0.99626154,0.00044342916,0.0015993934,0.00018181659,0.00091386033,0.00059997186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009428693,0.00030081073,0.00021082978,0.0010151245,0.0010489539,0.0009492555,0.0008125795,0.00079889357,0.0012996087],"category_scores_gemma":[0.003925996,0.00036213218,0.00041981696,0.0023182572,0.00077032583,0.00071654026,0.0010356368,0.0006706844,0.0002542662],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051263974,0.000046891208,0.9909174,0.000048180005,0.000041102685,0.00009992921,0.006295311,0.00007142238,0.0003038659,0.000030169316,0.00031849244,0.0017760831],"study_design_scores_gemma":[0.0000013513516,0.000036303663,0.9949384,0.000010641638,0.000005369641,0.000013306895,0.004660576,0.00006791648,0.00002971749,0.000002599344,0.00023016552,0.0000035890175],"about_ca_topic_score_codex":0.7992486,"about_ca_topic_score_gemma":0.8742,"teacher_disagreement_score":0.7992486,"about_ca_system_score_codex":0.0054229996,"about_ca_system_score_gemma":0.0028184152,"threshold_uncertainty_score":0.40386736},"labels":[],"label_agreement":null},{"id":"W4382279112","doi":"10.1515/9780773552449-010","title":"The Role of User Fees in Urban Transportation Public–Private Partnerships: Canada in a Global Perspective","year":2017,"lang":"en","type":"book-chapter","venue":"McGill-Queen's University Press eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Perspective (graphical); Business; Public transport; Public administration; Regional science; Transport engineering; Geography; Political science; Engineering; Computer science","score_opus":0.016920146030061502,"score_gpt":0.20498696838190616,"score_spread":0.18806682235184466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382279112","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.039284177,0.027156396,0.0022346172,0.13116568,0.001136285,0.00013674506,0.00047412963,0.000080216276,0.79833174],"genre_scores_gemma":[0.734794,0.037339453,0.0019957193,0.011116281,0.00039692246,0.00012315955,0.00027358503,0.000115384624,0.21384552],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99308664,0.0007644894,0.00012029739,0.00033536585,0.0026882004,0.0030050108],"domain_scores_gemma":[0.99147934,0.0023468467,0.00032908184,0.0002523028,0.0033113318,0.0022811915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003110268,0.0005573454,0.0006964268,0.002839805,0.014836715,0.02006065,0.0025215896,0.0051897103,0.0125810625],"category_scores_gemma":[0.012674613,0.00055658596,0.00061587675,0.010426133,0.010207666,0.0067759263,0.004774717,0.0069641257,0.0006046131],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030011559,0.00003017713,0.001948436,0.00011651515,0.000009787863,0.00022379133,0.0046530096,0.0009915767,0.00006641012,0.89237446,0.059972886,0.03958287],"study_design_scores_gemma":[0.00004799255,0.00004083183,0.013929485,0.0010074513,0.00006103008,0.00025183544,0.018443614,0.0025879377,0.00021056976,0.09792329,0.8653767,0.000119173834],"about_ca_topic_score_codex":0.9907664,"about_ca_topic_score_gemma":0.9944179,"teacher_disagreement_score":0.1637492,"about_ca_system_score_codex":0.1637492,"about_ca_system_score_gemma":0.314709,"threshold_uncertainty_score":0.9699324},"labels":[],"label_agreement":null},{"id":"W4382985772","doi":"10.1287/msom.2023.1221","title":"Ride-Hailing Networks with Strategic Drivers: The Impact of Platform Control Capabilities on Performance","year":2023,"lang":"en","type":"article","venue":"Manufacturing & Service Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":73,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Control (management); Matching (statistics); Computer science; Compensation (psychology); Operations research; Supply and demand; Business; Economics; Microeconomics; Engineering","score_opus":0.014932886539622516,"score_gpt":0.21955115281468104,"score_spread":0.20461826627505852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382985772","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.65863204,0.00062026025,0.31596127,0.0025997395,0.00012169815,0.00029514724,0.0003241495,0.00020785173,0.021237757],"genre_scores_gemma":[0.9934917,0.00013494393,0.0053543197,0.00006187371,0.000016391648,0.00004235482,0.000029108516,0.000012943276,0.0008563873],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981477,0.0007700056,0.0000462943,0.00033485674,0.00017812138,0.0005230433],"domain_scores_gemma":[0.9874899,0.008437953,0.001532165,0.00065600284,0.0009416526,0.0009423115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034956017,0.0012539452,0.0011337083,0.0007591202,0.0009426955,0.0030475655,0.0021341252,0.0021509368,0.004614274],"category_scores_gemma":[0.023872769,0.00045666948,0.00057628343,0.0006988078,0.0023696756,0.0039225365,0.002974819,0.0016935501,0.00034911177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028883002,0.00013891348,0.0030379351,0.00012315188,0.00005640289,0.00014415557,0.00017058662,0.9498816,0.0031386607,0.033767395,0.00084632944,0.008406003],"study_design_scores_gemma":[0.000027556101,0.0002460775,0.0006762281,0.00002492104,0.000024896479,0.00006656191,0.00029398082,0.98015356,0.0012402056,0.016887711,0.00033441163,0.000023794726],"about_ca_topic_score_codex":0.0077764075,"about_ca_topic_score_gemma":0.0034453196,"teacher_disagreement_score":0.0077764075,"about_ca_system_score_codex":0.0022841764,"about_ca_system_score_gemma":0.0020762575,"threshold_uncertainty_score":0.018486738},"labels":[],"label_agreement":null},{"id":"W4383070024","doi":"10.1016/j.cor.2023.106338","title":"Off-line approximate dynamic programming for the vehicle routing problem with a highly variable customer basis and stochastic demands","year":2023,"lang":"en","type":"article","venue":"Computers & Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Group for Research in Decision Analysis","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Vehicle routing problem; Computer science; Context (archaeology); Markov decision process; Mathematical optimization; Set (abstract data type); Variable (mathematics); Dynamic programming; State variable; Routing (electronic design automation); Markov process; Mathematics","score_opus":0.03419786777119948,"score_gpt":0.3140108607773663,"score_spread":0.2798129930061668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383070024","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05419,0.00031848758,0.9400373,0.0005867527,0.000059107977,0.00008486156,0.00023243608,0.00017109465,0.0043199994],"genre_scores_gemma":[0.85586035,0.0004530094,0.13331789,0.00019160059,0.00011330285,0.00027861033,0.00054366153,0.00017118453,0.009070394],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988267,0.0005852466,0.000033678854,0.00014072472,0.00023041146,0.0001833012],"domain_scores_gemma":[0.99605787,0.0031481527,0.00025124394,0.00013253206,0.00028163032,0.00012851867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020572657,0.0011475475,0.0020386833,0.0007190004,0.00049585087,0.0016772219,0.0017091825,0.0018170523,0.0033580558],"category_scores_gemma":[0.0076405206,0.0011886009,0.0008832685,0.0013096737,0.0010733692,0.0018515931,0.0011426895,0.001936586,0.00032918187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043903237,0.000027098116,0.000112201335,0.000021116375,0.000009328303,0.000016054275,0.000009788246,0.9921633,0.00010224352,0.0037924675,0.00030420852,0.003398188],"study_design_scores_gemma":[0.0000028785207,0.0000069826783,0.000016024565,0.0000012027517,0.0000012477439,0.000002384735,0.0000024788358,0.9984629,0.00001995642,0.0014383439,0.00004442596,0.0000011567963],"about_ca_topic_score_codex":0.012160595,"about_ca_topic_score_gemma":0.009951784,"teacher_disagreement_score":0.012160595,"about_ca_system_score_codex":0.0017996596,"about_ca_system_score_gemma":0.0019152107,"threshold_uncertainty_score":0.024179637},"labels":[],"label_agreement":null},{"id":"W4383499348","doi":"10.1109/tits.2023.3288978","title":"Guest Editorial Special Issue on Intelligent Autonomous Transportation Systems With 6G—Part IV","year":2023,"lang":"en","type":"editorial","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Exfo Electro-Optical Engineering (Canada)","funders":"","keywords":"Intelligent transportation system; Computer science; Process (computing); Intelligent decision support system; Presentational and representational acting; Quality (philosophy); Originality; Systems engineering; Engineering management; Data science; Engineering; Transport engineering; Artificial intelligence; Sociology","score_opus":0.015864824288054937,"score_gpt":0.24439870767526253,"score_spread":0.2285338833872076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383499348","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000048866423,0.0028392056,0.00016363418,0.01124169,0.98278564,0.000017709423,0.00003741641,0.000042278185,0.0028236038],"genre_scores_gemma":[0.0005390709,0.003478096,0.00009168933,0.0048312284,0.97826284,0.000014875349,0.00003650606,0.000047723886,0.012697996],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973744,0.00028248198,0.00028960672,0.0003670132,0.0014404011,0.00024604163],"domain_scores_gemma":[0.99042374,0.001994362,0.00055016263,0.00025296368,0.0051292856,0.0016493566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033369246,0.002427885,0.0019557814,0.0029323143,0.002050319,0.006636245,0.0016922429,0.005987253,0.027719602],"category_scores_gemma":[0.008925174,0.0005578128,0.0018174448,0.0010185402,0.0012396943,0.0033576554,0.0010516429,0.009112875,0.017342284],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003539612,0.000015631154,0.000036580048,0.00021722325,0.0000102908525,0.00011796636,0.000010780062,0.000034535467,0.00012914819,0.00057679263,0.99055934,0.008256337],"study_design_scores_gemma":[0.000019525876,0.000028225855,0.00020590726,0.00019761572,0.000023267496,0.00021634263,0.000027404623,0.00010942297,0.00017110046,0.0006961592,0.99829453,0.0000105496965],"about_ca_topic_score_codex":0.00063966773,"about_ca_topic_score_gemma":0.0015416935,"teacher_disagreement_score":0.027719602,"about_ca_system_score_codex":0.0018279109,"about_ca_system_score_gemma":0.002075725,"threshold_uncertainty_score":0.09273124},"labels":[],"label_agreement":null},{"id":"W4383620675","doi":"10.1016/j.tbs.2023.100637","title":"Identifying profiles of ride-sourcing users in the Metro Vancouver Region for a better understanding of ride-sourcing behaviour","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Multinomial logistic regression; Business; TRIPS architecture; Latent class model; Strategic sourcing; Crowd sourcing; Marketing; Transport engineering; Computer science; Data science; Engineering","score_opus":0.06806836674001245,"score_gpt":0.27907370660827735,"score_spread":0.21100533986826492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383620675","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974517,0.000067845496,0.00020714068,0.00007516037,0.0000018693318,0.000036068977,0.00094116776,0.000005927029,0.0012130716],"genre_scores_gemma":[0.9956741,0.00016802613,0.0006926767,0.000041446572,0.0000023898801,0.000044838496,0.0012255555,0.000007834711,0.002143077],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996804,0.0000631935,0.000021457454,0.000053721422,0.000071108196,0.000110095774],"domain_scores_gemma":[0.99892646,0.00016849366,0.00018211438,0.00005685081,0.00040112232,0.00026504163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031748548,0.00015699868,0.00024387633,0.0018039941,0.0012429559,0.0013090614,0.00040257367,0.00040847962,0.002421439],"category_scores_gemma":[0.0017577258,0.0001530633,0.00016697583,0.003086543,0.00016550798,0.00057347916,0.0006780735,0.00038186574,0.00059798587],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004189983,0.00005828349,0.9770821,0.00003462617,0.000022273534,0.00007718511,0.006772142,0.00010123532,0.0012020083,0.00010453866,0.00086408976,0.01363957],"study_design_scores_gemma":[0.0000012127806,0.00001741545,0.9764579,0.00003254898,0.000007996562,0.000055457516,0.020688059,0.00078195066,0.00015862401,0.00005707737,0.0017321494,0.000009580238],"about_ca_topic_score_codex":0.5518934,"about_ca_topic_score_gemma":0.75324446,"teacher_disagreement_score":0.4481066,"about_ca_system_score_codex":0.0011195281,"about_ca_system_score_gemma":0.0016189627,"threshold_uncertainty_score":0.90149117},"labels":[],"label_agreement":null},{"id":"W4383745888","doi":"10.1109/msmc.2022.3220315","title":"MDN-Enabled SO for Vehicle Proactive Guidance in Ride-Hailing Systems: Minimizing Travel Distance and Wait Time","year":2023,"lang":"en","type":"article","venue":"IEEE Systems Man and Cybernetics Magazine","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ericsson (Canada); HEC Montréal; Université de Montréal; Concordia University","funders":"","keywords":"Idle; Computer science; Travel time; Real-time computing; Guidance system; Transport engineering; Simulation; Engineering","score_opus":0.013035554932354034,"score_gpt":0.22232639531012366,"score_spread":0.20929084037776963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383745888","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15940349,0.00043559,0.83515644,0.00040500765,0.00007822436,0.00004443009,0.00014503383,0.0007996196,0.0035321068],"genre_scores_gemma":[0.97968847,0.000059670958,0.01891976,0.00006085646,0.000011077162,0.000024465942,0.00006717604,0.000018529045,0.0011500085],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998487,0.000026997568,0.000008787568,0.000044502045,0.000032094515,0.00003884481],"domain_scores_gemma":[0.9997118,0.00011321305,0.000043151394,0.000022501266,0.00008100422,0.000028235025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040335808,0.000488412,0.0005464913,0.0002181079,0.00028158646,0.00045832756,0.0009982137,0.00046081233,0.00097618013],"category_scores_gemma":[0.001215128,0.0003117004,0.00030223196,0.00020766044,0.00039877664,0.00072567794,0.0005770494,0.0007080363,0.0001481379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050404546,0.000026777057,0.00063189794,0.00001725674,0.00001540908,0.000022564827,0.000021024047,0.97588205,0.0019599241,0.0021256492,0.00036689398,0.018880181],"study_design_scores_gemma":[9.522328e-7,0.0000074946715,0.000055411037,7.8892145e-7,0.000001786341,0.0000020987648,0.000002014716,0.99929833,0.00022818167,0.0003368825,0.000064834225,0.0000012252602],"about_ca_topic_score_codex":0.015577628,"about_ca_topic_score_gemma":0.018770553,"teacher_disagreement_score":0.015577628,"about_ca_system_score_codex":0.001029062,"about_ca_system_score_gemma":0.0011511972,"threshold_uncertainty_score":0.030973911},"labels":[],"label_agreement":null},{"id":"W4383888655","doi":"10.1109/zinc58345.2023.10174221","title":"Tech in Motion - Where next with the next-generation vehicles?","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Automotive industry; Software; Intelligent transportation system; Motion (physics); Computer science; Engineering; Transport engineering; Engineering management; Artificial intelligence; Aerospace engineering; Operating system","score_opus":0.050246988012948794,"score_gpt":0.2342827242468767,"score_spread":0.1840357362339279,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383888655","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003269964,0.047676053,0.004147385,0.62508494,0.11584935,0.00003432978,0.00021310187,0.00033784934,0.20338704],"genre_scores_gemma":[0.07792723,0.09806452,0.004315331,0.16156131,0.043202832,0.00007045749,0.000504617,0.00080906396,0.61354464],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987112,0.0003248188,0.000048202204,0.00019913062,0.00037518996,0.00034147562],"domain_scores_gemma":[0.99851686,0.00022056678,0.00007170103,0.000060819035,0.0004158011,0.0007143768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018008668,0.00067771814,0.00037829098,0.00078724686,0.0035461376,0.012482126,0.0008036898,0.0046167867,0.03872393],"category_scores_gemma":[0.0034813457,0.00026467507,0.0003985482,0.0010868671,0.0026328093,0.01485334,0.003128521,0.0069184676,0.012976236],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024202835,0.0000333858,0.0006852488,0.00012364422,0.000006596129,0.000087397886,0.0010286866,0.0000735336,0.00042198258,0.05536754,0.87390655,0.06824128],"study_design_scores_gemma":[9.3306323e-7,0.000011720776,0.00014299978,0.00009152527,0.000002376533,0.000052098625,0.0017790527,0.0000282116,0.00009252743,0.0034824307,0.99431086,0.0000052340924],"about_ca_topic_score_codex":0.0029614305,"about_ca_topic_score_gemma":0.0072305077,"teacher_disagreement_score":0.03872393,"about_ca_system_score_codex":0.0018209802,"about_ca_system_score_gemma":0.002722572,"threshold_uncertainty_score":0.12954438},"labels":[],"label_agreement":null},{"id":"W4383987897","doi":"10.48550/arxiv.2307.03984","title":"Optimizing Task Waiting Times in Dynamic Vehicle Routing","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; European Commission","keywords":"Computer science; Queue; Robot; Task (project management); Stability (learning theory); Quality of service; Set (abstract data type); Real-time computing; Mathematical optimization; Artificial intelligence; Computer network; Machine learning; Engineering; Mathematics","score_opus":0.04999521179836423,"score_gpt":0.18475324710421517,"score_spread":0.13475803530585095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383987897","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3215783,0.0010645547,0.6728572,0.0006536863,0.00014717097,0.000067494264,0.00021573479,0.0006010709,0.002814728],"genre_scores_gemma":[0.9663715,0.00026962,0.031470336,0.00006326639,0.000033555054,0.00004796045,0.00013793542,0.00012008943,0.001485834],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916685,0.00026359982,0.000039898023,0.00015599164,0.00013517537,0.00023843552],"domain_scores_gemma":[0.9971439,0.0018272594,0.00036952054,0.0001114129,0.00027891566,0.00026899116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019219695,0.0010176242,0.0009852584,0.0007978441,0.00059497874,0.0010377903,0.0014574148,0.0009576429,0.0011775868],"category_scores_gemma":[0.0063072774,0.000546868,0.00038763406,0.0010256863,0.00087798055,0.0014990667,0.0009419655,0.0008214117,0.00019641811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000082388295,0.000018310562,0.0003520132,0.000023362592,0.000013093645,0.000020302068,0.000022187836,0.9903452,0.00068732095,0.0022051912,0.00030365077,0.0059270295],"study_design_scores_gemma":[0.000006882905,0.000035873432,0.00013365726,0.0000020438845,0.0000041861304,0.000010236219,0.00001868587,0.9968665,0.0002746827,0.0024535798,0.00018940576,0.000004213153],"about_ca_topic_score_codex":0.008637055,"about_ca_topic_score_gemma":0.0049602985,"teacher_disagreement_score":0.008637055,"about_ca_system_score_codex":0.0015345643,"about_ca_system_score_gemma":0.0014052498,"threshold_uncertainty_score":0.017173529},"labels":[],"label_agreement":null},{"id":"W4384025436","doi":"10.31979/mti.2023.2158","title":"Investing in California’s Transportation Future: 2022 Public Opinion on Critical Needs","year":2023,"lang":"en","type":"report","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Public transport; Business; Quarter (Canadian coin); Transport engineering; Work (physics); Transit (satellite); Traffic congestion; Finance; Engineering; Geography","score_opus":0.11298079097923203,"score_gpt":0.3381009107716266,"score_spread":0.22512011979239455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384025436","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7095189,0.002925787,0.00016982756,0.18573259,0.0008079066,0.00006570968,0.000816372,0.00003615948,0.099926755],"genre_scores_gemma":[0.9825398,0.0020082963,0.00015889348,0.0076149395,0.0003121367,0.000031759882,0.00041177947,0.0000068863174,0.0069155553],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993924,0.0001158261,0.000027780452,0.000038513837,0.00018459775,0.00024092829],"domain_scores_gemma":[0.99635255,0.0006660818,0.0006353688,0.000061437015,0.0009590965,0.0013255414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001902532,0.00013706392,0.000101792095,0.00073193497,0.0021230287,0.00210925,0.00034081386,0.0014653471,0.008510594],"category_scores_gemma":[0.0033068578,0.00015638147,0.0001906166,0.00040866868,0.0007030208,0.0021393623,0.0009791193,0.0014613486,0.00029557024],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002077434,0.0003867874,0.4938061,0.00050281006,0.000039114115,0.0008415719,0.047300935,0.00034101514,0.0013952535,0.009727239,0.33561802,0.10983338],"study_design_scores_gemma":[0.000030040123,0.00020246314,0.5334914,0.0005966218,0.000041357678,0.00031467027,0.21741891,0.0004310165,0.00021283494,0.0008509655,0.2463619,0.00004783941],"about_ca_topic_score_codex":0.09928028,"about_ca_topic_score_gemma":0.17544188,"teacher_disagreement_score":0.09928028,"about_ca_system_score_codex":0.003037457,"about_ca_system_score_gemma":0.0046227463,"threshold_uncertainty_score":0.19740486},"labels":[],"label_agreement":null},{"id":"W4384406331","doi":"10.1002/net.22170","title":"Two‐stage stochastic one‐to‐many driver matching for ridesharing","year":2023,"lang":"en","type":"article","venue":"Networks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Université de Montréal; Transport Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Matching (statistics); Benchmark (surveying); Profitability index; Computer science; Set (abstract data type); Mathematical optimization; Stochastic modelling; Operations research; Mathematics; Economics; Finance","score_opus":0.023998235086841346,"score_gpt":0.26334454789435763,"score_spread":0.23934631280751628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384406331","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0963943,0.0005696043,0.8952222,0.0006448593,0.00010629351,0.0002769472,0.0006453013,0.00037187486,0.0057685203],"genre_scores_gemma":[0.9412736,0.0003578415,0.050806306,0.00016261173,0.000051557658,0.00022500013,0.00046156746,0.00009303863,0.006568416],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976578,0.00091950956,0.00008124121,0.00048848597,0.0003152378,0.0005376869],"domain_scores_gemma":[0.99705553,0.0018312195,0.00032527052,0.0002586007,0.00021198906,0.00031725358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033605145,0.0012607739,0.0030886184,0.0007330606,0.000888088,0.0022409032,0.0031850198,0.0023142607,0.008835157],"category_scores_gemma":[0.006291938,0.0010922133,0.00202993,0.0014444869,0.0011905375,0.0026523026,0.0017988862,0.0022243368,0.00062703807],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004382722,0.00004198255,0.00024579346,0.00002718801,0.00001440771,0.000029916226,0.000019660054,0.9877165,0.00020103883,0.008381492,0.00042332927,0.002854809],"study_design_scores_gemma":[0.0000062597956,0.000023987326,0.00007605482,0.0000025177765,0.0000040792356,0.000010344435,0.000008325847,0.996172,0.00007737062,0.0034273467,0.00018666043,0.0000050761773],"about_ca_topic_score_codex":0.0121175265,"about_ca_topic_score_gemma":0.0065401914,"teacher_disagreement_score":0.0121175265,"about_ca_system_score_codex":0.002759132,"about_ca_system_score_gemma":0.002218312,"threshold_uncertainty_score":0.029556572},"labels":[],"label_agreement":null},{"id":"W4384408061","doi":"10.1080/03081060.2023.2230969","title":"Communication and mobility issues of visually impaired pedestrians with connected autonomous vehicles","year":2023,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"CNIB Foundation; University of Toronto","funders":"","keywords":"Pedestrian; Structural equation modeling; Context (archaeology); Computer science; Visually impaired; Confirmatory factor analysis; Latent variable; Econometrics; Transport engineering; Artificial intelligence; Human–computer interaction; Engineering; Machine learning; Mathematics; Geography","score_opus":0.01362594107256283,"score_gpt":0.2575904927464965,"score_spread":0.24396455167393366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384408061","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99660325,0.00013846745,0.0010073814,0.0005556586,0.0000068530576,0.000010091159,0.00010208295,0.0000039180263,0.001572081],"genre_scores_gemma":[0.9993844,0.0000826258,0.00023154753,0.000023084449,0.0000034731397,0.0000049272403,0.00003732005,6.139161e-7,0.00023199733],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988193,0.0005576183,0.0000846023,0.00012419827,0.00017412471,0.00024018442],"domain_scores_gemma":[0.9922404,0.003665877,0.0027637046,0.0002904133,0.0005774793,0.00046208035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014473881,0.00031177202,0.00031881733,0.0012264409,0.00098824,0.0023036222,0.0004765595,0.0009112426,0.0028650968],"category_scores_gemma":[0.0118917925,0.00023841257,0.00043617468,0.0009960942,0.0012326897,0.0015179471,0.0020111327,0.0010115134,0.00031236437],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001594357,0.0003235024,0.9431115,0.00014850333,0.00009531706,0.0012763422,0.018512398,0.004885698,0.0005058133,0.0054305964,0.0008739206,0.024676954],"study_design_scores_gemma":[0.000023634339,0.0006540002,0.79143816,0.0003011314,0.0002131471,0.001584202,0.1611817,0.026331292,0.00071315886,0.012274251,0.005193224,0.00009211036],"about_ca_topic_score_codex":0.033730514,"about_ca_topic_score_gemma":0.023569465,"teacher_disagreement_score":0.033730514,"about_ca_system_score_codex":0.0015516616,"about_ca_system_score_gemma":0.0012777615,"threshold_uncertainty_score":0.06706834},"labels":[],"label_agreement":null},{"id":"W4384464015","doi":"10.2139/ssrn.4502968","title":"Managing Multihoming Workers in the Gig Economy","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Multihoming; Incentive; Workforce; Business; TRIPS architecture; Gig economy; Labour economics; Industrial organization; Economics; Engineering; Microeconomics; Computer science; Transport engineering; The Internet; Labour law; Economic growth","score_opus":0.008955544303964752,"score_gpt":0.2251713343548291,"score_spread":0.21621579005086436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384464015","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90855634,0.00040156595,0.043078743,0.00634315,0.0001911077,0.00009382411,0.00008416373,0.0001686669,0.041082412],"genre_scores_gemma":[0.9892291,0.00014940486,0.0035889086,0.00015450615,0.000042672986,0.000022616901,0.000023870398,0.00001652874,0.0067724264],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99945575,0.00013391244,0.000015573503,0.00006449044,0.00006745675,0.00026283273],"domain_scores_gemma":[0.998248,0.00051721215,0.00022281683,0.00017388012,0.00016063549,0.0006775576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001518237,0.0003139952,0.00028834902,0.0003667818,0.0015951289,0.0028153732,0.0009485941,0.0014005109,0.0070205126],"category_scores_gemma":[0.003319098,0.00016840303,0.00013757091,0.0004686916,0.0006481629,0.0023205138,0.003264224,0.0012097653,0.0008758941],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017456796,0.0016231607,0.12073624,0.00025288668,0.00012612522,0.004699706,0.009623845,0.18986557,0.010769331,0.14225125,0.04995519,0.46835098],"study_design_scores_gemma":[0.00017575547,0.0013923133,0.030913288,0.00023539954,0.00012822592,0.001199332,0.09552232,0.4997718,0.005772079,0.25416648,0.11060327,0.000119740915],"about_ca_topic_score_codex":0.002443361,"about_ca_topic_score_gemma":0.0031396644,"teacher_disagreement_score":0.0070205126,"about_ca_system_score_codex":0.00058297144,"about_ca_system_score_gemma":0.0013527296,"threshold_uncertainty_score":0.023485899},"labels":[],"label_agreement":null},{"id":"W4384788896","doi":"10.1016/bs.atpp.2023.07.005","title":"Examining the impacts of the COVID-19 pandemic on ride-sourcing services: Findings from a literature review and case study","year":2023,"lang":"en","type":"review","venue":"Advances in transport policy and planning","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Pandemic; Business; TRIPS architecture; Paratransit; Perception; Risk perception; Marketing; Public transport; Coronavirus disease 2019 (COVID-19); Empirical evidence; Psychology; Engineering; Transport engineering; Infectious disease (medical specialty); Medicine","score_opus":0.07878559951261843,"score_gpt":0.38354331254706026,"score_spread":0.3047577130344418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384788896","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007317131,0.9971981,0.00006773012,0.0006512073,0.00009625326,0.00002406375,0.00011448445,0.0000021543046,0.0011143037],"genre_scores_gemma":[0.0044792583,0.99496764,0.00013679851,0.00024569102,0.000033589393,0.000013760457,0.000048765844,0.0000012325817,0.0000732959],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.9977792,0.00073125534,0.0004421691,0.0002047792,0.000666251,0.00017644047],"domain_scores_gemma":[0.9891049,0.008200619,0.0010570543,0.00009996947,0.0013941943,0.00014316195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042997655,0.0009368726,0.0017603566,0.0068631573,0.00051260565,0.0029248428,0.0009728367,0.001803424,0.004154399],"category_scores_gemma":[0.01380708,0.00038964604,0.0015367687,0.013693374,0.0005986331,0.0020401147,0.001283388,0.0013441477,0.00049633364],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014274639,0.00009021043,0.002342083,0.38466856,0.001014226,0.00054442935,0.0011514074,0.0007975615,0.00050593505,0.0073535545,0.01826547,0.58312386],"study_design_scores_gemma":[0.00004193307,0.00022691657,0.013724186,0.45140797,0.004541332,0.0010871276,0.0053248974,0.00031162833,0.0006862578,0.0021144005,0.52044123,0.00009207624],"about_ca_topic_score_codex":0.018868884,"about_ca_topic_score_gemma":0.044103816,"teacher_disagreement_score":0.018868884,"about_ca_system_score_codex":0.0028869663,"about_ca_system_score_gemma":0.01189642,"threshold_uncertainty_score":0.037518144},"labels":[],"label_agreement":null},{"id":"W4385065652","doi":"10.1287/mnsc.2023.4858","title":"Courier Dispatch in On-Demand Delivery","year":2023,"lang":"en","type":"article","venue":"Management Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Pooling; Service (business); Computer science; Exploit; Operations research; Microeconomics; Economics; Business; Marketing; Mathematics","score_opus":0.010832390506326875,"score_gpt":0.2341988601350254,"score_spread":0.22336646962869852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385065652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52844536,0.0030583746,0.41673574,0.002989642,0.0007409756,0.00048017714,0.0012639543,0.00065232284,0.045633428],"genre_scores_gemma":[0.9759176,0.0005399246,0.0132751595,0.00020846649,0.00011429058,0.00008080183,0.0002216407,0.00011742076,0.00952477],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99771845,0.00095163955,0.000087973116,0.0003809974,0.00027309326,0.00058788044],"domain_scores_gemma":[0.9911965,0.005607367,0.0014186612,0.00033655096,0.00052774366,0.0009132822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00326336,0.002142196,0.0027249644,0.00080729,0.0009719534,0.0030210873,0.0022088846,0.0023644408,0.011079493],"category_scores_gemma":[0.009714364,0.000979138,0.0014252566,0.00083753397,0.0017728244,0.0033801512,0.0017443176,0.0026625874,0.00062551926],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024076724,0.00011988725,0.0005769545,0.00012117683,0.000055020606,0.00019819257,0.00009368474,0.960461,0.0007792386,0.0318034,0.0012998933,0.0042507495],"study_design_scores_gemma":[0.00007132809,0.00012173129,0.00033946853,0.000011531032,0.000018507708,0.000038440732,0.00008029267,0.9815756,0.00021545403,0.016540354,0.0009632516,0.0000240918],"about_ca_topic_score_codex":0.01642394,"about_ca_topic_score_gemma":0.005529553,"teacher_disagreement_score":0.01642394,"about_ca_system_score_codex":0.0035062414,"about_ca_system_score_gemma":0.0017955088,"threshold_uncertainty_score":0.037064612},"labels":[],"label_agreement":null},{"id":"W4385187658","doi":"10.1016/j.tranpol.2023.07.022","title":"Unravelling the relationship between ride-sourcing services and conventional modes in the city of Toronto: A stated preference study","year":2023,"lang":"en","type":"article","venue":"Transport Policy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"TRIPS architecture; Business; Externality; Descriptive statistics; Population; Mode choice; Marketing; Public transport; Transport engineering; Economics; Engineering; Microeconomics","score_opus":0.09363112544444491,"score_gpt":0.3131485414918007,"score_spread":0.2195174160473558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385187658","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99892163,0.00007093168,0.00010448937,0.0002478653,0.0000031755678,0.000008419719,0.0001122063,5.273316e-7,0.0005307233],"genre_scores_gemma":[0.9995072,0.000057016598,0.0000560763,0.000031471765,0.000002572253,0.000004863073,0.00004885621,8.2282696e-7,0.0002910886],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979145,0.0011162672,0.000107862295,0.00013753564,0.00027780762,0.00044600535],"domain_scores_gemma":[0.98721015,0.008017909,0.0019981414,0.00038489868,0.0013920459,0.0009967373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031086092,0.00027029225,0.00036167572,0.00082668214,0.0020195271,0.0026006338,0.00081581756,0.0008722279,0.004632793],"category_scores_gemma":[0.010075618,0.00026592382,0.00060243794,0.002940006,0.0016973732,0.0013433561,0.001079044,0.0013123975,0.00018180184],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063984643,0.00035858824,0.9467314,0.000122003206,0.00023264822,0.00043348875,0.039038107,0.0010548842,0.00066292315,0.0032023243,0.0007337075,0.0067901034],"study_design_scores_gemma":[0.00005079121,0.00042302988,0.78946334,0.00008210402,0.00016523738,0.00007526482,0.20261824,0.0043322262,0.00034198983,0.0006862472,0.0017003533,0.00006113113],"about_ca_topic_score_codex":0.8123319,"about_ca_topic_score_gemma":0.8953809,"teacher_disagreement_score":0.18766809,"about_ca_system_score_codex":0.009132474,"about_ca_system_score_gemma":0.008277862,"threshold_uncertainty_score":0.37754655},"labels":[],"label_agreement":null},{"id":"W4385212075","doi":"10.1109/lra.2023.3295251","title":"Optimizing Task Waiting Times in Dynamic Vehicle Routing","year":2023,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Bounded function; Robot; Queue; Set (abstract data type); Euclidean geometry; Mathematical optimization; Artificial intelligence; Mathematics; Computer network; Programming language","score_opus":0.009246013254352873,"score_gpt":0.22177385451958626,"score_spread":0.21252784126523339,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385212075","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24648665,0.0011589698,0.7454404,0.0007756769,0.00020469514,0.000088807756,0.00023710249,0.00065796514,0.004949718],"genre_scores_gemma":[0.96204156,0.0003503811,0.034377184,0.00009619037,0.000043328742,0.00007047808,0.00014562371,0.0001555897,0.0027196119],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991761,0.00023314722,0.000037571215,0.00015470167,0.00013694075,0.00026152295],"domain_scores_gemma":[0.99769944,0.0014538218,0.00028263195,0.000083870036,0.00023672983,0.00024362493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015333454,0.001263045,0.0011324546,0.0007135373,0.00065136567,0.0011546776,0.0016814348,0.0010891437,0.0019832547],"category_scores_gemma":[0.005535708,0.00062255823,0.0004565106,0.000898663,0.0007793393,0.0014535133,0.001047953,0.0009128672,0.00026362838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000090576876,0.000021057274,0.0002546275,0.000032697044,0.000013312117,0.000026832808,0.000020739531,0.98906004,0.00070220145,0.0032254308,0.00041583055,0.0061367396],"study_design_scores_gemma":[0.000007993827,0.000030180849,0.000078536956,0.0000024512917,0.000004567059,0.000009097714,0.0000134044,0.9972452,0.00022237214,0.0021713288,0.00021100102,0.0000039479473],"about_ca_topic_score_codex":0.00818815,"about_ca_topic_score_gemma":0.0048010373,"teacher_disagreement_score":0.00818815,"about_ca_system_score_codex":0.0016996646,"about_ca_system_score_gemma":0.0015843683,"threshold_uncertainty_score":0.016281009},"labels":[],"label_agreement":null},{"id":"W4385281006","doi":"10.1016/j.jocm.2023.100431","title":"Theory-driven or data-driven? Modelling ride-sourcing mode choices using integrated choice and latent variable model and multi-task learning deep neural networks","year":2023,"lang":"en","type":"article","venue":"Journal of Choice Modelling","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Latent variable; Latent variable model; Econometrics; Discrete choice; Econometric model; Pandemic; Task (project management); Mode (computer interface); Preference; Coronavirus disease 2019 (COVID-19); Economics; Marketing; Business; Computer science; Artificial intelligence; Microeconomics","score_opus":0.07617742007943569,"score_gpt":0.2935783376492094,"score_spread":0.2174009175697737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385281006","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4632891,0.0010621257,0.522861,0.0047591846,0.00020678998,0.00009805513,0.003335687,0.0004925582,0.0038954567],"genre_scores_gemma":[0.97668856,0.00026273465,0.01825168,0.00017890053,0.000049953866,0.00006122496,0.0010887671,0.000050824692,0.0033672892],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930596,0.00030856408,0.00002445007,0.00020015614,0.0000490557,0.000111844165],"domain_scores_gemma":[0.99583495,0.0031489523,0.00035132532,0.00020723886,0.0002532788,0.00020422955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029210919,0.00060325273,0.0011315887,0.00061542087,0.00027521403,0.0018753588,0.0020072476,0.0013792969,0.004450703],"category_scores_gemma":[0.011339978,0.00079607655,0.001093868,0.0010555936,0.000846375,0.0030310508,0.0011430804,0.002526548,0.0006592275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029350148,0.00029710453,0.021736788,0.00014400108,0.00024883627,0.000118861586,0.00022480867,0.8989849,0.0006069597,0.04377496,0.0031502924,0.030419081],"study_design_scores_gemma":[0.0000071407935,0.000009983556,0.0010481792,0.00000952912,0.000009197546,0.000006767231,0.00002183714,0.981872,0.000071763105,0.016694296,0.00024132043,0.000007953673],"about_ca_topic_score_codex":0.023722839,"about_ca_topic_score_gemma":0.03073104,"teacher_disagreement_score":0.023722839,"about_ca_system_score_codex":0.0015039609,"about_ca_system_score_gemma":0.0014934522,"threshold_uncertainty_score":0.047169507},"labels":[],"label_agreement":null},{"id":"W4385407769","doi":"10.1016/j.cor.2023.106362","title":"Making opportunity sales in attended home delivery","year":2023,"lang":"en","type":"article","venue":"Computers & Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Computer science; Profit (economics); Vehicle routing problem; Operations research; Routing (electronic design automation); Order (exchange); Selection (genetic algorithm); Integer programming; Business; Economics; Microeconomics","score_opus":0.22373258892236814,"score_gpt":0.4004004801899891,"score_spread":0.17666789126762095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385407769","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5370773,0.00028518992,0.0043854034,0.0043270593,0.0003168236,0.00019586913,0.00019075892,0.00030335618,0.4529182],"genre_scores_gemma":[0.9528112,0.00010494514,0.0020825253,0.00016921133,0.000052063748,0.000026815795,0.00006502541,0.000056818542,0.04463149],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99899703,0.00032407188,0.000018893656,0.00011055293,0.00018206511,0.00036729194],"domain_scores_gemma":[0.9977316,0.0008805474,0.0001519184,0.00019879342,0.00024476578,0.0007924318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010513393,0.00022536198,0.00021415834,0.0005478408,0.0028755658,0.0054048593,0.00092966564,0.0012001604,0.059601683],"category_scores_gemma":[0.0053584883,0.00035578152,0.00031267962,0.0005276839,0.0010914656,0.0037543362,0.0021330887,0.0013916687,0.0054808985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001601007,0.004526234,0.068093665,0.00028332687,0.00007298732,0.002527884,0.027878128,0.0032296535,0.005248526,0.20478305,0.086488694,0.5952668],"study_design_scores_gemma":[0.00039249563,0.0017836321,0.15625107,0.0005640269,0.00024117412,0.0006691045,0.19424476,0.012546963,0.009500265,0.14426495,0.4793694,0.00017215272],"about_ca_topic_score_codex":0.006933925,"about_ca_topic_score_gemma":0.015929958,"teacher_disagreement_score":0.059601683,"about_ca_system_score_codex":0.0020316811,"about_ca_system_score_gemma":0.0023095917,"threshold_uncertainty_score":0.19938749},"labels":[],"label_agreement":null},{"id":"W4385416220","doi":"10.15607/rss.2023.xix.102","title":"Efficient Reinforcement Learning for Autonomous Driving with Parameterized Skills and Priors","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Toronto","funders":"","keywords":"Parameterized complexity; Reinforcement learning; Prior probability; Computer science; Artificial intelligence; Reinforcement; Machine learning; Human–computer interaction; Bayesian probability; Engineering; Algorithm; Structural engineering","score_opus":0.007457785226136705,"score_gpt":0.22339003441989666,"score_spread":0.21593224919375995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385416220","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037165523,0.00014413524,0.9597313,0.00018671688,0.000025987367,0.000061300016,0.000048377653,0.0008632363,0.001773406],"genre_scores_gemma":[0.8890061,0.00007157451,0.108478926,0.00013048039,0.000027215112,0.0001529469,0.00014732765,0.00009056585,0.001894908],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966574,0.00009205837,0.00001774447,0.000084471394,0.00007598892,0.00006398433],"domain_scores_gemma":[0.9987016,0.0007654035,0.00013212966,0.00011578423,0.0001699443,0.00011513941],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085415103,0.00086701143,0.00084049685,0.00033318665,0.00030234407,0.00051984296,0.0011058189,0.0008610857,0.0019057809],"category_scores_gemma":[0.004256466,0.00048966316,0.0004226261,0.00022130685,0.00090864813,0.0008105743,0.0012227311,0.0016320266,0.00035954497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000073365976,0.000056165827,0.000785649,0.00003872104,0.000018924366,0.000048729493,0.000052047042,0.9567224,0.0017084426,0.0031881968,0.0006026843,0.03670467],"study_design_scores_gemma":[0.000008968909,0.000013975071,0.00004940023,0.0000023487878,0.0000016095266,0.0000043855657,0.000002443336,0.99829406,0.00020572187,0.0013110273,0.00010404171,0.00000201708],"about_ca_topic_score_codex":0.006094742,"about_ca_topic_score_gemma":0.005736729,"teacher_disagreement_score":0.006094742,"about_ca_system_score_codex":0.000777333,"about_ca_system_score_gemma":0.0013238083,"threshold_uncertainty_score":0.012118578},"labels":[],"label_agreement":null},{"id":"W4385421388","doi":"10.1177/03611981231186991","title":"Matrix Factorization for Globally Consistent Periodic Flow Prediction in Taxi Systems","year":2023,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Factorization; Flow (mathematics); Matrix decomposition; Flow network; Matrix (chemical analysis); Data mining; Operations research; Mathematical optimization; Algorithm; Mathematics","score_opus":0.08691515631381114,"score_gpt":0.3682630361948646,"score_spread":0.2813478798810535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385421388","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06872728,0.00043776102,0.9280735,0.00025779594,0.00008202209,0.000056436056,0.00057337614,0.0009627648,0.0008290023],"genre_scores_gemma":[0.77302456,0.0003779946,0.22286557,0.000100230835,0.00011026527,0.00012285236,0.0016638187,0.0001231725,0.0016115223],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996723,0.00007159312,0.000016908913,0.00012396954,0.00005830035,0.000056994537],"domain_scores_gemma":[0.9990619,0.0004650233,0.0001551729,0.00008061488,0.00018325505,0.00005398278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071979465,0.0010938024,0.000847311,0.00068661623,0.0005583073,0.0005483828,0.0006332403,0.00063501875,0.0012511052],"category_scores_gemma":[0.0028897321,0.00040105107,0.0009095528,0.00085760275,0.00042528252,0.0011051649,0.00045663552,0.0011974861,0.00039326862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013708198,0.00007505858,0.00564196,0.000081957405,0.00006247192,0.00010063585,0.00009606449,0.9033734,0.003742866,0.0036456722,0.0028843752,0.08015847],"study_design_scores_gemma":[0.000001687207,0.0000059908143,0.00025302003,0.0000015185536,0.0000020226144,0.000004760509,0.000006390741,0.99849117,0.00013871165,0.0009878968,0.00010422763,0.0000025135068],"about_ca_topic_score_codex":0.034965396,"about_ca_topic_score_gemma":0.02951388,"teacher_disagreement_score":0.034965396,"about_ca_system_score_codex":0.00065651734,"about_ca_system_score_gemma":0.001180801,"threshold_uncertainty_score":0.06952375},"labels":[],"label_agreement":null},{"id":"W4385588096","doi":"10.1007/978-3-030-97940-9_126","title":"Energy-Smart Transportation Systems","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Electrification; Transport engineering; Sustainable transport; Greenhouse gas; Environmental economics; Engineering; Business; Sustainability; Electricity; Economics","score_opus":0.018805946524383513,"score_gpt":0.1951275667046215,"score_spread":0.176321620180238,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385588096","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00044993195,0.00680501,0.00600123,0.0016254511,0.00107707,0.00002112204,0.00008841972,0.00009266245,0.98383904],"genre_scores_gemma":[0.0087464545,0.008143357,0.0018685814,0.000692357,0.00032270476,0.000031813142,0.00011950147,0.00008738371,0.97998786],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99987733,0.000026462187,0.0000035868495,0.000020288684,0.00005859784,0.00001363],"domain_scores_gemma":[0.99995947,0.00001236342,0.0000023834968,0.000009192533,0.000012583123,0.0000039711254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013868281,0.0008904485,0.0002901426,0.00064680807,0.0007942319,0.0023868403,0.00048370656,0.0010258299,0.057141725],"category_scores_gemma":[0.000270811,0.00026268524,0.00023861154,0.0010704385,0.00081317755,0.0030514637,0.0011885636,0.0015458601,0.019175075],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059373956,0.000024355231,0.000048549373,0.00010632705,0.0000037226705,0.000037705253,0.0001493321,0.0013758161,0.00048283208,0.62980306,0.2539463,0.114016004],"study_design_scores_gemma":[8.8954135e-7,0.000004748373,0.000067181594,0.000055384793,0.0000012980539,0.000027255357,0.00005882438,0.0005426323,0.00013804092,0.060212146,0.9388893,0.0000023053876],"about_ca_topic_score_codex":0.0033742383,"about_ca_topic_score_gemma":0.007952716,"teacher_disagreement_score":0.057141725,"about_ca_system_score_codex":0.001598604,"about_ca_system_score_gemma":0.0008597256,"threshold_uncertainty_score":0.19115812},"labels":[],"label_agreement":null},{"id":"W4385599417","doi":"10.59962/9780774837354","title":"Thumbing a Ride","year":2018,"lang":"en","type":"book","venue":"University of British Columbia Press eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.010750408163963884,"score_gpt":0.16283334763641022,"score_spread":0.15208293947244633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385599417","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0028538026,0.016954903,0.002001288,0.0052176886,0.005120062,0.00006590086,0.0002222657,0.0005370243,0.96702695],"genre_scores_gemma":[0.012116456,0.005258225,0.0012762645,0.0021077334,0.00033504004,0.000018049497,0.0001596256,0.00016558626,0.978563],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994392,0.00009191752,0.000019720137,0.00009743356,0.00025698027,0.00009464014],"domain_scores_gemma":[0.99961495,0.00008819029,0.000013209739,0.000052364056,0.00014993263,0.000081376675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004114098,0.0008563309,0.00036689968,0.0014837211,0.0046082945,0.0054480704,0.001042893,0.0021208185,0.0688155],"category_scores_gemma":[0.001481305,0.00029978922,0.00052524806,0.0010979777,0.002737688,0.005681137,0.0027730877,0.0030412364,0.02063832],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025391259,0.000036087567,0.00032981567,0.00028007833,0.0000054762204,0.00036290294,0.005934862,0.000121908386,0.0004948585,0.09012163,0.7379058,0.16438125],"study_design_scores_gemma":[9.810866e-7,0.000009362937,0.0001142062,0.00008535102,0.0000013765155,0.00016141051,0.0008274624,0.00002212272,0.000074475174,0.0014313168,0.99726784,0.0000041549056],"about_ca_topic_score_codex":0.028608674,"about_ca_topic_score_gemma":0.08064928,"teacher_disagreement_score":0.9713913,"about_ca_system_score_codex":0.0025819552,"about_ca_system_score_gemma":0.0025260923,"threshold_uncertainty_score":0.23021078},"labels":[],"label_agreement":null},{"id":"W4385689056","doi":"10.1109/icaisc58445.2023.10200016","title":"The Future of Travel in public Bus Service: How a Mobile Bus Ticketing System is Revolutionizing the Public Travel","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Public transport; Service (business); Computer science; Telecommunications; Transport engineering; Business; Computer security; Engineering; Marketing","score_opus":0.021234540671861923,"score_gpt":0.22104039977667633,"score_spread":0.1998058591048144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385689056","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06622437,0.042926934,0.025931941,0.54093456,0.007534616,0.000094220064,0.00044989356,0.00089320267,0.31501025],"genre_scores_gemma":[0.755564,0.057736877,0.027330037,0.030793888,0.0032491037,0.0000834963,0.0005074849,0.00039246897,0.12434267],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9990202,0.00040099412,0.000028192417,0.00010681084,0.00023559498,0.0002081932],"domain_scores_gemma":[0.9986533,0.00019506991,0.000076065015,0.00006893851,0.0004773613,0.00052918954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015262077,0.0003202369,0.00015490555,0.0005966574,0.0023683368,0.008588145,0.00074579293,0.0027718882,0.012154387],"category_scores_gemma":[0.001975603,0.00019736013,0.00036934114,0.00081350264,0.001715035,0.010249802,0.0019337632,0.003402061,0.004087734],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015935724,0.00018659963,0.008808953,0.00075594045,0.000027696284,0.00082984235,0.0071568424,0.0016552194,0.0035743124,0.35119897,0.24398935,0.38165694],"study_design_scores_gemma":[0.000006025564,0.000105941464,0.0046665645,0.00034593625,0.000020349724,0.0008195729,0.0098593095,0.0034201914,0.0007088278,0.02705337,0.95293665,0.000057176596],"about_ca_topic_score_codex":0.014451145,"about_ca_topic_score_gemma":0.023014335,"teacher_disagreement_score":0.014451145,"about_ca_system_score_codex":0.0031795262,"about_ca_system_score_gemma":0.0036440766,"threshold_uncertainty_score":0.0406605},"labels":[],"label_agreement":null},{"id":"W4385794389","doi":"10.21203/rs.3.rs-3246777/v1","title":"Transit Pass Ownership as a Potential Source of Heterogeneity in the Determinants of Ride-sourcing Use in Metro Vancouver","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Transit (satellite); Business; Public transport; Limiting; Car ownership; Work (physics); Urban transit; Transport engineering; Engineering","score_opus":0.11541522704443379,"score_gpt":0.37176379089004863,"score_spread":0.25634856384561483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385794389","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978211,0.00007378261,0.000376906,0.000117082396,0.0000024107126,0.000023088951,0.00034566788,0.000005968859,0.0012339777],"genre_scores_gemma":[0.9984946,0.000080692604,0.00013009763,0.000014684316,0.0000026434377,0.000013917397,0.00029529925,0.0000039798183,0.0009640718],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99859387,0.00041312867,0.00010245018,0.00018826695,0.00036045717,0.00034178764],"domain_scores_gemma":[0.99128646,0.0043931725,0.0021230543,0.00059278385,0.00094445195,0.0006600711],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016789224,0.00021577078,0.00053898286,0.0008428889,0.0011121819,0.0024769632,0.0010966476,0.00047099387,0.0046445653],"category_scores_gemma":[0.008014549,0.00031030978,0.000792757,0.0025827228,0.00082748284,0.0007213129,0.0013346126,0.0008977404,0.00033907738],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000400526,0.00005572836,0.9917258,0.000033291144,0.000107594344,0.00016889235,0.0017176517,0.0012795882,0.00015952038,0.0004165642,0.00028359663,0.0040116827],"study_design_scores_gemma":[0.000004370879,0.00003550497,0.98737305,0.000052584754,0.000059236976,0.000057183297,0.00636938,0.0048626787,0.000111649715,0.00016388502,0.00089641404,0.00001392883],"about_ca_topic_score_codex":0.7648808,"about_ca_topic_score_gemma":0.78029823,"teacher_disagreement_score":0.23511922,"about_ca_system_score_codex":0.0040506353,"about_ca_system_score_gemma":0.0038066888,"threshold_uncertainty_score":0.47300774},"labels":[],"label_agreement":null},{"id":"W4385955579","doi":"10.5507/tots.2023.013","title":"Private Car Ownership in Presence of Shared Autonomous Vehicles, Case of Tehran","year":2023,"lang":"en","type":"article","venue":"Transactions on Transport Sciences","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Respondent; Car ownership; Business; Taxis; The Internet; Quarter (Canadian coin); Service (business); Car parking; Marketing; Transport engineering; Engineering; Public transport; Computer science; Geography","score_opus":0.03600047684268436,"score_gpt":0.26872452905133504,"score_spread":0.23272405220865067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385955579","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99873656,0.00006283358,0.000064873406,0.00017309624,0.0000039796514,0.000008988396,0.000119731376,0.0000014149924,0.0008285013],"genre_scores_gemma":[0.99960214,0.000059484042,0.000029374483,0.000009440895,0.000004628345,0.000004597831,0.00009451071,6.590559e-7,0.00019506708],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907637,0.00017569098,0.000050772873,0.00010133084,0.00014229395,0.00045348628],"domain_scores_gemma":[0.9983854,0.0003699155,0.0006949181,0.000084408595,0.00015962581,0.00030569386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005933543,0.00027379082,0.000299915,0.001374777,0.0009984976,0.0012615438,0.0010449423,0.00069324527,0.0051108142],"category_scores_gemma":[0.0020280078,0.00022586319,0.0010411623,0.0012996695,0.00088484114,0.0009237278,0.0013677647,0.00093269104,0.00026746726],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019419884,0.00029531893,0.97378254,0.00006484104,0.00008029388,0.011577393,0.004149158,0.0014205271,0.0003263475,0.0016539103,0.0009748169,0.005480491],"study_design_scores_gemma":[0.000025987705,0.00025289902,0.94013286,0.000059371567,0.00009698555,0.0059390487,0.043981016,0.006623112,0.00019656916,0.00083107373,0.0018263165,0.000034864453],"about_ca_topic_score_codex":0.06937192,"about_ca_topic_score_gemma":0.061883394,"teacher_disagreement_score":0.06937192,"about_ca_system_score_codex":0.0021075616,"about_ca_system_score_gemma":0.001268307,"threshold_uncertainty_score":0.13793623},"labels":[],"label_agreement":null},{"id":"W4385971446","doi":"10.1155/2023/5658495","title":"Policy Efforts to Promote the Adoption of Autonomous Vehicles: Subsidy and AV Lanes","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Subsidy; Market penetration; Software deployment; Profit (economics); Penetration rate; Computer science; Penetration (warfare); Business; Transport engineering; Operations research; Microeconomics; Economics; Engineering; Marketing; Market economy","score_opus":0.009310576203052735,"score_gpt":0.25172621392899486,"score_spread":0.24241563772594213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385971446","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31564912,0.0014325404,0.61312723,0.008174997,0.00027564407,0.0006683797,0.00045092404,0.00035842962,0.0598628],"genre_scores_gemma":[0.9805792,0.000548244,0.014458956,0.00015962457,0.00002336833,0.00016202143,0.000051666426,0.000012070965,0.004004843],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9990061,0.0003929013,0.000029805427,0.00017522668,0.00018861196,0.00020734279],"domain_scores_gemma":[0.9986461,0.00060207624,0.0003966672,0.000053495223,0.00020541753,0.0000962433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011730923,0.0006223008,0.0006033795,0.00049468904,0.0005780303,0.0018669234,0.0012857316,0.002122743,0.003838844],"category_scores_gemma":[0.0034728847,0.00042552545,0.0008829882,0.000542777,0.001146029,0.002444368,0.0010861912,0.0015721521,0.00021841652],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012235233,0.00036598652,0.0063692215,0.00043991988,0.00006936171,0.00045608674,0.00026387442,0.7041721,0.0040529156,0.24551815,0.003114706,0.035055425],"study_design_scores_gemma":[0.00012958205,0.00039334383,0.006871808,0.00020317877,0.00011723455,0.00014449777,0.00086955936,0.8922718,0.002579955,0.075988345,0.020370575,0.000060100385],"about_ca_topic_score_codex":0.011498617,"about_ca_topic_score_gemma":0.010952576,"teacher_disagreement_score":0.011498617,"about_ca_system_score_codex":0.0025752368,"about_ca_system_score_gemma":0.0045752497,"threshold_uncertainty_score":0.022863388},"labels":[],"label_agreement":null},{"id":"W4385977724","doi":"10.1038/s41598-023-40639-y","title":"Sustainability analysis framework for on-demand public transit systems","year":2023,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Toronto Metropolitan University","funders":"Canada Research Chairs","keywords":"Public transport; Sustainability; Equity (law); Environmental economics; Business; Electrification; Transit system; Transport engineering; Social equality; Transit (satellite); Carbon footprint; Sustainable transport; Carpool; Bus rapid transit; Economics; Greenhouse gas; Engineering","score_opus":0.023451520927971786,"score_gpt":0.2773491599893241,"score_spread":0.2538976390613523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385977724","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031759795,0.00088283134,0.8927266,0.0020702,0.00012813181,0.00019661954,0.0006168792,0.00021226377,0.07140667],"genre_scores_gemma":[0.907485,0.0011599609,0.06680595,0.0002041247,0.00018688248,0.00044291792,0.0006221855,0.00012431512,0.022968588],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988802,0.0004167533,0.00004509795,0.00014567726,0.00030795558,0.00020430701],"domain_scores_gemma":[0.9990018,0.00039076665,0.00010630726,0.00004237104,0.00038633932,0.00007241248],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018258935,0.0013742659,0.0007984176,0.0018168248,0.00082332524,0.0028035105,0.0012982974,0.0015743797,0.008991111],"category_scores_gemma":[0.0024650863,0.0004529197,0.0016141805,0.00094135635,0.0011708863,0.002227904,0.0024382817,0.0014990724,0.00055571296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010811632,0.0000592976,0.00079009123,0.00009308303,0.000034479635,0.00017267659,0.000097461,0.67371637,0.0007009814,0.31403902,0.0019812048,0.008304581],"study_design_scores_gemma":[0.0000050375043,0.000018889532,0.00026588145,0.00002899962,0.000011732917,0.000027759912,0.00012322528,0.9255486,0.00012766612,0.06993338,0.0038992378,0.000009622102],"about_ca_topic_score_codex":0.018362924,"about_ca_topic_score_gemma":0.010563564,"teacher_disagreement_score":0.018362924,"about_ca_system_score_codex":0.0036252094,"about_ca_system_score_gemma":0.0024232296,"threshold_uncertainty_score":0.036512136},"labels":[],"label_agreement":null},{"id":"W4386205000","doi":"10.2139/ssrn.4551405","title":"Pricing Shared Rides","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Business; Computer science","score_opus":0.009356359276269032,"score_gpt":0.22710056885787427,"score_spread":0.21774420958160523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386205000","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30039498,0.0019598026,0.21027087,0.005136706,0.0022381262,0.0009996594,0.0022570747,0.0020629426,0.4746798],"genre_scores_gemma":[0.9213676,0.000275123,0.0070914435,0.0001532383,0.0002459873,0.000114619885,0.00030052944,0.000110232235,0.070341274],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9966312,0.0008799815,0.00011891516,0.0006137053,0.0010119912,0.0007441552],"domain_scores_gemma":[0.996302,0.0011461208,0.00022687177,0.0011665489,0.00064496044,0.00051349186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001786187,0.0009292561,0.0018304703,0.0011440373,0.001226226,0.00521318,0.0035272175,0.0031921992,0.09006555],"category_scores_gemma":[0.011444728,0.00086152274,0.0011537891,0.0020399583,0.0012258271,0.00740689,0.0027879225,0.0034895572,0.005609241],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018275123,0.0006954166,0.002614737,0.00035634657,0.00030693915,0.00048787534,0.0003768885,0.108971156,0.0023352415,0.58453417,0.068713196,0.22878055],"study_design_scores_gemma":[0.00048429373,0.0014773905,0.0048442488,0.00015358996,0.0002527869,0.0006662942,0.0011643234,0.4229659,0.0018866061,0.47941336,0.086554304,0.00013691079],"about_ca_topic_score_codex":0.0027367626,"about_ca_topic_score_gemma":0.004138405,"teacher_disagreement_score":0.09006555,"about_ca_system_score_codex":0.0020337559,"about_ca_system_score_gemma":0.002198236,"threshold_uncertainty_score":0.3012992},"labels":[],"label_agreement":null},{"id":"W4386209697","doi":"10.3233/shti230652","title":"A Novel Geospatial Assistive Navigation Technology for Seamless Multimodal Mobility of Wheelchair Users","year":2023,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Centre for Interdisciplinary Research in Rehabilitation","funders":"","keywords":"Wheelchair; Geospatial analysis; Assistive technology; Perception; Computer science; Social acceptance; Human–computer interaction; Transport engineering; World Wide Web; Engineering; Psychology; Geography; Cartography","score_opus":0.03854292136897669,"score_gpt":0.34356597945414713,"score_spread":0.30502305808517044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386209697","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12863202,0.00081937097,0.8515031,0.0005712173,0.00034128202,0.0004407633,0.00043788724,0.004259072,0.012995329],"genre_scores_gemma":[0.5646646,0.0010044747,0.4153179,0.0004422031,0.0000652654,0.00059647654,0.0004596856,0.00012169309,0.017327636],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981946,0.000025716325,0.000016121636,0.00004249795,0.000072955634,0.000023350934],"domain_scores_gemma":[0.999853,0.000022981727,0.000017248176,0.000016298225,0.00007027628,0.00002012777],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018544737,0.00048805273,0.0002764996,0.00034081138,0.0002919373,0.00043397205,0.0006733471,0.000629878,0.0029056186],"category_scores_gemma":[0.00041656577,0.00016723873,0.0003173702,0.0002051508,0.0001820603,0.00097203394,0.0008752708,0.00027153984,0.00087085686],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024029402,0.00023707756,0.0027335477,0.0005950193,0.00006948886,0.001610636,0.0010185082,0.0024279554,0.68407106,0.007890477,0.008267871,0.29083803],"study_design_scores_gemma":[0.00020134827,0.003363193,0.018063897,0.0002816085,0.00057222636,0.012281154,0.0011849401,0.17553627,0.5045945,0.004224595,0.2793143,0.00038201245],"about_ca_topic_score_codex":0.0008147427,"about_ca_topic_score_gemma":0.0012808382,"teacher_disagreement_score":0.0029056186,"about_ca_system_score_codex":0.0001402003,"about_ca_system_score_gemma":0.00036078983,"threshold_uncertainty_score":0.009720206},"labels":[],"label_agreement":null},{"id":"W4386371852","doi":"10.1680/jensu.23.00023","title":"Determinants behind the acceptance of autonomous vehicles in mandatory and optional trips","year":2023,"lang":"en","type":"article","venue":"Proceedings of the Institution of Civil Engineers - Engineering Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"TRIPS architecture; Expectancy theory; Structural equation modeling; Latent variable; Psychology; Estimation; Variables; Schema (genetic algorithms); External variable; Econometrics; Business; Social psychology; Transport engineering; Computer science; Statistics; Economics; Engineering; Mathematics","score_opus":0.006156250033278568,"score_gpt":0.21384939871776554,"score_spread":0.20769314868448696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386371852","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99909604,0.000019552606,0.00012221336,0.000039475963,0.0000014837995,0.0000059815375,0.00002379728,0.000001425245,0.00069012376],"genre_scores_gemma":[0.9997452,0.000014515556,0.00005849474,0.0000040569985,0.0000011033088,0.000003252934,0.000028638011,5.881856e-7,0.00014415383],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99926585,0.00021339145,0.00006924602,0.00007883964,0.00021375135,0.00015898245],"domain_scores_gemma":[0.99318224,0.0027895859,0.0021343688,0.0002769703,0.00086804637,0.0007488246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089355506,0.00014622869,0.0001326524,0.0005234368,0.00023034633,0.0008357673,0.00026645884,0.00042587402,0.002652265],"category_scores_gemma":[0.0057436367,0.00011389756,0.000462537,0.00048302606,0.00048515998,0.00048015188,0.00045395075,0.0006801248,0.00024157643],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005522024,0.0001655264,0.99156255,0.000017977345,0.00003129381,0.00008166596,0.0013142119,0.00033132933,0.00045704134,0.000312221,0.00006934061,0.0056017186],"study_design_scores_gemma":[0.0000022664244,0.00010762965,0.99454826,0.0000101847345,0.00001568101,0.0000741816,0.0034131056,0.001283553,0.00015199116,0.00013660477,0.00025003724,0.000006560506],"about_ca_topic_score_codex":0.0061096707,"about_ca_topic_score_gemma":0.0064969677,"teacher_disagreement_score":0.0061096707,"about_ca_system_score_codex":0.00033086137,"about_ca_system_score_gemma":0.00036579743,"threshold_uncertainty_score":0.012148261},"labels":[],"label_agreement":null},{"id":"W4386515469","doi":"10.1111/poms.14064","title":"Hiding in plain sight: Surge pricing and strategic providers","year":2023,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Service provider; Stylized fact; Collusion; Business; Pricing strategies; Industrial organization; Microeconomics; Service (business); Marketing; Economics","score_opus":0.02228936062510617,"score_gpt":0.23092588480468396,"score_spread":0.2086365241795778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386515469","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70674527,0.0007904741,0.24350332,0.006500297,0.00025462583,0.00029476767,0.00033826506,0.00032226468,0.041250754],"genre_scores_gemma":[0.99347514,0.00013032556,0.004281947,0.00018019795,0.000029326455,0.000030729723,0.000021593822,0.000015968877,0.0018347214],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99810046,0.0007998814,0.000045388508,0.00019321518,0.00027527017,0.00058584765],"domain_scores_gemma":[0.9885639,0.0070729284,0.0023917642,0.0006924549,0.00058937614,0.0006896507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003253784,0.0010321214,0.0011304268,0.0006684656,0.0014306083,0.0030933924,0.0018561258,0.0027672418,0.007471385],"category_scores_gemma":[0.018740326,0.00077747117,0.0011623546,0.00059615064,0.0033495242,0.004949059,0.002719168,0.0032671308,0.00041010405],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004297717,0.00025467732,0.008282249,0.00013841898,0.00009443514,0.00092048995,0.0005163643,0.7072125,0.0023646567,0.26521802,0.0037298906,0.010838573],"study_design_scores_gemma":[0.00008984451,0.00019820807,0.0016413827,0.000044830984,0.000037418416,0.00016238046,0.00050272857,0.92363286,0.00065894704,0.07178893,0.001183134,0.000059326074],"about_ca_topic_score_codex":0.0105681745,"about_ca_topic_score_gemma":0.0054489467,"teacher_disagreement_score":0.0105681745,"about_ca_system_score_codex":0.0025276658,"about_ca_system_score_gemma":0.0024366376,"threshold_uncertainty_score":0.024994254},"labels":[],"label_agreement":null},{"id":"W4386629894","doi":"10.1016/j.omega.2023.102965","title":"Compensation guarantees in crowdsourced delivery: Impact on platform and driver welfare","year":2023,"lang":"en","type":"article","venue":"Omega","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wage; Flexibility (engineering); Welfare; Computer science; Profit (economics); Matching (statistics); Labour economics; Microeconomics; Work (physics); Scheduling (production processes); Business; Economics; Operations research; Operations management; Engineering; Mathematics","score_opus":0.01458762318414245,"score_gpt":0.24227885480931213,"score_spread":0.2276912316251697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386629894","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71699524,0.0020129702,0.18124008,0.010731235,0.0015607274,0.00063184777,0.0020928425,0.0021509998,0.08258406],"genre_scores_gemma":[0.9895253,0.00011177993,0.0035862722,0.00019973464,0.0001167844,0.00007500464,0.0001814824,0.00004571974,0.006157931],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99407476,0.0022771582,0.00018138741,0.00075633643,0.0018091362,0.00090116146],"domain_scores_gemma":[0.96577793,0.01992597,0.003496021,0.0040302016,0.004591092,0.0021787055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010768072,0.0008831103,0.0010329349,0.0010874388,0.0020898967,0.0038854121,0.0026998548,0.0031302734,0.02325051],"category_scores_gemma":[0.04291882,0.0004661175,0.0008657904,0.0010648175,0.0013535932,0.0042337882,0.0045242677,0.002806417,0.0025196557],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009387807,0.0034561567,0.047349073,0.000864136,0.00038412047,0.00071999105,0.0023429242,0.27427635,0.0056749517,0.18256353,0.049987704,0.42299324],"study_design_scores_gemma":[0.0015016347,0.0037177019,0.058052782,0.00076700386,0.00051064586,0.0005026471,0.006597779,0.64088,0.0064667375,0.23583603,0.0448191,0.00034800413],"about_ca_topic_score_codex":0.008083206,"about_ca_topic_score_gemma":0.006037138,"teacher_disagreement_score":0.02325051,"about_ca_system_score_codex":0.002707076,"about_ca_system_score_gemma":0.0051238774,"threshold_uncertainty_score":0.07778072},"labels":[],"label_agreement":null},{"id":"W4386688035","doi":"10.54254/2754-1169/13/20230664","title":"The New Transportation Paradigm: The Sharing Economy","year":2023,"lang":"en","type":"article","venue":"Advances in Economics Management and Political Sciences","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Paradigm shift; Transformative learning; Computer science; Scale (ratio); Sharing economy; Data sharing; Data science; Knowledge management; Sociology; World Wide Web","score_opus":0.01360315082190069,"score_gpt":0.2554764908102416,"score_spread":0.2418733399883409,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386688035","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09731425,0.003035616,0.3256818,0.04224277,0.0007142296,0.00019239416,0.00040684364,0.0001649977,0.5302471],"genre_scores_gemma":[0.9456509,0.0019721708,0.026982812,0.0016085624,0.0004204311,0.00022510506,0.00012209103,0.000071931565,0.022945905],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982627,0.0007823166,0.0000482707,0.00028616836,0.00039923,0.00022125762],"domain_scores_gemma":[0.9983303,0.00045453437,0.00016584726,0.00047402974,0.0003294698,0.00024587286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023076641,0.00036780935,0.00036098697,0.00064213725,0.0019821462,0.0048746057,0.0012723433,0.002011365,0.010657819],"category_scores_gemma":[0.003060168,0.00022189549,0.00074157445,0.001067341,0.0054493546,0.014955821,0.0033602223,0.0020004325,0.0008202231],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007984004,0.000006974652,0.00012474858,0.000016642854,0.0000029720961,0.000020119523,0.00012300817,0.0012798953,0.00006873547,0.99421847,0.0010784359,0.0030519338],"study_design_scores_gemma":[0.00001252189,0.000025021278,0.0002876217,0.000043921504,0.000007316747,0.000099355035,0.0005455766,0.008479201,0.0001993006,0.93651253,0.053774666,0.00001298555],"about_ca_topic_score_codex":0.0029030307,"about_ca_topic_score_gemma":0.0018870636,"teacher_disagreement_score":0.010657819,"about_ca_system_score_codex":0.004057778,"about_ca_system_score_gemma":0.0028227002,"threshold_uncertainty_score":0.03565395},"labels":[],"label_agreement":null},{"id":"W4386741680","doi":"10.3390/futuretransp3030061","title":"To Share or to Own? Understanding the Willingness to Adopt Shared and Owned Electric Automated Vehicles on Three Continents","year":2023,"lang":"en","type":"article","venue":"Future Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Descriptive statistics; Order (exchange); Logistic regression; Business; Sustainability; Marketing; Ordered logit; Geography; Computer science","score_opus":0.03170956568938442,"score_gpt":0.25742385026278375,"score_spread":0.22571428457339932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386741680","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999106,0.0000369165,0.00006179085,0.00013788696,0.0000011941285,0.0000021475137,0.000008429903,4.1505703e-7,0.0006451275],"genre_scores_gemma":[0.99972266,0.000046515226,0.000046419995,0.000025499206,0.0000010172745,0.000002031907,0.000011511997,5.032508e-7,0.00014377439],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990747,0.00039969213,0.00006461857,0.00009830695,0.00017269804,0.00018988126],"domain_scores_gemma":[0.9945186,0.0021535952,0.0018744239,0.00025009247,0.00063668756,0.00056677026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019871632,0.00012939495,0.00019810446,0.0005192274,0.0005205126,0.001959357,0.0004181616,0.00051047315,0.0022266272],"category_scores_gemma":[0.00751399,0.00018167672,0.0004018749,0.0005334736,0.0014692792,0.0017030475,0.0010508703,0.00072215335,0.0001808135],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000070864175,0.00013128339,0.91505367,0.000048061447,0.000083019295,0.00026985403,0.06154113,0.00031938154,0.0006111161,0.0013648912,0.00023566825,0.020271223],"study_design_scores_gemma":[0.0000034362922,0.00010197144,0.86203843,0.00007132079,0.000029973404,0.00020447778,0.13417938,0.0009900982,0.00018782787,0.00052697054,0.0016438653,0.000022164662],"about_ca_topic_score_codex":0.018780893,"about_ca_topic_score_gemma":0.022083566,"teacher_disagreement_score":0.018780893,"about_ca_system_score_codex":0.00063371373,"about_ca_system_score_gemma":0.00055648864,"threshold_uncertainty_score":0.037343144},"labels":[],"label_agreement":null},{"id":"W4386803124","doi":"10.23977/acss.2023.070705","title":"Design and Implementation of Travel System for Disabled People Based on User Interest Preference Recommendation Algorithm","year":2023,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National College Students Innovation and Entrepreneurship Training Program; Suzhou University","keywords":"Recommender system; Disabled people; Preference; Computer science; China; Order (exchange); Work (physics); Harmony (color); Internet privacy; Algorithm; World Wide Web; Psychology; Engineering; Business; Finance; Applied psychology; Economics","score_opus":0.04925266507548763,"score_gpt":0.29893327966182903,"score_spread":0.2496806145863414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386803124","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.101852156,0.00086106744,0.8701424,0.00035632102,0.0001919555,0.0007069273,0.00051106774,0.013543575,0.011834464],"genre_scores_gemma":[0.6298083,0.00079543266,0.34770462,0.00022126813,0.00005322898,0.0006226046,0.0013263244,0.00014351432,0.019324666],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99955446,0.00006370383,0.000045982717,0.00012262478,0.0001402679,0.0000729546],"domain_scores_gemma":[0.99966,0.000025713129,0.000015041107,0.000032279462,0.00022987624,0.0000370762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004044073,0.0005150008,0.00069995126,0.0008451202,0.0005965127,0.0006548745,0.0013453241,0.0007509116,0.0049475],"category_scores_gemma":[0.0006341626,0.00026799593,0.0006259669,0.00069326576,0.00013353278,0.00091772916,0.00043234517,0.00044615904,0.0020516873],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011449915,0.00086068385,0.016933832,0.0006288688,0.00031811142,0.0010152144,0.00049883185,0.030915001,0.08087653,0.0045293695,0.030188045,0.8320905],"study_design_scores_gemma":[0.00031453866,0.0006625395,0.011010348,0.000038752485,0.0002850925,0.0012115559,0.00035234034,0.90161556,0.051350433,0.0010054664,0.03200227,0.00015113968],"about_ca_topic_score_codex":0.014791424,"about_ca_topic_score_gemma":0.0071309865,"teacher_disagreement_score":0.014791424,"about_ca_system_score_codex":0.00037343786,"about_ca_system_score_gemma":0.0007133404,"threshold_uncertainty_score":0.02941066},"labels":[],"label_agreement":null},{"id":"W4386805108","doi":"10.1016/j.tranpol.2023.09.012","title":"Why do planners do what they do? and what are the implications? Guidance from on-demand ride-hailing policy in Toronto and Vancouver, Canada","year":2023,"lang":"en","type":"article","venue":"Transport Policy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Anticipation (artificial intelligence); Transportation planning; Thematic analysis; Marketing; Demand patterns; Economics; Business; Demand management; Sociology; Transport engineering; Qualitative research; Engineering; Computer science","score_opus":0.010647752816211583,"score_gpt":0.2526704929588324,"score_spread":0.24202274014262085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386805108","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16927215,0.010484271,0.005364349,0.5806117,0.000737341,0.00056894566,0.0028421648,0.0002508107,0.22986826],"genre_scores_gemma":[0.9266697,0.010623458,0.005262379,0.013491767,0.00011282876,0.00028589554,0.0010562122,0.00013426057,0.04236349],"study_design_codex":"not_applicable","study_design_gemma":"qualitative","domain_scores_codex":[0.9854372,0.0042503737,0.00039158633,0.00059930224,0.0025847917,0.0067368834],"domain_scores_gemma":[0.96495605,0.009994043,0.0012412342,0.00048494426,0.015934508,0.007389294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0106083825,0.0007982213,0.0010028391,0.002596338,0.012756508,0.017346103,0.0022515804,0.005026253,0.012181159],"category_scores_gemma":[0.047307562,0.0011341344,0.00055481424,0.0072337226,0.006936746,0.005696085,0.0030196803,0.0061200513,0.0011122958],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029812058,0.0002692228,0.075236596,0.0013731867,0.00012623364,0.0007195571,0.057832077,0.02593469,0.0004653452,0.19828607,0.52053416,0.11892468],"study_design_scores_gemma":[0.00038003465,0.00009943063,0.13147804,0.004191475,0.00019953727,0.000106265616,0.28716463,0.014131976,0.001079613,0.059623137,0.50105846,0.00048737536],"about_ca_topic_score_codex":0.99487996,"about_ca_topic_score_gemma":0.99805284,"teacher_disagreement_score":0.17660739,"about_ca_system_score_codex":0.17660739,"about_ca_system_score_gemma":0.44495714,"threshold_uncertainty_score":0.9550187},"labels":[],"label_agreement":null},{"id":"W4386820249","doi":"10.2139/ssrn.4554247","title":"A Long Distance from AV-iation: Estimating the Impact of Autonomous Vehicle (AV) Adoption on Airport Leakage and Terminal Area Forecasts","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Metropolitan area; Runway; Leakage (economics); Aviation; Transport engineering; International airport; Air travel; Business; Engineering; Economics; Geography","score_opus":0.011928671259006412,"score_gpt":0.24997515186972566,"score_spread":0.23804648061071926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386820249","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982179,0.00006785099,0.0005853852,0.000116546864,0.000012445212,0.0000048263446,0.000518242,0.000015123168,0.00046174548],"genre_scores_gemma":[0.99901795,0.00003776722,0.00015073371,0.000010663985,0.000008159668,0.0000023517734,0.00054835627,0.000002662434,0.00022126775],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995153,0.00015833498,0.000025312222,0.00011374255,0.0000655073,0.00012180483],"domain_scores_gemma":[0.9947631,0.0031042823,0.0010523091,0.00020559627,0.00046139144,0.00041337666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011419947,0.00044072137,0.0002774849,0.00060660765,0.0002948056,0.0013265604,0.0005365737,0.0012661464,0.001013221],"category_scores_gemma":[0.0061792056,0.00024303557,0.0007654152,0.0008052602,0.00048630012,0.0019306275,0.0007468972,0.0015692224,0.00032741477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010109737,0.0003751131,0.61837626,0.00004827833,0.00028645364,0.0005493105,0.0002504906,0.36679557,0.0015280652,0.0013907534,0.0015059644,0.007882758],"study_design_scores_gemma":[0.000047214755,0.0005929817,0.3717779,0.000022822942,0.00018586456,0.00015377035,0.0017075177,0.62085134,0.0022127065,0.0012555254,0.0011314426,0.000060939237],"about_ca_topic_score_codex":0.03940486,"about_ca_topic_score_gemma":0.031590104,"teacher_disagreement_score":0.03940486,"about_ca_system_score_codex":0.0010006875,"about_ca_system_score_gemma":0.00063493825,"threshold_uncertainty_score":0.07835102},"labels":[],"label_agreement":null},{"id":"W4386913035","doi":"10.1007/s10601-023-09355-2","title":"Constraint programming approaches to electric vehicle and robot routing problems","year":2023,"lang":"en","type":"article","venue":"Constraints","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Electric vehicle; Greenhouse gas; Robot; Mobile robot; Computer science; Battery (electricity); Variety (cybernetics); Investment (military); Electric motor; Vehicle routing problem; Automotive engineering; Routing (electronic design automation); Engineering; Electrical engineering; Embedded system; Artificial intelligence","score_opus":0.0801388474127351,"score_gpt":0.23323403081493707,"score_spread":0.15309518340220196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386913035","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031224347,0.0042342837,0.9590286,0.0018598832,0.00026352378,0.00008519808,0.00038529385,0.00006170142,0.030959154],"genre_scores_gemma":[0.23505111,0.020857578,0.69057494,0.0014245287,0.0016454809,0.00075292727,0.0012544726,0.00029970036,0.04813926],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982274,0.0008068067,0.00008200636,0.00025072848,0.00048034408,0.00015270188],"domain_scores_gemma":[0.9965752,0.002738123,0.00018179735,0.00010701788,0.0003071178,0.000090796486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021551289,0.001690329,0.0013004873,0.0015521122,0.00088582473,0.0029338594,0.003044199,0.0018150451,0.0096945865],"category_scores_gemma":[0.0068035997,0.0011385661,0.0014292682,0.0050023724,0.0018390914,0.0029144888,0.0012951801,0.0034128488,0.0007980779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024377245,0.00006069206,0.00014672017,0.00028734715,0.00007088641,0.00012523039,0.00009061392,0.38819683,0.00023477476,0.5722814,0.007834992,0.030646155],"study_design_scores_gemma":[0.000034958834,0.00001852223,0.00013350578,0.000098708995,0.00003310063,0.00006662152,0.000094585834,0.44210684,0.00020533509,0.5298969,0.027285188,0.000025734656],"about_ca_topic_score_codex":0.021010814,"about_ca_topic_score_gemma":0.019195603,"teacher_disagreement_score":0.021010814,"about_ca_system_score_codex":0.0025306623,"about_ca_system_score_gemma":0.0026581655,"threshold_uncertainty_score":0.041777015},"labels":[],"label_agreement":null},{"id":"W4386988126","doi":"10.2139/ssrn.4581195","title":"Navigating Uncertainty: A Consensus-Based Algorithm for Solving the Stochastic Canadian Traveler Problem","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Operations research; Algorithm; Mathematical optimization; Mathematics","score_opus":0.018260074282227732,"score_gpt":0.26470926397798655,"score_spread":0.24644918969575882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386988126","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05496641,0.00014516753,0.9383688,0.00040729478,0.00007110514,0.00011860078,0.00010515265,0.0004806975,0.005336763],"genre_scores_gemma":[0.7943618,0.000090051086,0.2011769,0.00014514443,0.00003913781,0.00022100308,0.00020716441,0.000090391644,0.0036684456],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996786,0.00006202753,0.000011726562,0.00008853333,0.00008863631,0.00007053903],"domain_scores_gemma":[0.99935895,0.00031666044,0.000046671703,0.0000374513,0.00017022295,0.00007002017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090229703,0.00086794666,0.0010723968,0.0005929492,0.0010063521,0.00077606254,0.0022503585,0.0020293603,0.0022916629],"category_scores_gemma":[0.0029727337,0.00046374093,0.0005380118,0.00087789935,0.00095742755,0.00086358807,0.0018854719,0.0011964006,0.00025781954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006255138,0.000020734828,0.00021928169,0.000020902755,0.000013858077,0.00002830884,0.000050379407,0.9716186,0.00042274993,0.004662772,0.0008530906,0.022026854],"study_design_scores_gemma":[0.000014601606,0.000012260284,0.00002622098,0.0000017014454,0.0000028282357,0.0000031692412,0.000007659342,0.99823016,0.00010268024,0.0014324446,0.00016332211,0.000002989817],"about_ca_topic_score_codex":0.070579566,"about_ca_topic_score_gemma":0.044946153,"teacher_disagreement_score":0.070579566,"about_ca_system_score_codex":0.001324372,"about_ca_system_score_gemma":0.0038274042,"threshold_uncertainty_score":0.14033747},"labels":[],"label_agreement":null},{"id":"W4387088895","doi":"10.1109/dcoss-iot58021.2023.00097","title":"Fuzzy-Based Dynamic Priority-Driven Allocation for Internet of Vehicles","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Computer science; Quality of service; Fuzzy logic; Queue; Resource allocation; Latency (audio); Priority queue; Throughput; Priority inheritance; Computer network; Queueing theory; The Internet; Priority ceiling protocol; Service (business); Distributed computing; Dynamic priority scheduling; Artificial intelligence; Telecommunications","score_opus":0.015065299695822794,"score_gpt":0.25939908597358396,"score_spread":0.24433378627776117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387088895","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03143477,0.00040903056,0.9633158,0.0001675599,0.00010467407,0.000097847726,0.00004175353,0.00033829734,0.0040901946],"genre_scores_gemma":[0.9346461,0.00017047753,0.06300002,0.00006724585,0.00003363028,0.00006606032,0.000040700714,0.000020532936,0.0019551553],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960715,0.00006855256,0.000025764004,0.000086987435,0.00012956074,0.000082053244],"domain_scores_gemma":[0.9995987,0.00014103886,0.000045764344,0.000017597364,0.00015657487,0.000040382998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083578564,0.00039857998,0.00049580453,0.0006095108,0.00061678403,0.00092201366,0.001274472,0.0005767635,0.0014699089],"category_scores_gemma":[0.0012550929,0.0002709324,0.0003763967,0.00043039687,0.00042629242,0.00064343476,0.00047513156,0.00047969786,0.00019001993],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001811031,0.000092906404,0.000620127,0.00008734411,0.000035691664,0.00011225071,0.00012531217,0.87573665,0.008511603,0.015905885,0.0019994706,0.096591644],"study_design_scores_gemma":[0.000006469195,0.000021524698,0.0000659188,0.0000024326528,0.0000045348015,0.000011024545,0.000009925246,0.99712485,0.00047436333,0.0019549013,0.00031884777,0.0000051660163],"about_ca_topic_score_codex":0.012382338,"about_ca_topic_score_gemma":0.01065132,"teacher_disagreement_score":0.012382338,"about_ca_system_score_codex":0.0013741566,"about_ca_system_score_gemma":0.0011980068,"threshold_uncertainty_score":0.024620533},"labels":[],"label_agreement":null},{"id":"W4387209537","doi":"10.1155/2023/6610624","title":"A Space-Time Model for Demand in Free-Floating Carsharing Systems","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Innosuisse - Schweizerische Agentur für Innovationsförderung","keywords":"Unavailability; Relocation; Poisson distribution; Service (business); Computer science; Poisson regression; Operations research; Demand patterns; Real-time computing; Demand management; Statistics; Engineering; Mathematics; Economics","score_opus":0.015470845260129337,"score_gpt":0.2479618555255655,"score_spread":0.23249101026543614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387209537","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07469982,0.0005053334,0.91265756,0.0013434021,0.00012353058,0.00014658488,0.00243047,0.00046372414,0.0076296916],"genre_scores_gemma":[0.9306992,0.0008400523,0.039999433,0.00019230759,0.00012501562,0.00048419714,0.0023027216,0.00018878288,0.025168251],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989209,0.0002768782,0.000061819366,0.00030799044,0.00019776386,0.00023461982],"domain_scores_gemma":[0.99824905,0.0010431904,0.0002534503,0.00007012087,0.0002822865,0.000101901765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018103136,0.0014865481,0.0016771173,0.0011786316,0.00077779836,0.002671505,0.0041868216,0.0029124594,0.0070592416],"category_scores_gemma":[0.0037907336,0.0012870358,0.0018379977,0.0020710859,0.0010904117,0.0029084259,0.001595827,0.002462775,0.0013534268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002684895,0.000025844058,0.000879731,0.000038954797,0.000023822537,0.00010878461,0.00007175386,0.97130597,0.00046922022,0.024731146,0.00061539176,0.0017025834],"study_design_scores_gemma":[0.000003590931,0.000008321105,0.00013110644,0.0000024974722,0.0000042994748,0.0000130078415,0.00001610311,0.99737984,0.0000326262,0.0021355015,0.00026699126,0.000006136306],"about_ca_topic_score_codex":0.04042991,"about_ca_topic_score_gemma":0.020076098,"teacher_disagreement_score":0.04042991,"about_ca_system_score_codex":0.0024988044,"about_ca_system_score_gemma":0.0016309222,"threshold_uncertainty_score":0.0803892},"labels":[],"label_agreement":null},{"id":"W4387630362","doi":"10.1016/j.tre.2023.103313","title":"The three-sided market of on-demand delivery","year":2023,"lang":"en","type":"article","venue":"Transportation Research Part E Logistics and Transportation Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Science Foundation","keywords":"Profit maximization; Commission; Social Welfare; Wage; Microeconomics; Business; Profit (economics); Welfare; Valuation (finance); Maximization; Economics; Industrial organization; Labour economics; Market economy; Finance","score_opus":0.10364479163559198,"score_gpt":0.351566109951703,"score_spread":0.24792131831611103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387630362","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022737596,0.16413629,0.032791086,0.04649472,0.0060626296,0.00011261175,0.0004678729,0.0001279696,0.7270693],"genre_scores_gemma":[0.56316715,0.26428735,0.00876742,0.023070104,0.012155642,0.00020374231,0.0004538661,0.00012958396,0.12776515],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989831,0.00020041478,0.00002200239,0.00013745569,0.00051074266,0.00014621494],"domain_scores_gemma":[0.9986344,0.000707843,0.0001168591,0.000111504014,0.0003148676,0.000114478906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014845845,0.0004862547,0.0006342515,0.00078148785,0.0006308609,0.0043528904,0.0019415627,0.0024544331,0.024065662],"category_scores_gemma":[0.002210564,0.00023968228,0.0006099903,0.0012410046,0.0035024001,0.009748976,0.0018495675,0.0030605332,0.0027596753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000097984164,0.00006444769,0.00017886113,0.0005247478,0.000015395643,0.00017271095,0.00009321794,0.0013428337,0.0006734671,0.8301666,0.037861094,0.12880872],"study_design_scores_gemma":[0.000052231488,0.00022924636,0.0011299903,0.00076448004,0.000024547175,0.00089765777,0.00042372354,0.006127697,0.0008544057,0.3620911,0.6273437,0.00006125354],"about_ca_topic_score_codex":0.001563359,"about_ca_topic_score_gemma":0.0016490191,"teacher_disagreement_score":0.024065662,"about_ca_system_score_codex":0.0027471727,"about_ca_system_score_gemma":0.0015822991,"threshold_uncertainty_score":0.080507696},"labels":[],"label_agreement":null},{"id":"W4387730902","doi":"10.36227/techrxiv.24311152","title":"Matching Mechanism Designs for Shared Mobility: A Review of the Literature","year":2023,"lang":"en","type":"review","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Matching (statistics); Rendering (computer graphics); Computer science; Perspective (graphical); Context (archaeology); Mechanism (biology); Risk analysis (engineering); Business; Knowledge management; Artificial intelligence","score_opus":0.09632124550356223,"score_gpt":0.33872830192131337,"score_spread":0.24240705641775112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387730902","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00037181182,0.9943258,0.002650679,0.00029843894,0.000098634875,0.000025674753,0.000019729421,0.00001564669,0.0021934942],"genre_scores_gemma":[0.0052855136,0.98976505,0.004041895,0.00019914692,0.00012424713,0.000058675414,0.000042469946,0.000006531426,0.00047653556],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986204,0.0003713956,0.00022077296,0.00025811,0.0004338098,0.00009542532],"domain_scores_gemma":[0.9929635,0.0056525897,0.0005280525,0.0001878002,0.00058117864,0.00008690565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031466507,0.0011865173,0.0014191193,0.004256711,0.0005007901,0.0022052715,0.002227387,0.0026020117,0.005900719],"category_scores_gemma":[0.009635817,0.00090409775,0.0012651074,0.0059848414,0.00095739105,0.004369365,0.0011784986,0.0012008894,0.0015899795],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008456541,0.00014759599,0.00039109398,0.06439122,0.00019042759,0.00012979469,0.0002514555,0.0026917297,0.00067281816,0.042238094,0.009438079,0.8793732],"study_design_scores_gemma":[0.00008116553,0.0004820401,0.0020968923,0.081533134,0.0009759916,0.0015409911,0.0006086557,0.0032673625,0.0016596382,0.031472046,0.8761755,0.000106565414],"about_ca_topic_score_codex":0.002553877,"about_ca_topic_score_gemma":0.0017434036,"teacher_disagreement_score":0.005900719,"about_ca_system_score_codex":0.0015591757,"about_ca_system_score_gemma":0.0040492234,"threshold_uncertainty_score":0.019739866},"labels":[],"label_agreement":null},{"id":"W4387731074","doi":"10.36227/techrxiv.24311152.v1","title":"Matching Mechanism Designs for Shared Mobility: A Review of the Literature","year":2023,"lang":"en","type":"review","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Matching (statistics); Rendering (computer graphics); Computer science; Perspective (graphical); Mechanism (biology); Context (archaeology); Knowledge management; Risk analysis (engineering); Business; Artificial intelligence","score_opus":0.09632124550356223,"score_gpt":0.33872830192131337,"score_spread":0.24240705641775112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387731074","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00024833452,0.99629503,0.0016279033,0.00020361313,0.000084193955,0.000017426395,0.00002009348,0.000012788622,0.0014905906],"genre_scores_gemma":[0.0031231663,0.9938508,0.0023882017,0.00013917561,0.00009878106,0.000036883914,0.000036115438,0.0000047424496,0.00032212678],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998889,0.00027990466,0.00018718452,0.00021078823,0.00036086608,0.000072165516],"domain_scores_gemma":[0.9941156,0.0046935226,0.00045665764,0.00015924385,0.00050394284,0.0000711501],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025125807,0.0012712658,0.0015724555,0.004279722,0.00045077899,0.00203738,0.0018370644,0.002305043,0.0052519715],"category_scores_gemma":[0.008165511,0.0008147128,0.0011984942,0.006024641,0.0007865551,0.0037131573,0.0010292772,0.0011819443,0.0014986378],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000082755214,0.00013689608,0.00033137272,0.087206624,0.00019921889,0.00012974911,0.00019697192,0.00245174,0.00076345546,0.031147853,0.009966709,0.8673865],"study_design_scores_gemma":[0.000056440593,0.00035518775,0.0016246893,0.084683016,0.0009892836,0.0013609767,0.00041720734,0.002021112,0.001317092,0.023396658,0.88369113,0.000087219036],"about_ca_topic_score_codex":0.0020355482,"about_ca_topic_score_gemma":0.0015690917,"teacher_disagreement_score":0.0052519715,"about_ca_system_score_codex":0.0013214087,"about_ca_system_score_gemma":0.0036026991,"threshold_uncertainty_score":0.017569602},"labels":[],"label_agreement":null},{"id":"W4387865054","doi":"10.1016/j.trb.2023.102818","title":"A data-driven discrete simulation-based optimization algorithm for car-sharing service design","year":2023,"lang":"en","type":"article","venue":"Transportation Research Part B Methodological","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"Ford Foundation; National Science Foundation","keywords":"Computer science; Algorithm; Reservation; Metamodeling; Mathematical optimization; Operator (biology); Mathematics","score_opus":0.6455356067752253,"score_gpt":0.5069070448368022,"score_spread":0.1386285619384231,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387865054","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009830749,0.00007074923,0.9869349,0.00012213836,0.000041056897,0.00008971106,0.000069173424,0.00044871063,0.0023928178],"genre_scores_gemma":[0.56129354,0.00011947054,0.4345013,0.00013626007,0.00003818297,0.0005860995,0.0003057542,0.00016584074,0.0028535514],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99959964,0.00012030536,0.000019933655,0.000071151226,0.00012661272,0.00006234084],"domain_scores_gemma":[0.9985404,0.0009132869,0.000084428546,0.0000673166,0.00029601602,0.00009861146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012876482,0.00097259117,0.0016130772,0.00082038454,0.0006828721,0.0010539677,0.0016100844,0.001465094,0.0049554547],"category_scores_gemma":[0.0032762543,0.00091674505,0.0009297148,0.00080180314,0.00072303135,0.00074108416,0.0013880725,0.0013672131,0.0006492785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003507307,0.000027274746,0.00011251396,0.000015582933,0.000009001654,0.000008593903,0.000010843269,0.9892812,0.0002246817,0.0014329614,0.00021223765,0.008629995],"study_design_scores_gemma":[0.0000075339544,0.0000058574146,0.000009253066,0.0000011589051,0.0000013236677,0.0000012117848,0.0000014188522,0.99950683,0.000050537932,0.00032596264,0.000087887405,0.0000010289846],"about_ca_topic_score_codex":0.018116746,"about_ca_topic_score_gemma":0.011504868,"teacher_disagreement_score":0.018116746,"about_ca_system_score_codex":0.0013520302,"about_ca_system_score_gemma":0.0027797827,"threshold_uncertainty_score":0.036022604},"labels":[],"label_agreement":null},{"id":"W4387917757","doi":"10.1007/978-3-031-44505-7_21","title":"Repositioning Fleet Vehicles: A Learning Pipeline","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"TRIPS architecture; Fleet management; Computer science; Pipeline (software); Adaptability; Operations research; Process (computing); Operator (biology); Transport engineering; Engineering; Telecommunications","score_opus":0.015106268247248084,"score_gpt":0.23312413632032833,"score_spread":0.21801786807308024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387917757","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03303683,0.00094355893,0.8403157,0.0010877006,0.00013769869,0.0003625928,0.0005899311,0.00695612,0.116569854],"genre_scores_gemma":[0.18118902,0.0022215163,0.70907074,0.00018367107,0.0000930324,0.00017877892,0.002227466,0.0010168477,0.10381897],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996729,0.000055164328,0.000013111164,0.00010645237,0.00011233128,0.000040019426],"domain_scores_gemma":[0.99931777,0.00027196074,0.00003587792,0.00016674786,0.00013523705,0.000072457355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006978914,0.001134383,0.0005607861,0.00080728665,0.00062319526,0.0020972507,0.0025222339,0.0013273066,0.04509058],"category_scores_gemma":[0.002147595,0.0005508465,0.0007458865,0.00091494835,0.0005499049,0.0038565139,0.0025967157,0.0014201088,0.0094586145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013105395,0.0002623476,0.0011048849,0.00019674504,0.000023227209,0.00012440736,0.0003829324,0.09550874,0.005139325,0.036711037,0.017699504,0.84271586],"study_design_scores_gemma":[0.000047815553,0.0005204091,0.0017168219,0.000283128,0.00003737245,0.0004863118,0.000947998,0.56464756,0.01876546,0.18643801,0.22603391,0.00007525937],"about_ca_topic_score_codex":0.004069678,"about_ca_topic_score_gemma":0.0076564783,"teacher_disagreement_score":0.04509058,"about_ca_system_score_codex":0.0010663363,"about_ca_system_score_gemma":0.0013879674,"threshold_uncertainty_score":0.15084302},"labels":[],"label_agreement":null},{"id":"W4388106840","doi":"10.1145/3616392.3623411","title":"Fastest Route and Charging Optimization of an Electric Vehicle With Battery's Life Consideration","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Trent University; Lakehead University; Wilfrid Laurier University","funders":"","keywords":"Computer science; Heuristic; Context (archaeology); Battery (electricity); Electric vehicle; Mathematical optimization; Vehicle routing problem; Grid; Path (computing); Routing (electronic design automation); Distributed computing; Artificial intelligence; Embedded system; Computer network; Power (physics)","score_opus":0.010211127863507929,"score_gpt":0.2024173981844187,"score_spread":0.19220627032091078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388106840","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20189454,0.0022993048,0.7518531,0.001780062,0.00032668817,0.0004143134,0.0013947743,0.0005489718,0.0394882],"genre_scores_gemma":[0.81343186,0.0010132472,0.162991,0.00017197077,0.00006914192,0.00029384013,0.0007207323,0.0002751998,0.021033026],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968326,0.000118454176,0.000012596286,0.00006796499,0.00004266498,0.00007505489],"domain_scores_gemma":[0.9992143,0.0004778447,0.00008333084,0.000034177847,0.000115081246,0.00007517316],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091867713,0.0014809684,0.0015813472,0.001145528,0.00070166105,0.001544869,0.0015042775,0.0018959191,0.0101893945],"category_scores_gemma":[0.0026729298,0.0008102232,0.0011941645,0.0013635956,0.0008344607,0.0015299013,0.00082692195,0.0010638194,0.0006813448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004107602,0.000022574615,0.00024184905,0.000061801235,0.000016744605,0.00007658862,0.000020077856,0.98721576,0.00027738258,0.0056494083,0.0009573688,0.0054193707],"study_design_scores_gemma":[0.000012775962,0.000033023927,0.00009914207,0.000009452278,0.000009281308,0.000029300552,0.000042918877,0.99322647,0.00016206701,0.00549897,0.00086955365,0.000006964916],"about_ca_topic_score_codex":0.010466518,"about_ca_topic_score_gemma":0.008182634,"teacher_disagreement_score":0.010466518,"about_ca_system_score_codex":0.0017460836,"about_ca_system_score_gemma":0.0019047736,"threshold_uncertainty_score":0.034086883},"labels":[],"label_agreement":null},{"id":"W4388115050","doi":"10.1155/2023/6658030","title":"Minimum Cost Flow-Based Integrated Model for Electric Vehicle and Crew Scheduling","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Crew scheduling; Solver; Scheduling (production processes); Mathematical optimization; Computer science; Electric vehicle; Integer programming; Crew; Linear programming; Operations research; Fleet management; Engineering; Algorithm; Mathematics; Telecommunications","score_opus":0.01701426297563755,"score_gpt":0.259765758216272,"score_spread":0.24275149524063447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388115050","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016985716,0.00026146232,0.9636872,0.00030473215,0.00006786777,0.00013931433,0.0006735429,0.00027508,0.017604996],"genre_scores_gemma":[0.71394324,0.0008279776,0.25270015,0.00021841866,0.00007709222,0.00093957584,0.0014958141,0.00020822324,0.029589497],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995547,0.00012214802,0.000012827821,0.000090020876,0.000120484925,0.00009983674],"domain_scores_gemma":[0.99967885,0.00015042977,0.000046765694,0.0000198066,0.00006704961,0.000037166505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006642982,0.001085692,0.0010953028,0.00077333266,0.0005136685,0.0014370175,0.0019673514,0.0016584868,0.0094855875],"category_scores_gemma":[0.0011220445,0.0007365471,0.001069675,0.0014558051,0.0005699614,0.0013531568,0.00094820827,0.0014991253,0.0007850148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010627403,0.0000136380095,0.000057797683,0.000011818403,0.0000046559194,0.000017825441,0.0000056143435,0.9920564,0.00013533357,0.0053724656,0.00032288246,0.0019909132],"study_design_scores_gemma":[0.0000051596453,0.000007747258,0.000024594687,0.0000019979943,0.0000029787811,0.000004357413,0.00000378405,0.99731123,0.000045029734,0.0021124305,0.00047889742,0.000001776665],"about_ca_topic_score_codex":0.019524336,"about_ca_topic_score_gemma":0.017393226,"teacher_disagreement_score":0.019524336,"about_ca_system_score_codex":0.0018500349,"about_ca_system_score_gemma":0.0027846023,"threshold_uncertainty_score":0.0388214},"labels":[],"label_agreement":null},{"id":"W4388156783","doi":"10.2139/ssrn.4591826","title":"Customers’ Multihoming Behavior in Ride-Hailing: Empirical Evidence from Uber and Lyft","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Multihoming; Advertising; Business; Computer science; The Internet; World Wide Web","score_opus":0.03979717190372164,"score_gpt":0.30158198344281156,"score_spread":0.26178481153908995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388156783","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99742055,0.00015119341,0.00013550589,0.0000551437,0.0000025429463,0.000007397182,0.00010870225,0.000003215456,0.0021157719],"genre_scores_gemma":[0.99868256,0.000111798065,0.00007016616,0.000033060653,0.0000038002693,0.0000062186637,0.00016240188,0.000003022373,0.00092709664],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99898726,0.00036375853,0.000053258682,0.00013931259,0.00022181935,0.000234577],"domain_scores_gemma":[0.97986674,0.012017456,0.004149507,0.001209898,0.0016861554,0.0010702076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021982777,0.00022844458,0.00042167117,0.0011146638,0.0014593898,0.0020206776,0.000761234,0.0013738752,0.007465914],"category_scores_gemma":[0.011549017,0.0002992715,0.00043021658,0.0018200887,0.000691,0.002243248,0.0009553605,0.0013227566,0.0014699446],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007762507,0.0010651895,0.9642865,0.0000780847,0.00014988394,0.00021322622,0.0059748697,0.0006388739,0.00034419415,0.0008126446,0.0013612182,0.02429902],"study_design_scores_gemma":[0.00002226363,0.00029088315,0.9798055,0.000044419976,0.0001208535,0.00012356299,0.015024821,0.0020232552,0.0003699918,0.00031108526,0.0018311031,0.000032175867],"about_ca_topic_score_codex":0.03199361,"about_ca_topic_score_gemma":0.039249483,"teacher_disagreement_score":0.03199361,"about_ca_system_score_codex":0.0006741812,"about_ca_system_score_gemma":0.00042785,"threshold_uncertainty_score":0.063614726},"labels":[],"label_agreement":null},{"id":"W4388159066","doi":"10.1016/j.dam.2023.10.016","title":"Rolling horizon strategies for a dynamic and stochastic ridesharing problem with rematches","year":2023,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Université de Montréal","funders":"","keywords":"Mathematics; Mathematical optimization; Dynamic programming; Horizon; Geometry","score_opus":0.01275822793577122,"score_gpt":0.23435627171026435,"score_spread":0.22159804377449313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388159066","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11686945,0.001464748,0.8589278,0.0017285816,0.00022828889,0.0004545092,0.00078793365,0.0005072237,0.019031579],"genre_scores_gemma":[0.9052508,0.00082465913,0.06592158,0.0002236081,0.00012448372,0.00035160413,0.00047533674,0.00015408322,0.026673742],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983158,0.0007035441,0.00008206542,0.0003403347,0.0001734972,0.00038472883],"domain_scores_gemma":[0.9967014,0.002158198,0.00035287163,0.00014366028,0.00023140076,0.00041241103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003091393,0.0021155544,0.004700326,0.0015117712,0.00095403066,0.0031363799,0.004632369,0.0047358787,0.010324323],"category_scores_gemma":[0.0066860956,0.0017471031,0.0018267592,0.0018462325,0.0015365368,0.0028028523,0.0023314918,0.0026231408,0.0008597108],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025006165,0.00009349808,0.0002133022,0.00015409422,0.00009117155,0.00017300974,0.00007583506,0.95515555,0.00084965146,0.032705277,0.0015614752,0.008677035],"study_design_scores_gemma":[0.000035034416,0.000087270666,0.00009780835,0.000012226025,0.000023973264,0.000020750396,0.000031570857,0.9871453,0.00011250556,0.011874403,0.0005417906,0.000017303955],"about_ca_topic_score_codex":0.013237414,"about_ca_topic_score_gemma":0.005724452,"teacher_disagreement_score":0.013237414,"about_ca_system_score_codex":0.002043212,"about_ca_system_score_gemma":0.001697438,"threshold_uncertainty_score":0.03453833},"labels":[],"label_agreement":null},{"id":"W4388461133","doi":"10.18280/isi.280510","title":"Remote-Controlled Bluetooth-Enabled Smart Shopping Cart: Prototype and Evaluation","year":2023,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cart; Bluetooth; Computer science; Embedded system; Human–computer interaction; Real-time computing; Telecommunications; Engineering; Wireless","score_opus":0.01906831397630744,"score_gpt":0.2451806195241003,"score_spread":0.22611230554779288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388461133","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9180458,0.00072664337,0.06007131,0.00037568176,0.00024955638,0.003558083,0.0006641396,0.0032144922,0.013094189],"genre_scores_gemma":[0.9159122,0.00077782164,0.061792564,0.00032412156,0.000063599975,0.00087555236,0.00069423905,0.00024490283,0.019315137],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99923265,0.00020377907,0.000043569136,0.00008885213,0.00034127387,0.00008990986],"domain_scores_gemma":[0.99888414,0.00022926954,0.000057902394,0.00014353672,0.00055674015,0.00012849798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010265264,0.00068454933,0.00054501556,0.0005951237,0.0003504832,0.00082405325,0.0020791404,0.0010651387,0.0082513485],"category_scores_gemma":[0.0019237101,0.0003042676,0.00040161173,0.0003657146,0.0005062857,0.0009301339,0.00057133666,0.00034802314,0.0018170885],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004995104,0.007992727,0.015155609,0.0066510336,0.00029399208,0.0057937982,0.0038922431,0.013525039,0.51044345,0.0026488272,0.016578129,0.4120301],"study_design_scores_gemma":[0.0041903695,0.09253044,0.1071632,0.0009869045,0.0012095128,0.013819877,0.0049660164,0.15014602,0.45644325,0.00091894914,0.16687945,0.0007460082],"about_ca_topic_score_codex":0.0015594037,"about_ca_topic_score_gemma":0.0017168451,"teacher_disagreement_score":0.0082513485,"about_ca_system_score_codex":0.00026362712,"about_ca_system_score_gemma":0.0004962225,"threshold_uncertainty_score":0.027603507},"labels":[],"label_agreement":null},{"id":"W4388503431","doi":"10.2139/ssrn.4622857","title":"Healthcare Dynamic and Stochastic Transportation","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Health care; Business; Computer science; Economics; Economic growth","score_opus":0.012008611739798464,"score_gpt":0.2568981516752009,"score_spread":0.24488953993540244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388503431","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19876319,0.010212672,0.61520714,0.090300635,0.0016054926,0.00016779853,0.0041815387,0.0004933249,0.079068206],"genre_scores_gemma":[0.9231745,0.0045111557,0.008482482,0.0014789684,0.0010094296,0.000093108414,0.0007998018,0.000107891006,0.060342744],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99862754,0.0005663347,0.000058312333,0.00030978824,0.00019115538,0.0002467959],"domain_scores_gemma":[0.994544,0.0035610332,0.0007524987,0.00019061081,0.0003803827,0.00057149143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022347886,0.00092740613,0.0021808292,0.0014247274,0.00094736315,0.0036881962,0.0011463369,0.004796992,0.016670816],"category_scores_gemma":[0.013890768,0.0010558863,0.001254325,0.0015116186,0.0022904617,0.0039253696,0.00229299,0.0031741261,0.0008898116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009189797,0.0000695362,0.0020750859,0.000107161075,0.00010124793,0.00025713764,0.00017410656,0.16763484,0.00026149303,0.8113234,0.011048885,0.0068550976],"study_design_scores_gemma":[0.000044222674,0.000056193043,0.0016258282,0.000059361075,0.000054763124,0.00020937328,0.00020305601,0.53075415,0.00007641269,0.46081808,0.0060553723,0.00004327338],"about_ca_topic_score_codex":0.02111257,"about_ca_topic_score_gemma":0.010923445,"teacher_disagreement_score":0.02111257,"about_ca_system_score_codex":0.0037695712,"about_ca_system_score_gemma":0.0019613423,"threshold_uncertainty_score":0.055769444},"labels":[],"label_agreement":null},{"id":"W4388506618","doi":"10.18757/ejtir.2018.18.1.3222","title":"Development of a household travel resource allocation model","year":2018,"lang":"en","type":"article","venue":"European journal of transport and infrastructure research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; University of Waterloo; University of Toronto","keywords":"Heuristics; Metropolitan area; Schedule; Context (archaeology); Public transport; Duration (music); Transport engineering; Demographics; Resource allocation; Land use; Travel behavior; Computer science; Budget constraint; Heuristic; Resource (disambiguation); Business; Operations research; Geography; Economics; Engineering; Microeconomics","score_opus":0.05091987550092156,"score_gpt":0.27973783713317246,"score_spread":0.2288179616322509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388506618","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.066246234,0.0002642551,0.8907081,0.0012124648,0.00011019773,0.0003578697,0.005801231,0.0009255998,0.03437412],"genre_scores_gemma":[0.6420468,0.00048340493,0.32070875,0.00027673863,0.00007563131,0.0011647899,0.0039685443,0.0002154281,0.031059915],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977154,0.00007735506,0.000011840302,0.000060191174,0.00003717076,0.00004191199],"domain_scores_gemma":[0.999587,0.00022720818,0.000033305023,0.000018695953,0.000097109165,0.000036748832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055640616,0.0004144696,0.000550032,0.00048307373,0.00038095584,0.0009252751,0.0015864454,0.0010568515,0.013744784],"category_scores_gemma":[0.0014895373,0.00047535423,0.00058309035,0.0010963018,0.00021187242,0.00076563365,0.0007462313,0.0009616911,0.001389121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016897444,0.000025797362,0.0009832927,0.000023016908,0.000012024711,0.00005222031,0.00002920563,0.9799438,0.000119841665,0.0089073805,0.0021544714,0.0077319285],"study_design_scores_gemma":[0.000005142705,0.0000052928826,0.00013777596,0.0000045132365,0.0000039468714,0.0000061181954,0.000024894327,0.99641645,0.000036921236,0.0020889326,0.0012678163,0.0000022672737],"about_ca_topic_score_codex":0.030465579,"about_ca_topic_score_gemma":0.02255613,"teacher_disagreement_score":0.030465579,"about_ca_system_score_codex":0.0014715939,"about_ca_system_score_gemma":0.0020469343,"threshold_uncertainty_score":0.0605765},"labels":[],"label_agreement":null},{"id":"W4388888799","doi":"10.1016/j.cities.2023.104663","title":"Ride-hailing and transit accessibility considering the trade-off between time and money","year":2023,"lang":"en","type":"article","venue":"Cities","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"TRIPS architecture; Equity (law); Subsidy; Business; Transit (satellite); Mile; Transport engineering; Finance; Economics; Public transport; Geography; Engineering","score_opus":0.024617433571979715,"score_gpt":0.2410250581140382,"score_spread":0.2164076245420585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388888799","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8882055,0.0014236693,0.070693254,0.0021689634,0.000077753386,0.000053725948,0.0004533012,0.000059171856,0.036864646],"genre_scores_gemma":[0.9948131,0.00018993083,0.0007162331,0.00001030766,0.000019898116,0.0000070351957,0.000029649125,0.000006954878,0.0042068954],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994011,0.00021440301,0.000018470422,0.000100189536,0.000046142755,0.00021970103],"domain_scores_gemma":[0.99730694,0.0014992815,0.0004459647,0.000102482605,0.00031492955,0.0003304521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070312596,0.00051161234,0.00073543965,0.0011152863,0.0006445632,0.0031741143,0.0011066619,0.0013446765,0.016489916],"category_scores_gemma":[0.0043315063,0.00035196787,0.00081606087,0.0014733508,0.0012504952,0.0038205236,0.0013854582,0.001107763,0.00040962896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004101354,0.00029326952,0.054911464,0.00026558508,0.00029571893,0.0015917622,0.0006216425,0.52127165,0.001307349,0.39409143,0.0023864072,0.022553535],"study_design_scores_gemma":[0.000034392608,0.00025955643,0.025823204,0.00008735298,0.00029163793,0.0004626608,0.0025908935,0.8243894,0.00049836567,0.14119434,0.0042996667,0.00006848872],"about_ca_topic_score_codex":0.013376314,"about_ca_topic_score_gemma":0.013443886,"teacher_disagreement_score":0.016489916,"about_ca_system_score_codex":0.0017032996,"about_ca_system_score_gemma":0.0007925247,"threshold_uncertainty_score":0.055164278},"labels":[],"label_agreement":null},{"id":"W4388895620","doi":"10.2139/ssrn.4617827","title":"Recipient-Dependent Last-Mile Delivery Routing with Autonomous Vehicle Applications","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; York University","funders":"","keywords":"Last mile (transportation); Mile; Vehicle routing problem; Routing (electronic design automation); Computer science; Transport engineering; Engineering; Business; Computer network; Geography","score_opus":0.006443139001538142,"score_gpt":0.20651064693000382,"score_spread":0.20006750792846567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388895620","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08655422,0.00042290866,0.90379584,0.00060013845,0.0002470014,0.00014195559,0.00018764086,0.001045256,0.007005014],"genre_scores_gemma":[0.9147434,0.00029018463,0.073957734,0.00010685094,0.000104637256,0.00008485493,0.00027698852,0.00013409705,0.010301083],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988611,0.00033598402,0.00006389966,0.00021881763,0.00029074124,0.00022936179],"domain_scores_gemma":[0.9973156,0.0010100984,0.00026934812,0.0005633303,0.0006648126,0.0001767992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021393867,0.00069047767,0.0011363794,0.00092008215,0.0011390353,0.0015800981,0.0025536877,0.001110533,0.0029627078],"category_scores_gemma":[0.006107647,0.00053021935,0.0006170765,0.0010999695,0.0007143292,0.0021847403,0.0028250364,0.0013478962,0.0010832781],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070894323,0.00024522253,0.0027854256,0.00016981745,0.00008592759,0.00027753855,0.00032820756,0.7545594,0.010553184,0.06391523,0.0070766727,0.1592944],"study_design_scores_gemma":[0.000010772502,0.00012440191,0.00026777235,0.000008086951,0.00001879419,0.000066411056,0.00007671346,0.98147136,0.0025103064,0.013887543,0.0015425718,0.000015278081],"about_ca_topic_score_codex":0.0019548454,"about_ca_topic_score_gemma":0.002792752,"teacher_disagreement_score":0.0029627078,"about_ca_system_score_codex":0.0008857011,"about_ca_system_score_gemma":0.0013248868,"threshold_uncertainty_score":0.0113143325},"labels":[],"label_agreement":null},{"id":"W4388906648","doi":"10.3390/su152316180","title":"What Makes Parents Consider Shared Autonomous Vehicles as a School Travel Mode?","year":2023,"lang":"en","type":"article","venue":"Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Socioeconomic status; Sustainable transport; Psychology; Mode (computer interface); Travel behavior; Estimation; Business; Applied psychology; Transport engineering; Environmental health; Sustainability; Computer science; Engineering; Medicine","score_opus":0.01636211921193557,"score_gpt":0.28675171327432375,"score_spread":0.27038959406238816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388906648","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9894364,0.0017932641,0.0005175916,0.0043852823,0.000100183854,0.000015529726,0.00013305333,0.0000068582954,0.0036119146],"genre_scores_gemma":[0.9981927,0.0009423926,0.00019576454,0.00022644184,0.000017937067,0.000008217876,0.000067843335,0.0000023289977,0.00034635473],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993001,0.00028515226,0.00004895069,0.00009913701,0.00014065267,0.00012591056],"domain_scores_gemma":[0.99555165,0.0016797336,0.0014210317,0.00011970293,0.0006054456,0.00062234845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013618531,0.00015179359,0.00024050272,0.00046093026,0.0005793276,0.0017252489,0.00028692084,0.00087410153,0.0030936392],"category_scores_gemma":[0.01000602,0.00021254945,0.0004792077,0.0004757373,0.0005662822,0.00186568,0.00044083482,0.00103565,0.0002733138],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009108225,0.00014632032,0.9318639,0.00018194754,0.000067691486,0.00078469183,0.020049173,0.00008822052,0.00022813216,0.0009953652,0.0023247313,0.043178815],"study_design_scores_gemma":[0.000020370533,0.0002399509,0.8579409,0.00064655585,0.00022469506,0.0016787503,0.122382954,0.0008814703,0.00041666903,0.0020981748,0.013414546,0.00005505628],"about_ca_topic_score_codex":0.008711467,"about_ca_topic_score_gemma":0.009989761,"teacher_disagreement_score":0.008711467,"about_ca_system_score_codex":0.0007237349,"about_ca_system_score_gemma":0.0009549787,"threshold_uncertainty_score":0.017321527},"labels":[],"label_agreement":null},{"id":"W4388931057","doi":"10.1007/s10707-023-00509-1","title":"Efficient algorithms for community aware ridesharing","year":2023,"lang":"en","type":"article","venue":"GeoInformatica","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Heuristic; Set (abstract data type); Data mining; Location-based service; Information retrieval; Artificial intelligence; Computer network","score_opus":0.0396533816415193,"score_gpt":0.2713921622510499,"score_spread":0.2317387806095306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388931057","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04471842,0.0006577629,0.93947214,0.000676614,0.00018155917,0.0005101285,0.0008014694,0.0030965996,0.009885399],"genre_scores_gemma":[0.34403986,0.0003479127,0.6415731,0.00018846648,0.00014371725,0.00033631633,0.0019904461,0.00039426642,0.010985974],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978656,0.0004634444,0.00010931391,0.00059503067,0.0005428843,0.00042373926],"domain_scores_gemma":[0.9958769,0.0019398156,0.00023120095,0.001125,0.0005291753,0.00029803521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014680576,0.0014730771,0.0027921146,0.0023685396,0.0028262306,0.0032515484,0.005616883,0.0036599245,0.014543832],"category_scores_gemma":[0.008873729,0.0010367848,0.0017752689,0.0042048865,0.00113655,0.005218811,0.0058895354,0.0020603724,0.0030351847],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005322249,0.0007120221,0.0019148972,0.0003762606,0.00013153073,0.0001436155,0.00038369634,0.5086151,0.0036146794,0.039885733,0.023529612,0.42016074],"study_design_scores_gemma":[0.00007002773,0.000055872835,0.00017481798,0.000015447236,0.000022738643,0.000068298825,0.00015094387,0.95842445,0.00091549515,0.03727021,0.0028178564,0.000013949718],"about_ca_topic_score_codex":0.010223047,"about_ca_topic_score_gemma":0.015129257,"teacher_disagreement_score":0.014543832,"about_ca_system_score_codex":0.0015155309,"about_ca_system_score_gemma":0.002576261,"threshold_uncertainty_score":0.04865396},"labels":[],"label_agreement":null},{"id":"W4389131017","doi":"10.1007/s10288-023-00556-2","title":"A survey of attended home delivery and service problems with a focus on applications","year":2023,"lang":"en","type":"article","venue":"4OR","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Work (physics); Coronavirus disease 2019 (COVID-19); Service (business); Service delivery framework; Focus (optics); Pandemic; Engineering; Business; Marketing; Medicine","score_opus":0.024031435490344904,"score_gpt":0.220609661804598,"score_spread":0.19657822631425312,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389131017","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9583839,0.014156898,0.0012470682,0.003853668,0.00011042654,0.00018901369,0.002889963,0.00007398473,0.019095037],"genre_scores_gemma":[0.9217177,0.040168058,0.0028134857,0.0025554064,0.00021871644,0.00019748928,0.0055496898,0.00009553574,0.026683796],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99773264,0.00052503345,0.00035812557,0.0002122354,0.00074180297,0.00043012956],"domain_scores_gemma":[0.99234045,0.003104576,0.0018784646,0.00016750222,0.0015747021,0.0009343059],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011646914,0.0003113814,0.00037070716,0.005107145,0.0011692513,0.0012172022,0.0008372798,0.0011562548,0.009460732],"category_scores_gemma":[0.0071647866,0.00030366398,0.00069087686,0.007282697,0.0005992188,0.0015991392,0.0011506062,0.00094057457,0.0012242601],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025775068,0.0009586432,0.76082027,0.0014980708,0.00008093583,0.0019552347,0.009954054,0.0004196832,0.001112732,0.0018669246,0.022930486,0.19814515],"study_design_scores_gemma":[0.000011301578,0.00054302,0.875877,0.00062579627,0.000070070746,0.0046987967,0.038604446,0.00046849347,0.00045859633,0.000348729,0.07825455,0.000039098184],"about_ca_topic_score_codex":0.011918082,"about_ca_topic_score_gemma":0.016609456,"teacher_disagreement_score":0.011918082,"about_ca_system_score_codex":0.0012033827,"about_ca_system_score_gemma":0.0021916546,"threshold_uncertainty_score":0.031649232},"labels":[],"label_agreement":null},{"id":"W4389147287","doi":"10.54254/2753-8818/14/20240872","title":"Study on flying car transportation system","year":2023,"lang":"en","type":"article","venue":"Theoretical and Natural Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Praxis Spinal Cord Institute","funders":"","keywords":"Transport engineering; Ground transportation; Space (punctuation); Dimension (graph theory); Traffic congestion; Order (exchange); Development (topology); Population; Computer science; Engineering; Business","score_opus":0.009486870210230655,"score_gpt":0.25226301043209853,"score_spread":0.2427761402218679,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389147287","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28068122,0.02863069,0.25527295,0.0060358522,0.0011922927,0.00026607298,0.0008426981,0.00018423227,0.426894],"genre_scores_gemma":[0.9374903,0.0127156405,0.012921593,0.00034643267,0.00041688303,0.00008002711,0.0004041783,0.000038324808,0.035586644],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977547,0.000044698903,0.000009346338,0.00005814788,0.00005856232,0.00005388941],"domain_scores_gemma":[0.99986076,0.000030888867,0.00001737754,0.000010001024,0.00006446025,0.000016388956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023875377,0.00032167564,0.00026786103,0.0009908307,0.0011833868,0.001233869,0.0005573725,0.0006476488,0.008668554],"category_scores_gemma":[0.00066322216,0.00012311486,0.00059341197,0.0008928686,0.00056658883,0.002339261,0.0005552473,0.00059259386,0.000815011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022614156,0.00003108643,0.0050913356,0.00026735218,0.000028681101,0.0008258369,0.00084991095,0.044637207,0.0022182185,0.90641874,0.009677555,0.029931534],"study_design_scores_gemma":[0.000021882814,0.00018661495,0.009218724,0.00031103368,0.00008079969,0.0022327206,0.0033196658,0.46212655,0.0021397437,0.30427086,0.21598724,0.000104043225],"about_ca_topic_score_codex":0.017660372,"about_ca_topic_score_gemma":0.006110273,"teacher_disagreement_score":0.017660372,"about_ca_system_score_codex":0.0014478914,"about_ca_system_score_gemma":0.00095958094,"threshold_uncertainty_score":0.035115182},"labels":[],"label_agreement":null},{"id":"W4389329889","doi":"10.1155/2023/2604479","title":"Performance Assessment of a Rehabilitation Transportation Reservation Matching Service with Market Design Mechanisms","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Ministry of Science and Technology, Taiwan; National Dong Hwa University","keywords":"Reservation; Schedule; Rehabilitation; Service (business); Matching (statistics); Subsidy; Order (exchange); Business; Transport engineering; Service provider; Operations research; Computer science; Marketing; Engineering; Finance; Economics; Medicine","score_opus":0.01306941003058271,"score_gpt":0.2532916403222366,"score_spread":0.2402222302916539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389329889","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91392833,0.00034436234,0.07650097,0.00037726908,0.00007324797,0.00049713755,0.00012694445,0.00050765433,0.007644222],"genre_scores_gemma":[0.99480337,0.000033628425,0.004457446,0.00002013689,0.0000062387717,0.00006230278,0.00004220267,0.000008079979,0.0005664616],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9974897,0.0011407447,0.00010589328,0.00028187924,0.0004054457,0.0005762638],"domain_scores_gemma":[0.9949831,0.002745129,0.00050573586,0.00024525702,0.0009469033,0.00057393656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055316566,0.0010761111,0.0011358692,0.0010156372,0.00074424944,0.0016710263,0.0015719158,0.0014758509,0.0044094143],"category_scores_gemma":[0.009522233,0.00031936917,0.0006685246,0.00057364017,0.00058118056,0.0013475862,0.0011643054,0.00072478916,0.00042299795],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024410966,0.0014292154,0.007993318,0.0002070188,0.0000932333,0.0002292333,0.00009167859,0.93134326,0.0053884527,0.0049094628,0.0010108538,0.044863142],"study_design_scores_gemma":[0.000059527993,0.0008046272,0.0006620684,0.0000038488247,0.000023976847,0.000022966682,0.00003728049,0.9970862,0.00085174135,0.00030969712,0.00012937345,0.000008802329],"about_ca_topic_score_codex":0.006355938,"about_ca_topic_score_gemma":0.0016697914,"teacher_disagreement_score":0.006355938,"about_ca_system_score_codex":0.0023099247,"about_ca_system_score_gemma":0.0023790074,"threshold_uncertainty_score":0.029254556},"labels":[],"label_agreement":null},{"id":"W4389427281","doi":"10.2139/ssrn.4657564","title":"Mobile Policies and Their Periodization: The Evolution of the Bus Rapid Transit Model","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Periodization; Transit (satellite); Business; Computer science; Telecommunications; Transport engineering; History; Engineering; Public transport; Ancient history","score_opus":0.011118575380494608,"score_gpt":0.21605505079137585,"score_spread":0.20493647541088125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389427281","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7631538,0.0028485006,0.12501125,0.014725372,0.00021992883,0.00008137724,0.0020736845,0.00035993638,0.091526225],"genre_scores_gemma":[0.97980016,0.0013275911,0.0018168158,0.00014641056,0.000069136964,0.000029554416,0.00017827436,0.000062205676,0.016569935],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99976736,0.00008541485,0.0000047032095,0.000037031376,0.000019215602,0.00008640315],"domain_scores_gemma":[0.9983689,0.0008231791,0.0003458181,0.00008724934,0.00011654471,0.00025834146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011366962,0.00044504553,0.00087114645,0.0006750279,0.0008772388,0.0029662282,0.001159412,0.0014761293,0.0103237135],"category_scores_gemma":[0.0056850608,0.00054797344,0.000761901,0.0010627233,0.0011431191,0.00279276,0.00090700586,0.0020643254,0.0005275],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018933575,0.000058908205,0.0021206094,0.000065709835,0.00005815498,0.00018780572,0.00032219567,0.22278732,0.00046246423,0.76202804,0.006398183,0.0053213825],"study_design_scores_gemma":[0.00012624009,0.00007530681,0.0024226785,0.00005095232,0.000069061934,0.00013411634,0.00045869383,0.60963815,0.00018912191,0.3795248,0.007271186,0.000039733022],"about_ca_topic_score_codex":0.016196571,"about_ca_topic_score_gemma":0.009345995,"teacher_disagreement_score":0.016196571,"about_ca_system_score_codex":0.002475471,"about_ca_system_score_gemma":0.0015427757,"threshold_uncertainty_score":0.034536242},"labels":[],"label_agreement":null},{"id":"W4389478400","doi":"10.1007/978-3-031-49611-0_26","title":"Algorithms for the Ridesharing with Profit Constraint Problem","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Mathematical optimization; Constraint (computer-aided design); Profit (economics); Operations research; Algorithm; Mathematics; Microeconomics","score_opus":0.028683295076837,"score_gpt":0.24469970345708508,"score_spread":0.21601640838024808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389478400","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014760677,0.00096017035,0.9609937,0.00097335724,0.0001978884,0.00034901054,0.00050185795,0.0013683772,0.019895028],"genre_scores_gemma":[0.17506939,0.0008911633,0.80374163,0.0004223678,0.00029455728,0.00061739975,0.0015364579,0.00082445826,0.016602611],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99828666,0.0005370004,0.0000841576,0.00042674973,0.00029871278,0.0003667575],"domain_scores_gemma":[0.9955989,0.003094086,0.00020290814,0.00060772937,0.00029904433,0.00019726715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002290602,0.0021047115,0.0032750724,0.0014406919,0.0015490899,0.0039107036,0.006562552,0.0035073182,0.02276331],"category_scores_gemma":[0.0090816375,0.0014246596,0.0019919323,0.0035753574,0.0014621768,0.0063681947,0.003990881,0.004422888,0.0035244133],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049406436,0.0004927952,0.00055891444,0.00051966275,0.00012682675,0.000115058145,0.00019626573,0.56528366,0.0010711664,0.12068938,0.03440524,0.27604687],"study_design_scores_gemma":[0.00016440432,0.0000589786,0.000114252245,0.000035691806,0.00002940232,0.000053807664,0.00007389374,0.8706048,0.00041611574,0.12391099,0.004519048,0.000018669547],"about_ca_topic_score_codex":0.0074104033,"about_ca_topic_score_gemma":0.006690027,"teacher_disagreement_score":0.02276331,"about_ca_system_score_codex":0.0022672454,"about_ca_system_score_gemma":0.0028413855,"threshold_uncertainty_score":0.076150894},"labels":[],"label_agreement":null},{"id":"W4389540803","doi":"10.17118/11143/21168","title":"A coupled vehicle ride and handling model","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Automotive engineering; Engineering","score_opus":0.019309205768574634,"score_gpt":0.2299957224680926,"score_spread":0.21068651669951796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389540803","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19118832,0.0017609398,0.61499083,0.0031551698,0.0005431973,0.00034964256,0.0039503733,0.001213045,0.1828485],"genre_scores_gemma":[0.92668927,0.00063948747,0.0129112275,0.00024460498,0.0000957654,0.00035261497,0.0013298872,0.00015545725,0.05758172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995881,0.00008374265,0.00001976825,0.00012915744,0.0000829793,0.00009630239],"domain_scores_gemma":[0.9993556,0.00024124843,0.0000853061,0.00004064713,0.00019861803,0.00007858773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006568522,0.0011182538,0.001284113,0.0009785859,0.0009997026,0.002416221,0.003475186,0.0036974438,0.01826828],"category_scores_gemma":[0.0015728171,0.0009878987,0.001426205,0.0008530892,0.0013345801,0.0017187397,0.0028198669,0.0018399503,0.0025893522],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058076064,0.000044503246,0.0006189285,0.00007656316,0.000038596347,0.00022591434,0.00007479706,0.9787174,0.0004661632,0.015766913,0.0014466261,0.0024656507],"study_design_scores_gemma":[0.000022366028,0.00002750562,0.00015263795,0.000010497532,0.000017263194,0.000021342405,0.000022424547,0.99622154,0.00004083356,0.0023387414,0.0011143348,0.00001036738],"about_ca_topic_score_codex":0.036956668,"about_ca_topic_score_gemma":0.013502887,"teacher_disagreement_score":0.036956668,"about_ca_system_score_codex":0.0014040051,"about_ca_system_score_gemma":0.0013173072,"threshold_uncertainty_score":0.07348311},"labels":[],"label_agreement":null},{"id":"W4389667914","doi":"10.1155/2023/9763635","title":"Retracted: Optimization Drive on a Flat Tire Vehicular System for Autonomous E-Vehicles Using Network Distribution Simulations","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":true,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Automotive engineering; Computer science; Distribution (mathematics); Simulation; Engineering; Mathematics","score_opus":0.013431759059776404,"score_gpt":0.25155288960362215,"score_spread":0.23812113054384576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389667914","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.67325014,0.0005262874,0.23542076,0.0017377974,0.00059429975,0.00023936736,0.002075789,0.0034312082,0.082724325],"genre_scores_gemma":[0.98328376,0.00005272075,0.0073491414,0.00005563601,0.00001768983,0.000044736047,0.00032718686,0.00016398416,0.008705256],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999045,0.000030871313,0.0000037303857,0.0000165688,0.000019853778,0.000024391284],"domain_scores_gemma":[0.99944013,0.00030983667,0.000020206799,0.0000388902,0.00014781728,0.000043045187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036325556,0.00055806595,0.0007145702,0.00041382608,0.0006162097,0.00071496563,0.00072267867,0.0010902684,0.013028147],"category_scores_gemma":[0.0013027671,0.0003945346,0.0005915051,0.00024058299,0.00030921798,0.0006107436,0.0005944326,0.00073746726,0.00085564546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005318642,0.000028242355,0.00035542744,0.000022900602,0.000009269177,0.0000329925,0.000016673815,0.9948443,0.0002180666,0.0005208784,0.0008831963,0.0030149103],"study_design_scores_gemma":[0.0000053824165,0.000012418015,0.000068376845,0.0000017297435,0.0000018919048,0.0000017828993,0.000009138063,0.9994344,0.00006740515,0.00014069825,0.0002550298,0.0000017019522],"about_ca_topic_score_codex":0.05097149,"about_ca_topic_score_gemma":0.028606158,"teacher_disagreement_score":0.05097149,"about_ca_system_score_codex":0.000743496,"about_ca_system_score_gemma":0.0009821989,"threshold_uncertainty_score":0.10134959},"labels":[],"label_agreement":null},{"id":"W4389898553","doi":"10.1109/jsac.2023.3322070","title":"Guest Editorial Special Issue on 5G/6G Precise Positioning on Cooperative Intelligent Transportation Systems (C-ITS) and Connected Automated Vehicles (CAV)—Part II","year":2023,"lang":"en","type":"editorial","venue":"IEEE Journal on Selected Areas in Communications","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Intelligent transportation system; Telecommunications; Systems engineering; Engineering management; Transport engineering; Engineering","score_opus":0.02025991325077089,"score_gpt":0.28911412887955545,"score_spread":0.2688542156287846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389898553","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006509094,0.002547534,0.0001801244,0.010055874,0.9840605,0.000015483383,0.000052654672,0.000052953998,0.002969813],"genre_scores_gemma":[0.0006217028,0.0028547414,0.00009361188,0.004071765,0.97930473,0.000012804376,0.000045316214,0.00004936628,0.012945943],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99794847,0.00025449696,0.00024403134,0.00031690032,0.0010657544,0.00017033046],"domain_scores_gemma":[0.99054366,0.001978854,0.00056797103,0.00025036995,0.0051703355,0.0014888365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026727938,0.0020086172,0.0019194813,0.0024058623,0.0016320694,0.005053612,0.0014459898,0.0046693357,0.02852157],"category_scores_gemma":[0.008867524,0.0004805333,0.001290319,0.00091754855,0.0009576374,0.002447875,0.0008890929,0.0069837375,0.017438572],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041741776,0.000011005473,0.000031362346,0.00018999753,0.000008882178,0.00012101675,0.000009615911,0.0000315935,0.00015591673,0.00043372865,0.99160236,0.0073628607],"study_design_scores_gemma":[0.000027420703,0.000038670274,0.0002266847,0.00020215569,0.000025121362,0.00033029678,0.00003336499,0.00017010768,0.00026975086,0.000797902,0.9978672,0.000011317018],"about_ca_topic_score_codex":0.00043224418,"about_ca_topic_score_gemma":0.0011080798,"teacher_disagreement_score":0.02852157,"about_ca_system_score_codex":0.0012747148,"about_ca_system_score_gemma":0.0016826927,"threshold_uncertainty_score":0.09541416},"labels":[],"label_agreement":null},{"id":"W4389993197","doi":"10.2139/ssrn.4662398","title":"Subscription vs. Spot Pricing in On-Demand Economy","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Spot market; Economics; Spot contract; Business; Industrial organization; Commerce; Financial economics; Engineering","score_opus":0.00857088970062337,"score_gpt":0.21789996939789186,"score_spread":0.2093290796972685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389993197","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56188655,0.0073431106,0.19492494,0.014095784,0.0015294668,0.00019479559,0.0014657693,0.0010790586,0.21748048],"genre_scores_gemma":[0.98191327,0.00095254503,0.0013770681,0.0001925507,0.00042933953,0.000013463702,0.00007452141,0.00006328809,0.014983972],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986058,0.0005812327,0.00005054484,0.00018826273,0.00020242902,0.00037182716],"domain_scores_gemma":[0.99381,0.004698808,0.0003805305,0.00033789984,0.00034871718,0.00042405765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024611908,0.00068996684,0.0026309933,0.0008306741,0.00094635907,0.0055320864,0.0020688185,0.0035155185,0.0299874],"category_scores_gemma":[0.009931044,0.00062336336,0.0012151216,0.0015026432,0.0022544253,0.007586462,0.0012864004,0.0031332313,0.0014003089],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012213425,0.0003049054,0.002939134,0.00039559556,0.00009226033,0.0006950839,0.00025265725,0.09918415,0.0016526814,0.83503675,0.013691857,0.044533577],"study_design_scores_gemma":[0.00018919987,0.00026447073,0.002574386,0.000059171893,0.00013570156,0.00043271622,0.00041949176,0.3869498,0.0006745033,0.6035485,0.00468391,0.00006816127],"about_ca_topic_score_codex":0.0038903963,"about_ca_topic_score_gemma":0.0032909391,"teacher_disagreement_score":0.0299874,"about_ca_system_score_codex":0.0018050856,"about_ca_system_score_gemma":0.0011688593,"threshold_uncertainty_score":0.100317836},"labels":[],"label_agreement":null},{"id":"W4390103372","doi":"10.5267/j.ijiec.2023.9.009","title":"A multi-objective site selection of electric vehicle charging station based on NSGA-II","year":2023,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Foundation of Inner Mongolia; National Natural Science Foundation of China","keywords":"Charging station; Site selection; Electric vehicle; Maximization; Selection (genetic algorithm); Cluster analysis; Computer science; Point (geometry); Transport engineering; Mathematical optimization; Operations research; Engineering; Mathematics","score_opus":0.023864676336733358,"score_gpt":0.26197651348998713,"score_spread":0.23811183715325376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390103372","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11012844,0.0003963518,0.87249404,0.0004522808,0.00014969584,0.000670697,0.00030361363,0.00049579353,0.014909141],"genre_scores_gemma":[0.87275285,0.0002573771,0.117785834,0.00015405845,0.000030741307,0.0009538182,0.0003828294,0.00003902298,0.0076434994],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948776,0.00021478222,0.000021946888,0.000059287522,0.00011398863,0.00010222777],"domain_scores_gemma":[0.9996468,0.00013462314,0.00004296065,0.000014870214,0.00012233229,0.00003828145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009189848,0.001099914,0.0011085168,0.0006824909,0.0004813119,0.0008992463,0.0011428337,0.0007950027,0.003389007],"category_scores_gemma":[0.0012653249,0.0005503417,0.0007843194,0.0007406934,0.00044001258,0.00039951064,0.0006231504,0.0007754028,0.0002907787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020776084,0.000015628517,0.00027517634,0.000022103375,0.000012443124,0.000028872562,0.000012946011,0.9942827,0.00021356733,0.0009440077,0.000387468,0.0037842433],"study_design_scores_gemma":[0.0000130333665,0.00002197933,0.00011889689,0.0000050081335,0.0000049291916,0.000005237388,0.000011025257,0.9991073,0.00010530476,0.0003757698,0.00022815262,0.0000033598783],"about_ca_topic_score_codex":0.026591947,"about_ca_topic_score_gemma":0.019297503,"teacher_disagreement_score":0.026591947,"about_ca_system_score_codex":0.001223263,"about_ca_system_score_gemma":0.0022152637,"threshold_uncertainty_score":0.052874327},"labels":[],"label_agreement":null},{"id":"W4390397198","doi":"10.3917/sh.170.0006","title":"10.3917/sh.170.0006","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.0037413410616927724,"score_gpt":0.15546245885814405,"score_spread":0.15172111779645128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390397198","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00072934857,0.00014504061,0.00031102466,0.00047059398,0.0004068758,0.00003648562,0.000854553,0.0006923689,0.9963536],"genre_scores_gemma":[0.0015556155,0.00012639703,0.00014204589,0.00020138582,0.00005413071,0.000015088301,0.00045938694,0.00013800396,0.9973079],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99978536,0.000015211522,0.000014975032,0.000056257602,0.00007800419,0.00005019676],"domain_scores_gemma":[0.99922276,0.00009482579,0.000030812156,0.00011587935,0.00024328775,0.00029245415],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00046943428,0.0014643143,0.00054232165,0.0016652769,0.0014993408,0.0029086734,0.00072568655,0.0017791832,0.971901],"category_scores_gemma":[0.000780253,0.0004507676,0.00045550082,0.0012493827,0.0010704594,0.0020501153,0.001943876,0.0011884952,0.9739863],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015134878,0.00023988789,0.0012306394,0.00018800271,0.000009168958,0.00012693428,0.00011203182,0.00016102177,0.0014411788,0.005883678,0.5997244,0.39073166],"study_design_scores_gemma":[0.000025329477,0.00003148849,0.0011648999,0.00014410634,0.0000068303975,0.00014019979,0.00014757297,0.00017456019,0.00046471736,0.0011048178,0.9965843,0.000011213549],"about_ca_topic_score_codex":0.005831946,"about_ca_topic_score_gemma":0.008156646,"teacher_disagreement_score":0.028099,"about_ca_system_score_codex":0.0010992995,"about_ca_system_score_gemma":0.0010997662,"threshold_uncertainty_score":0.040079832},"labels":[],"label_agreement":null},{"id":"W4390422037","doi":"10.1109/jiot.2023.3348516","title":"Strategy-Proof Computational Resource Reservation Based on Dynamic Matching for Vehicular Edge Computing","year":2023,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Science, Technology and Innovation Commission of Shenzhen Municipality; National Natural Science Foundation of China; Toyota Motor Corporation; U.S. Department of Transportation; National Science Foundation","keywords":"Reservation; Computer science; Edge computing; Resource (disambiguation); Distributed computing; Enhanced Data Rates for GSM Evolution; Matching (statistics); Computation; Software deployment; Computational complexity theory; Computer network; Algorithm; Telecommunications","score_opus":0.02240981788000247,"score_gpt":0.27453480053816925,"score_spread":0.2521249826581668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390422037","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018178338,0.00026722436,0.97622687,0.0002445682,0.0000741249,0.000090578484,0.00004570894,0.00028520965,0.0045874105],"genre_scores_gemma":[0.9280268,0.00022787048,0.06899543,0.0001654503,0.000046193218,0.00008447072,0.000077467535,0.00006632926,0.0023099352],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99833256,0.0004816838,0.000083768544,0.00036601856,0.00035936828,0.0003765709],"domain_scores_gemma":[0.99789494,0.0012104054,0.0002185099,0.00026526558,0.00026574716,0.00014519104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016363863,0.00069714896,0.000987782,0.00060780125,0.00090409775,0.0017227969,0.00202647,0.0009504351,0.0033605497],"category_scores_gemma":[0.0061206543,0.00042361068,0.0006916401,0.00096515944,0.0011806233,0.0021623198,0.001897684,0.0015330176,0.0004935469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039771263,0.00012999351,0.0011427854,0.00015714747,0.00006462211,0.00036350722,0.00025136606,0.7509156,0.0066290405,0.17372575,0.0034535227,0.06276899],"study_design_scores_gemma":[0.000012843417,0.000033163986,0.000046099434,0.000005349273,0.000006766689,0.0000552295,0.000027071788,0.9784517,0.0006842484,0.019999009,0.0006697129,0.000008938164],"about_ca_topic_score_codex":0.0032748918,"about_ca_topic_score_gemma":0.002535302,"teacher_disagreement_score":0.0033605497,"about_ca_system_score_codex":0.0012251881,"about_ca_system_score_gemma":0.0022379467,"threshold_uncertainty_score":0.011242151},"labels":[],"label_agreement":null},{"id":"W4390562500","doi":"10.1016/j.cor.2024.106529","title":"Algorithms and computational study on a transportation system integrating public transit and ridesharing of personal vehicles","year":2024,"lang":"en","type":"article","venue":"Computers & Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Public transport; Transit (satellite); Computer science; Hypergraph; Set (abstract data type); Matching (statistics); Transport engineering; Rounding; Operations research; Algorithm; Engineering; Mathematics","score_opus":0.06851897095731482,"score_gpt":0.3377080033727808,"score_spread":0.269189032415466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390562500","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56349444,0.0010354511,0.4169524,0.0026052298,0.00021072627,0.00015838654,0.00038393697,0.00027405407,0.014885348],"genre_scores_gemma":[0.8610799,0.00047173584,0.13152738,0.00011182673,0.00014274105,0.00011378095,0.00032232754,0.000057893903,0.0061724647],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99956316,0.00017735283,0.000021323938,0.00009487854,0.00006495967,0.00007835356],"domain_scores_gemma":[0.9963648,0.0029880193,0.00013204243,0.00012380637,0.00029494095,0.00009648204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010485087,0.00063888234,0.0009254483,0.0008334821,0.0015254572,0.0015052231,0.0013029873,0.0016908168,0.0030620801],"category_scores_gemma":[0.004519018,0.00037005785,0.0010782363,0.0011574334,0.0009694554,0.0014428997,0.0008709224,0.0009847578,0.00015946016],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000717691,0.0001220986,0.001545663,0.000058707657,0.00002578189,0.00007442174,0.00005784507,0.9686951,0.00052552356,0.015154174,0.0010095198,0.012659366],"study_design_scores_gemma":[0.0000041000403,0.000007763913,0.00012059823,0.0000011019041,0.0000034194777,0.0000054886477,0.00001646333,0.99795616,0.0000657121,0.0017156705,0.0001017016,0.0000017874805],"about_ca_topic_score_codex":0.046967257,"about_ca_topic_score_gemma":0.025650548,"teacher_disagreement_score":0.046967257,"about_ca_system_score_codex":0.0014861907,"about_ca_system_score_gemma":0.0021282204,"threshold_uncertainty_score":0.09338778},"labels":[],"label_agreement":null},{"id":"W4390733084","doi":"10.1016/j.trd.2024.104056","title":"Changes in emerging mobility tool adoption: A path towards sustainability?","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Sustainability; Emerging markets; Sustainable transport; Public transport; Emerging technologies; Business; Car sharing; Coronavirus disease 2019 (COVID-19); Descriptive statistics; Sharing economy; Transport engineering; Environmental economics; Marketing; Engineering; Economics; Computer science; Finance","score_opus":0.030712619906008928,"score_gpt":0.2969193583208792,"score_spread":0.26620673841487025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390733084","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89789206,0.0025325431,0.0053834557,0.055048663,0.0004274849,0.00007071467,0.0017176834,0.00014747892,0.036779895],"genre_scores_gemma":[0.99595106,0.0005877447,0.0012388817,0.00075791613,0.00004891657,0.000018278926,0.00024100966,0.000017928338,0.0011382207],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99671304,0.00082178955,0.00030563702,0.00065088,0.00070224114,0.0008065186],"domain_scores_gemma":[0.99013114,0.002871107,0.0029055602,0.00071163423,0.002527861,0.0008525801],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045813886,0.0002767499,0.0003029757,0.001361168,0.0010280586,0.0059476034,0.0011661825,0.0022237909,0.012073056],"category_scores_gemma":[0.019147316,0.00022697108,0.00056627573,0.0028736193,0.0025156923,0.010663964,0.0022989954,0.0024037287,0.00089651125],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041262124,0.0009561288,0.5898452,0.0006177857,0.00023696675,0.00048491184,0.024261206,0.0014321075,0.0029632812,0.09903289,0.010649774,0.2691072],"study_design_scores_gemma":[0.00002911241,0.00035814632,0.83647406,0.0005655153,0.000079611564,0.00040383555,0.06802879,0.002005858,0.0015627159,0.035046365,0.05537623,0.00006975523],"about_ca_topic_score_codex":0.0112081235,"about_ca_topic_score_gemma":0.017958293,"teacher_disagreement_score":0.012073056,"about_ca_system_score_codex":0.0023263276,"about_ca_system_score_gemma":0.00396969,"threshold_uncertainty_score":0.040388465},"labels":[],"label_agreement":null},{"id":"W4390901485","doi":"10.1155/2024/6681895","title":"A Systematic Review of the Coopetition Relationship between Bike‐Sharing and Public Transit","year":2024,"lang":"en","type":"review","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Coopetition; Bike sharing; Public transport; Transport engineering; Transit (satellite); Business; Rail transit; Engineering; Economics; Microeconomics; Game theory","score_opus":0.0443722751402514,"score_gpt":0.3081004200480484,"score_spread":0.263728144907797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390901485","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001409049,0.99620074,0.00024861482,0.0004089284,0.0001326926,0.00024016367,0.0006899513,0.0000075663916,0.0006622859],"genre_scores_gemma":[0.012695648,0.9848952,0.0008155468,0.0004618217,0.00006788821,0.00048308534,0.0003997921,0.000006634313,0.00017424888],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9882544,0.0038684877,0.0048051127,0.00083213515,0.0019777133,0.00026220377],"domain_scores_gemma":[0.9352259,0.0487653,0.008924681,0.0008627288,0.0056087705,0.00061263394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009497539,0.0011923034,0.004773068,0.014555865,0.000970544,0.003215876,0.0018733669,0.0018211978,0.005734481],"category_scores_gemma":[0.059156198,0.0009808985,0.0056309756,0.019769892,0.001127618,0.0032646894,0.0018573956,0.001531178,0.00045570018],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009504039,0.000023167524,0.0015356292,0.93453777,0.0035812976,0.0001778437,0.00071265036,0.00008929419,0.00013691404,0.0005760565,0.0023628497,0.056171518],"study_design_scores_gemma":[0.00006627667,0.000114855306,0.007865642,0.9365283,0.020297186,0.00048427284,0.00082550955,0.00007174614,0.00012888836,0.00040225274,0.0331748,0.000040087885],"about_ca_topic_score_codex":0.02112488,"about_ca_topic_score_gemma":0.063147664,"teacher_disagreement_score":0.02112488,"about_ca_system_score_codex":0.0043755574,"about_ca_system_score_gemma":0.027883507,"threshold_uncertainty_score":0.050228357},"labels":[],"label_agreement":null},{"id":"W4391019887","doi":"10.1109/cdc49753.2023.10384067","title":"Communication-Efficient Allocation of Multiple Indivisible Resources in a Federated Multi-Agent System","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Mitacs","keywords":"Computer science; Resource allocation; Distributed computing; Probabilistic logic; Population; Multi-agent system; Resource (disambiguation); Resource management (computing); Convergence (economics); Enhanced Data Rates for GSM Evolution; Intelligent agent; Shared resource; Computer network; Telecommunications; Artificial intelligence","score_opus":0.027279538228612215,"score_gpt":0.24876090403744264,"score_spread":0.22148136580883043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391019887","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.055666465,0.00017377791,0.94034225,0.00032998048,0.000039034254,0.000041606225,0.00003361377,0.00019499248,0.0031782084],"genre_scores_gemma":[0.9001169,0.00014376116,0.096374355,0.00008029209,0.000020681786,0.0000935297,0.000032193177,0.000025515614,0.0031128703],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990368,0.00037798868,0.000050729723,0.00016462251,0.00021965594,0.00015024401],"domain_scores_gemma":[0.99891853,0.00044842038,0.00018355057,0.00013121996,0.00021561641,0.00010270343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016270796,0.0006230554,0.0010895447,0.00045604326,0.00095735595,0.0013370169,0.0014452559,0.0013622384,0.0010772644],"category_scores_gemma":[0.002549503,0.0003659968,0.00067487254,0.0006534234,0.0009997045,0.0013286112,0.0014975572,0.0008329708,0.00019762566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042798336,0.0000210378,0.00020110558,0.00001712924,0.00002047405,0.000098231874,0.000043251526,0.98036855,0.0012757005,0.012806466,0.0002197359,0.0048855008],"study_design_scores_gemma":[0.0000053250506,0.000009800284,0.000032836688,0.0000013856743,0.0000029141297,0.000010299535,0.000007854065,0.9964121,0.00016248992,0.0031954846,0.00015709101,0.0000024925992],"about_ca_topic_score_codex":0.005765131,"about_ca_topic_score_gemma":0.003455298,"teacher_disagreement_score":0.005765131,"about_ca_system_score_codex":0.0012887967,"about_ca_system_score_gemma":0.0014766257,"threshold_uncertainty_score":0.011463165},"labels":[],"label_agreement":null},{"id":"W4391124869","doi":"10.1155/2024/7764326","title":"Optimal Fleet Policy of Rental Vehicles with Relocation: A Simulation Study","year":2024,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"University of Auckland","keywords":"Renting; Relocation; Fleet management; Operations research; Pooling; Service (business); Popularity; Transport engineering; Profit (economics); Business; Computer science; Operations management; Engineering; Marketing; Economics; Microeconomics","score_opus":0.009588414409366072,"score_gpt":0.2801643830024549,"score_spread":0.2705759685930888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391124869","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9613153,0.00044185208,0.017327122,0.0007915662,0.00006319158,0.00016075603,0.0009510405,0.000085560845,0.01886372],"genre_scores_gemma":[0.99389815,0.00018735591,0.003101978,0.000047367383,0.0000075150347,0.00007191624,0.00027258878,0.000017478429,0.0023955521],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999196,0.00033775016,0.000027248454,0.000080754755,0.00005083089,0.0003074281],"domain_scores_gemma":[0.99208224,0.0057489877,0.00072674535,0.00020579877,0.00055248686,0.00068367156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018456208,0.0008535791,0.0013935062,0.0011417032,0.0008179686,0.0017354682,0.0017113644,0.0024938234,0.0073582116],"category_scores_gemma":[0.0061853407,0.00067083945,0.0018007675,0.0012117317,0.001031567,0.0017261928,0.0009918677,0.002216296,0.00035266145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008895832,0.00009434606,0.0015811177,0.00002373981,0.000018360317,0.00007085986,0.00002058428,0.9955035,0.0000832155,0.0015708995,0.00030386986,0.0006405915],"study_design_scores_gemma":[0.000039622853,0.00009471448,0.00073202315,0.000010016029,0.000020614958,0.00001258283,0.00014228678,0.9980432,0.00006652719,0.0005894873,0.000238643,0.000010211979],"about_ca_topic_score_codex":0.10599558,"about_ca_topic_score_gemma":0.05585318,"teacher_disagreement_score":0.10599558,"about_ca_system_score_codex":0.004061638,"about_ca_system_score_gemma":0.0024801604,"threshold_uncertainty_score":0.21075726},"labels":[],"label_agreement":null},{"id":"W4391130935","doi":"10.1155/2024/6170743","title":"Cost Analysis of Vehicle‐Road Cooperative Intelligence Solutions for High‐Level Autonomous Driving: A Beijing Case Study","year":2024,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Foundation of Beijing Municipality; National Natural Science Foundation of China","keywords":"Beijing; Transport engineering; Automotive engineering; Computer science; Engineering; Operations research; China; Geography","score_opus":0.04640316131848892,"score_gpt":0.3213276025621538,"score_spread":0.2749244412436649,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391130935","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9774914,0.00030738258,0.008700987,0.00023758665,0.000009807832,0.00015971196,0.00030927034,0.000050549144,0.012733396],"genre_scores_gemma":[0.9965648,0.000113512724,0.0018347092,0.0000063648,0.0000018459527,0.00004255745,0.000115204224,0.0000068049653,0.001314197],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9993944,0.00019272961,0.000022069695,0.00006316724,0.00017784265,0.00014970626],"domain_scores_gemma":[0.99886096,0.00055371545,0.00013012726,0.00009136127,0.0002801681,0.00008362844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010642284,0.00087597343,0.00041994505,0.0015716972,0.00070036063,0.0012357492,0.0010908486,0.0008844677,0.0029926312],"category_scores_gemma":[0.001989439,0.000316281,0.0007286991,0.0016828417,0.0006677353,0.0019976308,0.0007928035,0.00054098497,0.00015585717],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030527805,0.00030107072,0.024843086,0.00017560898,0.000086392065,0.0011889786,0.00018115454,0.9217322,0.002314778,0.017115531,0.0014041077,0.030351887],"study_design_scores_gemma":[0.000031421507,0.00032796335,0.021666149,0.000018257435,0.00009340299,0.00017406412,0.0008459726,0.9697817,0.0021053897,0.0030325043,0.0018813066,0.000041827767],"about_ca_topic_score_codex":0.049932234,"about_ca_topic_score_gemma":0.03897508,"teacher_disagreement_score":0.049932234,"about_ca_system_score_codex":0.0066310703,"about_ca_system_score_gemma":0.0016443423,"threshold_uncertainty_score":0.09928322},"labels":[],"label_agreement":null},{"id":"W4391526341","doi":"10.1007/s44007-024-00098-x","title":"An Incentive Algorithm for a Closed Stochastic Network: Data and Mean-Field Analysis","year":2024,"lang":"en","type":"article","venue":"La Matematica","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Incentive; Ode; Computer science; Mathematical optimization; Algorithm; Mathematics; Economics; Applied mathematics; Microeconomics","score_opus":0.017683797841305016,"score_gpt":0.29206391273742266,"score_spread":0.27438011489611763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391526341","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012472319,0.00014872271,0.98438764,0.0008513312,0.00006312402,0.00011286897,0.00012135477,0.000167088,0.0016755889],"genre_scores_gemma":[0.41675806,0.00061337894,0.56774974,0.0005621531,0.00027916676,0.000701018,0.0005550705,0.00030437493,0.012477016],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99735355,0.0012258434,0.00012648567,0.00063372124,0.00040409918,0.00025628114],"domain_scores_gemma":[0.9743862,0.020227024,0.0011304182,0.0012177961,0.0018179076,0.001220526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0077067283,0.0011959921,0.0027976471,0.0015446035,0.001350843,0.0024355925,0.0044421377,0.004979365,0.006532763],"category_scores_gemma":[0.037415214,0.001141966,0.0012862625,0.00209654,0.0027782063,0.0063157533,0.0037578852,0.0039703366,0.00075668766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027415756,0.000205924,0.0009653825,0.00021287793,0.000053297143,0.00006789986,0.00019176536,0.63101125,0.001160384,0.31401747,0.00673686,0.04510274],"study_design_scores_gemma":[0.00005082318,0.000042026426,0.0000904512,0.00002145321,0.000008547922,0.000030232213,0.000012940538,0.9012402,0.00018682357,0.09754116,0.0007620203,0.000013217519],"about_ca_topic_score_codex":0.0036427178,"about_ca_topic_score_gemma":0.0029398692,"teacher_disagreement_score":0.0077067283,"about_ca_system_score_codex":0.0029899974,"about_ca_system_score_gemma":0.0057386067,"threshold_uncertainty_score":0.040757596},"labels":[],"label_agreement":null},{"id":"W4391546832","doi":"10.1007/978-3-031-34027-7_49","title":"What Can We Learn from On-Demand Transit Services for Ridership? A Case Study at the City of Regina, Canada","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Regina; Western University","funders":"","keywords":"Transit (satellite); Transport engineering; Business; Computer science; Geography; Engineering; Public transport","score_opus":0.0152000694827495,"score_gpt":0.21364466601704718,"score_spread":0.1984445965342977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391546832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6219283,0.005343353,0.0013283872,0.09785253,0.0003162179,0.00014829828,0.00074810564,0.000058435162,0.27227643],"genre_scores_gemma":[0.9583558,0.0052617425,0.00088069297,0.0021234418,0.00005715534,0.000022265132,0.00023979497,0.000029955869,0.03302912],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.997658,0.00060599734,0.000026827536,0.000116139745,0.0005569423,0.001035999],"domain_scores_gemma":[0.9969375,0.0010450737,0.00016004061,0.00010687103,0.00096256426,0.0007878921],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017219081,0.00030946662,0.00039281114,0.0008387299,0.008281344,0.009651052,0.0021488718,0.0023584757,0.009732202],"category_scores_gemma":[0.0058179186,0.00022374254,0.00042284714,0.0024203658,0.00430402,0.0045899274,0.0024797937,0.0022928799,0.0007771719],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000180577,0.0012083125,0.12715626,0.0011075088,0.00009563288,0.015047512,0.345892,0.005016133,0.001384532,0.09415576,0.1663222,0.24243364],"study_design_scores_gemma":[0.000017850265,0.000089062574,0.043712385,0.00086873217,0.000043465116,0.00075159635,0.745979,0.0012474926,0.0003972891,0.0068762004,0.19997638,0.00004054641],"about_ca_topic_score_codex":0.916661,"about_ca_topic_score_gemma":0.9756881,"teacher_disagreement_score":0.083338976,"about_ca_system_score_codex":0.03157891,"about_ca_system_score_gemma":0.04407297,"threshold_uncertainty_score":0.2291221},"labels":[],"label_agreement":null},{"id":"W4391621141","doi":"10.2139/ssrn.4718671","title":"Closures, Mobility, Busy Parents, and Distracted Retail Investors","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Business; Distracted driving; Advertising; Marketing; Psychology; Distraction; Cognitive psychology","score_opus":0.009218438429403598,"score_gpt":0.22258258843183895,"score_spread":0.21336415000243536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391621141","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89197683,0.0022695158,0.00065509416,0.042963468,0.0002811177,0.000013549421,0.0000723427,0.000012443826,0.06175554],"genre_scores_gemma":[0.9936215,0.0006694965,0.000049879814,0.0009137006,0.00007217169,0.0000060887296,0.0000146395705,0.0000072629505,0.0046451534],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99836165,0.0006655955,0.00006679276,0.00014931399,0.0002514979,0.0005051415],"domain_scores_gemma":[0.98981535,0.003798859,0.0032287298,0.00033400208,0.0006405215,0.0021825416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031677387,0.00016914298,0.0003420082,0.0010477224,0.0045646555,0.008102057,0.0008224549,0.0025415898,0.015113981],"category_scores_gemma":[0.017249873,0.0002645532,0.00016912103,0.0011785518,0.006544344,0.007244771,0.0038503583,0.0039027338,0.0005887796],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008752171,0.00067305955,0.3318016,0.00016190807,0.00007480072,0.0049334713,0.24837166,0.0006012099,0.0003082983,0.2709235,0.04095337,0.100321904],"study_design_scores_gemma":[0.00009703248,0.00016173338,0.086190686,0.0003784706,0.00006371677,0.0017470422,0.7632383,0.00070010993,0.0002517455,0.06708889,0.08000411,0.00007812096],"about_ca_topic_score_codex":0.012731935,"about_ca_topic_score_gemma":0.017911186,"teacher_disagreement_score":0.015113981,"about_ca_system_score_codex":0.002532648,"about_ca_system_score_gemma":0.002337422,"threshold_uncertainty_score":0.05056131},"labels":[],"label_agreement":null},{"id":"W4391669268","doi":"10.1016/j.trd.2024.104079","title":"Understanding the daily operations of electric taxis from macro-patterns to micro-behaviors","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Fundamental Research Funds for the Central Universities; Canada Foundation for Innovation; National Natural Science Foundation of China; National University's Basic Research Foundation of China; Natural Science Foundation of Heilongjiang Province; Natural Sciences and Engineering Research Council of Canada","keywords":"Taxis; Computer science; Transport engineering; Macro; Electric vehicle; Battery (electricity); Operations research; Engineering","score_opus":0.0805302044224419,"score_gpt":0.29820188288706284,"score_spread":0.21767167846462093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391669268","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98319477,0.0002975425,0.008108501,0.0006628625,0.000013844118,0.000022179536,0.0006594668,0.000040088064,0.0070007998],"genre_scores_gemma":[0.9968046,0.00020510524,0.0018689274,0.00004359033,0.000009440898,0.000009143331,0.00023258498,0.000008705297,0.000817964],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987805,0.00003481724,0.000007349397,0.000037753114,0.000017119977,0.000024770554],"domain_scores_gemma":[0.99946195,0.0001940105,0.00014615645,0.00005022878,0.000083433806,0.000064218475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016626994,0.00015436912,0.00013080808,0.0006533948,0.00020388523,0.0015374625,0.0003199595,0.00026159207,0.0022174676],"category_scores_gemma":[0.0017156801,0.0001778321,0.00014468927,0.0006970745,0.00031698827,0.001952256,0.00044168346,0.00037067977,0.00031672002],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055136104,0.0001877088,0.87823045,0.00009722151,0.0001092175,0.00013603023,0.0046657054,0.010884551,0.003602221,0.009604983,0.0025977849,0.08982907],"study_design_scores_gemma":[0.0000023722569,0.00004019308,0.9376767,0.000045461453,0.000018935074,0.0000923694,0.010876964,0.03270227,0.0004601908,0.013303763,0.004763566,0.000017138354],"about_ca_topic_score_codex":0.021914875,"about_ca_topic_score_gemma":0.04974309,"teacher_disagreement_score":0.021914875,"about_ca_system_score_codex":0.0005090408,"about_ca_system_score_gemma":0.00048429362,"threshold_uncertainty_score":0.04357463},"labels":[],"label_agreement":null},{"id":"W4391720525","doi":"10.1016/j.trc.2024.104516","title":"A column-generation matheuristic approach for optimizing first-mile ridesharing services with publicly- and privately-owned autonomous vehicles","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part C Emerging Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"National Key Research and Development Program of China; China Scholarship Council; National Natural Science Foundation of China","keywords":"Public transport; Mile; Reservation; Transport engineering; Schedule; Operations research; Computer science; Integer programming; Column generation; Scheduling (production processes); Fleet management; TRIPS architecture; Last mile (transportation); Service quality; Service (business); Engineering; Business; Operations management; Computer network; Mathematical optimization","score_opus":0.05906875228969753,"score_gpt":0.30157484440049287,"score_spread":0.24250609211079532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391720525","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06571661,0.0011173983,0.8938459,0.0019031889,0.00038791506,0.0003329958,0.0014790804,0.0009151417,0.034301754],"genre_scores_gemma":[0.80242515,0.00038124237,0.17416736,0.000956221,0.00025180663,0.00038256007,0.0011901027,0.00037853804,0.019866964],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907494,0.0003876901,0.000028384915,0.00014312066,0.00015672509,0.00020919996],"domain_scores_gemma":[0.9962675,0.002781081,0.00018277038,0.00010627829,0.0004636762,0.00019870969],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018609342,0.0018156689,0.002695452,0.0016870719,0.0010881957,0.0024222685,0.0030074352,0.0029597934,0.015504973],"category_scores_gemma":[0.005856431,0.0015895328,0.0015030719,0.0017575393,0.0016918886,0.0017170617,0.0021808802,0.0019367731,0.001162982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005622724,0.000039851508,0.00028655046,0.000039494647,0.000026625985,0.000056239038,0.000020356312,0.98851633,0.00010397378,0.0041774376,0.0016200884,0.005056916],"study_design_scores_gemma":[0.000007736326,0.000010680609,0.000041966814,0.0000038535873,0.000004593322,0.000004575995,0.000010727147,0.99782324,0.000030454179,0.0019035853,0.00015531994,0.0000033422868],"about_ca_topic_score_codex":0.037176486,"about_ca_topic_score_gemma":0.03728708,"teacher_disagreement_score":0.037176486,"about_ca_system_score_codex":0.0021029427,"about_ca_system_score_gemma":0.0032381741,"threshold_uncertainty_score":0.07392019},"labels":[],"label_agreement":null},{"id":"W4391768483","doi":"10.1109/itsc57777.2023.10422357","title":"Demand Density Forecasting in Mobility-on-Demand Systems Through Recurrent Mixture Density Networks","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Demand forecasting; On demand; Computer science; Operations research; Engineering; Multimedia","score_opus":0.0308705652817126,"score_gpt":0.24540172454162537,"score_spread":0.21453115925991278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391768483","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4067413,0.0008930897,0.5851396,0.0012218736,0.00012527936,0.00004843437,0.00082231546,0.00077645533,0.0042316276],"genre_scores_gemma":[0.9848,0.00020740589,0.012882712,0.00007252046,0.000025413463,0.000023451243,0.00046619063,0.0000232219,0.0014991648],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980134,0.000055762484,0.000010824576,0.0000611341,0.000033733206,0.0000371584],"domain_scores_gemma":[0.99943537,0.0003084513,0.00007641385,0.00003396171,0.00011777336,0.000027989796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006488684,0.0006115603,0.0005991074,0.00038708182,0.00023395105,0.00054119725,0.00089128385,0.0005701486,0.0009870916],"category_scores_gemma":[0.0024280965,0.00044814128,0.0005572017,0.00047541133,0.00038669768,0.0011370579,0.0005880772,0.0011919622,0.00021267068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053248812,0.000026794038,0.0039118384,0.000020294914,0.00002905474,0.000047378908,0.000030165767,0.97611916,0.00040301197,0.003773054,0.0007484064,0.014837736],"study_design_scores_gemma":[8.385773e-7,0.0000018088118,0.00015933599,8.2339363e-7,0.0000014255841,0.0000019641398,0.0000021446642,0.9991335,0.000039143604,0.00060916384,0.00004865186,0.0000011997136],"about_ca_topic_score_codex":0.03268051,"about_ca_topic_score_gemma":0.024270615,"teacher_disagreement_score":0.03268051,"about_ca_system_score_codex":0.00089372916,"about_ca_system_score_gemma":0.00046389343,"threshold_uncertainty_score":0.06498057},"labels":[],"label_agreement":null},{"id":"W4391768912","doi":"10.1109/itsc57777.2023.10421996","title":"Interactive Car-Following: Matters but NOT Always","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","score_opus":0.016640991420938823,"score_gpt":0.246838520078859,"score_spread":0.23019752865792018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391768912","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.60467964,0.0006279043,0.3770756,0.0005973587,0.00010914853,0.0000889375,0.000115452385,0.0008539062,0.015852088],"genre_scores_gemma":[0.9947299,0.000064940934,0.004500745,0.000036420086,0.000013804494,0.000011132982,0.000032520034,0.000014358757,0.0005962786],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9991417,0.00015725089,0.000043195607,0.00026740655,0.00023012745,0.00016033128],"domain_scores_gemma":[0.9983937,0.00054169056,0.00034815335,0.00022615117,0.00027833122,0.00021191838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006415833,0.00050072663,0.000451187,0.00031032218,0.0007074802,0.00079950213,0.000718537,0.00059699896,0.0015959988],"category_scores_gemma":[0.0023119827,0.00023758816,0.0003211125,0.00024238553,0.0010427659,0.0012535851,0.00084987987,0.00058451615,0.00025970413],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022543822,0.0006492556,0.13030615,0.0007966719,0.0004937397,0.0027498016,0.0035526906,0.21224397,0.21385375,0.049010888,0.006077847,0.3780109],"study_design_scores_gemma":[0.000054164717,0.0011723978,0.11489115,0.00013174402,0.00037951922,0.002666021,0.0040813484,0.7426819,0.064454034,0.05368015,0.015587341,0.00022026309],"about_ca_topic_score_codex":0.0025356866,"about_ca_topic_score_gemma":0.0034234475,"teacher_disagreement_score":0.0025356866,"about_ca_system_score_codex":0.00031629606,"about_ca_system_score_gemma":0.00062321604,"threshold_uncertainty_score":0.0053391457},"labels":[],"label_agreement":null},{"id":"W4391832064","doi":"10.1177/10591478241235005","title":"Regulation of Privatized Public Service Systems","year":2024,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Delegate; Profit maximization; Economics; Social Welfare; Microeconomics; Business; Public service; Profit (economics); Finance; Public economics; Public relations","score_opus":0.016811791591126272,"score_gpt":0.21977420878727164,"score_spread":0.20296241719614536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391832064","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64886856,0.00075075345,0.2804154,0.0041509643,0.00018118652,0.00021293196,0.00046516597,0.0010166822,0.06393838],"genre_scores_gemma":[0.9939042,0.00010418746,0.0031793294,0.000113775735,0.000021957332,0.00004543607,0.0000427516,0.000016501932,0.002571961],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9967692,0.001248917,0.00014889255,0.0005150491,0.0006776374,0.00064030924],"domain_scores_gemma":[0.99238455,0.0034245031,0.0017398982,0.0014560386,0.0007485733,0.00024639143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025005285,0.00024330406,0.00038118326,0.00040770406,0.0006890794,0.0028434314,0.0012979296,0.0010400311,0.0050423485],"category_scores_gemma":[0.00894641,0.00044828802,0.00048522497,0.00067563064,0.0020156242,0.003057478,0.001674413,0.0013695564,0.0004360396],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024204631,0.0002342738,0.007336024,0.00018841257,0.00009588636,0.00033418828,0.00056885096,0.34902978,0.011117619,0.6013564,0.0046041347,0.024892412],"study_design_scores_gemma":[0.00017408622,0.00018596997,0.007034447,0.000076185126,0.00005874102,0.00015464042,0.00045548196,0.72568154,0.0046742056,0.2412831,0.020165307,0.000056242876],"about_ca_topic_score_codex":0.0064463457,"about_ca_topic_score_gemma":0.005325705,"teacher_disagreement_score":0.0064463457,"about_ca_system_score_codex":0.004615779,"about_ca_system_score_gemma":0.0039950777,"threshold_uncertainty_score":0.033490002},"labels":[],"label_agreement":null},{"id":"W4391942782","doi":"10.21203/rs.3.rs-3960869/v1","title":"The Potential of Vehicle-to-Home Integration for Residential Prosumers: A Case Study","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Business","score_opus":0.05282141327178594,"score_gpt":0.39571068376853724,"score_spread":0.34288927049675133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391942782","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9475287,0.00029842378,0.009383884,0.0005399916,0.000040111623,0.0001773733,0.00016572743,0.00006250138,0.041803394],"genre_scores_gemma":[0.9926005,0.000114053815,0.0030898375,0.00002897358,0.0000073483884,0.000031029707,0.000047537178,0.000008640625,0.0040721595],"study_design_codex":"simulation_or_modeling","study_design_gemma":"case_report","domain_scores_codex":[0.99871826,0.0006776399,0.000023924698,0.0001086829,0.00017973378,0.00029179067],"domain_scores_gemma":[0.9980288,0.00116773,0.00007441885,0.00021013324,0.00028563789,0.00023310992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015083072,0.0006706617,0.00031210866,0.0006657074,0.001834522,0.0026172467,0.0016179881,0.0030555497,0.008704408],"category_scores_gemma":[0.002700204,0.00025973213,0.00063139776,0.0010681155,0.0011467275,0.0028835286,0.0018779438,0.0010998453,0.0009649581],"study_design_candidate":"case_report","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0060281954,0.010890078,0.106471844,0.0012633916,0.00037232094,0.060435805,0.016913112,0.29331434,0.02071529,0.22377935,0.017501598,0.24231458],"study_design_scores_gemma":[0.0008270456,0.007132874,0.03408935,0.00047354522,0.0006200048,0.014468959,0.09185317,0.6789647,0.03776189,0.05191556,0.081578806,0.00031417375],"about_ca_topic_score_codex":0.005920715,"about_ca_topic_score_gemma":0.007434394,"teacher_disagreement_score":0.008704408,"about_ca_system_score_codex":0.0011867587,"about_ca_system_score_gemma":0.00074213505,"threshold_uncertainty_score":0.029119074},"labels":[],"label_agreement":null},{"id":"W4391949446","doi":"","title":"Promoting urban carpooling: a total social cost approach based on the Lyon case study","year":2024,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Regional science; Computer science; Environmental planning; Business; Geography","score_opus":0.023846196310893485,"score_gpt":0.2397065395084632,"score_spread":0.21586034319756972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391949446","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93181443,0.00045548478,0.022998853,0.0005830758,0.000022994047,0.00021459123,0.00064435013,0.00006301809,0.04320314],"genre_scores_gemma":[0.9935893,0.00027473905,0.0037347146,0.000015695245,0.0000062447807,0.0000765778,0.000093328905,0.000008792647,0.0022006454],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9990645,0.0006073308,0.000019070349,0.000052933654,0.00008284256,0.00017330177],"domain_scores_gemma":[0.99904674,0.0006241225,0.00009240701,0.000055352517,0.000117456286,0.000063977284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009241967,0.0007451369,0.00054251606,0.0018036024,0.000612891,0.0018618194,0.0008821738,0.0009433114,0.0045333914],"category_scores_gemma":[0.0014137715,0.00021042874,0.0011743075,0.0018227857,0.00075164833,0.00090862386,0.00088928145,0.0005573284,0.00014360821],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018351595,0.00022432904,0.008400654,0.00015017511,0.00009242117,0.0006685104,0.0002475204,0.94828427,0.00065446197,0.032466996,0.0007661242,0.007861026],"study_design_scores_gemma":[0.00009769995,0.0004959139,0.012709083,0.000080482445,0.00015113156,0.00022571818,0.0030980627,0.9635733,0.0013439594,0.012577231,0.0055486043,0.000098777724],"about_ca_topic_score_codex":0.043650504,"about_ca_topic_score_gemma":0.038266752,"teacher_disagreement_score":0.043650504,"about_ca_system_score_codex":0.0044679493,"about_ca_system_score_gemma":0.0011545126,"threshold_uncertainty_score":0.086792886},"labels":[],"label_agreement":null},{"id":"W4391974266","doi":"10.2139/ssrn.4732767","title":"Modelling Demand-Response Bus Scheduling for Urban Rail Transit","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Demand response; Scheduling (production processes); Transit (satellite); Computer science; Transport engineering; Urban rail transit; Rail transit; Business; Public transport; Engineering; Operations management; Electrical engineering","score_opus":0.014961238809689753,"score_gpt":0.24325315978254647,"score_spread":0.22829192097285672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391974266","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6557115,0.0009208367,0.3167364,0.0021412256,0.0003089449,0.00022186957,0.0024186105,0.00058557955,0.020955058],"genre_scores_gemma":[0.9801065,0.0001725651,0.01052138,0.00007526204,0.000040961975,0.00007157192,0.00054172263,0.0001340738,0.008335929],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947447,0.00016258257,0.000019094958,0.00011635254,0.00004539801,0.00018219311],"domain_scores_gemma":[0.99763846,0.0017831879,0.00015812782,0.0000593861,0.0001795795,0.00018116653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010404543,0.0009814921,0.0014938974,0.00061656657,0.00056268496,0.0018631703,0.0016441505,0.0023603826,0.008068957],"category_scores_gemma":[0.0044782967,0.0013150977,0.0012058273,0.0009246644,0.0008539467,0.001004323,0.0009274835,0.0015797007,0.00048934354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025112646,0.000017951239,0.00016976363,0.000012121779,0.000006073766,0.000012713211,0.000011055872,0.99808335,0.00009189504,0.0009776449,0.00017010949,0.0004221208],"study_design_scores_gemma":[0.0000043651235,0.0000048345164,0.000051777763,9.988004e-7,0.0000019871627,0.0000011598613,0.000009610625,0.9993104,0.000023189996,0.0005334963,0.00005683129,0.000001327465],"about_ca_topic_score_codex":0.08563958,"about_ca_topic_score_gemma":0.04597973,"teacher_disagreement_score":0.08563958,"about_ca_system_score_codex":0.002626028,"about_ca_system_score_gemma":0.0026665104,"threshold_uncertainty_score":0.17028224},"labels":[],"label_agreement":null},{"id":"W4391989376","doi":"","title":"Best mobility practices on University campuses worldwide : a literature review","year":2023,"lang":"fr","type":"review","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Computer science; Best practice; Engineering ethics; Data science; Political science; Engineering","score_opus":0.03416626133075479,"score_gpt":0.2797607509938647,"score_spread":0.24559448966310993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391989376","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011274943,0.9976495,0.000053440715,0.000597163,0.00008415691,0.0000189375,0.00011602108,0.000003470306,0.00034984382],"genre_scores_gemma":[0.008823636,0.9903639,0.00024934686,0.000350714,0.000047805115,0.000026718953,0.00007160333,0.0000020844045,0.00006427761],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.99705493,0.0008692059,0.0007840738,0.00038995044,0.00070280506,0.00019903257],"domain_scores_gemma":[0.9825539,0.012212695,0.0027110854,0.0001903882,0.0018160827,0.00051579956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0054296516,0.0007309637,0.0031405408,0.0105659515,0.0008222849,0.004355544,0.0013883065,0.0018188304,0.0045667836],"category_scores_gemma":[0.017886227,0.0005953784,0.0021321287,0.015271873,0.0011175872,0.0035587363,0.0020120468,0.0015779344,0.00040872867],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018472578,0.00012350678,0.0050966493,0.36266354,0.0017049592,0.0002158399,0.0025321336,0.00029397226,0.00026061045,0.0020791464,0.014459145,0.6103858],"study_design_scores_gemma":[0.00006978994,0.00020600997,0.029940236,0.76039875,0.0072738538,0.00093594193,0.008943947,0.00011974208,0.00026224332,0.0012575556,0.19047046,0.00012148088],"about_ca_topic_score_codex":0.012659578,"about_ca_topic_score_gemma":0.03727513,"teacher_disagreement_score":0.012659578,"about_ca_system_score_codex":0.003388018,"about_ca_system_score_gemma":0.011295048,"threshold_uncertainty_score":0.028715134},"labels":[],"label_agreement":null},{"id":"W4392103996","doi":"10.1016/j.cor.2024.106588","title":"A ride time-oriented scheduling algorithm for dial-a-ride problems","year":2024,"lang":"en","type":"article","venue":"Computers & Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Alliance de recherche numérique du Canada","keywords":"Computer science; Mathematical optimization; Scheduling (production processes); Benchmark (surveying); Algorithm; Linear programming; Job shop scheduling; Schedule; Mathematics","score_opus":0.04061754838773477,"score_gpt":0.33895546316266717,"score_spread":0.2983379147749324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392103996","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03448796,0.0003109545,0.9541438,0.0003077579,0.00022901772,0.00038057216,0.00025196947,0.0015003552,0.008387713],"genre_scores_gemma":[0.1968298,0.00023325474,0.7963312,0.000194386,0.00008470572,0.00032613814,0.00060032395,0.00033369116,0.0050665434],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995425,0.0001162869,0.000028649603,0.00011247387,0.000103603044,0.000096619966],"domain_scores_gemma":[0.99934715,0.0002564687,0.000045279943,0.000082443024,0.00017054968,0.000098111756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011551687,0.0009797493,0.0015935329,0.0010918009,0.0011972819,0.0012995017,0.0023303197,0.0011863704,0.005844129],"category_scores_gemma":[0.002121408,0.0007382073,0.0008573941,0.0014103652,0.0005491606,0.0013576355,0.0013569477,0.0013097428,0.00086478615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005695193,0.0006128149,0.00061112444,0.00022192388,0.00007048379,0.00007266677,0.00012867189,0.699377,0.005695853,0.021985358,0.011123519,0.2595311],"study_design_scores_gemma":[0.0001225286,0.00008618612,0.00011727641,0.000007551918,0.000015320713,0.00001760931,0.000018449542,0.9918469,0.0006393025,0.0054011387,0.0017170284,0.000010600615],"about_ca_topic_score_codex":0.008491247,"about_ca_topic_score_gemma":0.007909533,"teacher_disagreement_score":0.008491247,"about_ca_system_score_codex":0.0012535457,"about_ca_system_score_gemma":0.002662638,"threshold_uncertainty_score":0.019550502},"labels":[],"label_agreement":null},{"id":"W4392124644","doi":"10.1109/tiv.2024.3369324","title":"Uncertainty-Aware Decision Making and Planning for ICV Based on Asymmetric Driving Aggressiveness","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Vehicles","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Computer science; Psychology","score_opus":0.02262730012647406,"score_gpt":0.29500859970038934,"score_spread":0.27238129957391527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392124644","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10394094,0.00017970978,0.88937527,0.00032248916,0.000034449924,0.000090699774,0.00009453815,0.00015864475,0.0058031473],"genre_scores_gemma":[0.98168105,0.00009551315,0.017224757,0.000033244512,0.000008639405,0.00006983102,0.000062636245,0.000011277734,0.0008131372],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992494,0.00018155393,0.000033037388,0.00018495863,0.00015925191,0.00019185866],"domain_scores_gemma":[0.99893755,0.0004960461,0.00021806608,0.000053858003,0.00017567982,0.00011884619],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008858762,0.0009770576,0.00079810375,0.00061701686,0.0008102962,0.001379134,0.0011516634,0.00093148946,0.0012683179],"category_scores_gemma":[0.0022412243,0.0005741863,0.0008005564,0.00053569145,0.00096352847,0.0012150795,0.0013812273,0.0011506387,0.000100933976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029510471,0.000015421272,0.00090636156,0.000022914495,0.000017413255,0.00008553099,0.00007348264,0.9857458,0.00066423806,0.0069933343,0.00014296628,0.0053030197],"study_design_scores_gemma":[0.000003253569,0.000018580235,0.00019591476,0.0000034360473,0.000008642838,0.00000894971,0.000027984264,0.9954248,0.00020603246,0.0039758855,0.00012046706,0.000006036274],"about_ca_topic_score_codex":0.018685194,"about_ca_topic_score_gemma":0.010788287,"teacher_disagreement_score":0.018685194,"about_ca_system_score_codex":0.0015254979,"about_ca_system_score_gemma":0.0026235452,"threshold_uncertainty_score":0.037152886},"labels":[],"label_agreement":null},{"id":"W4392248117","doi":"10.1109/aixvr59861.2024.00017","title":"Design Frameworks for Spatial Zone Agents in XRI Metaverse Smart Environments","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario College of Art and Design","funders":"Canada Research Chairs","keywords":"Metaverse; Computer science; Human–computer interaction; Virtual reality","score_opus":0.03093430098866756,"score_gpt":0.25743721929854013,"score_spread":0.22650291830987257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392248117","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008621744,0.0001965032,0.9675803,0.00039980665,0.000053470838,0.0001826239,0.00002964113,0.00070235133,0.022233587],"genre_scores_gemma":[0.24965307,0.0004339627,0.7303594,0.00019111711,0.000024392913,0.0006731905,0.00011632304,0.00034464343,0.018203963],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987419,0.0005690987,0.00008424152,0.00017664525,0.0002874162,0.00014067038],"domain_scores_gemma":[0.99922144,0.00024226385,0.00007889669,0.00017519193,0.0001522316,0.00012995095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002152665,0.0008093486,0.00032928388,0.0006548523,0.0014472207,0.0042344015,0.0018432172,0.0015579589,0.008063105],"category_scores_gemma":[0.0023368874,0.0007054584,0.0010922295,0.00032024024,0.003382253,0.004973007,0.004815485,0.0014607871,0.001391543],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029618515,0.00005591347,0.00039481567,0.00019916447,0.000018500023,0.00028039963,0.0059042936,0.014086953,0.005528396,0.9503714,0.0014535092,0.021676926],"study_design_scores_gemma":[0.000108167325,0.00025553725,0.00059563137,0.00036149134,0.000096793716,0.0009865044,0.007256971,0.21527503,0.020428285,0.27729526,0.477236,0.000104317856],"about_ca_topic_score_codex":0.0016334249,"about_ca_topic_score_gemma":0.003095259,"teacher_disagreement_score":0.008063105,"about_ca_system_score_codex":0.0011656015,"about_ca_system_score_gemma":0.0013087714,"threshold_uncertainty_score":0.026973784},"labels":[],"label_agreement":null},{"id":"W4392731200","doi":"10.1177/10591478231224973","title":"Business Model Innovation for Ambulance Systems in Low- and Middle-Income Countries: “Coordination and Competition”","year":2024,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Business; Competition (biology); Business model; Industrial organization; Operations management; Marketing; Economics","score_opus":0.0137486102492085,"score_gpt":0.23369758939528412,"score_spread":0.2199489791460756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392731200","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5408763,0.0012374583,0.25124767,0.016100358,0.00017215653,0.00089054526,0.00059047854,0.00021275785,0.18867226],"genre_scores_gemma":[0.98284364,0.00032260513,0.008187052,0.00037726504,0.00004256563,0.00019263852,0.00007173807,0.00001202366,0.007950517],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9968721,0.0015849359,0.000058060024,0.0005201098,0.00031525578,0.0006494479],"domain_scores_gemma":[0.9924385,0.0042368793,0.0014737822,0.0003364098,0.00049490697,0.0010196331],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035938278,0.0006685382,0.0010684778,0.0010512713,0.001837054,0.005489087,0.0019155619,0.0037189247,0.009903407],"category_scores_gemma":[0.008228343,0.00044865417,0.0012747827,0.0008141812,0.0036723886,0.0037501547,0.0021771,0.002975754,0.0008545483],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017004869,0.00025683074,0.0071571083,0.00015290441,0.000072692754,0.00064849906,0.0005732268,0.16326445,0.0009743897,0.8097579,0.005517309,0.011454656],"study_design_scores_gemma":[0.00021547805,0.0003054883,0.0042692255,0.000114885464,0.000070146816,0.0003474515,0.0015799246,0.7204972,0.0006086634,0.2539977,0.01787712,0.00011679372],"about_ca_topic_score_codex":0.007047763,"about_ca_topic_score_gemma":0.0064473483,"teacher_disagreement_score":0.009903407,"about_ca_system_score_codex":0.0055110278,"about_ca_system_score_gemma":0.0037360128,"threshold_uncertainty_score":0.039985538},"labels":[],"label_agreement":null},{"id":"W4392845585","doi":"10.2139/ssrn.4760815","title":"The Impacts of On-Demand Transit Service on Ridership and its Growth","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina; Western University","funders":"","keywords":"Transit (satellite); Business; Transport engineering; Service (business); Public transport; Engineering; Marketing","score_opus":0.011099442541380683,"score_gpt":0.23367379349107403,"score_spread":0.22257435094969336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392845585","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98321474,0.0006761496,0.00043459557,0.0014220842,0.000030172807,0.000014816258,0.001891073,0.000021634472,0.012294836],"genre_scores_gemma":[0.9968354,0.0002934744,0.000025562542,0.000020446543,0.000018857123,0.0000036001531,0.000317081,0.000004127116,0.0024814552],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993887,0.00017071966,0.000030031877,0.000068425776,0.00008322743,0.00025879976],"domain_scores_gemma":[0.99346983,0.0032991725,0.0010330267,0.00017392871,0.00095882424,0.001065151],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008176114,0.00026745093,0.00037520318,0.00082024623,0.0004099737,0.0023492577,0.00050098775,0.00094322604,0.0157296],"category_scores_gemma":[0.006126969,0.00016100696,0.0006836864,0.0017886508,0.00065079634,0.0015963711,0.0012517483,0.0013480502,0.0011892772],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002005216,0.00075932476,0.8856745,0.00021184958,0.00030879804,0.001435593,0.0013585624,0.042797565,0.0021026642,0.024707561,0.0070823682,0.03155606],"study_design_scores_gemma":[0.00004636463,0.0005073266,0.9330735,0.00006406299,0.0002739919,0.00026862606,0.008678269,0.037031364,0.0013278116,0.010759619,0.007933401,0.00003555286],"about_ca_topic_score_codex":0.05033934,"about_ca_topic_score_gemma":0.05256002,"teacher_disagreement_score":0.05033934,"about_ca_system_score_codex":0.001995795,"about_ca_system_score_gemma":0.0013043396,"threshold_uncertainty_score":0.10009265},"labels":[],"label_agreement":null},{"id":"W4392846187","doi":"10.2139/ssrn.4760786","title":"Will You Still Drive or are You Ready to Ride? Exploring Readiness to Use Demand-Responsive Transport in the City of Vienna","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Business; On demand; Transport engineering; Engineering; Commerce","score_opus":0.04540166792939436,"score_gpt":0.2779729292737434,"score_spread":0.23257126134434902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392846187","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9951127,0.00007956376,0.0003811616,0.00045602737,0.000008995783,0.0000133584,0.000096491836,0.000005081924,0.0038465536],"genre_scores_gemma":[0.9986205,0.0000717858,0.000141297,0.000028897814,0.0000014800244,0.000011088715,0.00007506819,0.000007362876,0.0010424204],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990337,0.00028827466,0.000022680786,0.00012030285,0.00011804835,0.000417108],"domain_scores_gemma":[0.9987698,0.00043075555,0.00014983531,0.0000621173,0.000244684,0.0003428005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011473435,0.00020821656,0.00030036367,0.0008175471,0.0012048968,0.003849857,0.00075227354,0.0007178813,0.0037100154],"category_scores_gemma":[0.0040462897,0.00029361824,0.00048541464,0.00090612494,0.0011549339,0.0022284405,0.0025634677,0.0014460359,0.00055174535],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045771935,0.00056080037,0.59389555,0.00020851678,0.00019105856,0.0011909226,0.32348707,0.0022291755,0.0023816102,0.024518099,0.004444823,0.04643476],"study_design_scores_gemma":[0.000008551125,0.00016392594,0.46358392,0.00019580114,0.00007899954,0.00016435423,0.51751494,0.0025800525,0.0004925542,0.0031491183,0.012003386,0.00006444791],"about_ca_topic_score_codex":0.13508573,"about_ca_topic_score_gemma":0.18659748,"teacher_disagreement_score":0.13508573,"about_ca_system_score_codex":0.0043830774,"about_ca_system_score_gemma":0.0029597809,"threshold_uncertainty_score":0.2685989},"labels":[],"label_agreement":null},{"id":"W4392861939","doi":"10.32920/25417444.v1","title":"Policymaking and Planning for On-Demand Ride-Hailing in Toronto and Vancouver: Explanatory Factors and Policy Implications","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University; University of British Columbia","funders":"","keywords":"Variety (cybernetics); Business; Transportation planning; Emerging technologies; Marketing; Point (geometry); Economics; Industrial organization; Transport engineering; Engineering; Computer science","score_opus":0.027726419082528393,"score_gpt":0.32614463231137786,"score_spread":0.2984182132288495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392861939","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9643251,0.0004733785,0.0005560139,0.008210089,0.000025120818,0.00015632517,0.00030430724,0.00001226846,0.025937295],"genre_scores_gemma":[0.9968838,0.00046565058,0.0002389097,0.00014538279,0.000003282253,0.000026441905,0.00009225515,0.0000026623443,0.002141478],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9976004,0.00078035466,0.0000836222,0.0001481197,0.0003004994,0.0010870722],"domain_scores_gemma":[0.99045753,0.0046618963,0.0009175687,0.00017197269,0.0017804166,0.0020106162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019484366,0.0003022988,0.00024138835,0.0010873791,0.005890063,0.0048397635,0.00095743896,0.0010995588,0.00505483],"category_scores_gemma":[0.010486884,0.00028626667,0.000285033,0.0024191753,0.003243892,0.0010936799,0.0019103704,0.0016950195,0.000198925],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025734835,0.0006280353,0.73452336,0.0005266623,0.00009348034,0.0025289687,0.13893376,0.010955037,0.0010577906,0.059914604,0.008969108,0.04161179],"study_design_scores_gemma":[0.000046138855,0.000090392874,0.34157178,0.0005931636,0.00006647512,0.00011558635,0.61648303,0.008082537,0.0006192556,0.0062506762,0.025998563,0.00008229635],"about_ca_topic_score_codex":0.9788943,"about_ca_topic_score_gemma":0.98744166,"teacher_disagreement_score":0.07358939,"about_ca_system_score_codex":0.07358939,"about_ca_system_score_gemma":0.09866061,"threshold_uncertainty_score":0.5339309},"labels":[],"label_agreement":null},{"id":"W4392862091","doi":"10.32920/25417444","title":"Policymaking and Planning for On-Demand Ride-Hailing in Toronto and Vancouver: Explanatory Factors and Policy Implications","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University; University of British Columbia","funders":"","keywords":"Variety (cybernetics); Transportation planning; Business; Emerging technologies; Marketing; Economics; Regional science; Industrial organization; Transport engineering; Engineering; Sociology; Computer science","score_opus":0.027726419082528393,"score_gpt":0.32614463231137786,"score_spread":0.2984182132288495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392862091","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9643251,0.0004733785,0.0005560139,0.008210089,0.000025120818,0.00015632517,0.00030430724,0.00001226846,0.025937295],"genre_scores_gemma":[0.9968838,0.00046565058,0.0002389097,0.00014538279,0.000003282253,0.000026441905,0.00009225515,0.0000026623443,0.002141478],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9976004,0.00078035466,0.0000836222,0.0001481197,0.0003004994,0.0010870722],"domain_scores_gemma":[0.99045753,0.0046618963,0.0009175687,0.00017197269,0.0017804166,0.0020106162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019484366,0.0003022988,0.00024138835,0.0010873791,0.005890063,0.0048397635,0.00095743896,0.0010995588,0.00505483],"category_scores_gemma":[0.010486884,0.00028626667,0.000285033,0.0024191753,0.003243892,0.0010936799,0.0019103704,0.0016950195,0.000198925],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025734835,0.0006280353,0.73452336,0.0005266623,0.00009348034,0.0025289687,0.13893376,0.010955037,0.0010577906,0.059914604,0.008969108,0.04161179],"study_design_scores_gemma":[0.000046138855,0.000090392874,0.34157178,0.0005931636,0.00006647512,0.00011558635,0.61648303,0.008082537,0.0006192556,0.0062506762,0.025998563,0.00008229635],"about_ca_topic_score_codex":0.9788943,"about_ca_topic_score_gemma":0.98744166,"teacher_disagreement_score":0.07358939,"about_ca_system_score_codex":0.07358939,"about_ca_system_score_gemma":0.09866061,"threshold_uncertainty_score":0.5339309},"labels":[],"label_agreement":null},{"id":"W4392950201","doi":"10.32920/25417375.v1","title":"On-demand Ride-hailing as Publicly Subsidized Mobility: An Empirical Case Study of Innisfil Transit","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto; Dalhousie University","funders":"","keywords":"Subsidy; Transit (satellite); Business; Urban transit; Public transport; Transport engineering; Economics; Engineering; Market economy","score_opus":0.04593143295143795,"score_gpt":0.3375559917619219,"score_spread":0.291624558810484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392950201","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99568427,0.000039938368,0.00024165411,0.00013526008,0.0000016736799,0.000048741345,0.00025443683,0.0000042663128,0.0035897037],"genre_scores_gemma":[0.994381,0.00020753374,0.0007227851,0.000041897325,0.000004832792,0.00006310502,0.0005343218,0.0000059817185,0.004038558],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99923265,0.00025915794,0.000022956934,0.00007440423,0.0001357003,0.00027510713],"domain_scores_gemma":[0.99822754,0.00078527705,0.0002862503,0.00016706961,0.00031105382,0.00022274451],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007984682,0.00030958108,0.00027261247,0.0007738863,0.0024118721,0.0009430926,0.0010659975,0.0009403734,0.0025900071],"category_scores_gemma":[0.0029998247,0.00020925966,0.0003356444,0.0019032964,0.0010406396,0.0009642494,0.0009247472,0.0007510021,0.0002894182],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038971228,0.0029976568,0.89186656,0.0002465022,0.00009163538,0.010436839,0.02922868,0.017710555,0.0012871193,0.012492196,0.0066509787,0.02660153],"study_design_scores_gemma":[0.000104354694,0.00065328693,0.7784564,0.00013833547,0.0000728177,0.001916598,0.15405276,0.030540792,0.0014405206,0.0011124306,0.031425845,0.00008591936],"about_ca_topic_score_codex":0.61759984,"about_ca_topic_score_gemma":0.80324745,"teacher_disagreement_score":0.38240016,"about_ca_system_score_codex":0.007131422,"about_ca_system_score_gemma":0.003564751,"threshold_uncertainty_score":0.7693044},"labels":[],"label_agreement":null},{"id":"W4392950474","doi":"10.32920/25417375","title":"On-demand Ride-hailing as Publicly Subsidized Mobility: An Empirical Case Study of Innisfil Transit","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto; Dalhousie University","funders":"","keywords":"Subsidy; Transit (satellite); Business; Urban transit; Public transport; Transport engineering; Economics; Engineering; Market economy","score_opus":0.04593143295143795,"score_gpt":0.3375559917619219,"score_spread":0.291624558810484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392950474","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99568427,0.000039938368,0.00024165411,0.00013526008,0.0000016736799,0.000048741345,0.00025443683,0.0000042663128,0.0035897037],"genre_scores_gemma":[0.994381,0.00020753374,0.0007227851,0.000041897325,0.000004832792,0.00006310502,0.0005343218,0.0000059817185,0.004038558],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99923265,0.00025915794,0.000022956934,0.00007440423,0.0001357003,0.00027510713],"domain_scores_gemma":[0.99822754,0.00078527705,0.0002862503,0.00016706961,0.00031105382,0.00022274451],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007984682,0.00030958108,0.00027261247,0.0007738863,0.0024118721,0.0009430926,0.0010659975,0.0009403734,0.0025900071],"category_scores_gemma":[0.0029998247,0.00020925966,0.0003356444,0.0019032964,0.0010406396,0.0009642494,0.0009247472,0.0007510021,0.0002894182],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038971228,0.0029976568,0.89186656,0.0002465022,0.00009163538,0.010436839,0.02922868,0.017710555,0.0012871193,0.012492196,0.0066509787,0.02660153],"study_design_scores_gemma":[0.000104354694,0.00065328693,0.7784564,0.00013833547,0.0000728177,0.001916598,0.15405276,0.030540792,0.0014405206,0.0011124306,0.031425845,0.00008591936],"about_ca_topic_score_codex":0.61759984,"about_ca_topic_score_gemma":0.80324745,"teacher_disagreement_score":0.38240016,"about_ca_system_score_codex":0.007131422,"about_ca_system_score_gemma":0.003564751,"threshold_uncertainty_score":0.7693044},"labels":[],"label_agreement":null},{"id":"W4393027480","doi":"10.48550/arxiv.2403.12678","title":"Empowering Air Travelers: A Chatbot for Canadian Air Passenger Rights","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Alliance de recherche numérique du Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Air travel; Chatbot; Business; Computer science; World Wide Web; Engineering; Aviation; Aerospace engineering","score_opus":0.040971908888946786,"score_gpt":0.19207614008356633,"score_spread":0.15110423119461955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393027480","genre_codex":"empirical","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6410494,0.0023619393,0.17565826,0.006414865,0.0009956438,0.0022070215,0.0036076189,0.053842176,0.11386315],"genre_scores_gemma":[0.8680344,0.00060354563,0.07205054,0.0007527242,0.00017973398,0.000520581,0.0023200943,0.00062853214,0.05490987],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993813,0.00023377225,0.000028840093,0.00009983028,0.00013584209,0.00012046563],"domain_scores_gemma":[0.9967353,0.0017199904,0.000094712486,0.00021368556,0.0005615606,0.0006747895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011983961,0.00093604776,0.00031809657,0.0008639338,0.002552716,0.0011494878,0.0010234641,0.0011918185,0.014283418],"category_scores_gemma":[0.005276807,0.00018460758,0.00028623996,0.0004509851,0.0007691082,0.0019323528,0.0017757905,0.00075451884,0.0021027175],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029771796,0.0013418752,0.017309712,0.0025684442,0.00012621081,0.005253804,0.067045465,0.004708402,0.123341866,0.012788757,0.19105133,0.5714869],"study_design_scores_gemma":[0.0006551428,0.002294206,0.048873268,0.0009197247,0.00044424745,0.0030170116,0.045843627,0.11361165,0.05524027,0.008091837,0.7202866,0.0007224731],"about_ca_topic_score_codex":0.14557226,"about_ca_topic_score_gemma":0.21309628,"teacher_disagreement_score":0.85442775,"about_ca_system_score_codex":0.0021149677,"about_ca_system_score_gemma":0.0029244842,"threshold_uncertainty_score":0.2894498},"labels":[],"label_agreement":null},{"id":"W4393057924","doi":"10.29007/zx61","title":"Bike sharing systems via birth-death process and simulation modelling","year":2024,"lang":"en","type":"article","venue":"EPiC series in computing","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trent University; Ontario Tech University","funders":"","keywords":"Process (computing); Computer science; Operating system","score_opus":0.023927820477129387,"score_gpt":0.27270394397977177,"score_spread":0.2487761235026424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393057924","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30032226,0.00112182,0.67964685,0.00079346076,0.000121383804,0.00018742647,0.0002824618,0.00034356426,0.01718085],"genre_scores_gemma":[0.9737916,0.0005816696,0.020819517,0.00006694404,0.000032366497,0.00014997492,0.00010778374,0.000035234734,0.0044148555],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989862,0.00051327486,0.00004295913,0.00011244827,0.00019350747,0.00015159171],"domain_scores_gemma":[0.9972378,0.002087403,0.00023894577,0.00013596528,0.0002083528,0.00009151743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00127686,0.00078188896,0.0012017613,0.0008222606,0.0009867704,0.0017960148,0.0014138159,0.001758962,0.0029235915],"category_scores_gemma":[0.004894232,0.00047705421,0.00091706956,0.00094615616,0.0011184056,0.002224845,0.0014882527,0.0011790375,0.00032496333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026037234,0.000024058423,0.000530148,0.00001673588,0.000016952108,0.00006335891,0.00006547014,0.9826089,0.00035480357,0.01503415,0.00008391195,0.0011754506],"study_design_scores_gemma":[0.0000043301684,0.000011570529,0.00007758346,0.0000035150345,0.0000042968804,0.000014831188,0.000019072268,0.9965109,0.00011003849,0.003067229,0.0001704113,0.0000061799005],"about_ca_topic_score_codex":0.014140875,"about_ca_topic_score_gemma":0.0063325693,"teacher_disagreement_score":0.014140875,"about_ca_system_score_codex":0.001298238,"about_ca_system_score_gemma":0.0010390849,"threshold_uncertainty_score":0.02811712},"labels":[],"label_agreement":null},{"id":"W4393157400","doi":"10.1609/aaai.v38i18.30001","title":"PRP Rebooted: Advancing the State of the Art in FOND Planning","year":2024,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Vector Institute; Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"State (computer science); Art; Political science; Aesthetics; Computer science","score_opus":0.04231844455838684,"score_gpt":0.2864380058647946,"score_spread":0.24411956130640777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393157400","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.052216873,0.012385199,0.89497876,0.002822281,0.00048607777,0.00020455691,0.00051008887,0.0064647337,0.029931445],"genre_scores_gemma":[0.5390083,0.004156548,0.44792056,0.00067046506,0.00018559383,0.00019369951,0.0011005129,0.00090098794,0.0058633406],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99740833,0.0009170289,0.00012846313,0.00038961388,0.0009371914,0.00021946778],"domain_scores_gemma":[0.9942702,0.0036701546,0.00021047854,0.001186145,0.0005134497,0.00014956511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029332708,0.0011483912,0.0010884803,0.0009637383,0.0007921578,0.0017187693,0.002335927,0.001329441,0.0056274068],"category_scores_gemma":[0.010407238,0.0005280265,0.00091382704,0.0011325824,0.0020123369,0.002844082,0.002951903,0.002437086,0.0011165135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041090447,0.00018671347,0.0014880094,0.0010077967,0.00008889984,0.00023945226,0.000345727,0.37676656,0.0034909195,0.07695779,0.0139039075,0.5251133],"study_design_scores_gemma":[0.00007763027,0.00019519262,0.00039934446,0.00020175337,0.00004991394,0.00014154514,0.0001271699,0.8945337,0.0037564794,0.07017886,0.030298416,0.00003999533],"about_ca_topic_score_codex":0.010619083,"about_ca_topic_score_gemma":0.012838027,"teacher_disagreement_score":0.010619083,"about_ca_system_score_codex":0.0010728923,"about_ca_system_score_gemma":0.0033973195,"threshold_uncertainty_score":0.021114528},"labels":[],"label_agreement":null},{"id":"W4393308154","doi":"10.36227/techrxiv.171173290.00128329/v1","title":"Driving Support Technology with Human Emotion Regulation: A Review","year":2024,"lang":"en","type":"review","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Psychology; Cognitive psychology; Human–computer interaction; Business; Cognitive science; Computer science","score_opus":0.027761457054603908,"score_gpt":0.3173288276353235,"score_spread":0.2895673705807196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393308154","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007721672,0.9991911,0.000070327544,0.00011111639,0.00007580731,0.00000459057,0.000011205181,0.0000030534006,0.0004554922],"genre_scores_gemma":[0.00056265056,0.9989894,0.00012257908,0.00007736489,0.00006959306,0.000007082006,0.000014949532,0.0000010264462,0.00015538628],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99968445,0.00006363306,0.00007222601,0.00006110452,0.00009361941,0.000024924437],"domain_scores_gemma":[0.99886143,0.0007758387,0.00012134081,0.000023829703,0.0001765537,0.000041005773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088337995,0.0010927265,0.0015583875,0.002791812,0.00036943654,0.0014824106,0.00096265774,0.0015811808,0.004222784],"category_scores_gemma":[0.0016661652,0.0004584949,0.0008893527,0.0033999796,0.00050748297,0.001742637,0.00085705833,0.0012050689,0.0014858008],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006515031,0.00010749493,0.0002810876,0.08978362,0.00020358957,0.00016277832,0.00016259463,0.0003611643,0.00078271347,0.0029401907,0.015916629,0.8892331],"study_design_scores_gemma":[0.000019643294,0.00018142433,0.0020931866,0.037574004,0.0006498555,0.0012896882,0.0002049312,0.00014436405,0.000496341,0.0020628958,0.95523995,0.00004366884],"about_ca_topic_score_codex":0.0020265365,"about_ca_topic_score_gemma":0.0023363237,"teacher_disagreement_score":0.004222784,"about_ca_system_score_codex":0.0005551711,"about_ca_system_score_gemma":0.001694504,"threshold_uncertainty_score":0.014126599},"labels":[],"label_agreement":null},{"id":"W4393416253","doi":"10.4236/jtts.2024.142012","title":"Intermodal Competition: Cargo Airships versus Long-Haul Trucking for Perishable Commodities","year":2024,"lang":"en","type":"article","venue":"Journal of Transportation Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Competition (biology); Business; Air cargo; Transport engineering; Industrial organization; Engineering; Biology; Ecology","score_opus":0.024673220238818305,"score_gpt":0.2608386698652495,"score_spread":0.2361654496264312,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393416253","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5652265,0.0019995596,0.012237689,0.003182845,0.00020332815,0.00011918488,0.0004655551,0.00003292192,0.41653237],"genre_scores_gemma":[0.98335373,0.00035377019,0.00079072156,0.0002805099,0.000043599943,0.00002695918,0.00009481382,0.000009187404,0.015046702],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99929214,0.00015278622,0.000013744923,0.00010208629,0.00016424977,0.00027504977],"domain_scores_gemma":[0.99919647,0.00030376838,0.00012873518,0.00004397233,0.00015982757,0.00016715047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063255004,0.0003865243,0.00048421376,0.0006260155,0.0016467873,0.0028241593,0.0008616578,0.0016718323,0.03871092],"category_scores_gemma":[0.0014322257,0.00016714053,0.0007142669,0.0010033462,0.0018416668,0.0028498974,0.001137522,0.0008346273,0.0011716003],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013317873,0.0006960006,0.03918275,0.0006473304,0.00012605677,0.0014775265,0.0013579399,0.046515685,0.005539623,0.8094021,0.0142217,0.079501554],"study_design_scores_gemma":[0.00052649045,0.0033402704,0.14040077,0.00089622877,0.0004218263,0.0018217971,0.021735566,0.1866531,0.005123492,0.45049772,0.18816361,0.000419136],"about_ca_topic_score_codex":0.031740107,"about_ca_topic_score_gemma":0.0571828,"teacher_disagreement_score":0.03871092,"about_ca_system_score_codex":0.0038012497,"about_ca_system_score_gemma":0.0017664924,"threshold_uncertainty_score":0.12950093},"labels":[],"label_agreement":null},{"id":"W4393862672","doi":"10.1016/j.apmr.2024.02.280","title":"Innovative Methods to Co-design, Develop and Evaluate Personalized Approaches to Mobility Programming for Adults with Physical Disability","year":2024,"lang":"en","type":"article","venue":"Archives of Physical Medicine and Rehabilitation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Physical medicine and rehabilitation; Medicine","score_opus":0.06399193850560346,"score_gpt":0.3629163871079801,"score_spread":0.2989244486023766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393862672","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20059994,0.00056255877,0.76619023,0.0011165646,0.00029728393,0.008518852,0.0011225351,0.0017097839,0.019882176],"genre_scores_gemma":[0.22886847,0.00014141675,0.7609259,0.00016767888,0.000022202268,0.0069717416,0.0003157263,0.000068112604,0.0025188571],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.98801684,0.007112099,0.0007561853,0.0012381797,0.0025734683,0.0003031785],"domain_scores_gemma":[0.97462285,0.015845764,0.0029914507,0.0023640613,0.0035486226,0.00062722754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012221739,0.0009116386,0.00065783295,0.0020570809,0.000707734,0.0034436747,0.0015153418,0.0010424689,0.0057728007],"category_scores_gemma":[0.040210705,0.0005360342,0.001053773,0.0011749543,0.00065686315,0.0021672186,0.0023460502,0.00088875805,0.0006490533],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001133845,0.005612008,0.038354564,0.0011789942,0.0007156071,0.00008832755,0.003183773,0.016521296,0.009162252,0.022788078,0.00523454,0.8960267],"study_design_scores_gemma":[0.0037808076,0.013811727,0.10567599,0.0019648196,0.0032721472,0.00079938734,0.01161274,0.57206327,0.07428644,0.12227976,0.08974417,0.0007086786],"about_ca_topic_score_codex":0.003103455,"about_ca_topic_score_gemma":0.009009664,"teacher_disagreement_score":0.012221739,"about_ca_system_score_codex":0.0022875061,"about_ca_system_score_gemma":0.0054105963,"threshold_uncertainty_score":0.064635515},"labels":[],"label_agreement":null},{"id":"W4393900547","doi":"10.1177/03611981241236480","title":"Greenhouse Gas Emissions and Potential for Electrifying Transportation Network Companies in Toronto","year":2024,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Greenhouse gas; Transport engineering; Environmental science; Global-warming potential; Engineering; Business; Geology; Oceanography","score_opus":0.054168097563566185,"score_gpt":0.3651849326109763,"score_spread":0.3110168350474101,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393900547","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99315345,0.0003910544,0.00018128222,0.00021103499,0.000003755581,0.000013096384,0.0010890531,0.0000073438064,0.0049499553],"genre_scores_gemma":[0.99771994,0.00031120414,0.00008939971,0.000016908316,0.0000018852222,0.0000044177314,0.00048707332,0.0000013820877,0.0013677764],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997571,0.000020998494,0.000008455436,0.000033377026,0.00008810144,0.000092032205],"domain_scores_gemma":[0.99939907,0.00007184703,0.00015741565,0.000012789449,0.0002558351,0.00010310682],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017527817,0.00019722807,0.00009716005,0.000610238,0.0008005598,0.0009574536,0.00033350632,0.00021403363,0.0019193597],"category_scores_gemma":[0.00085019664,0.00013641095,0.00021267797,0.0016505537,0.00032937241,0.0004797907,0.0005075006,0.00024752558,0.00012804274],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014193756,0.000046733694,0.96819246,0.00013044015,0.00007260857,0.0008398037,0.0024103776,0.00806265,0.0030939057,0.0010251204,0.0022512155,0.013732753],"study_design_scores_gemma":[0.0000037700943,0.000027564678,0.98852926,0.000026098462,0.000024686162,0.00007534431,0.0047093863,0.0028046106,0.00035078998,0.0000555231,0.0033833317,0.000009567251],"about_ca_topic_score_codex":0.9563037,"about_ca_topic_score_gemma":0.9801168,"teacher_disagreement_score":0.043696284,"about_ca_system_score_codex":0.015696768,"about_ca_system_score_gemma":0.005239115,"threshold_uncertainty_score":0.1138885},"labels":[],"label_agreement":null},{"id":"W4394608731","doi":"10.1080/03081060.2024.2338873","title":"Optimization of E-bike networks","year":2024,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Group for Research in Decision Analysis","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transport engineering; Poison control; Engineering; Computer science; Medical emergency; Medicine","score_opus":0.006393701261182617,"score_gpt":0.2181879870261782,"score_spread":0.2117942857649956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394608731","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28262058,0.003592701,0.6343818,0.0020444908,0.00028023566,0.0005259382,0.002262363,0.00076030206,0.07353169],"genre_scores_gemma":[0.8945035,0.0011661412,0.08638863,0.00024678296,0.00004218928,0.0004740669,0.0010579628,0.00019147705,0.01592914],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993561,0.00029607705,0.000019041454,0.00011020554,0.00007377957,0.000144854],"domain_scores_gemma":[0.9977927,0.0017236447,0.0001321607,0.00004998261,0.00018194257,0.00011950319],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010112455,0.0019770374,0.0016508948,0.00087295164,0.0005919588,0.0018349086,0.0013115016,0.0022079884,0.0101355575],"category_scores_gemma":[0.0040533734,0.00073775015,0.0008419099,0.0011546413,0.00083031086,0.0013189254,0.0014084599,0.0014744723,0.0007849774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047328427,0.000032865424,0.00027892168,0.000046990575,0.000017012611,0.00004119572,0.000009479786,0.99220884,0.00012598906,0.0024997038,0.000545035,0.0041466192],"study_design_scores_gemma":[0.000013613909,0.000030778643,0.00016642793,0.000011248342,0.000007704735,0.000011194245,0.00003183532,0.99559104,0.00008803755,0.0033839357,0.00066054065,0.0000037613179],"about_ca_topic_score_codex":0.009156751,"about_ca_topic_score_gemma":0.006805897,"teacher_disagreement_score":0.0101355575,"about_ca_system_score_codex":0.001668269,"about_ca_system_score_gemma":0.0014259884,"threshold_uncertainty_score":0.033906817},"labels":[],"label_agreement":null},{"id":"W4394779296","doi":"10.1016/j.tra.2024.104073","title":"Relax on the way to work or work on the way to relax? Influences of vehicle interior on travel time perceptions in autonomous vehicles","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Context (archaeology); Perception; Work (physics); Value of time; Mixed logit; Preference; Travel time; Transport engineering; Logit; Mode choice; Mode (computer interface); Computer science; Arrival time; Logistic regression; Econometrics; Geography; Statistics; Psychology; Economics; Public transport; Engineering; Mathematics","score_opus":0.08723335774432711,"score_gpt":0.3879773490748581,"score_spread":0.300743991330531,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394779296","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985266,0.00003779587,0.000062385196,0.00014167634,0.0000034090847,0.000004775657,0.000051614294,9.200513e-7,0.0011706861],"genre_scores_gemma":[0.99931264,0.000055158805,0.00006610661,0.000025384388,0.0000012001118,0.0000025951529,0.00004307994,0.0000014292622,0.0004923119],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993839,0.00017667774,0.000021395803,0.000055792814,0.00015167738,0.00021046572],"domain_scores_gemma":[0.997891,0.00058357057,0.00042656634,0.00006373845,0.00041641365,0.00061863824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009163036,0.00012189868,0.0001826588,0.00028644688,0.0009854194,0.0015131738,0.00044283603,0.00033806934,0.0035487572],"category_scores_gemma":[0.0031616327,0.0001654837,0.00045385907,0.0004143177,0.0011023475,0.0005000953,0.0005164428,0.0006547446,0.00021289689],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033955238,0.0002607071,0.9305521,0.00007389181,0.00007524708,0.00024223894,0.049903885,0.00054044474,0.0013629294,0.0008430545,0.0014222028,0.014383726],"study_design_scores_gemma":[0.0000057897855,0.0000711894,0.92659557,0.00003435083,0.000015483041,0.000029881141,0.070504576,0.0008344836,0.00011591903,0.000120744146,0.0016513569,0.000020685156],"about_ca_topic_score_codex":0.786946,"about_ca_topic_score_gemma":0.9002799,"teacher_disagreement_score":0.786946,"about_ca_system_score_codex":0.00468188,"about_ca_system_score_gemma":0.0042825905,"threshold_uncertainty_score":0.42861742},"labels":[],"label_agreement":null},{"id":"W4394880263","doi":"10.7202/1110484ar","title":"Dynamiques de l’organisation collective des coursiers et des chauffeurs en Belgique.","year":2023,"lang":"fr","type":"article","venue":"Relations industrielles","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Political science","score_opus":0.03239760223131219,"score_gpt":0.2764242668970124,"score_spread":0.2440266646657002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394880263","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8960254,0.011220811,0.0031641966,0.004579126,0.00010906659,0.00003403277,0.0017463815,0.00004389065,0.08307702],"genre_scores_gemma":[0.9780146,0.0011245873,0.0009008787,0.00005750662,0.000019755254,0.000012480283,0.00038555596,0.000012079647,0.01947257],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9991773,0.00017353072,0.000017763494,0.000107157,0.00017317377,0.00035107965],"domain_scores_gemma":[0.9988569,0.0001868849,0.00033334398,0.000040970328,0.00032578828,0.00025613833],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010676043,0.00021062803,0.00016614806,0.0018970545,0.0020339352,0.0019957125,0.00025885823,0.0004069368,0.0056855674],"category_scores_gemma":[0.0015434243,0.00017292537,0.00021655356,0.0028474715,0.0015495186,0.00085659215,0.00075936987,0.00052207155,0.0004135538],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00086665497,0.00014921708,0.42754886,0.00052850816,0.00023993322,0.0016575241,0.077214524,0.008851061,0.0063707833,0.21636838,0.033188984,0.22701551],"study_design_scores_gemma":[0.000013435691,0.000038807746,0.8463073,0.0001259923,0.000028870536,0.0002797034,0.02314725,0.0013358183,0.0003424979,0.0033593122,0.12499625,0.00002477221],"about_ca_topic_score_codex":0.44528016,"about_ca_topic_score_gemma":0.54928815,"teacher_disagreement_score":0.44528016,"about_ca_system_score_codex":0.008166052,"about_ca_system_score_gemma":0.004258241,"threshold_uncertainty_score":0.8853767},"labels":[],"label_agreement":null},{"id":"W4394972221","doi":"10.3390/su16135618","title":"Synthetic Participatory Planning of Shared Automated Electric Mobility Systems","year":2024,"lang":"en","type":"preprint","venue":"Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University","funders":"","keywords":"Citizen journalism; Computer science; Business; World Wide Web","score_opus":0.022708074353059042,"score_gpt":0.29949188519352377,"score_spread":0.2767838108404647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394972221","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15769786,0.00007634548,0.82542795,0.0005157527,0.000027538159,0.00024249524,0.00019968011,0.00026658937,0.015545825],"genre_scores_gemma":[0.8231213,0.000051835832,0.17368035,0.00003903631,0.000005672931,0.00031646562,0.00017728993,0.000054761556,0.002553238],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969156,0.002253173,0.000062256404,0.00033563707,0.00028155503,0.00015180717],"domain_scores_gemma":[0.9950465,0.0038660383,0.0002248886,0.0005137146,0.00018028101,0.00016858903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032857538,0.000629141,0.00041021782,0.00042047902,0.0010137439,0.0015273954,0.0011852566,0.0011109504,0.0032118126],"category_scores_gemma":[0.0067737116,0.00040693776,0.0009367017,0.00045935932,0.0022195599,0.0013590655,0.003706297,0.000769774,0.00018848143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008261707,0.00005384472,0.0008331978,0.00008161205,0.000030847852,0.00035344742,0.0018467768,0.9202708,0.0023059738,0.06138339,0.00035340595,0.012404085],"study_design_scores_gemma":[0.000030900108,0.0000655256,0.00015485354,0.000020538944,0.000011530274,0.000034837703,0.0008752333,0.9334853,0.0017338159,0.05889171,0.004679515,0.000016272608],"about_ca_topic_score_codex":0.0050801886,"about_ca_topic_score_gemma":0.007904543,"teacher_disagreement_score":0.0050801886,"about_ca_system_score_codex":0.0016050065,"about_ca_system_score_gemma":0.0018146209,"threshold_uncertainty_score":0.0173769},"labels":[],"label_agreement":null},{"id":"W4395661441","doi":"10.2139/ssrn.4807963","title":"Optimal Ordering Policy for Perishable Products by Incorporating Demand Forecasts","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Business; Economics; Industrial organization","score_opus":0.0073309824102748096,"score_gpt":0.23768970788650556,"score_spread":0.23035872547623076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395661441","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33626953,0.0010420779,0.6333626,0.0034881595,0.0005028188,0.00024213814,0.0010757652,0.0009651414,0.023051798],"genre_scores_gemma":[0.9632456,0.000275798,0.028258217,0.00012260834,0.00010483367,0.000039250142,0.0002071149,0.00007407643,0.007672473],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934226,0.00022256069,0.00002544263,0.00014274493,0.00008966685,0.00017723723],"domain_scores_gemma":[0.9965758,0.002414164,0.00026483758,0.000109741515,0.000404056,0.00023139034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016860497,0.0010988237,0.0018549194,0.0012605325,0.0006264458,0.0028052707,0.0013413196,0.002622153,0.006113917],"category_scores_gemma":[0.0056356178,0.0012253387,0.0006663498,0.0013754155,0.0007355024,0.002815566,0.00056156813,0.0019380131,0.00070270937],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012513786,0.000048119633,0.0002621785,0.000033461187,0.00000990846,0.000036543446,0.00002016024,0.9859659,0.00051167357,0.0057028993,0.0011376634,0.006146237],"study_design_scores_gemma":[0.000008389146,0.000011319813,0.000068542315,0.0000030539009,0.0000045896804,0.0000021891829,0.000008740428,0.997071,0.00011745296,0.0025527312,0.00014715739,0.0000048050742],"about_ca_topic_score_codex":0.019884747,"about_ca_topic_score_gemma":0.016733402,"teacher_disagreement_score":0.019884747,"about_ca_system_score_codex":0.0025699171,"about_ca_system_score_gemma":0.0029337408,"threshold_uncertainty_score":0.039537966},"labels":[],"label_agreement":null},{"id":"W4395698484","doi":"10.2139/ssrn.4809477","title":"Investment and Financing of Roadway Digital Infrastructure for Automated Driving","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Stylized fact; Investment (military); Software deployment; Computer science; Budget constraint; Critical infrastructure; Transport engineering; Business; Computer security; Engineering; Economics","score_opus":0.0040604553642536205,"score_gpt":0.21968894986158347,"score_spread":0.21562849449732985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395698484","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8185085,0.0020275952,0.010355637,0.009265275,0.00015310456,0.00014361145,0.0038112593,0.00021687246,0.15551813],"genre_scores_gemma":[0.9852202,0.00056279346,0.00043468244,0.00007312657,0.000047786187,0.000022613794,0.0004612622,0.00001348081,0.013164126],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99915624,0.00018987991,0.00002672808,0.00008047731,0.00014478154,0.0004019183],"domain_scores_gemma":[0.99747026,0.00101342,0.0005498269,0.00012819988,0.00042323943,0.00041511343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009127029,0.00033227247,0.0002465366,0.0011213532,0.00040214832,0.003221025,0.00055507687,0.0016737873,0.015649715],"category_scores_gemma":[0.007023173,0.00031323306,0.0003525132,0.0011999724,0.0005685342,0.0021302132,0.0010101253,0.001156273,0.00092996296],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017087009,0.0005769102,0.12215107,0.0006308901,0.00026710637,0.0017633645,0.0006873372,0.09211258,0.004822301,0.57504183,0.03139615,0.16884173],"study_design_scores_gemma":[0.000579621,0.0012149662,0.1966646,0.00092224334,0.00093449035,0.0018657983,0.0057897493,0.21509689,0.019250266,0.2311591,0.32636744,0.00015479639],"about_ca_topic_score_codex":0.009946707,"about_ca_topic_score_gemma":0.010118221,"teacher_disagreement_score":0.015649715,"about_ca_system_score_codex":0.004209979,"about_ca_system_score_gemma":0.0034008278,"threshold_uncertainty_score":0.0523535},"labels":[],"label_agreement":null},{"id":"W4396597997","doi":"10.53555/sfs.v10i1.2670","title":"Evolution Of Client Satisfaction With Palani's Pilgrimage Bus Services","year":2023,"lang":"en","type":"article","venue":"Journal of Survey in Fisheries Sciences","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Pilgrimage; Customer satisfaction; Computer science; Business; World Wide Web; Marketing; Ancient history; History","score_opus":0.06988521549852181,"score_gpt":0.24709472170055133,"score_spread":0.17720950620202952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396597997","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998475,0.000022111235,0.000034246914,0.00013139017,0.0000020624518,0.000004452216,0.000106841166,0.000007232403,0.0012167254],"genre_scores_gemma":[0.9993137,0.000016270398,0.000025221703,0.000012251068,0.0000012375831,0.0000043314867,0.000060452963,0.0000016513317,0.00056494743],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994844,0.00012650146,0.00002477391,0.000054118627,0.00013204041,0.00017809306],"domain_scores_gemma":[0.9977888,0.00045786027,0.0004926169,0.000064542604,0.0006014022,0.00059474946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004112159,0.00012966224,0.00018089316,0.0007096954,0.0005636208,0.001197164,0.00037716067,0.000434482,0.00652605],"category_scores_gemma":[0.0032175088,0.00013092763,0.0002784615,0.0011770109,0.0003383358,0.00036841136,0.00062358263,0.0006992636,0.0009064082],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017722962,0.00017332796,0.97655666,0.000015752092,0.000021505846,0.00028968512,0.0068073412,0.00012890829,0.00038607517,0.000111344736,0.00085477735,0.014477289],"study_design_scores_gemma":[0.0000020562325,0.0001004674,0.9888398,0.0000058239057,0.0000065793847,0.00021730077,0.009764757,0.0005123395,0.00010936848,0.00002991297,0.00040329515,0.000008342391],"about_ca_topic_score_codex":0.029402459,"about_ca_topic_score_gemma":0.026073562,"teacher_disagreement_score":0.029402459,"about_ca_system_score_codex":0.001674479,"about_ca_system_score_gemma":0.0006942757,"threshold_uncertainty_score":0.05846262},"labels":[],"label_agreement":null},{"id":"W4396659094","doi":"10.1016/j.erss.2024.103558","title":"Is a robot car still a car? Consumer perceptions of fully automated vehicles and automobility in Canada","year":2024,"lang":"en","type":"article","venue":"Energy Research & Social Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Robot; Perception; Computer science; Engineering; Human–computer interaction; Transport engineering; Psychology; Artificial intelligence; Neuroscience","score_opus":0.02959751081892603,"score_gpt":0.33491618161280534,"score_spread":0.3053186707938793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396659094","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9944049,0.00010533531,0.000104390274,0.0007050505,0.000004129605,0.00000887853,0.000041496227,0.000002977647,0.0046228045],"genre_scores_gemma":[0.9986191,0.00013532229,0.0000706983,0.000079798745,7.8836564e-7,0.000003235448,0.000023530833,0.0000026349448,0.0010649051],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.9992561,0.00014931541,0.000023725876,0.0000814271,0.00024548484,0.00024399902],"domain_scores_gemma":[0.99795145,0.000495754,0.00022672437,0.00004914897,0.00079554546,0.0004813787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010358874,0.00014974456,0.00022886602,0.00044005303,0.00561562,0.0031061897,0.0007025336,0.0005913165,0.0038248363],"category_scores_gemma":[0.0028155418,0.00019948228,0.0001945974,0.0010904076,0.0035884855,0.0009400648,0.0014525398,0.0008692805,0.00013347753],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037261655,0.00013325256,0.35966247,0.00022351643,0.000043045206,0.001515445,0.5877437,0.000905049,0.0036188774,0.0072862683,0.004387248,0.034108598],"study_design_scores_gemma":[0.0000083417735,0.000071852206,0.19972172,0.00012374192,0.000021808859,0.00012546759,0.7836675,0.0009919837,0.00032956706,0.0003087372,0.014558797,0.000070405906],"about_ca_topic_score_codex":0.98649955,"about_ca_topic_score_gemma":0.9910381,"teacher_disagreement_score":0.026310975,"about_ca_system_score_codex":0.026310975,"about_ca_system_score_gemma":0.020431401,"threshold_uncertainty_score":0.19090039},"labels":[],"label_agreement":null},{"id":"W4396668190","doi":"10.1016/j.ejor.2024.04.037","title":"Dynamic rebalancing optimization for bike-sharing systems: A modeling framework and empirical comparison","year":2024,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Polytechnique Montréal; Transport Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Flexibility (engineering); Set (abstract data type); Operations research; Variety (cybernetics); Mathematical optimization; Integer programming; Interdependence; TRIPS architecture; Event (particle physics); Industrial engineering; Artificial intelligence","score_opus":0.13384685511076894,"score_gpt":0.4194569935858371,"score_spread":0.28561013847506816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396668190","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82548624,0.0029837994,0.15671396,0.0006411002,0.000048505197,0.00022474825,0.00076338724,0.00028744317,0.012850766],"genre_scores_gemma":[0.9851328,0.00062972505,0.013106822,0.000025052994,0.000011876356,0.000078310586,0.00031709013,0.000026564801,0.00067174924],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939275,0.0002800469,0.000026739914,0.00010236399,0.0000820718,0.00011606652],"domain_scores_gemma":[0.9959955,0.003060516,0.00038197063,0.00019190587,0.0002681428,0.00010195874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021389623,0.0012187684,0.00086561183,0.0010602514,0.00044206675,0.0013568676,0.001210458,0.0010374078,0.0026618517],"category_scores_gemma":[0.0045300378,0.00036794244,0.00077292445,0.0015572528,0.0004868017,0.0018506513,0.00080797233,0.0015279738,0.0002293208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054073953,0.00015293632,0.0016406836,0.00008842298,0.000022676006,0.00003571719,0.00003082634,0.9890203,0.00025956784,0.0027210924,0.00036908095,0.0056046234],"study_design_scores_gemma":[0.000003888276,0.000035323177,0.00053509884,0.000007937424,0.0000066347498,0.000007627292,0.000043173244,0.9983854,0.00009094875,0.0006959142,0.00018424615,0.0000038635762],"about_ca_topic_score_codex":0.013833433,"about_ca_topic_score_gemma":0.0080276495,"teacher_disagreement_score":0.013833433,"about_ca_system_score_codex":0.0015357675,"about_ca_system_score_gemma":0.00080862007,"threshold_uncertainty_score":0.027505815},"labels":[],"label_agreement":null},{"id":"W4396669819","doi":"10.1016/j.scs.2024.105485","title":"BM-RCWTSG: An integrated matching framework for electric vehicle ride-hailing services under stochastic guidance","year":2024,"lang":"en","type":"article","venue":"Sustainable Cities and Society","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Matching (statistics); Key (lock); Service (business); Computer science; Operations research; Idle; Electric vehicle; Probabilistic logic; Transport engineering; Engineering; Business; Computer security; Artificial intelligence; Marketing","score_opus":0.007172209278585289,"score_gpt":0.2460840028183503,"score_spread":0.23891179353976502,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396669819","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004684185,0.00006731726,0.9906935,0.00017820374,0.00004729379,0.00006720418,0.00021668756,0.00049927906,0.0035462093],"genre_scores_gemma":[0.5581968,0.0003280344,0.41725743,0.00031857862,0.00015612668,0.00036364226,0.0011396103,0.0006488779,0.021590874],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974934,0.00087993336,0.00009139886,0.00043962258,0.0005865188,0.0005092069],"domain_scores_gemma":[0.9985379,0.0005357369,0.000120443525,0.00022140073,0.00039009418,0.00019442468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035647661,0.00093407265,0.0017259497,0.0009817311,0.0008358258,0.00209979,0.0045067645,0.0024785094,0.011162309],"category_scores_gemma":[0.007113011,0.00072635704,0.0014284464,0.0016315527,0.001065295,0.0029056547,0.0040436485,0.0022525825,0.0017595206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000102530605,0.00008671687,0.0003376539,0.000050088893,0.000038088398,0.00004518216,0.000049062688,0.8187311,0.0005007944,0.14355306,0.0034966434,0.0330091],"study_design_scores_gemma":[0.000007869367,0.00001390978,0.000033219803,0.0000037985753,0.0000048606903,0.000005365644,0.00000703609,0.97738135,0.00009557186,0.021457106,0.0009853292,0.0000045896977],"about_ca_topic_score_codex":0.027323036,"about_ca_topic_score_gemma":0.016066486,"teacher_disagreement_score":0.027323036,"about_ca_system_score_codex":0.002147976,"about_ca_system_score_gemma":0.004906176,"threshold_uncertainty_score":0.054328024},"labels":[],"label_agreement":null},{"id":"W4396712067","doi":"10.2139/ssrn.4819061","title":"Models of Emerging Regulation of GHG Emissions in the Transportation-for-Hire Industry","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Greenhouse gas; Natural resource economics; Business; Industrial organization; Economics; Environmental economics","score_opus":0.01658601133042275,"score_gpt":0.2640335120640756,"score_spread":0.24744750073365285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396712067","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27656406,0.0037164965,0.33385858,0.026178848,0.0006923975,0.00016306386,0.0029056016,0.0006019671,0.35531902],"genre_scores_gemma":[0.9405509,0.0012313797,0.00456623,0.0004791459,0.00013476468,0.00010533628,0.00027678141,0.0000704495,0.052584995],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922204,0.00027599477,0.00002423644,0.0001648045,0.00009751222,0.00021541119],"domain_scores_gemma":[0.99802846,0.0011771917,0.00024622786,0.000116041134,0.00023309185,0.00019894325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014260848,0.0008251718,0.0014999177,0.0007163095,0.0009866975,0.0039722077,0.0034525357,0.0048994436,0.019212678],"category_scores_gemma":[0.0040727076,0.00064776366,0.0017831976,0.0009134319,0.0022654955,0.0034696057,0.0013980969,0.002800569,0.0011970442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057619614,0.00005357596,0.00040222192,0.000056603363,0.000027277421,0.00010512938,0.000075441036,0.32735544,0.0004063479,0.6657954,0.0035415739,0.0021233205],"study_design_scores_gemma":[0.00008453729,0.000035112636,0.00043208935,0.000027744773,0.0000233515,0.000029116172,0.00010732863,0.570869,0.00013140951,0.4249487,0.0032811426,0.000030437572],"about_ca_topic_score_codex":0.025141748,"about_ca_topic_score_gemma":0.017077921,"teacher_disagreement_score":0.025141748,"about_ca_system_score_codex":0.003916393,"about_ca_system_score_gemma":0.0023250068,"threshold_uncertainty_score":0.06427288},"labels":[],"label_agreement":null},{"id":"W4396805574","doi":"10.1007/s11116-024-10484-7","title":"Design of the “Future Mobility in Canada Survey” (FMCS) to assess the evolving mobility landscape in urban Canada with an emphasis on automated vehicles","year":2024,"lang":"en","type":"article","venue":"Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University; McMaster University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Emphasis (telecommunications); Transport engineering; Regional science; Travel behavior; Urban landscape; Geography; Economic geography; Computer science; Environmental planning; Engineering; Telecommunications","score_opus":0.016784792704485917,"score_gpt":0.22860599155051664,"score_spread":0.21182119884603073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396805574","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.65134335,0.00046520226,0.028743053,0.0018258543,0.00039529856,0.18127106,0.09855767,0.0004507312,0.0369478],"genre_scores_gemma":[0.60069764,0.00057871325,0.09115675,0.0021998486,0.000099405515,0.23003538,0.05189815,0.00017407039,0.023160059],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9942688,0.0018471555,0.00027183176,0.000660756,0.0013289447,0.0016226486],"domain_scores_gemma":[0.99019545,0.00065272383,0.0008072079,0.00027538207,0.0071181688,0.0009510676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007387798,0.001310391,0.000897575,0.0026691114,0.0038605754,0.0023988525,0.0022872973,0.00089134916,0.0062253857],"category_scores_gemma":[0.010150199,0.0008044005,0.0017194934,0.004407702,0.0012415237,0.0006785522,0.0021335778,0.001158681,0.0009708692],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032692628,0.0043508024,0.7329713,0.0010975752,0.0007588205,0.0005808222,0.0055478336,0.02856632,0.0035753723,0.016033117,0.07052768,0.13272113],"study_design_scores_gemma":[0.0012028865,0.0030760842,0.85633445,0.00044898156,0.0004838771,0.00006999281,0.016048832,0.02832179,0.0026417219,0.0019894415,0.089118764,0.00026305407],"about_ca_topic_score_codex":0.975469,"about_ca_topic_score_gemma":0.9839167,"teacher_disagreement_score":0.052055754,"about_ca_system_score_codex":0.052055754,"about_ca_system_score_gemma":0.14049087,"threshold_uncertainty_score":0.3776927},"labels":[],"label_agreement":null},{"id":"W4396807394","doi":"10.1016/j.ejor.2024.05.008","title":"The future of transport: Coordination in a new field between public and private transport","year":2024,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Public transport; Field (mathematics); Business; Industrial organization; Transport engineering; Engineering; Mathematics","score_opus":0.052208767578920005,"score_gpt":0.3252113714085458,"score_spread":0.27300260382962577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396807394","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045893513,0.038843963,0.09039244,0.4934336,0.0057622464,0.00008409178,0.00026818254,0.00019979216,0.32512212],"genre_scores_gemma":[0.9410396,0.017169029,0.011790927,0.0070961243,0.0031099722,0.0001352659,0.00013046847,0.00011216878,0.019416373],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9963775,0.0017441374,0.00011390929,0.00041293728,0.00069475314,0.0006567843],"domain_scores_gemma":[0.99376774,0.0020737608,0.0006477194,0.00056985824,0.0011718621,0.0017689847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007644072,0.0004911979,0.0007060065,0.0012043363,0.0045105163,0.020768195,0.0016647379,0.007072483,0.012741697],"category_scores_gemma":[0.0066154865,0.0004168659,0.00061393454,0.0024247216,0.012718702,0.034329038,0.0062123276,0.005036405,0.0012711781],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006996398,0.000035810455,0.0006586692,0.000092177885,0.000013101375,0.000075900505,0.002288487,0.0017289264,0.00021945269,0.960269,0.013069666,0.021478854],"study_design_scores_gemma":[0.000026866095,0.00004338067,0.0011136681,0.00031308612,0.000014919673,0.000094622155,0.008354153,0.003561541,0.00014446494,0.7712113,0.21508543,0.000036560232],"about_ca_topic_score_codex":0.008184991,"about_ca_topic_score_gemma":0.0064568785,"teacher_disagreement_score":0.020768195,"about_ca_system_score_codex":0.008786307,"about_ca_system_score_gemma":0.016200235,"threshold_uncertainty_score":0.06374943},"labels":[],"label_agreement":null},{"id":"W4396827216","doi":"10.1145/3613905.3650776","title":"Podscape: Exploring the Comfort Level with Pods in Pedestrian Spaces through Immersive Simulation","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Pedestrian; Virtual reality; Computer science; Human–computer interaction; Space (punctuation); Psychology; Simulation; Architectural engineering; Engineering; Transport engineering","score_opus":0.09501877424014743,"score_gpt":0.28638551802185364,"score_spread":0.1913667437817062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396827216","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97173506,0.0000959706,0.023256084,0.00006462953,0.000030613,0.00013263384,0.0004118616,0.00028575782,0.0039874897],"genre_scores_gemma":[0.97510976,0.00011632908,0.02312558,0.000034291155,0.0000076233196,0.00015372466,0.00030354285,0.000040412986,0.0011087001],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998066,0.00008442216,0.000007781805,0.00003156976,0.000032208944,0.000037474438],"domain_scores_gemma":[0.9996051,0.00021875417,0.0000234885,0.000043363892,0.00003791327,0.00007143105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004121574,0.0005819968,0.000304178,0.0003388602,0.00031615346,0.0011870249,0.00055375975,0.00052211486,0.003471103],"category_scores_gemma":[0.0011812825,0.00025208984,0.0006782137,0.00021582222,0.0005167848,0.00067313213,0.0014723614,0.0004778477,0.00030467604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005382462,0.00931948,0.1760347,0.0039763916,0.0007842064,0.0041867513,0.0940026,0.20342663,0.24877517,0.014781891,0.012293065,0.22703671],"study_design_scores_gemma":[0.0008857903,0.009860561,0.20043373,0.0007099228,0.0006746975,0.0019087199,0.03708655,0.64425695,0.053999197,0.010474843,0.039138373,0.000570649],"about_ca_topic_score_codex":0.0025317904,"about_ca_topic_score_gemma":0.005780633,"teacher_disagreement_score":0.003471103,"about_ca_system_score_codex":0.00019892368,"about_ca_system_score_gemma":0.00033157057,"threshold_uncertainty_score":0.011611998},"labels":[],"label_agreement":null},{"id":"W4396900408","doi":"10.1080/21650020.2024.2354400","title":"The urban motorcycle taxi sector in Sub-Saharan Africa: needs, practices and equity issues","year":2024,"lang":"en","type":"article","venue":"Urban Planning and Transport Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Volvo Research and Educational Foundations","keywords":"Taxis; Equity (law); Business; Sustainable transport; Economic growth; Private sector; Quarter (Canadian coin); Transport engineering; Geography; Sustainability; Political science; Engineering; Economics","score_opus":0.1086225046589079,"score_gpt":0.37752911320997873,"score_spread":0.26890660855107085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396900408","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9528886,0.0062372037,0.00042682694,0.02576294,0.000057971698,0.000058542388,0.00010982604,0.0000065292343,0.014451624],"genre_scores_gemma":[0.99299765,0.005074067,0.0002493664,0.0006117563,0.00002197927,0.000033890883,0.00001981804,0.0000023878654,0.0009889869],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9984176,0.0006294829,0.00006033031,0.000060698156,0.00014784261,0.0006840458],"domain_scores_gemma":[0.9981306,0.0007688752,0.00039374892,0.00003831598,0.00028310678,0.00038538445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018807898,0.00022462274,0.00018906045,0.0009648325,0.0028196054,0.0027927177,0.00061356253,0.0007820652,0.0045929393],"category_scores_gemma":[0.004606497,0.00020762044,0.000105663676,0.0023139392,0.0018296839,0.0031839255,0.0018643688,0.00068488927,0.00025281025],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007804628,0.00025375097,0.23863384,0.002136977,0.000047409387,0.0049660644,0.47460064,0.00045727738,0.0015128601,0.029842278,0.0068047186,0.24066617],"study_design_scores_gemma":[0.000005005676,0.00007622725,0.08635814,0.0014901048,0.00001648552,0.0007647289,0.87788683,0.00021682613,0.0002176924,0.0027898862,0.030161297,0.000016714128],"about_ca_topic_score_codex":0.031550806,"about_ca_topic_score_gemma":0.048814543,"teacher_disagreement_score":0.031550806,"about_ca_system_score_codex":0.0020616455,"about_ca_system_score_gemma":0.005363469,"threshold_uncertainty_score":0.062734306},"labels":[],"label_agreement":null},{"id":"W4396997801","doi":"10.1016/j.tra.2024.104090","title":"Modeling impacts of freight automated vehicles in the Greater Toronto and Hamilton Area","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Transport engineering; Computer science; Regional science; Engineering; Geography","score_opus":0.0999787583017147,"score_gpt":0.4069030017645665,"score_spread":0.3069242434628518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396997801","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9855906,0.0000918765,0.0015200065,0.0002429854,0.0000105586005,0.000057841648,0.0005686418,0.000029971474,0.011887583],"genre_scores_gemma":[0.9967438,0.00010588769,0.0005199965,0.000017412693,0.0000023415312,0.000018019895,0.00019307256,0.0000073361616,0.0023921311],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966383,0.00007532807,0.0000066712755,0.000048617974,0.00004733998,0.00015830218],"domain_scores_gemma":[0.9995882,0.00012914614,0.00004928106,0.000016598617,0.000141476,0.000075325246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024978514,0.0007122366,0.00022639228,0.00050570525,0.0010575413,0.0013761466,0.0011324029,0.00084944756,0.0024836373],"category_scores_gemma":[0.00071296626,0.00034088336,0.0005553582,0.00078055676,0.0010415943,0.00074639946,0.00074392505,0.0005535421,0.00012183046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058196572,0.000054717457,0.014002969,0.000019237681,0.000024431869,0.00018436965,0.00012248365,0.98033303,0.0007245423,0.0022968282,0.0006458459,0.0015333551],"study_design_scores_gemma":[0.000033718687,0.00007635226,0.016351657,0.00001423246,0.00003909329,0.000021424561,0.00095333764,0.97984993,0.0005778261,0.0006088951,0.0014481435,0.00002531021],"about_ca_topic_score_codex":0.9570829,"about_ca_topic_score_gemma":0.95367706,"teacher_disagreement_score":0.9761695,"about_ca_system_score_codex":0.02383047,"about_ca_system_score_gemma":0.007402212,"threshold_uncertainty_score":0.172903},"labels":[],"label_agreement":null},{"id":"W4398134819","doi":"10.1177/03611981241239970","title":"Innovative On-Demand Transit for First-Mile Trips: A Cutting-Edge Approach","year":2024,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University","funders":"","keywords":"TRIPS architecture; Mile; Transport engineering; Transit (satellite); Last mile (transportation); Enhanced Data Rates for GSM Evolution; Travel behavior; Engineering; Transit system; Business; Public transport; Computer science; Geography; Telecommunications","score_opus":0.09826938492841121,"score_gpt":0.3739636577911235,"score_spread":0.2756942728627123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398134819","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08696701,0.0019227362,0.81660753,0.0014596545,0.00042717083,0.00044550802,0.00031826575,0.00074311654,0.09110909],"genre_scores_gemma":[0.7761525,0.002056044,0.19985247,0.00044160715,0.00016933432,0.00015477053,0.00093467865,0.00015581075,0.020082818],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995425,0.00009169937,0.0000111515665,0.000077732264,0.00015241666,0.00012448843],"domain_scores_gemma":[0.9996222,0.000055668603,0.000024032512,0.00005561294,0.00017674314,0.000065658925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004228798,0.0008588012,0.00061826425,0.0010394328,0.00076161104,0.0016569172,0.0023051647,0.0012110013,0.0057555456],"category_scores_gemma":[0.00055147085,0.00026894375,0.0007902526,0.0010051228,0.00038241417,0.0015376931,0.0016823098,0.0008305344,0.0011203998],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004056893,0.0008097858,0.0037697416,0.00072620716,0.00012534656,0.0010149857,0.0003900613,0.31528398,0.027537871,0.12009121,0.015023288,0.5148218],"study_design_scores_gemma":[0.0000316332,0.00043750025,0.0013427042,0.00008213591,0.00008819574,0.0006708423,0.00055870216,0.9300265,0.00460625,0.02443873,0.037679426,0.00003745053],"about_ca_topic_score_codex":0.0049791127,"about_ca_topic_score_gemma":0.007225584,"teacher_disagreement_score":0.0057555456,"about_ca_system_score_codex":0.0010483584,"about_ca_system_score_gemma":0.0012850887,"threshold_uncertainty_score":0.019254208},"labels":[],"label_agreement":null},{"id":"W4398474937","doi":"10.7910/dvn/gl5ccd/6zpcgs","title":"5_cross_iv.do","year":2018,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Statistics Canada; Université du Québec à Montréal","funders":"","keywords":"Replication (statistics); Computer science; Biology; Virology","score_opus":0.012454170679821007,"score_gpt":0.23663102480669093,"score_spread":0.2241768541268699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398474937","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00022324092,0.00012455684,0.000112685375,0.00016172389,0.00008752126,0.000012865471,0.99659556,0.0011557654,0.0015260434],"genre_scores_gemma":[0.00054042897,0.00006255844,0.00022956131,0.000073155185,0.000020805828,0.0000496679,0.9977831,0.00016457155,0.0010762216],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99852693,0.00033267215,0.0001106306,0.00045860052,0.0002493627,0.00032186913],"domain_scores_gemma":[0.99759644,0.00054338394,0.0001956006,0.0008565126,0.00046495668,0.00034305573],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0015887409,0.0036555056,0.0018355385,0.0051751565,0.001410143,0.0045617553,0.004534829,0.0029771945,0.1335578],"category_scores_gemma":[0.007890507,0.0008288907,0.0021693676,0.0062207296,0.0008262501,0.00252545,0.0038271695,0.0024849866,0.22102988],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032524214,0.000018334398,0.00058803847,0.0002489269,0.000023337832,0.000010935854,0.000015683183,0.00015952287,0.0000341018,0.00033679325,0.9971204,0.001411404],"study_design_scores_gemma":[0.00024832215,0.000031156065,0.002853252,0.00034138825,0.000039788225,0.000068479414,0.000119489916,0.00083000085,0.00033913495,0.0018318414,0.9932608,0.0000364375],"about_ca_topic_score_codex":0.020979695,"about_ca_topic_score_gemma":0.037394773,"teacher_disagreement_score":0.8664422,"about_ca_system_score_codex":0.0014518477,"about_ca_system_score_gemma":0.002022519,"threshold_uncertainty_score":0.44679534},"labels":[],"label_agreement":null},{"id":"W4399058486","doi":"10.1007/978-3-031-60597-0_2","title":"A Constraint Programming Model for the Electric Bus Assignment Problem with Parking Constraints","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal; Polytechnique Montréal","funders":"","keywords":"Computer science; Constraint programming; Constraint (computer-aided design); Mathematical optimization; Operations research; Stochastic programming; Mathematics","score_opus":0.017509549209417007,"score_gpt":0.23010401161395375,"score_spread":0.21259446240453675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399058486","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0073356205,0.0007513028,0.9533936,0.0013043727,0.00015395173,0.00018745422,0.0019144999,0.000321491,0.034637786],"genre_scores_gemma":[0.26575708,0.0029164904,0.66779745,0.0008803125,0.00032216604,0.0010973255,0.0038926725,0.00038108026,0.056955364],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990859,0.00029232513,0.000051614745,0.00020612119,0.00023502093,0.00012907939],"domain_scores_gemma":[0.99908483,0.000592215,0.00007909835,0.0000477123,0.00014132522,0.000054745844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008814596,0.0012246531,0.0010388087,0.000789977,0.0008522816,0.0030161622,0.0027260156,0.0020982977,0.013243905],"category_scores_gemma":[0.002251993,0.0009853475,0.0016849731,0.0031018208,0.0008226309,0.0024239132,0.0012506685,0.0025725537,0.0019831907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006668201,0.00011285719,0.00018263249,0.00017798887,0.000037226575,0.00039013915,0.00009378504,0.7457045,0.0013500792,0.21621604,0.010733632,0.024934502],"study_design_scores_gemma":[0.000049900136,0.000035642977,0.000103953906,0.00004555269,0.000023657138,0.00013855241,0.000053136857,0.8953385,0.0004071439,0.08759145,0.016185217,0.000027332044],"about_ca_topic_score_codex":0.019283492,"about_ca_topic_score_gemma":0.020617416,"teacher_disagreement_score":0.019283492,"about_ca_system_score_codex":0.0017200747,"about_ca_system_score_gemma":0.0026817152,"threshold_uncertainty_score":0.044305325},"labels":[],"label_agreement":null},{"id":"W4399058564","doi":"10.1007/978-3-031-60597-0_1","title":"Online Optimization of a Dial-a-Ride Problem with the Integral Primal Simplex","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Computer science; Simplex; Simplex algorithm; Dial; Mathematical optimization; Algorithm; Linear programming; Mathematics; Electrical engineering; Combinatorics; Engineering","score_opus":0.01076557083709737,"score_gpt":0.22360696648500933,"score_spread":0.21284139564791196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399058564","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01919891,0.0008270659,0.95534265,0.00066856353,0.00024171769,0.00010900993,0.00022314161,0.0003628868,0.02302605],"genre_scores_gemma":[0.55334014,0.0008620321,0.41539025,0.00036831034,0.00027102523,0.00046365467,0.0005052636,0.00065005216,0.028149145],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990804,0.00040101603,0.00003128552,0.0001868189,0.00016163805,0.00013874122],"domain_scores_gemma":[0.9972958,0.0020517951,0.00010392331,0.00018676624,0.00017652882,0.00018521934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021084775,0.0013709976,0.0035469986,0.0007781097,0.00080590544,0.0032542075,0.002478683,0.0031873188,0.015260462],"category_scores_gemma":[0.007314381,0.0013219486,0.0012098409,0.0011880996,0.0016218201,0.0034802791,0.0032139625,0.0037235445,0.001439156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031490956,0.00024596293,0.0003269332,0.0002580279,0.0000593724,0.0001228629,0.000077125114,0.8685233,0.00060499005,0.079949774,0.008667388,0.040849272],"study_design_scores_gemma":[0.0000250475,0.00003550129,0.000035648292,0.00001828684,0.0000074231443,0.00001610659,0.000015099201,0.98034656,0.0001110896,0.01848298,0.00090002106,0.0000062276436],"about_ca_topic_score_codex":0.0043345755,"about_ca_topic_score_gemma":0.0037065132,"teacher_disagreement_score":0.015260462,"about_ca_system_score_codex":0.0013608516,"about_ca_system_score_gemma":0.0020520212,"threshold_uncertainty_score":0.05105132},"labels":[],"label_agreement":null},{"id":"W4399120146","doi":"10.1109/drcn60692.2024.10539171","title":"BNART: A Novel Centralized Traffic Management Approach for Autonomous Vehicles","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Lakehead University; Wilfrid Laurier University","funders":"","keywords":"Computer science; Heuristic; Integer programming; Traffic congestion; Metropolitan area; Shortest path problem; Path (computing); Routing (electronic design automation); Distributed computing; Operations research; Mathematical optimization; Transport engineering; Computer network; Artificial intelligence; Engineering; Graph; Algorithm","score_opus":0.017869260913904318,"score_gpt":0.23426674122559774,"score_spread":0.21639748031169342,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399120146","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019140145,0.00024891848,0.9731916,0.00016789793,0.00011370926,0.000109018874,0.00012469811,0.0011972069,0.005706842],"genre_scores_gemma":[0.54364353,0.00028661895,0.44810945,0.00013484193,0.00011384626,0.0002532635,0.00050271966,0.00024838344,0.0067073735],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999469,0.00011812288,0.000017716158,0.00014180735,0.00015141307,0.00010192884],"domain_scores_gemma":[0.9995833,0.00012282518,0.00006565224,0.00005223377,0.00011366473,0.000062284795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007654889,0.0008925727,0.0010882999,0.0008827413,0.001016845,0.001256931,0.0024802808,0.00094389525,0.0025911618],"category_scores_gemma":[0.0011204707,0.0004034544,0.0006255607,0.0009780485,0.0005155226,0.0011445654,0.000996575,0.0006552425,0.0005652539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006810836,0.000099299345,0.00053689623,0.00007352207,0.000030331006,0.00007275052,0.00005655947,0.8997356,0.0022614333,0.013741234,0.004232915,0.07909132],"study_design_scores_gemma":[0.000006434523,0.000020331867,0.00004014469,0.0000022674258,0.0000050911176,0.000015202181,0.000013032625,0.99715436,0.00024352735,0.0014175655,0.001077972,0.0000041245876],"about_ca_topic_score_codex":0.012400031,"about_ca_topic_score_gemma":0.016355932,"teacher_disagreement_score":0.012400031,"about_ca_system_score_codex":0.0011109271,"about_ca_system_score_gemma":0.0023049135,"threshold_uncertainty_score":0.0246557},"labels":[],"label_agreement":null},{"id":"W4399391125","doi":"10.1287/opre.2021.0062","title":"Dynamic Relocations in Car-Sharing Networks","year":2024,"lang":"en","type":"article","venue":"Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Windsor","funders":"","keywords":"Computer science; Car sharing; Operations research; Computer network; Transport engineering; Mathematics; Engineering","score_opus":0.043911093766056744,"score_gpt":0.3757931439051127,"score_spread":0.331882050139056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399391125","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18692403,0.00065770163,0.8034473,0.00080807274,0.00015260975,0.0000716657,0.000108136155,0.00027784682,0.0075525623],"genre_scores_gemma":[0.9806732,0.00023688727,0.016079025,0.00007430227,0.000018900504,0.00003543534,0.00004929511,0.000031699696,0.002801114],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929225,0.00024736323,0.000016886548,0.00015617826,0.000093126146,0.00019413097],"domain_scores_gemma":[0.9993124,0.00036400658,0.00009458916,0.000049442846,0.00009586492,0.00008368029],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007391432,0.0006737364,0.00076814723,0.0003554864,0.0007518543,0.00092829246,0.0012006412,0.0007088198,0.0027092013],"category_scores_gemma":[0.0021125146,0.00040595207,0.00063613575,0.0006038328,0.0011902982,0.0020906567,0.0015742201,0.000856806,0.000172129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057005902,0.000024623801,0.00036377172,0.000029480418,0.000015429505,0.00005643195,0.00005424989,0.9698374,0.0008202965,0.019664634,0.00055610004,0.008520621],"study_design_scores_gemma":[0.0000070719802,0.000038872528,0.00011480758,0.00000460359,0.0000070334872,0.00002827484,0.000080886224,0.984539,0.0004959926,0.013402483,0.0012700446,0.000010880295],"about_ca_topic_score_codex":0.0077882856,"about_ca_topic_score_gemma":0.0056551364,"teacher_disagreement_score":0.0077882856,"about_ca_system_score_codex":0.0014097838,"about_ca_system_score_gemma":0.0009850599,"threshold_uncertainty_score":0.015485942},"labels":[],"label_agreement":null},{"id":"W4399398502","doi":"10.46254/an14.20240176","title":"Freight Broker Business Models in the Digital Age: A Comparative Analysis and Recommendations for Start-ups","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Start up; Business; Business administration","score_opus":0.05062033974493139,"score_gpt":0.28925861666834835,"score_spread":0.23863827692341696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399398502","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7095546,0.100075394,0.008568383,0.031043923,0.0004214064,0.00029979768,0.00039166526,0.0000887565,0.14955606],"genre_scores_gemma":[0.9491363,0.04125363,0.0033599997,0.00050448277,0.00008315654,0.00004676664,0.00022867779,0.000016874214,0.005370089],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99894625,0.00042570694,0.00005105826,0.00009503599,0.0002364691,0.0002454476],"domain_scores_gemma":[0.99568367,0.0024812194,0.00048631625,0.000120610486,0.00081165676,0.00041652724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025834132,0.00033571414,0.0003191905,0.004689096,0.0014364313,0.0064576343,0.0006738244,0.0010593034,0.00818633],"category_scores_gemma":[0.0054961746,0.00016292132,0.00072279543,0.0057558813,0.0011502731,0.011272694,0.0012154869,0.00094502507,0.0009501431],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040372188,0.0006806414,0.12632824,0.0016308394,0.00011645479,0.0026293283,0.025529154,0.0021325706,0.0006436395,0.49582532,0.021157602,0.3229225],"study_design_scores_gemma":[0.00007673889,0.00057903654,0.17828634,0.0054730014,0.0004623457,0.0017921994,0.30458874,0.020661106,0.0012503684,0.07109143,0.41559443,0.00014431943],"about_ca_topic_score_codex":0.009830014,"about_ca_topic_score_gemma":0.01234075,"teacher_disagreement_score":0.009830014,"about_ca_system_score_codex":0.0060695973,"about_ca_system_score_gemma":0.0025737614,"threshold_uncertainty_score":0.044038236},"labels":[],"label_agreement":null},{"id":"W4399400291","doi":"10.1109/tiv.2024.3409468","title":"Car-Following Models: A Multidisciplinary Review","year":2024,"lang":"en","type":"review","venue":"IEEE Transactions on Intelligent Vehicles","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"U.S. Department of Homeland Security; National Science Foundation","keywords":"Multidisciplinary approach; Psychology; Sociology; Social science","score_opus":0.08055116983468454,"score_gpt":0.33946614836292005,"score_spread":0.25891497852823553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399400291","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00069532444,0.9895489,0.005127219,0.00062169734,0.00031564015,0.000015895535,0.00012008304,0.000047525005,0.0035076912],"genre_scores_gemma":[0.007092725,0.98937196,0.0017369679,0.00018652318,0.00026294627,0.00002053453,0.00018824766,0.000013560566,0.0011265894],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997224,0.000046547342,0.000034469962,0.00007674981,0.00009899312,0.000020751866],"domain_scores_gemma":[0.9991221,0.000546229,0.00007854016,0.00003317373,0.00019374191,0.000026271327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007585627,0.0013759256,0.0014633037,0.001961471,0.0003437159,0.0015952376,0.0018175382,0.0014789278,0.0041455487],"category_scores_gemma":[0.0021142613,0.0005757457,0.0010174487,0.0025701798,0.000503326,0.0023107743,0.00069437793,0.0012523977,0.002108017],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061438914,0.0001289171,0.0012799238,0.027821383,0.0002628685,0.00018971138,0.0001649702,0.024318138,0.0010505803,0.046113715,0.03916575,0.85944253],"study_design_scores_gemma":[0.000013809406,0.00013124397,0.0015789121,0.009629745,0.00046428348,0.000738814,0.00021709742,0.0145820165,0.000998712,0.027198909,0.944332,0.0001142586],"about_ca_topic_score_codex":0.0043154275,"about_ca_topic_score_gemma":0.00341813,"teacher_disagreement_score":0.0043154275,"about_ca_system_score_codex":0.0008617928,"about_ca_system_score_gemma":0.0018434303,"threshold_uncertainty_score":0.013868272},"labels":[],"label_agreement":null},{"id":"W4399429607","doi":"10.1016/j.trd.2024.104268","title":"Autonomous vehicle impacts on airport leakage with demand forecasting and environment implications","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Leakage (economics); Environmental science; Business; Computer science; Automotive engineering; Engineering; Economics","score_opus":0.048734704512814433,"score_gpt":0.2720170505393791,"score_spread":0.22328234602656466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399429607","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99600214,0.00005522995,0.0009580106,0.0001773029,0.000021581156,0.000011269439,0.00039215083,0.000024059062,0.0023583113],"genre_scores_gemma":[0.99897027,0.000028977352,0.00023075203,0.000010859421,0.0000036206304,0.000003199818,0.00019311154,0.0000058331207,0.0005535448],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992931,0.00028254776,0.000034263303,0.00009963686,0.0001253454,0.00016507953],"domain_scores_gemma":[0.9959409,0.0024175467,0.00040239087,0.0002133211,0.00089516945,0.00013067208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010437847,0.00040309862,0.0002817073,0.0004256851,0.00036114408,0.0014701434,0.00041141923,0.0008542752,0.0035428589],"category_scores_gemma":[0.0044406448,0.00030828457,0.0008343263,0.0009782023,0.0003670368,0.0018023881,0.0006115731,0.0005980312,0.00034100315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020935314,0.00070577214,0.26311737,0.00012827154,0.0002472797,0.0007026282,0.0002524448,0.69811916,0.005374883,0.0025436915,0.0019021125,0.024812924],"study_design_scores_gemma":[0.000058085072,0.0007776375,0.28755537,0.00003254321,0.00022154761,0.00012776942,0.0019713042,0.69554687,0.007307166,0.004424821,0.0018869364,0.00009001112],"about_ca_topic_score_codex":0.032882076,"about_ca_topic_score_gemma":0.023756173,"teacher_disagreement_score":0.032882076,"about_ca_system_score_codex":0.0012331611,"about_ca_system_score_gemma":0.0010497925,"threshold_uncertainty_score":0.06538135},"labels":[],"label_agreement":null},{"id":"W4399452577","doi":"10.2139/ssrn.4855350","title":"Analyzing the Influence of Transit Pass Ownership on Ride-Sourcing Frequency in Metro Vancouver: Implications for Policy and Urban Mobility Planning","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Transit (satellite); Business; Transport engineering; Urban transit; Transport policy; Environmental planning; Public transport; Geography; Engineering","score_opus":0.014107455339089804,"score_gpt":0.27458066750733273,"score_spread":0.26047321216824293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399452577","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977719,0.00007895914,0.00008446822,0.00020316396,0.0000021232838,0.00000639531,0.00025566568,0.000002514064,0.0015947212],"genre_scores_gemma":[0.9978358,0.00008394224,0.000047813755,0.00001584696,0.0000030289505,0.000004002793,0.00014617089,0.0000032704008,0.0018602171],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99907994,0.00025773575,0.000033004453,0.00009866362,0.00013870715,0.0003919337],"domain_scores_gemma":[0.992769,0.0034700804,0.00095220725,0.00024783352,0.0012788365,0.0012820761],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092423277,0.00019838876,0.00035470133,0.0008180014,0.0011653934,0.0028624118,0.0008346837,0.0006728717,0.0058254222],"category_scores_gemma":[0.00850475,0.00027068733,0.00035645423,0.0020786764,0.0008718113,0.00073729263,0.0010343381,0.0011183971,0.00042815637],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025778663,0.00012573824,0.9870194,0.000023614026,0.000102402344,0.00021169102,0.0013246251,0.002537353,0.0004895785,0.001109014,0.00059871573,0.006200097],"study_design_scores_gemma":[0.000016195369,0.00007362956,0.9771178,0.00002672412,0.00011939559,0.00004489007,0.012894589,0.0074735167,0.00032471248,0.00050401496,0.001388892,0.000015519156],"about_ca_topic_score_codex":0.88627315,"about_ca_topic_score_gemma":0.94071937,"teacher_disagreement_score":0.113726854,"about_ca_system_score_codex":0.005994048,"about_ca_system_score_gemma":0.006574728,"threshold_uncertainty_score":0.2287932},"labels":[],"label_agreement":null},{"id":"W4399460405","doi":"10.1080/15568318.2024.2363203","title":"Examining ride sourcing services as an emerging mode in Metro Vancouver: Insights into trip characteristics and impacts on multimodal competitions","year":2024,"lang":"en","type":"article","venue":"International Journal of Sustainable Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mode choice; Business; Transport engineering; Mode (computer interface); Marketing; Public transport; Engineering; Computer science","score_opus":0.008302975452092055,"score_gpt":0.2688479934357601,"score_spread":0.260545017983668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399460405","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99895203,0.000022747488,0.000049047398,0.000024361403,5.759933e-7,0.000011134642,0.00011975173,8.2772186e-7,0.0008194952],"genre_scores_gemma":[0.99843377,0.00007395215,0.00016488017,0.000014081909,0.0000010498326,0.000016819347,0.00022881698,0.0000023286582,0.0010642095],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99956506,0.00012489784,0.000017049862,0.00005816953,0.00009564749,0.00013907684],"domain_scores_gemma":[0.99832386,0.0004300033,0.00027634163,0.00006223557,0.0005547938,0.00035275336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005444626,0.00024892474,0.00029177536,0.0009079458,0.0012795744,0.0018167347,0.0005807987,0.00039749837,0.0025918866],"category_scores_gemma":[0.002596044,0.00019943721,0.000290305,0.0023990748,0.0004977332,0.0004916792,0.0010252695,0.0005594597,0.00030825782],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010648048,0.00022119247,0.9789781,0.00005039995,0.000042232394,0.00027555926,0.007178186,0.00067108835,0.00082248874,0.00021897063,0.0003697927,0.011065453],"study_design_scores_gemma":[0.0000040956706,0.000093168506,0.95913386,0.000027381278,0.000018437244,0.00007935891,0.03723611,0.0021943161,0.0001314369,0.00008071749,0.0009856321,0.00001541577],"about_ca_topic_score_codex":0.77270716,"about_ca_topic_score_gemma":0.90903777,"teacher_disagreement_score":0.22729284,"about_ca_system_score_codex":0.0034387673,"about_ca_system_score_gemma":0.0038169317,"threshold_uncertainty_score":0.4572628},"labels":[],"label_agreement":null},{"id":"W4399728952","doi":"10.1109/syscon61195.2024.10553563","title":"Optimal Path Generation and Real-time Scheduling for Autonomous Mobile Platforms","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Korea Institute of Industrial Technology","keywords":"Computer science; Scheduling (production processes); Distributed computing; Real-time computing; Path (computing); Computer network; Mathematical optimization","score_opus":0.013734617106094868,"score_gpt":0.24236004133378222,"score_spread":0.22862542422768736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399728952","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042114817,0.00024216618,0.9543227,0.000095199546,0.000026462041,0.00005216833,0.00006072844,0.00049303623,0.00259275],"genre_scores_gemma":[0.6628038,0.000269875,0.33396575,0.00003259857,0.000019075023,0.00015886404,0.00023804158,0.00009565933,0.0024164356],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998017,0.000052229883,0.0000067342103,0.000049676295,0.000051311385,0.00003821883],"domain_scores_gemma":[0.99975497,0.00010055225,0.000051200965,0.000026895847,0.000047339065,0.00001900351],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027879464,0.00062654045,0.00044049145,0.00061657565,0.00048494543,0.0005255683,0.00065915496,0.00048653843,0.0014669537],"category_scores_gemma":[0.00084124756,0.00036913296,0.0004184852,0.0006270482,0.0004310875,0.0005498438,0.0004339131,0.00045425142,0.00029418792],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029778357,0.000019096718,0.0003243869,0.000034739274,0.000011433836,0.000028955803,0.000044121516,0.9630026,0.0020139334,0.0042866203,0.00047329496,0.02973098],"study_design_scores_gemma":[0.000004089069,0.00001659208,0.00010333612,0.0000020823231,0.000002400225,0.00000860808,0.000016408914,0.9965205,0.0005759379,0.0021663858,0.0005807003,0.00000296632],"about_ca_topic_score_codex":0.00835423,"about_ca_topic_score_gemma":0.0081796115,"teacher_disagreement_score":0.00835423,"about_ca_system_score_codex":0.0008335805,"about_ca_system_score_gemma":0.0016788698,"threshold_uncertainty_score":0.016611159},"labels":[],"label_agreement":null},{"id":"W4399751143","doi":"10.1007/978-3-031-53594-9_12","title":"The New Kids on the Street: Ride-Hailing Platform Drivers Competing with Informal Motorbike-Taxi Livelihoods in Hanoi, Vietnam","year":2024,"lang":"en","type":"book-chapter","venue":"Economic geography","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Livelihood; Business; Geography; Economic growth; Economics; Archaeology; Agriculture","score_opus":0.0071115591548230475,"score_gpt":0.17861447257752727,"score_spread":0.1715029134227042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399751143","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.731367,0.0062824246,0.00045656273,0.014986848,0.00063588115,0.00009497186,0.00039374238,0.000020515592,0.24576215],"genre_scores_gemma":[0.779581,0.0067553823,0.000396861,0.0011870938,0.00007213418,0.00006583531,0.00021674548,0.00003139999,0.21169356],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.99980754,0.000049592705,0.0000024824958,0.000017926413,0.000018044107,0.00010442328],"domain_scores_gemma":[0.9998404,0.0000188208,0.0000149222515,0.0000017626083,0.000011126692,0.00011299676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024275792,0.00024956733,0.00016729232,0.00030185186,0.005439244,0.0030743715,0.0006287469,0.00053827977,0.011677921],"category_scores_gemma":[0.00024110082,0.00021608,0.000114107585,0.0007934716,0.0009913797,0.0018702077,0.0016326973,0.0011308419,0.00068026903],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056150308,0.00025193384,0.06357884,0.0002865533,0.000015918571,0.004540487,0.6525302,0.00019305565,0.00061968627,0.061273877,0.12387647,0.092776775],"study_design_scores_gemma":[0.0000032903758,0.000027302289,0.023466507,0.00014140156,0.000005876491,0.00021870877,0.81558424,0.0001044971,0.00007413411,0.0009072725,0.15945958,0.000007141959],"about_ca_topic_score_codex":0.23494159,"about_ca_topic_score_gemma":0.6160566,"teacher_disagreement_score":0.23494159,"about_ca_system_score_codex":0.0038767036,"about_ca_system_score_gemma":0.005969444,"threshold_uncertainty_score":0.46714818},"labels":[],"label_agreement":null},{"id":"W4399760282","doi":"10.28924/2291-8639-22-2024-101","title":"Intentions to Adopt Contactless Travel in the Post-Pandemic Era: Adapting to a New Normal","year":2024,"lang":"en","type":"article","venue":"International Journal of Analysis and Applications","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Pandemic; New normal; Coronavirus disease 2019 (COVID-19); Psychology; Mathematics; Medicine","score_opus":0.013006311696680015,"score_gpt":0.28257378504296954,"score_spread":0.2695674733462895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399760282","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9973821,0.00009675746,0.0002962165,0.00040575548,0.0000145002905,0.000014826936,0.00003242524,0.0000042119564,0.0017531003],"genre_scores_gemma":[0.9993893,0.0001164915,0.0001223716,0.000057463967,0.000004369671,0.0000056239046,0.000026405543,0.0000015520835,0.0002764417],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995216,0.00018972758,0.00003298924,0.00004582781,0.00009142405,0.00011842214],"domain_scores_gemma":[0.99716824,0.00068822084,0.0010038826,0.00015020746,0.00043688944,0.0005526069],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012193368,0.00013478029,0.00013352156,0.00032110728,0.00045536712,0.00143367,0.0002657659,0.0004581026,0.0026603194],"category_scores_gemma":[0.007641147,0.00013755097,0.0003371294,0.0002458214,0.00057764945,0.0010497611,0.0008321247,0.0011006645,0.0002649975],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016143364,0.00034254583,0.9354664,0.00013872642,0.000097126074,0.00044232397,0.028464422,0.0004302262,0.0012830104,0.0009624786,0.0007179692,0.031493373],"study_design_scores_gemma":[0.000004261816,0.0003610825,0.94352883,0.00010987249,0.00005412951,0.00033696095,0.051028866,0.001059091,0.00031485528,0.00044768438,0.002725036,0.000029458795],"about_ca_topic_score_codex":0.009290457,"about_ca_topic_score_gemma":0.013134437,"teacher_disagreement_score":0.009290457,"about_ca_system_score_codex":0.0004645884,"about_ca_system_score_gemma":0.00072577613,"threshold_uncertainty_score":0.018472731},"labels":[],"label_agreement":null},{"id":"W4399765558","doi":"10.32920/26052466","title":"Matching Problem in Shared Ridehailing Services: Dynamics, Structures, and Algorithms","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Dynamics (music); Computer science; Matching (statistics); Algorithm; Theoretical computer science; Mathematics; Sociology; Statistics","score_opus":0.008491160705928558,"score_gpt":0.23269514844949787,"score_spread":0.2242039877435693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399765558","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06571497,0.0016298258,0.9218759,0.0012481337,0.00013302536,0.00028201676,0.00036683062,0.000366417,0.008382935],"genre_scores_gemma":[0.6061985,0.0017595853,0.37751952,0.0004577857,0.00025339646,0.0005059896,0.0012525459,0.00019289157,0.011859765],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980558,0.0005074128,0.00011838591,0.00061738474,0.0002684874,0.0004325176],"domain_scores_gemma":[0.99388605,0.0042768354,0.00063888385,0.0002734718,0.00056996313,0.0003547287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025248444,0.0012471902,0.0029424476,0.0013258075,0.0012948354,0.002645832,0.0037379356,0.0033644345,0.0055823596],"category_scores_gemma":[0.010386888,0.0007258052,0.0018698543,0.0026669113,0.0012066247,0.004834734,0.0029589478,0.002517968,0.00066897774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022734712,0.00029499078,0.0025202127,0.00030078785,0.0001229616,0.00014592614,0.00021817996,0.8538644,0.00067097665,0.045530763,0.006212528,0.08989091],"study_design_scores_gemma":[0.000018560197,0.000033621385,0.00021210194,0.000016342306,0.00001525233,0.00004088288,0.00006983276,0.9749775,0.00013316513,0.023648972,0.00082477304,0.000009040051],"about_ca_topic_score_codex":0.009967385,"about_ca_topic_score_gemma":0.0063970406,"teacher_disagreement_score":0.009967385,"about_ca_system_score_codex":0.0021386917,"about_ca_system_score_gemma":0.002538869,"threshold_uncertainty_score":0.019818723},"labels":[],"label_agreement":null},{"id":"W4399765559","doi":"10.32920/26052466.v1","title":"Matching Problem in Shared Ridehailing Services: Dynamics, Structures, and Algorithms","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Algorithm; Dynamics (music); Matching (statistics); Theoretical computer science; Mathematics; Psychology","score_opus":0.008491160705928558,"score_gpt":0.23269514844949787,"score_spread":0.2242039877435693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399765559","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06571497,0.0016298258,0.9218759,0.0012481337,0.00013302536,0.00028201676,0.00036683062,0.000366417,0.008382935],"genre_scores_gemma":[0.6061985,0.0017595853,0.37751952,0.0004577857,0.00025339646,0.0005059896,0.0012525459,0.00019289157,0.011859765],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980558,0.0005074128,0.00011838591,0.00061738474,0.0002684874,0.0004325176],"domain_scores_gemma":[0.99388605,0.0042768354,0.00063888385,0.0002734718,0.00056996313,0.0003547287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025248444,0.0012471902,0.0029424476,0.0013258075,0.0012948354,0.002645832,0.0037379356,0.0033644345,0.0055823596],"category_scores_gemma":[0.010386888,0.0007258052,0.0018698543,0.0026669113,0.0012066247,0.004834734,0.0029589478,0.002517968,0.00066897774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022734712,0.00029499078,0.0025202127,0.00030078785,0.0001229616,0.00014592614,0.00021817996,0.8538644,0.00067097665,0.045530763,0.006212528,0.08989091],"study_design_scores_gemma":[0.000018560197,0.000033621385,0.00021210194,0.000016342306,0.00001525233,0.00004088288,0.00006983276,0.9749775,0.00013316513,0.023648972,0.00082477304,0.000009040051],"about_ca_topic_score_codex":0.009967385,"about_ca_topic_score_gemma":0.0063970406,"teacher_disagreement_score":0.009967385,"about_ca_system_score_codex":0.0021386917,"about_ca_system_score_gemma":0.002538869,"threshold_uncertainty_score":0.019818723},"labels":[],"label_agreement":null},{"id":"W4399805581","doi":"10.1155/2024/7312690","title":"Data‐Driven Approach to Evaluate the Level of Service (LOS) of Demand‐Responsive Transport for the Disabled (DRTD) with an ANFIS Algorithm","year":2024,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"University of Seoul","keywords":"Adaptive neuro fuzzy inference system; Service (business); Computer science; Transport engineering; Simulation; Algorithm; Engineering; Artificial intelligence; Business; Fuzzy logic","score_opus":0.06425955610883972,"score_gpt":0.3188059229580608,"score_spread":0.2545463668492211,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399805581","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16809916,0.0004066725,0.82545185,0.00029201712,0.000096724,0.000178715,0.0002376758,0.0008065959,0.0044306247],"genre_scores_gemma":[0.9599934,0.00012670811,0.038040187,0.000049807873,0.000013423082,0.00020670738,0.00015717102,0.000015360829,0.0013971742],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998292,0.000031588996,0.000020656636,0.000043171523,0.000049717946,0.000025735442],"domain_scores_gemma":[0.99958855,0.00023431495,0.00005173782,0.0000091448355,0.00010236511,0.000013953946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000613445,0.00093138026,0.00067170657,0.00058722385,0.00032675397,0.00067066937,0.0006588798,0.0011144547,0.001256919],"category_scores_gemma":[0.0010958246,0.00044222694,0.0007081635,0.00035643045,0.0002737483,0.0003717533,0.00039093132,0.00082620524,0.00012760285],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004112333,0.00003970551,0.0012452092,0.00004960704,0.000032576496,0.0000631203,0.000038438415,0.98473233,0.0015264963,0.00053136173,0.0001543915,0.011545627],"study_design_scores_gemma":[0.0000022477323,0.000015641417,0.00014486289,0.0000027217436,0.000003728707,0.0000029352097,0.0000058543433,0.9995136,0.00017956771,0.000078352445,0.000048764265,0.0000017977811],"about_ca_topic_score_codex":0.020055054,"about_ca_topic_score_gemma":0.011210766,"teacher_disagreement_score":0.020055054,"about_ca_system_score_codex":0.0006726108,"about_ca_system_score_gemma":0.0007525112,"threshold_uncertainty_score":0.03987664},"labels":[],"label_agreement":null},{"id":"W4399808436","doi":"10.1177/03611981241255028","title":"What is the Right Size for Truckload Carrier Alliances?","year":2024,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Transport engineering; Business; Engineering","score_opus":0.06022821870142922,"score_gpt":0.37677896175824926,"score_spread":0.31655074305682007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399808436","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3658102,0.004403696,0.41166216,0.08495359,0.001136171,0.0011292027,0.0010361592,0.0012361988,0.12863268],"genre_scores_gemma":[0.9430683,0.0007271162,0.051874503,0.00075727986,0.00016818775,0.00030665114,0.00013552015,0.000107985616,0.002854383],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99549156,0.0024254532,0.00016881184,0.0006484548,0.00055321935,0.00071248005],"domain_scores_gemma":[0.97353077,0.01442335,0.0027893581,0.0028540115,0.0016284619,0.0047740275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007841934,0.00061978697,0.001156468,0.0008118528,0.002379784,0.006428303,0.0026011518,0.0026774218,0.017045205],"category_scores_gemma":[0.048244957,0.00058387336,0.00065628055,0.00068334566,0.0028792256,0.020908577,0.003707265,0.0024200375,0.0026560805],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001087934,0.00079013134,0.012541368,0.0007082282,0.00013822627,0.0006599012,0.0015788737,0.061563008,0.005723515,0.7369377,0.034214254,0.1440569],"study_design_scores_gemma":[0.0003974183,0.0004166432,0.0041847336,0.00037976663,0.00008300883,0.0005527385,0.0055691884,0.10452048,0.002432163,0.8508001,0.030579196,0.00008461247],"about_ca_topic_score_codex":0.0028002372,"about_ca_topic_score_gemma":0.0043937294,"teacher_disagreement_score":0.017045205,"about_ca_system_score_codex":0.0017020053,"about_ca_system_score_gemma":0.0037553047,"threshold_uncertainty_score":0.057021856},"labels":[],"label_agreement":null},{"id":"W4399828020","doi":"10.32920/26060707.v1","title":"Clustering Analysis of Attitudes Towards Automated Vehicles","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; Nova Scotia Community College; Dalhousie University","funders":"","keywords":"Cluster analysis; Computer science; Artificial intelligence","score_opus":0.023350808070933957,"score_gpt":0.2965357991205182,"score_spread":0.2731849910495842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399828020","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98776615,0.000048750917,0.0039206734,0.000119772085,0.000017641683,0.00021278887,0.0019449284,0.00007522758,0.0058939946],"genre_scores_gemma":[0.992898,0.000030789353,0.002653406,0.000022000613,0.000008209237,0.0001526308,0.0018564602,0.000020863778,0.002357614],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998626,0.00039522452,0.00010215298,0.00028805068,0.00043407915,0.00015451155],"domain_scores_gemma":[0.9940141,0.0020046867,0.0013235203,0.0004712427,0.0018839501,0.00030257436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013454676,0.00029988756,0.000255247,0.0026159037,0.0004955492,0.0007624726,0.00054891256,0.00041337084,0.008083981],"category_scores_gemma":[0.0063490514,0.0001244276,0.0007785596,0.002311259,0.00031754875,0.00042829194,0.0006509018,0.00047418417,0.00117764],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047393236,0.00036049477,0.8618544,0.00022264203,0.0002906002,0.00017267662,0.012276411,0.003087383,0.0036254614,0.0030909446,0.0070327204,0.107512295],"study_design_scores_gemma":[0.000006942111,0.00014901477,0.9830388,0.000034210763,0.00003976117,0.00007161552,0.0056417226,0.0073219854,0.0008980068,0.00051576726,0.0022502837,0.000031932068],"about_ca_topic_score_codex":0.023909904,"about_ca_topic_score_gemma":0.014504078,"teacher_disagreement_score":0.023909904,"about_ca_system_score_codex":0.0010911667,"about_ca_system_score_gemma":0.00083657645,"threshold_uncertainty_score":0.04754144},"labels":[],"label_agreement":null},{"id":"W4399828201","doi":"10.32920/26060707","title":"Clustering Analysis of Attitudes Towards Automated Vehicles","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; Nova Scotia Community College; Dalhousie University","funders":"","keywords":"Cluster analysis; Computer science; Artificial intelligence; Data mining","score_opus":0.023350808070933957,"score_gpt":0.2965357991205182,"score_spread":0.2731849910495842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399828201","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98776615,0.000048750917,0.0039206734,0.000119772085,0.000017641683,0.00021278887,0.0019449284,0.00007522758,0.0058939946],"genre_scores_gemma":[0.992898,0.000030789353,0.002653406,0.000022000613,0.000008209237,0.0001526308,0.0018564602,0.000020863778,0.002357614],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998626,0.00039522452,0.00010215298,0.00028805068,0.00043407915,0.00015451155],"domain_scores_gemma":[0.9940141,0.0020046867,0.0013235203,0.0004712427,0.0018839501,0.00030257436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013454676,0.00029988756,0.000255247,0.0026159037,0.0004955492,0.0007624726,0.00054891256,0.00041337084,0.008083981],"category_scores_gemma":[0.0063490514,0.0001244276,0.0007785596,0.002311259,0.00031754875,0.00042829194,0.0006509018,0.00047418417,0.00117764],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047393236,0.00036049477,0.8618544,0.00022264203,0.0002906002,0.00017267662,0.012276411,0.003087383,0.0036254614,0.0030909446,0.0070327204,0.107512295],"study_design_scores_gemma":[0.000006942111,0.00014901477,0.9830388,0.000034210763,0.00003976117,0.00007161552,0.0056417226,0.0073219854,0.0008980068,0.00051576726,0.0022502837,0.000031932068],"about_ca_topic_score_codex":0.023909904,"about_ca_topic_score_gemma":0.014504078,"teacher_disagreement_score":0.023909904,"about_ca_system_score_codex":0.0010911667,"about_ca_system_score_gemma":0.00083657645,"threshold_uncertainty_score":0.04754144},"labels":[],"label_agreement":null},{"id":"W4399828433","doi":"10.32920/26060836.v1","title":"TD Bank Site Selection Using a Multi-criteria Decision Approach","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Selection (genetic algorithm); Site selection; Computer science; Business; Artificial intelligence; Political science","score_opus":0.04462225035652506,"score_gpt":0.30664353077908585,"score_spread":0.2620212804225608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399828433","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24679565,0.001517918,0.6997982,0.0016491675,0.00014858929,0.010820518,0.0016378019,0.00039685567,0.037235215],"genre_scores_gemma":[0.5608178,0.00053605,0.43034115,0.00013182755,0.00004014712,0.002639542,0.0006272743,0.000055606874,0.0048105684],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.98988837,0.006601848,0.0005612169,0.0006620738,0.00163821,0.0006482707],"domain_scores_gemma":[0.9898532,0.006924072,0.000475791,0.0001739698,0.0019192417,0.00065374176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009414955,0.0015013717,0.0017831068,0.007879271,0.001865448,0.0055648484,0.0019600526,0.001636554,0.009243064],"category_scores_gemma":[0.012079746,0.00084261707,0.001989274,0.005829599,0.0008983253,0.0013424462,0.0020348849,0.0012629391,0.0005572575],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009600336,0.0011219253,0.011222662,0.0032971415,0.0007689298,0.0015223533,0.005310541,0.65324455,0.0061627976,0.034622204,0.0071727354,0.2745941],"study_design_scores_gemma":[0.00025578635,0.0011312746,0.0051193046,0.0006296759,0.00031387666,0.00014584542,0.0063785035,0.946695,0.0026641388,0.02459734,0.011905503,0.00016374525],"about_ca_topic_score_codex":0.019138098,"about_ca_topic_score_gemma":0.03119272,"teacher_disagreement_score":0.019138098,"about_ca_system_score_codex":0.0068205786,"about_ca_system_score_gemma":0.009494458,"threshold_uncertainty_score":0.049791634},"labels":[],"label_agreement":null},{"id":"W4399903363","doi":"10.1016/j.omega.2024.103134","title":"A column and row generation approach to the crowd-shipping problem with transfers","year":2024,"lang":"en","type":"article","venue":"Omega","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Column generation; Column (typography); Computer science; Mathematics; Mathematical optimization; Telecommunications","score_opus":0.015361237532867405,"score_gpt":0.19844033657746812,"score_spread":0.1830790990446007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399903363","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058055036,0.0005365893,0.92957586,0.0006510151,0.00018510918,0.00035464595,0.0004955142,0.00095174834,0.009194476],"genre_scores_gemma":[0.5619924,0.00035112663,0.42579207,0.00038844443,0.00013326984,0.00038484507,0.00091754453,0.00030961298,0.009730677],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946636,0.00021275591,0.000018353558,0.000104529,0.000075060365,0.00012295767],"domain_scores_gemma":[0.9990802,0.0005043705,0.00009972304,0.00008040836,0.00013004092,0.00010528102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082090346,0.0011073141,0.0010807136,0.00062000647,0.00080589927,0.0009875026,0.001765262,0.0010572049,0.006288022],"category_scores_gemma":[0.0015389982,0.0005542461,0.0010295052,0.001029211,0.0006895475,0.0010891784,0.0011482205,0.0011741247,0.00073273934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007029072,0.00008328727,0.0005362614,0.00007958506,0.000030686606,0.00013761547,0.000048947306,0.9685129,0.0009422778,0.006036147,0.0035762275,0.019945715],"study_design_scores_gemma":[0.000018923412,0.00003538256,0.000083429775,0.000005698015,0.0000081894195,0.000028141269,0.000029363879,0.9946585,0.0003225288,0.003846096,0.0009574462,0.0000062624686],"about_ca_topic_score_codex":0.009278768,"about_ca_topic_score_gemma":0.011108401,"teacher_disagreement_score":0.009278768,"about_ca_system_score_codex":0.00096499163,"about_ca_system_score_gemma":0.0015610564,"threshold_uncertainty_score":0.021035552},"labels":[],"label_agreement":null},{"id":"W4400013649","doi":"10.1177/03611981241257510","title":"How Does the Introduction of Shared Ride-Sourcing Services Affect Demand for Existing Modes for Non-Commuting Trips? Evidence from a Joint RP-SP Study in Metro Vancouver","year":2024,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"TRIPS architecture; Affect (linguistics); Joint (building); Transport engineering; Business; Marketing; Engineering; Psychology; Architectural engineering","score_opus":0.12121184376793896,"score_gpt":0.38466860722209995,"score_spread":0.26345676345416097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400013649","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983376,0.0000869713,0.00010471321,0.0001517022,0.0000033027698,0.000011560066,0.00020451448,0.0000015321004,0.0010980591],"genre_scores_gemma":[0.99838316,0.00016254715,0.00015088754,0.00006277889,0.0000029334285,0.000026289003,0.00025682457,0.000004195015,0.000950352],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970969,0.0012263855,0.00014790635,0.0004112085,0.0005493106,0.00056840305],"domain_scores_gemma":[0.98918486,0.0040909327,0.0018355177,0.00081205746,0.0025504087,0.0015262335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027261425,0.00034539096,0.0007958005,0.0006148879,0.0022321546,0.0027849544,0.0015577378,0.0008164809,0.0034330396],"category_scores_gemma":[0.01142417,0.00066098495,0.00084818783,0.0020938455,0.0013216465,0.0010658894,0.0021236078,0.0020737546,0.00048598083],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021531616,0.00038470284,0.9715962,0.00009974874,0.00021061499,0.00030629314,0.015608204,0.00043234706,0.00030787222,0.00039877644,0.00074277027,0.009697053],"study_design_scores_gemma":[0.000017485441,0.00015817049,0.9496383,0.00010681468,0.00007761231,0.00007491294,0.04592317,0.0018315817,0.000111142384,0.00019714807,0.0018293342,0.000034343528],"about_ca_topic_score_codex":0.86573845,"about_ca_topic_score_gemma":0.9294837,"teacher_disagreement_score":0.13426155,"about_ca_system_score_codex":0.0058508483,"about_ca_system_score_gemma":0.006829674,"threshold_uncertainty_score":0.27010447},"labels":[],"label_agreement":null},{"id":"W4400142435","doi":"10.1145/3643834.3661553","title":"“Shotitwo First!”: Unraveling Global South Women’s Challenges in Public Transport to Inform Autonomous Vehicle Design","year":2024,"lang":"en","type":"article","venue":"Designing Interactive Systems Conference","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Public transport; Computer science; Transport engineering; Engineering","score_opus":0.08899658336752383,"score_gpt":0.2731694254788382,"score_spread":0.18417284211131438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400142435","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82640815,0.0043254644,0.024707753,0.042155027,0.0006376149,0.0003605748,0.00030294058,0.00014177134,0.10096065],"genre_scores_gemma":[0.97517496,0.003028202,0.008188276,0.0028121267,0.000047476075,0.00023099969,0.00007862802,0.00008277006,0.010356564],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9983082,0.0012370201,0.000036229074,0.000090958194,0.00012282607,0.00020483519],"domain_scores_gemma":[0.99811953,0.0010789306,0.00018063094,0.00015976634,0.00024342762,0.00021772963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040709167,0.00057795015,0.0002803828,0.00075071305,0.0052241436,0.00492156,0.00076528534,0.001416019,0.010763486],"category_scores_gemma":[0.0049665463,0.00033143532,0.0002802131,0.000999534,0.0054162163,0.0053170426,0.004559361,0.0015955536,0.001072245],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008402502,0.00007271794,0.016367532,0.001116922,0.000019141942,0.0012068528,0.8370065,0.00030876033,0.005887082,0.028681232,0.009280986,0.09996836],"study_design_scores_gemma":[0.000006912389,0.00013909588,0.003330498,0.00064680533,0.000021909404,0.00026883787,0.8314133,0.0002575054,0.0010334856,0.0067273476,0.15613224,0.000022044715],"about_ca_topic_score_codex":0.006992473,"about_ca_topic_score_gemma":0.018240849,"teacher_disagreement_score":0.010763486,"about_ca_system_score_codex":0.0021534183,"about_ca_system_score_gemma":0.0027903442,"threshold_uncertainty_score":0.036007464},"labels":[],"label_agreement":null},{"id":"W4400274616","doi":"10.1007/s10479-024-06136-9","title":"Hybrid metaheuristic for the dial-a-ride problem with private fleet and common carrier integrated with public transportation","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Metaheuristic; Transport engineering; Public transport; Business; Fleet management; Computer science; Operations research; Telecommunications; Engineering; Artificial intelligence","score_opus":0.10714165070929006,"score_gpt":0.36874486405725626,"score_spread":0.2616032133479662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400274616","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36104703,0.0020052034,0.61540955,0.00077705324,0.00029634064,0.00031425367,0.0004312981,0.0005445862,0.01917461],"genre_scores_gemma":[0.8693576,0.00030649512,0.1244313,0.00011334623,0.000068273286,0.00020936024,0.00020964375,0.00006334338,0.0052405093],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993272,0.00025873768,0.000021551574,0.000102706654,0.00009213161,0.0001978022],"domain_scores_gemma":[0.999099,0.00058426807,0.00006711042,0.0000499092,0.00009970838,0.00010008936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012359486,0.0011212988,0.0018656417,0.0014017485,0.00068217097,0.0016492152,0.0022888072,0.0024929447,0.0030755831],"category_scores_gemma":[0.0015802785,0.000749078,0.0015535161,0.0017049497,0.0006847265,0.0015210189,0.0011764314,0.0015015268,0.00017099324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000804063,0.00011234492,0.00021619826,0.000034165245,0.00005425754,0.000036894715,0.000016088377,0.98713,0.00024188822,0.0031900562,0.0004612269,0.008426573],"study_design_scores_gemma":[0.000026170852,0.000040161583,0.00006413734,0.0000037685863,0.000014709064,0.0000068051622,0.000014357591,0.99857056,0.00007555546,0.0009267505,0.00025355493,0.0000033878598],"about_ca_topic_score_codex":0.024240194,"about_ca_topic_score_gemma":0.020321837,"teacher_disagreement_score":0.024240194,"about_ca_system_score_codex":0.0018326263,"about_ca_system_score_gemma":0.002576575,"threshold_uncertainty_score":0.048198223},"labels":[],"label_agreement":null},{"id":"W4400412761","doi":"10.1007/978-3-031-54650-1_14","title":"Advanced Data Analysis","year":2024,"lang":"en","type":"book-chapter","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Computer science","score_opus":0.03072695506674347,"score_gpt":0.2571165754848985,"score_spread":0.22638962041815505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400412761","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009499759,0.001870656,0.86217034,0.0016211072,0.00088564,0.00038671563,0.010529544,0.027126854,0.094459124],"genre_scores_gemma":[0.013452413,0.0032231447,0.6171597,0.0014734365,0.00081700314,0.00073122163,0.027184278,0.0069303876,0.32902846],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99781966,0.000350669,0.00015160195,0.00045738497,0.0011266213,0.000094010764],"domain_scores_gemma":[0.99603075,0.0012913801,0.000098975266,0.0013719493,0.0011079115,0.00009894997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024982672,0.0017956834,0.0012050363,0.0031410272,0.0009388944,0.0042862315,0.0019149939,0.0010291924,0.13085033],"category_scores_gemma":[0.0076008355,0.0009969492,0.0013689466,0.0034104118,0.0007737723,0.0034390711,0.0026097007,0.0020452626,0.16521856],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004246207,0.000039356324,0.0003262295,0.0001931755,0.00003326224,0.000065755,0.00010524648,0.0010777048,0.0031022541,0.024690026,0.35776177,0.61256284],"study_design_scores_gemma":[0.000012458559,0.00002782109,0.00102209,0.0001457115,0.000039566265,0.00034853816,0.00013859567,0.019076772,0.008660557,0.076641425,0.89384484,0.000041660027],"about_ca_topic_score_codex":0.002179962,"about_ca_topic_score_gemma":0.0026354503,"teacher_disagreement_score":0.13085033,"about_ca_system_score_codex":0.00080475514,"about_ca_system_score_gemma":0.0015603609,"threshold_uncertainty_score":0.43773794},"labels":[],"label_agreement":null},{"id":"W4400491106","doi":"10.1109/cscwd61410.2024.10580473","title":"Bus Driver Rostering via Extending Group Multirole Assignment","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nipissing University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Group (periodic table)","score_opus":0.008317017120878355,"score_gpt":0.21915229768738045,"score_spread":0.2108352805665021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400491106","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08338403,0.00012673445,0.90947574,0.00018181957,0.000050659924,0.00020863937,0.000060717055,0.0003641481,0.0061475346],"genre_scores_gemma":[0.83948326,0.00006638983,0.1578692,0.000058539285,0.000017728107,0.00014875788,0.000082631996,0.000040382147,0.0022331416],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871445,0.00056870223,0.000040841922,0.00025287442,0.00023267619,0.00019048322],"domain_scores_gemma":[0.9990932,0.00028130782,0.0001542041,0.0001527316,0.00016698694,0.00015156688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014102316,0.0009947517,0.0007494271,0.0007074104,0.00081501366,0.0008012273,0.0014589049,0.000768409,0.0035436044],"category_scores_gemma":[0.002419393,0.00029047002,0.0009081058,0.00064252934,0.0005169681,0.0013552242,0.001777728,0.0007344259,0.00046551248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022491084,0.00025450156,0.0030452802,0.00011433832,0.000056833996,0.00024151649,0.00033000548,0.8397063,0.008102641,0.014684769,0.0019441785,0.13129468],"study_design_scores_gemma":[0.000016902337,0.00012594282,0.00031283483,0.0000065102386,0.000015020998,0.000053809294,0.00008090592,0.9908908,0.0009909809,0.0060917074,0.0014017937,0.000012873676],"about_ca_topic_score_codex":0.003587192,"about_ca_topic_score_gemma":0.0032182995,"teacher_disagreement_score":0.003587192,"about_ca_system_score_codex":0.0006184083,"about_ca_system_score_gemma":0.0009042783,"threshold_uncertainty_score":0.011854589},"labels":[],"label_agreement":null},{"id":"W4400652020","doi":"10.1287/ijoc.2023.0280","title":"A Model-Free Approach for Solving Choice-Based Competitive Facility Location Problems Using Simulation and Submodularity","year":2024,"lang":"en","type":"article","venue":"INFORMS journal on computing","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Facility location problem; Mathematical optimization; Operations research; Mathematics","score_opus":0.05482827226882548,"score_gpt":0.2874064715621021,"score_spread":0.2325781992932766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400652020","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0064494736,0.000104947634,0.99164116,0.00018880522,0.000014109962,0.00006388956,0.000060395698,0.00013540521,0.0013417779],"genre_scores_gemma":[0.39639667,0.00033280722,0.5985777,0.00027815014,0.00007753575,0.0008397388,0.0004563243,0.00015615088,0.0028849554],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99808204,0.0010800831,0.000056534533,0.00029422448,0.00032122905,0.0001659025],"domain_scores_gemma":[0.9913051,0.007294765,0.0004964461,0.00034071397,0.00034447273,0.00021846606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031599998,0.0017936988,0.002425273,0.00151217,0.0007611256,0.0015780855,0.0026245473,0.0018574531,0.0042743064],"category_scores_gemma":[0.010744241,0.0013682839,0.0025753728,0.0016600428,0.0018649857,0.0018402936,0.0022046473,0.0029723647,0.0004279422],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020834783,0.00003361738,0.0002054312,0.000035806268,0.00002430855,0.0000154392,0.000021785494,0.9817467,0.00012988946,0.012642993,0.000209243,0.004913981],"study_design_scores_gemma":[0.0000066515754,0.0000110385545,0.000014927204,0.000003822656,0.0000029475066,0.000003840678,0.0000037708423,0.99184567,0.0000512495,0.007896612,0.00015738679,0.0000021374333],"about_ca_topic_score_codex":0.0074100564,"about_ca_topic_score_gemma":0.007712868,"teacher_disagreement_score":0.0074100564,"about_ca_system_score_codex":0.0023174249,"about_ca_system_score_gemma":0.0031529749,"threshold_uncertainty_score":0.016814172},"labels":[],"label_agreement":null},{"id":"W4400726035","doi":"10.1007/978-3-031-60867-4_11","title":"Business Model Innovation for Ambulance Systems in Low- and Middle-Income Countries","year":2024,"lang":"en","type":"book-chapter","venue":"Springer series in supply chain management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Business; Low and middle income countries; Middle income; Economic growth; Economics; Demographic economics; Developing country","score_opus":0.012928213389732093,"score_gpt":0.21409896352923125,"score_spread":0.20117075013949914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400726035","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22187297,0.040823888,0.039097305,0.016617069,0.0009215296,0.00020528543,0.0004149839,0.00033743936,0.6797096],"genre_scores_gemma":[0.81178236,0.024980456,0.016956164,0.00078406144,0.0001751242,0.000113973954,0.0005752213,0.000094337185,0.14453827],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9990565,0.00032832078,0.000033865766,0.00010482209,0.00021719642,0.00025927144],"domain_scores_gemma":[0.9987716,0.00062644464,0.00009555571,0.00010511299,0.000229301,0.00017184467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015473048,0.00036255445,0.00030506146,0.00092527113,0.001188858,0.0059644347,0.00077172,0.0012011697,0.0113194045],"category_scores_gemma":[0.0024554082,0.00017354198,0.0005468602,0.0026811347,0.0012808302,0.003019518,0.0012794483,0.0014005277,0.001292415],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008098117,0.00022638866,0.0067552147,0.00032377086,0.000035088615,0.00031863182,0.003242724,0.016995816,0.0009950832,0.51888686,0.053426787,0.39871272],"study_design_scores_gemma":[0.000025856643,0.0002986106,0.0158572,0.00082079554,0.00003626742,0.00031177336,0.0071550244,0.04132783,0.0022303865,0.13495,0.7969256,0.000060727227],"about_ca_topic_score_codex":0.008433026,"about_ca_topic_score_gemma":0.0076926257,"teacher_disagreement_score":0.0113194045,"about_ca_system_score_codex":0.005749486,"about_ca_system_score_gemma":0.004493388,"threshold_uncertainty_score":0.041715562},"labels":[],"label_agreement":null},{"id":"W4400772767","doi":"10.1016/j.aej.2024.07.010","title":"An optimal resource assignment and mode selection for vehicular communication using proximal on-policy scheme","year":2024,"lang":"en","type":"article","venue":"Alexandria Engineering Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Selection (genetic algorithm); Scheme (mathematics); Mode (computer interface); Resource (disambiguation); Computer science; Mathematical optimization; Environmental economics; Computer network; Mathematics; Economics; Artificial intelligence","score_opus":0.01390812097530052,"score_gpt":0.27794644860046147,"score_spread":0.26403832762516094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400772767","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02745239,0.00087444053,0.9649742,0.00042226425,0.00013557769,0.00008605449,0.000069112124,0.00031196565,0.0056739696],"genre_scores_gemma":[0.9587985,0.00032377223,0.037097022,0.0001611327,0.00005580261,0.000092953494,0.00005803096,0.00003091058,0.0033818153],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919266,0.00024799496,0.00003062567,0.00017336631,0.00014977672,0.00020567625],"domain_scores_gemma":[0.9990509,0.0004987654,0.000110015855,0.00006121722,0.00016319612,0.00011588119],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091959833,0.0010640931,0.0014988863,0.0005368771,0.0006774302,0.0011521402,0.0016227678,0.0009833341,0.0037862957],"category_scores_gemma":[0.0021457023,0.0004116575,0.00051524286,0.0006734295,0.0010748499,0.0010013159,0.0013006588,0.0012456296,0.0005015528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022759094,0.00008280268,0.00048548146,0.00013246706,0.000050422877,0.00019257545,0.00016017313,0.92205954,0.002642687,0.021448862,0.0032896046,0.04922786],"study_design_scores_gemma":[0.00001366802,0.000029211045,0.000046494737,0.0000054088,0.000006683985,0.000025072057,0.0000138621845,0.9955374,0.00025285155,0.0037262717,0.0003352428,0.000007838987],"about_ca_topic_score_codex":0.005492227,"about_ca_topic_score_gemma":0.0047101784,"teacher_disagreement_score":0.005492227,"about_ca_system_score_codex":0.0010996175,"about_ca_system_score_gemma":0.0016032076,"threshold_uncertainty_score":0.012666404},"labels":[],"label_agreement":null},{"id":"W4400995152","doi":"10.1177/03611981241257513","title":"Dynamic Calibration of a Carsharing System in Multiagent Transport Simulation","year":2024,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Calibration; Computer science; Mode (computer interface); Simulation; Process (computing); Computation; Public transport; Traffic simulation; Relation (database); Real-time computing; Microsimulation; Transport engineering; Algorithm; Data mining; Engineering","score_opus":0.06791879043422243,"score_gpt":0.37434340291005763,"score_spread":0.3064246124758352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400995152","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28253525,0.000111920395,0.70734906,0.00022486043,0.000055739452,0.00020564513,0.00012772097,0.0010901844,0.008299625],"genre_scores_gemma":[0.9572566,0.000041646188,0.04182313,0.000015725855,0.0000036484655,0.00010638713,0.000068513036,0.000038853104,0.00064546877],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940956,0.00029002194,0.00003060636,0.000090835805,0.00012157377,0.00005744245],"domain_scores_gemma":[0.99885917,0.0005518159,0.00014514655,0.00016325054,0.00021347351,0.000067181834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012787422,0.00050571584,0.00046909385,0.0004274336,0.00048580646,0.00096377276,0.0008546896,0.0007849617,0.0015776317],"category_scores_gemma":[0.0040516853,0.00035718252,0.00042931506,0.0003554188,0.00057144125,0.0008552489,0.0011058932,0.00084566197,0.00020384675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028349124,0.000023376802,0.00069329893,0.000016803608,0.000007968012,0.00002789966,0.000050231025,0.9915677,0.0010263462,0.0025190227,0.00008525083,0.0039536543],"study_design_scores_gemma":[0.0000050627687,0.000021713493,0.00019226882,0.0000044727976,0.000002834701,0.000006189472,0.000013968878,0.99794775,0.0007824879,0.00068394653,0.00033394762,0.000005232517],"about_ca_topic_score_codex":0.0058708293,"about_ca_topic_score_gemma":0.0023114912,"teacher_disagreement_score":0.0058708293,"about_ca_system_score_codex":0.0008933333,"about_ca_system_score_gemma":0.00091049104,"threshold_uncertainty_score":0.011673272},"labels":[],"label_agreement":null},{"id":"W4401072134","doi":"10.1016/j.trb.2024.103027","title":"Approximate dynamic programming for pickup and delivery problem with crowd-shipping","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part B Methodological","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Computer science; Markov decision process; Dynamic programming; Mathematical optimization; Matching (statistics); Scalability; Bellman equation; Convergence (economics); Stochastic programming; Pickup; Markov process; Function (biology); Operations research; Engineering; Mathematics; Algorithm; Artificial intelligence","score_opus":0.2657432137070771,"score_gpt":0.42983313295290426,"score_spread":0.16408991924582716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401072134","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027823605,0.0007472603,0.9631572,0.0008665008,0.00013538385,0.0001065525,0.0002345999,0.00020852956,0.0067204037],"genre_scores_gemma":[0.86271733,0.0009606772,0.12699592,0.00038880497,0.000112621514,0.0003712024,0.00038698016,0.00012848138,0.007937986],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990344,0.00033462385,0.00004292533,0.00020305991,0.00017109522,0.00021395838],"domain_scores_gemma":[0.99638677,0.0027595714,0.0003038606,0.00008517443,0.00026673358,0.00019790375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001951813,0.0015884792,0.002483559,0.0006994688,0.00076235237,0.0020203239,0.0015550946,0.0022633893,0.0045295516],"category_scores_gemma":[0.005605846,0.00091035047,0.0011052402,0.0012116648,0.0011595567,0.0015634394,0.001718316,0.0023674085,0.0004054576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031744017,0.000016381047,0.00015916543,0.00003979109,0.00001266926,0.000047417547,0.00001615547,0.99076086,0.00010337445,0.0056852405,0.00040448908,0.0027227816],"study_design_scores_gemma":[0.000005623663,0.000010121967,0.000028668528,0.000003900334,0.00000322893,0.00000595958,0.000008730908,0.99677086,0.000038933573,0.0029310593,0.00019011686,0.0000026979749],"about_ca_topic_score_codex":0.015900534,"about_ca_topic_score_gemma":0.0075960755,"teacher_disagreement_score":0.015900534,"about_ca_system_score_codex":0.0019435438,"about_ca_system_score_gemma":0.002594895,"threshold_uncertainty_score":0.031615913},"labels":[],"label_agreement":null},{"id":"W4401113943","doi":"10.1109/ict62760.2024.10606121","title":"Charging Station Planning for Electric Ride-Hailing Taxi Services","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Telecommunications; Business; Transport engineering; Engineering","score_opus":0.012438808441368078,"score_gpt":0.26004855877094335,"score_spread":0.24760975032957527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401113943","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73550117,0.00023471969,0.23211084,0.0004303279,0.00005960673,0.00036887327,0.0008335928,0.0007574475,0.0297034],"genre_scores_gemma":[0.97895974,0.00006655575,0.017760696,0.000016708858,0.000003617999,0.000037334572,0.00018179418,0.000028932911,0.0029447428],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987173,0.000041865493,0.0000042993006,0.000019508387,0.000019258852,0.00004324931],"domain_scores_gemma":[0.99983954,0.00006108143,0.000019077519,0.00000814805,0.00004348888,0.00002862572],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024952902,0.00036475383,0.00039280567,0.00044207368,0.0005003077,0.00083362183,0.0004990846,0.0005159181,0.0048302533],"category_scores_gemma":[0.0008455415,0.00041084757,0.00037347878,0.0005343558,0.00023975405,0.00045298855,0.00033368793,0.00041996606,0.00032114526],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033262884,0.00001689479,0.0010518685,0.000011367576,0.000006811994,0.0000386038,0.000020386608,0.9924973,0.0005050871,0.00079880917,0.00037292458,0.0046467413],"study_design_scores_gemma":[0.000008897669,0.000028963703,0.0005819202,0.0000022038153,0.0000061495502,0.0000066916864,0.000054569537,0.9981741,0.0002891244,0.00037770043,0.00046547997,0.0000042128777],"about_ca_topic_score_codex":0.058418345,"about_ca_topic_score_gemma":0.06474884,"teacher_disagreement_score":0.058418345,"about_ca_system_score_codex":0.0015092863,"about_ca_system_score_gemma":0.0019479413,"threshold_uncertainty_score":0.11615658},"labels":[],"label_agreement":null},{"id":"W4401140885","doi":"10.18280/mmep.110722","title":"Optimization of Logistic Solutions for Incoming and Outgoing Trucks System Using a Simulated Cross-Docking Centre Environment","year":2024,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Truck; Logistic regression; Docking (animal); Computer science; Aeronautics; Engineering; Simulation; Aerospace engineering; Medicine; Machine learning; Veterinary medicine","score_opus":0.04659370288504632,"score_gpt":0.23971323873144992,"score_spread":0.1931195358464036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401140885","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71709204,0.00034557795,0.26445222,0.00020680774,0.000046461213,0.00017144899,0.0003974999,0.00054785976,0.016740054],"genre_scores_gemma":[0.9636635,0.0001355796,0.03327234,0.00002209124,0.000004881119,0.00010539895,0.00022322725,0.00006335367,0.0025097327],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969065,0.00011053477,0.000011171464,0.000040592447,0.00004460688,0.000102482336],"domain_scores_gemma":[0.99929,0.00044956442,0.00008124463,0.000024652934,0.00007881893,0.00007563998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061037496,0.00085271086,0.000718923,0.00067488546,0.0004448621,0.0010936027,0.00064657384,0.00078105787,0.0030010054],"category_scores_gemma":[0.0015407108,0.00052913843,0.00078446296,0.0005820165,0.0003887919,0.00047522126,0.0007769646,0.00060420437,0.00022063014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035987116,0.000016275502,0.00020694527,0.000013591561,0.0000056802073,0.000015520998,0.000009812094,0.99782985,0.0002795111,0.00033571126,0.000045857178,0.0012051738],"study_design_scores_gemma":[0.0000113615215,0.000058865247,0.00019692742,0.0000030296912,0.000005957535,0.000004904761,0.000023441544,0.9988292,0.00040461528,0.00022547739,0.00023210493,0.0000041089997],"about_ca_topic_score_codex":0.010792857,"about_ca_topic_score_gemma":0.007931601,"teacher_disagreement_score":0.010792857,"about_ca_system_score_codex":0.001293965,"about_ca_system_score_gemma":0.0016237932,"threshold_uncertainty_score":0.021460056},"labels":[],"label_agreement":null},{"id":"W4401167308","doi":"10.1016/j.trc.2024.104782","title":"A parking incentive allocation problem for ridesharing systems","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part C Emerging Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Université de Montréal","funders":"","keywords":"Incentive; Transport engineering; Computer science; Operations research; Economics; Engineering; Microeconomics","score_opus":0.0735828554201343,"score_gpt":0.35662632164254243,"score_spread":0.2830434662224081,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401167308","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19982474,0.0023630452,0.74523073,0.0048683966,0.0005420099,0.0010700054,0.0023159909,0.0006545717,0.043130465],"genre_scores_gemma":[0.89699763,0.0008058835,0.0718651,0.00037588563,0.00024844674,0.0003571163,0.0008485635,0.00016977389,0.02833165],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99807596,0.00085874624,0.00008550683,0.00043065177,0.00016465502,0.00038439693],"domain_scores_gemma":[0.9965718,0.002343779,0.00018600536,0.0001737339,0.00027835264,0.0004463105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002793586,0.0015030446,0.00502922,0.0010525931,0.0013220948,0.004084928,0.0035540725,0.005147622,0.017947543],"category_scores_gemma":[0.0075427745,0.0015960869,0.0016951608,0.0020303233,0.0016850366,0.003958482,0.0028217796,0.002790003,0.0008969234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005849719,0.0003431197,0.0006691821,0.0005533202,0.00012663289,0.00029175816,0.00013929525,0.87529296,0.0015071819,0.07811871,0.010249154,0.03212378],"study_design_scores_gemma":[0.0001314263,0.00014681,0.00031115144,0.000032927433,0.000040338993,0.00006477353,0.0000733701,0.95561355,0.00031790594,0.040697828,0.0025415889,0.000028243565],"about_ca_topic_score_codex":0.006690791,"about_ca_topic_score_gemma":0.004062971,"teacher_disagreement_score":0.017947543,"about_ca_system_score_codex":0.0027342546,"about_ca_system_score_gemma":0.002445853,"threshold_uncertainty_score":0.060040534},"labels":[],"label_agreement":null},{"id":"W4401357153","doi":"10.1109/tits.2024.3434561","title":"Crowdsourcing Regional Coverage Balancing Method Based on Transfer Learning in Taxi Service","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"National Natural Science Foundation of China","keywords":"Crowdsourcing; Transfer of learning; Computer science; Service (business); Transport engineering; Artificial intelligence; Engineering; Business; World Wide Web; Marketing","score_opus":0.0222041113797995,"score_gpt":0.2616059251083965,"score_spread":0.23940181372859698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401357153","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14591165,0.0005496481,0.8451743,0.0005345793,0.00011880746,0.00020814563,0.0001091893,0.0018340648,0.005559575],"genre_scores_gemma":[0.93240154,0.000119288365,0.06388932,0.00015164072,0.000056080265,0.00011157148,0.00013016837,0.00009548713,0.0030448646],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898416,0.00022475704,0.000038745104,0.00028064128,0.00027243546,0.00019923483],"domain_scores_gemma":[0.9986375,0.0005643582,0.00014329232,0.0001582934,0.00033111617,0.00016548272],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011943551,0.0009144473,0.0016149138,0.0010675723,0.0009626279,0.0009682701,0.0020914983,0.001059805,0.0019282629],"category_scores_gemma":[0.0033070873,0.0003531452,0.0007927789,0.0012224143,0.0007559392,0.0015861562,0.0013059282,0.0009338947,0.00050167565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037046193,0.00033967706,0.0033874444,0.00010921443,0.0000775788,0.00022422559,0.00030277498,0.73922443,0.0078960005,0.0035568043,0.003410963,0.24110045],"study_design_scores_gemma":[0.000009498025,0.000028321541,0.00022566608,0.000001911293,0.000007081351,0.000015003649,0.00003295328,0.99790204,0.0006601571,0.00083165115,0.00027981217,0.0000058928144],"about_ca_topic_score_codex":0.014100643,"about_ca_topic_score_gemma":0.008772617,"teacher_disagreement_score":0.014100643,"about_ca_system_score_codex":0.0015074967,"about_ca_system_score_gemma":0.0014449051,"threshold_uncertainty_score":0.02803713},"labels":[],"label_agreement":null},{"id":"W4401457558","doi":"10.1155/2024/4166852","title":"Unlocking the Maze: Exploring Nested Ecosystem of Mobility as a Service through Systematic Literature Review","year":2024,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Charles Darwin University; University of Wollongong","keywords":"Service (business); Ecosystem; Computer science; Environmental science; Business; Ecology; Biology; Marketing","score_opus":0.021457438974727953,"score_gpt":0.2673217872398316,"score_spread":0.24586434826510362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401457558","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019546004,0.95282376,0.010243599,0.005495478,0.00050487014,0.004572795,0.0028034637,0.000060936287,0.00394908],"genre_scores_gemma":[0.18110457,0.7748093,0.030257927,0.0034120895,0.0001942933,0.007435196,0.0020409366,0.000038258073,0.00070741575],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.97553045,0.011854491,0.0070712245,0.0014842298,0.003514995,0.0005444504],"domain_scores_gemma":[0.8943389,0.08138923,0.010200314,0.002687239,0.010626518,0.00075781986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.037183274,0.0011866135,0.002988245,0.030816223,0.0011216721,0.005226937,0.0017013776,0.0016291544,0.0028833367],"category_scores_gemma":[0.11384856,0.00082991057,0.0035003237,0.019775044,0.001696798,0.007487456,0.0033832125,0.0012672456,0.00036562106],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014925741,0.00006583766,0.009981597,0.77367085,0.0067918045,0.00078592694,0.011315659,0.0006407777,0.0006755858,0.014253805,0.005310165,0.17635874],"study_design_scores_gemma":[0.000061001363,0.00018860605,0.0064970376,0.8864871,0.017454091,0.0006886689,0.015844757,0.00064021256,0.0003987786,0.0077301455,0.063921206,0.000088364075],"about_ca_topic_score_codex":0.00856995,"about_ca_topic_score_gemma":0.029260352,"teacher_disagreement_score":0.037183274,"about_ca_system_score_codex":0.0049720276,"about_ca_system_score_gemma":0.03471524,"threshold_uncertainty_score":0.19664627},"labels":[],"label_agreement":null},{"id":"W4401465780","doi":"10.1177/03611981241247047","title":"Correlates of Modal Substitution and Induced Travel of Ridehailing in California","year":2024,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of California, Davis; California Air Resources Board","keywords":"TRIPS architecture; Public transport; Metropolitan area; Equity (law); Travel behavior; Mode choice; Modal; Transport engineering; Transit (satellite); Business; Sample (material); Demographic economics; Geography; Public economics; Economics; Engineering; Political science","score_opus":0.07134757430610023,"score_gpt":0.35404507688968856,"score_spread":0.28269750258358833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401465780","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982948,0.00007337903,0.000052960706,0.00003898945,0.000002630374,0.000009817172,0.0006708304,0.0000041433045,0.0008524355],"genre_scores_gemma":[0.99863344,0.00011445172,0.00008216671,0.000010130326,0.0000032393043,0.000009018385,0.00085980084,0.000001929356,0.00028584254],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995658,0.000063447005,0.00006490492,0.00010817326,0.00013157398,0.000066154],"domain_scores_gemma":[0.99769527,0.00032095826,0.0011531506,0.00015466256,0.0004293696,0.00024649096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004585336,0.00011330566,0.00016919202,0.00069603126,0.0004369369,0.0006765334,0.00052369555,0.00025378907,0.002932557],"category_scores_gemma":[0.0030847227,0.00021199894,0.0003039629,0.0014331936,0.00033220847,0.00037878592,0.00052955997,0.00042868528,0.00018651543],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021658772,0.00003730324,0.9973551,0.000019323546,0.000025433992,0.00003444535,0.00027033797,0.00020606005,0.0000612554,0.00004405985,0.0003660433,0.0015589357],"study_design_scores_gemma":[0.0000011730433,0.000015563237,0.9988148,0.000008970012,0.0000064415635,0.000027182266,0.0005330378,0.00018357631,0.000014988256,0.000009409128,0.0003809767,0.0000037854131],"about_ca_topic_score_codex":0.22222316,"about_ca_topic_score_gemma":0.29245153,"teacher_disagreement_score":0.22222316,"about_ca_system_score_codex":0.0008019598,"about_ca_system_score_gemma":0.000597877,"threshold_uncertainty_score":0.44185936},"labels":[],"label_agreement":null},{"id":"W4401488377","doi":"","title":"Modèle générique inclusif de système ambiant dédié à l'assistance basé sur le paradigme multi-agent","year":2021,"lang":"fr","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Humanities; Philosophy","score_opus":0.027000052909227204,"score_gpt":0.2183953903172156,"score_spread":0.19139533740798842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401488377","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11866561,0.000873247,0.840566,0.0014155947,0.00020952881,0.00018326267,0.000997394,0.0013476644,0.035741698],"genre_scores_gemma":[0.9146649,0.00063084724,0.05373578,0.00009575682,0.000050709223,0.0003529915,0.0006816046,0.00013887657,0.029648412],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996772,0.000084763924,0.000015249905,0.00006813773,0.00010736471,0.000047285524],"domain_scores_gemma":[0.9992874,0.00043149534,0.00004910956,0.000044774333,0.00015832364,0.00002890622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005282278,0.00060981215,0.00067063136,0.00069580646,0.0007449669,0.002326568,0.0011115036,0.0019753575,0.007266578],"category_scores_gemma":[0.0016985033,0.000357235,0.00079939014,0.0005116423,0.00067330763,0.0015126005,0.0006996485,0.0010303947,0.0008158035],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010574013,0.000046853886,0.00083454035,0.00009392335,0.0000326998,0.00030194176,0.0001464612,0.944093,0.0023522065,0.042505264,0.0010794173,0.008407965],"study_design_scores_gemma":[0.000016717335,0.00001513983,0.00013408407,0.0000084131825,0.000008597833,0.000035402652,0.000023540288,0.9935656,0.0004964746,0.004292512,0.0013975786,0.0000059049626],"about_ca_topic_score_codex":0.018824413,"about_ca_topic_score_gemma":0.010334387,"teacher_disagreement_score":0.018824413,"about_ca_system_score_codex":0.0014073336,"about_ca_system_score_gemma":0.0011838587,"threshold_uncertainty_score":0.03742963},"labels":[],"label_agreement":null},{"id":"W4401580197","doi":"10.33424/futurum521","title":"How should we interact with strangers on the bus?","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Social Sciences and Humanities Research Council; University of British Columbia","funders":"","keywords":"Computer science; Psychology; Business","score_opus":0.035157705274766464,"score_gpt":0.23579210393256642,"score_spread":0.20063439865779994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401580197","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11939283,0.012704888,0.017750304,0.60930973,0.008456285,0.00017958904,0.00026570374,0.00043825968,0.23150234],"genre_scores_gemma":[0.84502804,0.013929557,0.0083031,0.07684504,0.0019869523,0.00019893593,0.00031068447,0.00040955518,0.052988023],"study_design_codex":"qualitative","study_design_gemma":"not_applicable","domain_scores_codex":[0.9900855,0.006877029,0.00020193559,0.000723215,0.0012773523,0.0008349397],"domain_scores_gemma":[0.9881491,0.002014877,0.0012961879,0.00067235366,0.0026980143,0.0051693968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005074531,0.0006372104,0.0007087367,0.0010306808,0.012111614,0.011856617,0.0015363795,0.0052039814,0.008958011],"category_scores_gemma":[0.023721805,0.00047915376,0.0006446307,0.0006396284,0.018079327,0.013377788,0.00446683,0.0072872285,0.0067709885],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011466427,0.0002761084,0.04593811,0.0005982635,0.0002262239,0.002025951,0.4855275,0.0004175248,0.0019138516,0.09329926,0.24114062,0.12852184],"study_design_scores_gemma":[0.000018981384,0.00012951411,0.008387362,0.0005921346,0.000065756474,0.0015820899,0.39655298,0.00036581562,0.00044189775,0.057001065,0.53471273,0.00014968395],"about_ca_topic_score_codex":0.016180638,"about_ca_topic_score_gemma":0.018093582,"teacher_disagreement_score":0.016180638,"about_ca_system_score_codex":0.0022205473,"about_ca_system_score_gemma":0.0028714247,"threshold_uncertainty_score":0.03217292},"labels":[],"label_agreement":null},{"id":"W4401597675","doi":"10.1109/icmlcn59089.2024.10624773","title":"Reinforcement Learning-Based Edge-User Allocation with Fairness for Multisource Real-Time Systems","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reinforcement learning; Computer science; Enhanced Data Rates for GSM Evolution; Artificial intelligence; Reinforcement; Machine learning; Engineering","score_opus":0.008028501797242588,"score_gpt":0.2210883521494911,"score_spread":0.2130598503522485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401597675","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.038535256,0.0006897657,0.955745,0.000497407,0.00014482728,0.00007904542,0.00005584595,0.0006842876,0.0035685657],"genre_scores_gemma":[0.95961404,0.00011414057,0.03712954,0.0002469302,0.000073809744,0.00007101424,0.000051851082,0.000080285245,0.002618383],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910444,0.00028198733,0.00004035795,0.00021727044,0.00013558951,0.00022036345],"domain_scores_gemma":[0.99734855,0.001791725,0.00020807746,0.00012471646,0.0003138369,0.0002130391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019173467,0.0012231593,0.0016728194,0.00040486146,0.00058895926,0.0010747649,0.0017448599,0.0011963722,0.0032754894],"category_scores_gemma":[0.005134839,0.00047041188,0.0004945858,0.00040542457,0.0011266012,0.0011826019,0.0013497163,0.0019289375,0.00047831118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000069698086,0.00005488045,0.00031247357,0.00003179695,0.000018228986,0.00004093316,0.000026453397,0.9842045,0.0006553639,0.0024576907,0.0005998817,0.011528103],"study_design_scores_gemma":[0.000005535522,0.000008717756,0.000026631926,0.0000018444782,0.0000019060851,0.0000043658074,0.0000029931957,0.9984237,0.00009675649,0.0013523743,0.00007332177,0.0000019983052],"about_ca_topic_score_codex":0.006660417,"about_ca_topic_score_gemma":0.00656885,"teacher_disagreement_score":0.006660417,"about_ca_system_score_codex":0.0012726634,"about_ca_system_score_gemma":0.0014576238,"threshold_uncertainty_score":0.013243318},"labels":[],"label_agreement":null},{"id":"W4401633964","doi":"10.1109/ojvt.2024.3443630","title":"Navigating the Handover: Reviewing Takeover Requests in Level 3 Autonomous Vehicles","year":2024,"lang":"en","type":"article","venue":"IEEE Open Journal of Vehicular Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Handover; Computer science; Computer network; Business; Telecommunications","score_opus":0.03729456897353877,"score_gpt":0.3148996253082061,"score_spread":0.2776050563346673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401633964","genre_codex":"empirical","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58683556,0.14420885,0.19200125,0.018628927,0.0050013787,0.0010982555,0.0005393274,0.0013455349,0.050340842],"genre_scores_gemma":[0.8317726,0.07712801,0.06504859,0.0027592608,0.0012826768,0.00026881712,0.0011809025,0.00034997062,0.02020919],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9957072,0.002036486,0.00049082073,0.00030718613,0.0012084275,0.00024990615],"domain_scores_gemma":[0.9891584,0.005445626,0.0011356561,0.0003276134,0.0035707909,0.00036199074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003715995,0.00050876377,0.00031093878,0.0018623327,0.0009859687,0.0034059368,0.0010817477,0.0012774392,0.0010971889],"category_scores_gemma":[0.017963357,0.00022804091,0.00033233897,0.0012656166,0.0008397175,0.0033356766,0.0009962854,0.00069643406,0.0006067993],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023418118,0.00015376121,0.019162066,0.00485653,0.00006014735,0.0029263396,0.04491864,0.007954494,0.008968034,0.011446822,0.029091109,0.8702278],"study_design_scores_gemma":[0.000023089779,0.0007612292,0.026964422,0.0054636593,0.00019881898,0.0032383248,0.11251685,0.01461751,0.013326796,0.009844149,0.8128433,0.00020177414],"about_ca_topic_score_codex":0.004666644,"about_ca_topic_score_gemma":0.0127880685,"teacher_disagreement_score":0.004666644,"about_ca_system_score_codex":0.0020109592,"about_ca_system_score_gemma":0.0025235382,"threshold_uncertainty_score":0.019652307},"labels":[],"label_agreement":null},{"id":"W4401707949","doi":"10.1155/2024/6671487","title":"Impact of Level 4 Automated Vehicles on Mode Choice Using a Needs‐Based Approach","year":2024,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Baidu","keywords":"Mode choice; Mode (computer interface); Transport engineering; Computer science; Engineering; Public transport; Human–computer interaction","score_opus":0.03622320057092725,"score_gpt":0.3231529233152811,"score_spread":0.28692972274435385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401707949","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98349816,0.000068029214,0.009988954,0.0002471257,0.000008851059,0.00009131173,0.0002542889,0.000015847063,0.005827555],"genre_scores_gemma":[0.99643266,0.00003812901,0.0022660536,0.000017730299,0.000002850312,0.000049319646,0.00009975924,0.0000028289428,0.0010907107],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99865806,0.00070054026,0.000048174134,0.00014245158,0.00025269573,0.00019797712],"domain_scores_gemma":[0.99481875,0.0032173358,0.00064963056,0.00022152305,0.0007496909,0.00034308722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015878864,0.00051281974,0.00030619724,0.0014025839,0.00041401293,0.0015211978,0.00088690117,0.0008786969,0.0077939737],"category_scores_gemma":[0.0055890395,0.00032467936,0.0015435516,0.0009705908,0.00048949814,0.0017480553,0.0011567848,0.0009153748,0.0003453867],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008178504,0.0015127682,0.73722607,0.00029574768,0.00063990214,0.00072878465,0.0022820863,0.17324337,0.0025499433,0.033266265,0.001049361,0.04638782],"study_design_scores_gemma":[0.000046088237,0.0010278627,0.30319375,0.00007473458,0.00040642894,0.00017933261,0.005384311,0.6682142,0.001176409,0.016875265,0.00331006,0.00011159829],"about_ca_topic_score_codex":0.017893463,"about_ca_topic_score_gemma":0.02201694,"teacher_disagreement_score":0.017893463,"about_ca_system_score_codex":0.0026403542,"about_ca_system_score_gemma":0.001311964,"threshold_uncertainty_score":0.03557861},"labels":[],"label_agreement":null},{"id":"W4401722720","doi":"10.1109/rew61692.2024.00047","title":"Towards an Approach for Generating iStar Goal Models from Journey Maps","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science","score_opus":0.04380792340475221,"score_gpt":0.2642802207603853,"score_spread":0.22047229735563312,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401722720","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002765255,0.000044838227,0.9901259,0.00023001777,0.00002554313,0.00018911816,0.0006673964,0.0024700887,0.003481907],"genre_scores_gemma":[0.036205567,0.00015252098,0.95771176,0.00007544715,0.000008595271,0.000352764,0.0024992898,0.00081881287,0.002175182],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99760973,0.0008342334,0.00022323507,0.00041116012,0.00077770447,0.00014400706],"domain_scores_gemma":[0.9944014,0.0018124087,0.00039695692,0.0014835531,0.0016904174,0.00021530727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003455876,0.0015694973,0.0006479417,0.0037339975,0.0014441265,0.004774794,0.0024521449,0.0015304084,0.006813118],"category_scores_gemma":[0.011120282,0.0016033738,0.003529647,0.0027473099,0.0013771193,0.0058798697,0.0060100956,0.0027801078,0.0031597086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024343157,0.00034963718,0.0049970215,0.0012787685,0.00022521042,0.0009023347,0.009585443,0.19495276,0.008559195,0.450599,0.020309584,0.3079976],"study_design_scores_gemma":[0.000046762783,0.00013114697,0.0008916832,0.0004186701,0.00010159547,0.00043954526,0.0033438026,0.60039973,0.013629075,0.20291398,0.1775406,0.00014336989],"about_ca_topic_score_codex":0.009005208,"about_ca_topic_score_gemma":0.020916758,"teacher_disagreement_score":0.009005208,"about_ca_system_score_codex":0.0016944646,"about_ca_system_score_gemma":0.003749068,"threshold_uncertainty_score":0.0227921},"labels":[],"label_agreement":null},{"id":"W4401841840","doi":"10.1016/j.trc.2024.104810","title":"Carsharing adoption dynamics considering service type and area expansions with insights from a Montreal case study","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part C Emerging Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"Japan Society for the Promotion of Science","keywords":"Service (business); Transport engineering; Dynamics (music); Type (biology); Operations research; Engineering; Computer science; Business; Marketing; Sociology; Geology","score_opus":0.06427861801580712,"score_gpt":0.32141061000886517,"score_spread":0.25713199199305803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401841840","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9922978,0.00027839097,0.0013775644,0.0005243986,0.000007234588,0.000049593473,0.0026739326,0.00005103324,0.0027400737],"genre_scores_gemma":[0.9933878,0.00019356841,0.0017493864,0.000054394855,0.000010053001,0.000030152087,0.0029612111,0.0000127553185,0.00160065],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99956506,0.0001359478,0.000013693966,0.00009449675,0.00007189119,0.00011892493],"domain_scores_gemma":[0.99819726,0.0008073338,0.00023799342,0.0001457634,0.00040872407,0.00020293969],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012078466,0.0004579262,0.0002747796,0.0012862466,0.00066534267,0.00128324,0.0012871627,0.00063773897,0.0022472239],"category_scores_gemma":[0.0027626914,0.00020119132,0.00058352813,0.002834521,0.0006486301,0.00096299394,0.000635939,0.0006711221,0.0002705462],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031010853,0.00045163362,0.73268276,0.00015186807,0.00019992764,0.0020607733,0.002134698,0.20898324,0.0025439158,0.0074506085,0.01051953,0.03251086],"study_design_scores_gemma":[0.000058299403,0.0001856154,0.49574283,0.0000577362,0.00010659299,0.00020266994,0.00545047,0.48192012,0.0009158747,0.001308525,0.013933614,0.00011766262],"about_ca_topic_score_codex":0.86087537,"about_ca_topic_score_gemma":0.90469956,"teacher_disagreement_score":0.13912463,"about_ca_system_score_codex":0.0074949227,"about_ca_system_score_gemma":0.0022566307,"threshold_uncertainty_score":0.2798879},"labels":[],"label_agreement":null},{"id":"W4401882612","doi":"10.1145/3670653.3670663","title":"Deriving Non-Driving-Related Activities in Highly Automated Driving via an Autoethnographic Approach by Traveling Canada in a Recreational Vehicle","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Recreation; Remotely operated underwater vehicle; Computer science; Aeronautics; Autoethnography; Human–computer interaction; Transport engineering; Simulation; Marine engineering; Engineering; Mobile robot; Artificial intelligence; Robot; Sociology; Ecology","score_opus":0.005745039655452139,"score_gpt":0.21192426544342327,"score_spread":0.20617922578797113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401882612","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98838204,0.00007689154,0.0059394627,0.00037969174,0.00002351812,0.00016103139,0.00007065378,0.00002063178,0.0049460847],"genre_scores_gemma":[0.9931243,0.00014920962,0.0032067355,0.00022527036,0.0000121658,0.00015290688,0.000067437206,0.000020731306,0.0030412485],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.99535143,0.0036775407,0.00011759911,0.0002765706,0.00024089443,0.00033603614],"domain_scores_gemma":[0.9945229,0.003641581,0.00043773252,0.00053378736,0.00047652284,0.00038752507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003964757,0.0005232532,0.00027410244,0.00085183507,0.0029966915,0.0028325957,0.0008180053,0.00087200856,0.0023353016],"category_scores_gemma":[0.0064006574,0.0003378032,0.00030177043,0.0005374657,0.00408845,0.0020324548,0.0033009052,0.001328154,0.00040323296],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004893873,0.00031272808,0.015125421,0.00019028177,0.000013576841,0.0009270989,0.96356773,0.000187226,0.002874526,0.002219398,0.0007885818,0.013744423],"study_design_scores_gemma":[0.000010670105,0.0001792673,0.009364756,0.00020910277,0.000015374917,0.00083367317,0.9645474,0.00058686564,0.0023513623,0.0013810849,0.020469725,0.000050642364],"about_ca_topic_score_codex":0.0044620675,"about_ca_topic_score_gemma":0.012752407,"teacher_disagreement_score":0.99553794,"about_ca_system_score_codex":0.0013127652,"about_ca_system_score_gemma":0.0013340166,"threshold_uncertainty_score":0.020967841},"labels":[],"label_agreement":null},{"id":"W4401936418","doi":"10.1016/j.tbs.2024.100891","title":"Labor issues from the perspective of drivers on the Uber and Lyft apps and the impact on riders who use wheelchairs","year":2024,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Perspective (graphical); Poison control; Injury prevention; Suicide prevention; Psychology; Engineering; Computer science; Medical emergency; Medicine; Artificial intelligence","score_opus":0.01420213675749185,"score_gpt":0.26234864480282516,"score_spread":0.2481465080453333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401936418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9770333,0.0010505033,0.0007385932,0.0075830626,0.00009843224,0.00007757073,0.00010302386,0.000010287586,0.01330527],"genre_scores_gemma":[0.9921077,0.0011662747,0.00030472194,0.0015248917,0.000019990834,0.00008728747,0.000039594877,0.000014171622,0.004735293],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9960068,0.0023809308,0.00014343917,0.00015531408,0.00051604945,0.00079751643],"domain_scores_gemma":[0.9928468,0.004159509,0.0007465491,0.00016460774,0.001329144,0.0007533737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005245436,0.0003730884,0.00031506692,0.0010708214,0.006590243,0.0053896033,0.0008491898,0.0012498171,0.004445382],"category_scores_gemma":[0.010190077,0.00039263273,0.00053347845,0.00075639,0.0032770236,0.0053039547,0.004413527,0.0019685426,0.00063664827],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002244327,0.00006523511,0.020744665,0.00016527234,0.000008663516,0.00054731464,0.96736187,0.000021769654,0.00026557417,0.0011672172,0.001826588,0.0078033106],"study_design_scores_gemma":[0.0000013121428,0.000025994766,0.0033450532,0.000101529135,0.0000062407194,0.00008095434,0.9891389,0.000024053565,0.000084619554,0.0001214336,0.0070628794,0.000006960412],"about_ca_topic_score_codex":0.031654544,"about_ca_topic_score_gemma":0.048362926,"teacher_disagreement_score":0.031654544,"about_ca_system_score_codex":0.003251487,"about_ca_system_score_gemma":0.0045050685,"threshold_uncertainty_score":0.0629406},"labels":[],"label_agreement":null},{"id":"W4401937015","doi":"10.1016/j.retrec.2024.101476","title":"Success in tandem? The impact of the introduction of e-bike sharing on bike sharing usage","year":2024,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"","keywords":"Bike sharing; Transport engineering; Car sharing; Tandem; Business; Computer science; Engineering","score_opus":0.058750155510847495,"score_gpt":0.3535912489129293,"score_spread":0.2948410934020818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401937015","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9821082,0.00024780375,0.0003131311,0.0031563353,0.00011207684,0.000027324402,0.00012999678,0.00003284271,0.01387233],"genre_scores_gemma":[0.9967174,0.00009951813,0.000118223885,0.00018418444,0.000044112705,0.000016156568,0.00006741361,0.000014331725,0.0027387945],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.995424,0.0011315028,0.00022675225,0.00054928265,0.0007505399,0.0019179228],"domain_scores_gemma":[0.9695454,0.009458583,0.0045599737,0.0014136429,0.0033085023,0.01171388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041683004,0.00040783273,0.00066336093,0.00068604626,0.0020949636,0.0056406646,0.0014338966,0.0026848095,0.024460552],"category_scores_gemma":[0.026850313,0.00042514227,0.000680544,0.0013370679,0.0015527059,0.0051705386,0.004370979,0.0031255363,0.0044262554],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004289413,0.006310226,0.78015333,0.00029588636,0.00042240816,0.0010333824,0.012977447,0.0029694473,0.0033203785,0.013556404,0.007659522,0.1670122],"study_design_scores_gemma":[0.00019665984,0.002891796,0.8977757,0.0002927522,0.0003608525,0.00035566717,0.062354475,0.0037163687,0.002315292,0.006046293,0.023550203,0.00014385486],"about_ca_topic_score_codex":0.014111298,"about_ca_topic_score_gemma":0.018875165,"teacher_disagreement_score":0.024460552,"about_ca_system_score_codex":0.0014178933,"about_ca_system_score_gemma":0.0052177124,"threshold_uncertainty_score":0.08182871},"labels":[],"label_agreement":null},{"id":"W4401946718","doi":"10.3390/su16177454","title":"Environmental Impacts of Transportation Network Company (TNC)/Ride-Hailing Services: Evaluating Net Vehicle Miles Traveled and Greenhouse Gas Emission Impacts within San Francisco, Los Angeles, and Washington, D.C. Using Survey and Activity Data","year":2024,"lang":"en","type":"article","venue":"Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Hewitt Foundation","keywords":"Metropolitan area; Vehicle miles of travel; Greenhouse gas; Transport engineering; Geography; Agricultural economics; Population; Engineering; Business; Environmental science; Economics; Archaeology","score_opus":0.024793186959494413,"score_gpt":0.29002577348439634,"score_spread":0.26523258652490195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401946718","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99452114,0.00018589136,0.00037059316,0.000095600466,0.000010557235,0.000056700257,0.0019887658,0.000014207249,0.0027565723],"genre_scores_gemma":[0.9953962,0.00024392425,0.00066462497,0.000031915017,0.000008645977,0.00004370398,0.0027937398,0.0000063498715,0.0008108964],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990025,0.00023754638,0.000054772037,0.00014232537,0.00043514528,0.00012774144],"domain_scores_gemma":[0.99884254,0.00022235479,0.00032542148,0.000056730463,0.00044986478,0.00010312215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011070864,0.000685107,0.00020291787,0.0013077111,0.0002734199,0.00079819356,0.00035479284,0.0003022507,0.00084813655],"category_scores_gemma":[0.0016797668,0.00014425092,0.00069869997,0.0017384008,0.0002878705,0.0008776405,0.0005869527,0.0003878394,0.00018188574],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013984453,0.0002805748,0.9620427,0.00009952531,0.00030004152,0.00015761006,0.00021700545,0.012828916,0.00075272087,0.00022507203,0.0013140906,0.021642037],"study_design_scores_gemma":[0.000006624571,0.00044544926,0.97772574,0.00004871722,0.00017037726,0.000053228123,0.0017963679,0.015555263,0.0014175125,0.00014406655,0.0026169524,0.000019736017],"about_ca_topic_score_codex":0.14049536,"about_ca_topic_score_gemma":0.23897354,"teacher_disagreement_score":0.14049536,"about_ca_system_score_codex":0.0021834332,"about_ca_system_score_gemma":0.001276336,"threshold_uncertainty_score":0.27935517},"labels":[],"label_agreement":null},{"id":"W4401979611","doi":"10.1287/trsc.2022.0418","title":"Heatmap Design for Probabilistic Driver Repositioning in Crowdsourced Delivery","year":2024,"lang":"en","type":"article","venue":"Transportation Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo; Toronto Metropolitan University","funders":"","keywords":"Probabilistic logic; Crowdsourcing; Computer science; Transport engineering; Engineering; Artificial intelligence; World Wide Web","score_opus":0.025921696902829673,"score_gpt":0.26634226731243993,"score_spread":0.24042057040961026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401979611","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015245289,0.00014239445,0.9803678,0.00023353279,0.00006865144,0.00017144368,0.00015392988,0.00057629816,0.0030406497],"genre_scores_gemma":[0.8286508,0.00018289477,0.16584633,0.00012618868,0.00004588147,0.0005503532,0.00024444613,0.00014284873,0.0042103967],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985885,0.0005159714,0.0000643328,0.00036006255,0.00025712568,0.0002140551],"domain_scores_gemma":[0.9976387,0.001194415,0.00024429505,0.00023222085,0.00046001218,0.00023040183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021315455,0.0010856093,0.0010207858,0.0007840321,0.000768122,0.0014396529,0.0023813,0.0010880491,0.0060953],"category_scores_gemma":[0.0062517016,0.0008113683,0.0007979832,0.00078090234,0.0010353823,0.0018386617,0.0023800058,0.0014441796,0.00070261286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010685424,0.00004929935,0.00055766606,0.000062191735,0.000022755528,0.00006153058,0.00010335681,0.9582658,0.0014487163,0.013045549,0.001169846,0.025106477],"study_design_scores_gemma":[0.0000108875765,0.00004106323,0.00011765189,0.0000055713876,0.000005878646,0.000009851727,0.000029064895,0.9914534,0.00051178865,0.0067365505,0.001069326,0.000009006623],"about_ca_topic_score_codex":0.0074367346,"about_ca_topic_score_gemma":0.0048339013,"teacher_disagreement_score":0.0074367346,"about_ca_system_score_codex":0.0016542271,"about_ca_system_score_gemma":0.0020092328,"threshold_uncertainty_score":0.020390749},"labels":[],"label_agreement":null},{"id":"W4401990836","doi":"10.1109/tsmc.2024.3443116","title":"Flexible Districting Policy for the Multiperiod Emergency Resource Allocation Problem With Demand Priority","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Science and Technology Support Plan for Youth Innovation of Colleges and Universities of Shandong Province of China; National Natural Science Foundation of China","keywords":"Resource allocation; Operations research; Resource (disambiguation); Computer science; Business; Engineering; Computer network","score_opus":0.013183674520386924,"score_gpt":0.23877362032589158,"score_spread":0.22558994580550465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401990836","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.065744095,0.00049497467,0.92628497,0.00038027542,0.00008207524,0.000120844416,0.00013361798,0.0002031713,0.0065559987],"genre_scores_gemma":[0.9094371,0.0003034259,0.086544655,0.000080845035,0.00003147045,0.0001313727,0.00015824888,0.00004440187,0.0032684077],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994116,0.00020850908,0.000030753035,0.000104412095,0.00008429945,0.00016035944],"domain_scores_gemma":[0.99962366,0.00017885646,0.000053599804,0.000024843708,0.000059595994,0.00005946944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007561229,0.00072495255,0.00095022377,0.00055062183,0.00057374185,0.0010819008,0.0008824302,0.0008677458,0.002938814],"category_scores_gemma":[0.0010473646,0.00041337957,0.0007106301,0.0007108262,0.00038020537,0.0011220312,0.0007885405,0.00087651063,0.00018098443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007051828,0.000049512622,0.0005558175,0.0000863312,0.000022813707,0.000088588866,0.000045021345,0.9685675,0.0015650283,0.010031936,0.0009426675,0.017974224],"study_design_scores_gemma":[0.000013597584,0.000029970184,0.0001723486,0.0000045427946,0.000006415869,0.00002320736,0.000030969557,0.99603635,0.00034485423,0.0026673595,0.0006650533,0.0000054773054],"about_ca_topic_score_codex":0.0060079964,"about_ca_topic_score_gemma":0.00520085,"teacher_disagreement_score":0.0060079964,"about_ca_system_score_codex":0.0009919249,"about_ca_system_score_gemma":0.001344932,"threshold_uncertainty_score":0.011946082},"labels":[],"label_agreement":null},{"id":"W4402001824","doi":"10.1080/09687599.2024.2397731","title":"Why app-hailed transportation remains inadequately accessible to wheelchair users","year":2024,"lang":"en","type":"article","venue":"Disability & Society","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Wheelchair; Physical medicine and rehabilitation; Psychology; Internet privacy; Computer science; Human–computer interaction; World Wide Web; Medicine","score_opus":0.01761202478480441,"score_gpt":0.2683911610939613,"score_spread":0.2507791363091569,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402001824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87691045,0.0034759594,0.0030061402,0.06462122,0.0004590067,0.00007123508,0.0005286877,0.00027399647,0.050653275],"genre_scores_gemma":[0.9847727,0.0018872871,0.0008780635,0.0048701586,0.00006044461,0.000043347536,0.0001531998,0.00007732222,0.007257422],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99777335,0.000699923,0.00015912773,0.00019984687,0.0005681024,0.00059961865],"domain_scores_gemma":[0.99480224,0.0014972656,0.000729787,0.00031562985,0.0017861095,0.0008689774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001453222,0.00019690773,0.0002669366,0.00059457374,0.0025360025,0.004227858,0.00092026324,0.0014209151,0.011433538],"category_scores_gemma":[0.012500613,0.00027474447,0.0003052299,0.0007450059,0.001412148,0.0044842106,0.0028200706,0.0015197167,0.0026666918],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003066704,0.0004702688,0.35240737,0.0010747828,0.00008534333,0.004457265,0.12923537,0.00038383607,0.0034318545,0.0251332,0.13048486,0.35252914],"study_design_scores_gemma":[0.000036594825,0.0003644901,0.25248232,0.0031140787,0.00017310199,0.0069783158,0.382335,0.0019794977,0.0019740677,0.011882184,0.33853066,0.0001497757],"about_ca_topic_score_codex":0.039385527,"about_ca_topic_score_gemma":0.045919556,"teacher_disagreement_score":0.039385527,"about_ca_system_score_codex":0.0012964377,"about_ca_system_score_gemma":0.0026509345,"threshold_uncertainty_score":0.078312576},"labels":[],"label_agreement":null},{"id":"W4402035413","doi":"10.32920/26882509","title":"Life Cycle Effects of Mobility Technologies and Services","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; Toronto Metropolitan University","funders":"","keywords":"Business","score_opus":0.00494339964120846,"score_gpt":0.2191336797337238,"score_spread":0.21419028009251534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402035413","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7769115,0.0038957146,0.03200479,0.002236951,0.00018056651,0.0005515269,0.013845189,0.00019317665,0.17018047],"genre_scores_gemma":[0.9735224,0.0014062016,0.0028370155,0.000109154884,0.00001397032,0.00009324144,0.0018400287,0.000030562882,0.02014749],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9992023,0.00019381069,0.00002632837,0.00007562489,0.00026390576,0.00023798144],"domain_scores_gemma":[0.99862754,0.0005362565,0.00018335575,0.00007159035,0.00049055304,0.00009072008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078743557,0.000593129,0.00020782185,0.0012521698,0.00044754174,0.0013067039,0.0005854663,0.0005797852,0.011520002],"category_scores_gemma":[0.0034038466,0.0002717999,0.0010335254,0.0012491114,0.00044171858,0.0013091012,0.00073024305,0.00048788733,0.0007955468],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006021243,0.00022707047,0.027301144,0.0004203064,0.00019323485,0.0005933336,0.00020208744,0.7486306,0.008309438,0.09112705,0.00818845,0.11420515],"study_design_scores_gemma":[0.000087829314,0.0010488111,0.05578591,0.00019200562,0.00033332326,0.00049917586,0.0014907941,0.7679351,0.015803767,0.055560805,0.10113343,0.00012905999],"about_ca_topic_score_codex":0.041233577,"about_ca_topic_score_gemma":0.030264096,"teacher_disagreement_score":0.041233577,"about_ca_system_score_codex":0.0048039244,"about_ca_system_score_gemma":0.0022882628,"threshold_uncertainty_score":0.08198714},"labels":[],"label_agreement":null},{"id":"W4402169468","doi":"10.32920/26866426","title":"A Platform for Empowerment: Addressing the Emerging Needs of E-Bike Couriers in Toronto","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Empowerment; Business; Transport engineering; Economic growth; Engineering; Economics","score_opus":0.037114440418680276,"score_gpt":0.313481337007253,"score_spread":0.2763668965885727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402169468","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9516244,0.000834192,0.0005190902,0.015522088,0.00008783879,0.00011187345,0.00006951198,0.000018029254,0.031213064],"genre_scores_gemma":[0.9906508,0.00070543005,0.00041572412,0.0005319845,0.0000116188,0.00003669139,0.000043589473,0.000008633141,0.007595582],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9979577,0.0006840604,0.00004207057,0.00011168091,0.00021813302,0.0009862176],"domain_scores_gemma":[0.9975183,0.00044133316,0.0001760181,0.00005131875,0.00031443592,0.0014987086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015689589,0.0003187985,0.00018605786,0.00050179614,0.014304648,0.004296892,0.00086111407,0.000995046,0.005621892],"category_scores_gemma":[0.0025352982,0.00025938964,0.0001997794,0.00085931685,0.0054257778,0.002422877,0.0061514964,0.001583633,0.00025933818],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000074524345,0.00007739505,0.029772373,0.00032021588,0.000012836651,0.0031954828,0.91240394,0.00019420205,0.0023455406,0.013113079,0.01263245,0.025858035],"study_design_scores_gemma":[0.0000051795687,0.000034963803,0.017910143,0.0001050799,0.0000076194647,0.00010307903,0.9328842,0.00015377518,0.00021014828,0.00050066295,0.04807204,0.0000130674625],"about_ca_topic_score_codex":0.7389594,"about_ca_topic_score_gemma":0.90854424,"teacher_disagreement_score":0.7389594,"about_ca_system_score_codex":0.028669104,"about_ca_system_score_gemma":0.042375818,"threshold_uncertainty_score":0.5251559},"labels":[],"label_agreement":null},{"id":"W4402197129","doi":"10.32920/26866426.v1","title":"A Platform for Empowerment: Addressing the Emerging Needs of E-Bike Couriers in Toronto","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Empowerment; Business; Regional science; Sociology; Economic growth; Economics","score_opus":0.037114440418680276,"score_gpt":0.313481337007253,"score_spread":0.2763668965885727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402197129","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9516244,0.000834192,0.0005190902,0.015522088,0.00008783879,0.00011187345,0.00006951198,0.000018029254,0.031213064],"genre_scores_gemma":[0.9906508,0.00070543005,0.00041572412,0.0005319845,0.0000116188,0.00003669139,0.000043589473,0.000008633141,0.007595582],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9979577,0.0006840604,0.00004207057,0.00011168091,0.00021813302,0.0009862176],"domain_scores_gemma":[0.9975183,0.00044133316,0.0001760181,0.00005131875,0.00031443592,0.0014987086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015689589,0.0003187985,0.00018605786,0.00050179614,0.014304648,0.004296892,0.00086111407,0.000995046,0.005621892],"category_scores_gemma":[0.0025352982,0.00025938964,0.0001997794,0.00085931685,0.0054257778,0.002422877,0.0061514964,0.001583633,0.00025933818],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000074524345,0.00007739505,0.029772373,0.00032021588,0.000012836651,0.0031954828,0.91240394,0.00019420205,0.0023455406,0.013113079,0.01263245,0.025858035],"study_design_scores_gemma":[0.0000051795687,0.000034963803,0.017910143,0.0001050799,0.0000076194647,0.00010307903,0.9328842,0.00015377518,0.00021014828,0.00050066295,0.04807204,0.0000130674625],"about_ca_topic_score_codex":0.7389594,"about_ca_topic_score_gemma":0.90854424,"teacher_disagreement_score":0.26104063,"about_ca_system_score_codex":0.028669104,"about_ca_system_score_gemma":0.042375818,"threshold_uncertainty_score":0.5251559},"labels":[],"label_agreement":null},{"id":"W4402271878","doi":"10.1016/j.tre.2024.103749","title":"A math-heuristic and exact algorithm for first-mile ridesharing problem with passenger service quality preferences","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part E Logistics and Transportation Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"China Scholarship Council; National Natural Science Foundation of China","keywords":"Heuristic; Service quality; Mile; Quality (philosophy); Computer science; Transport engineering; Service (business); Mathematical optimization; Engineering; Operations research; Mathematics; Business; Marketing; Geography","score_opus":0.1185667033840764,"score_gpt":0.37285745968623607,"score_spread":0.2542907563021597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402271878","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045894343,0.0009602974,0.9163516,0.0012110156,0.000429651,0.0008167912,0.001036907,0.0017898941,0.031509575],"genre_scores_gemma":[0.2349545,0.00045434808,0.75310874,0.00051004137,0.00019335738,0.00069648866,0.0012179817,0.0002793128,0.008585225],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990214,0.00020438305,0.000040181672,0.0002770492,0.00017456154,0.0002824583],"domain_scores_gemma":[0.99814665,0.00121666,0.00010555284,0.00015704666,0.00022214225,0.00015195187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013447911,0.0017207626,0.002867359,0.0018438884,0.001408435,0.002270649,0.003963219,0.003930681,0.015433941],"category_scores_gemma":[0.0035565863,0.0010784571,0.002207123,0.0021514425,0.0011077679,0.0025101164,0.0019685014,0.0023340809,0.001426512],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025809137,0.000431257,0.0007744399,0.00029655325,0.00007540693,0.000127913,0.0001239391,0.86449385,0.0012805403,0.017933613,0.011275129,0.10292931],"study_design_scores_gemma":[0.00010357198,0.000055152115,0.00018837223,0.000020167774,0.000024502515,0.000037983515,0.000064556334,0.9877916,0.00023956988,0.010188625,0.0012717898,0.000014131421],"about_ca_topic_score_codex":0.022022927,"about_ca_topic_score_gemma":0.01691386,"teacher_disagreement_score":0.022022927,"about_ca_system_score_codex":0.0028849111,"about_ca_system_score_gemma":0.004855493,"threshold_uncertainty_score":0.05163169},"labels":[],"label_agreement":null},{"id":"W4402290502","doi":"10.1016/j.cstp.2024.101292","title":"Car ownership, carsharing, neighbourhood types and travel attitudes: A latent-cluster analysis","year":2024,"lang":"en","type":"article","venue":"Case Studies on Transport Policy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"National Research Council Canada; Fonds de recherche du Québec – Nature et technologies; Ministère de l'Économie, de l’Innovation et des Exportations du Québec","keywords":"Neighbourhood (mathematics); Business; Latent class model; Cluster (spacecraft); Travel behavior; Transport engineering; Marketing; Geography; Regional science; Computer science; Engineering; Mathematics","score_opus":0.02816510719907675,"score_gpt":0.3028063431363125,"score_spread":0.2746412359372358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402290502","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9896075,0.00016033986,0.005288141,0.00028036532,0.000009586953,0.00016553943,0.003039082,0.000056535868,0.0013929518],"genre_scores_gemma":[0.9901452,0.000085175154,0.00367172,0.000023313232,0.0000051006105,0.00010382451,0.0036521123,0.000012990304,0.0023005868],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990606,0.00036822545,0.000035054265,0.00016206934,0.00017960173,0.00019448265],"domain_scores_gemma":[0.99732095,0.0008096134,0.00043174846,0.00028756095,0.0007347396,0.00041548273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017027889,0.00054168026,0.00047155583,0.0019552342,0.0016909853,0.00170141,0.0011962348,0.0003688858,0.004730167],"category_scores_gemma":[0.003925116,0.0002679706,0.0014432123,0.003835124,0.000776169,0.00053890946,0.0015293785,0.0008085446,0.00049182854],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018750978,0.00020220384,0.9762082,0.0000637284,0.0004068251,0.000085045256,0.0016937917,0.0049485806,0.0003981345,0.0014882592,0.002261443,0.012056211],"study_design_scores_gemma":[0.000032866075,0.00012134806,0.93806314,0.000048175294,0.00023237683,0.000030645628,0.005545252,0.051862363,0.00029093013,0.0006266206,0.003097721,0.000048569764],"about_ca_topic_score_codex":0.899198,"about_ca_topic_score_gemma":0.8726768,"teacher_disagreement_score":0.899198,"about_ca_system_score_codex":0.008718671,"about_ca_system_score_gemma":0.008897875,"threshold_uncertainty_score":0.20279127},"labels":[],"label_agreement":null},{"id":"W4402423639","doi":"10.24908/iqurcp17958","title":"Development of Modified Ride-On-Cars for Children with Mobility Impairments","year":2024,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Transport engineering; Psychology; Aeronautics; Advertising; Physical medicine and rehabilitation; Business; Engineering; Medicine","score_opus":0.08991610104819618,"score_gpt":0.3550981088746362,"score_spread":0.26518200782644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402423639","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9777509,0.0004884629,0.011746926,0.00040556333,0.00007233531,0.0017760042,0.00039881634,0.00081367214,0.0065473025],"genre_scores_gemma":[0.7311761,0.0019147914,0.25607243,0.00024070441,0.000022019492,0.0026056466,0.0014398107,0.000175304,0.00635313],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99907875,0.00020666631,0.00009899735,0.00014003227,0.00029757567,0.0001778828],"domain_scores_gemma":[0.99891376,0.00019082145,0.00014003064,0.00011792594,0.0003843932,0.0002531107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001662113,0.0010307104,0.00044412204,0.0007423872,0.000512884,0.00063316524,0.0019462262,0.0005543425,0.0029371448],"category_scores_gemma":[0.0040684952,0.00041677392,0.0012136122,0.00025051448,0.00043023913,0.00080444384,0.0015721396,0.00063271227,0.0007834907],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063522847,0.008847524,0.14524758,0.0021070903,0.00019274447,0.0058559347,0.014077664,0.00421865,0.034779716,0.0008780837,0.012286477,0.7708733],"study_design_scores_gemma":[0.0007890221,0.02023336,0.64684576,0.001809579,0.00085674826,0.023094488,0.023881907,0.013096451,0.05337229,0.0014037769,0.21406856,0.0005480796],"about_ca_topic_score_codex":0.005938296,"about_ca_topic_score_gemma":0.018048551,"teacher_disagreement_score":0.005938296,"about_ca_system_score_codex":0.0007357982,"about_ca_system_score_gemma":0.0024579018,"threshold_uncertainty_score":0.011807442},"labels":[],"label_agreement":null},{"id":"W4402474524","doi":"10.1109/ccece59415.2024.10667146","title":"Autonomous Ride-Hailing Services: A Scalable Heuristic Approach for Efficient Transportation","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Lakehead University; Wilfrid Laurier University","funders":"","keywords":"Scalability; Heuristic; Computer science; Distributed computing; World Wide Web; Database; Artificial intelligence","score_opus":0.01010970653258179,"score_gpt":0.22293070168103293,"score_spread":0.21282099514845115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402474524","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11207313,0.000677728,0.8693317,0.00074137194,0.00009946662,0.00059094926,0.00038604453,0.00095019996,0.01514933],"genre_scores_gemma":[0.6714718,0.0003063007,0.3250055,0.00013209463,0.000042697375,0.00031297884,0.0002833136,0.0000946757,0.0023506985],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995382,0.0001630081,0.00001930849,0.000076670425,0.00007357006,0.00012934636],"domain_scores_gemma":[0.9992872,0.00045764263,0.000075114425,0.000042061423,0.00007160008,0.000066328525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008416894,0.0009594812,0.0009967269,0.0008170175,0.0006219311,0.0011609895,0.0017681482,0.0011436826,0.003953792],"category_scores_gemma":[0.0015662884,0.0004588801,0.0006839764,0.0008501246,0.000577059,0.0010364939,0.00091014494,0.0007776731,0.00031285704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007774353,0.00011966332,0.00052453415,0.00008046773,0.00004321396,0.000086094464,0.000046533904,0.9658838,0.0010552655,0.00539933,0.0011174013,0.025565824],"study_design_scores_gemma":[0.000016292544,0.000029387895,0.0000507662,0.000004409788,0.000007273292,0.000010524484,0.000031073803,0.99754566,0.00014717621,0.0017495393,0.0004045962,0.0000033541723],"about_ca_topic_score_codex":0.009945617,"about_ca_topic_score_gemma":0.013423815,"teacher_disagreement_score":0.009945617,"about_ca_system_score_codex":0.0011737221,"about_ca_system_score_gemma":0.002480853,"threshold_uncertainty_score":0.01977551},"labels":[],"label_agreement":null},{"id":"W4402509460","doi":"10.1016/j.cstp.2024.101294","title":"An agent-based simulation modeling framework for Mobility-as-a-Service (MaaS)","year":2024,"lang":"en","type":"article","venue":"Case Studies on Transport Policy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Service (business); Agent-based model; Transport engineering; Business; Engineering; Artificial intelligence; Marketing","score_opus":0.0633575464847876,"score_gpt":0.3834223978155145,"score_spread":0.32006485133072693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402509460","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008772709,0.00020247501,0.98146033,0.0005003934,0.00011707396,0.00015906715,0.00033356168,0.0013183589,0.007136102],"genre_scores_gemma":[0.48312908,0.0008432384,0.5038024,0.00023802317,0.00012839647,0.000694982,0.0009448731,0.0004007059,0.009818251],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991171,0.00039184885,0.000063748994,0.00012415973,0.0002105862,0.000092585804],"domain_scores_gemma":[0.99909985,0.00038787024,0.000082574625,0.00007429423,0.000236882,0.00011862339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016688529,0.0009047199,0.0011483135,0.0009579317,0.0011980998,0.0027131,0.0026923236,0.0018542566,0.004494316],"category_scores_gemma":[0.0029024223,0.00064983265,0.0016503031,0.00088133453,0.00080721703,0.0017238731,0.0020923754,0.001621874,0.0008693061],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022617654,0.00004426147,0.0003842884,0.00003573311,0.00004032317,0.0000740855,0.00008299612,0.9369959,0.00048287385,0.055723384,0.0009022097,0.005211257],"study_design_scores_gemma":[0.000005604074,0.000006314112,0.00002476546,0.000006315653,0.000007781896,0.000008039034,0.0000111830195,0.99274945,0.00008917127,0.0049277237,0.002158696,0.0000049836635],"about_ca_topic_score_codex":0.05090366,"about_ca_topic_score_gemma":0.030860236,"teacher_disagreement_score":0.05090366,"about_ca_system_score_codex":0.0021064829,"about_ca_system_score_gemma":0.003995791,"threshold_uncertainty_score":0.10121471},"labels":[],"label_agreement":null},{"id":"W4402547446","doi":"10.1007/s10479-024-06241-9","title":"An updated survey of attended home delivery and service problems with a focus on applications","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Focus (optics); Theory of computation; Computer science; Service (business); Operations research; Management science; Mathematics; Business; Engineering; Marketing; Algorithm","score_opus":0.14443607513241238,"score_gpt":0.3954565609906834,"score_spread":0.25102048585827097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402547446","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22318372,0.6996731,0.005660227,0.018145483,0.00096989924,0.00019791207,0.0053005605,0.00017228122,0.04669676],"genre_scores_gemma":[0.33047122,0.6480729,0.0049207048,0.002345921,0.00083817873,0.0001495576,0.005882397,0.00008607886,0.007232985],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99726945,0.0006031811,0.0004792776,0.00028610294,0.0010728978,0.00028908314],"domain_scores_gemma":[0.9844641,0.0089558875,0.002241074,0.00030507348,0.0034672453,0.0005665966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022840675,0.00047846689,0.0007446656,0.008894874,0.00076880126,0.0026516167,0.0008875609,0.0011663112,0.006963205],"category_scores_gemma":[0.010696321,0.00031499605,0.0007921454,0.016777582,0.000855033,0.0042915074,0.001238749,0.0011531892,0.00097354426],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017595255,0.0002878861,0.08228367,0.010850092,0.0001389806,0.00066386064,0.0034935472,0.0016003185,0.0005692523,0.014652606,0.08456712,0.80071664],"study_design_scores_gemma":[0.000015923813,0.0004136934,0.3062243,0.016413514,0.00022271447,0.0051748413,0.020853676,0.0033703984,0.0006174722,0.0076497574,0.6389105,0.00013327596],"about_ca_topic_score_codex":0.007469313,"about_ca_topic_score_gemma":0.0069832643,"teacher_disagreement_score":0.008894874,"about_ca_system_score_codex":0.0017371567,"about_ca_system_score_gemma":0.0020195483,"threshold_uncertainty_score":0.02329421},"labels":[],"label_agreement":null},{"id":"W4402567823","doi":"10.1080/03081060.2024.2401507","title":"What influences intention to use a first-mile/last-mile automated shuttle service in a suburban area? A case study in Toronto, Canada","year":2024,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mile; Last mile (transportation); Transport engineering; Vehicle miles of travel; Service (business); Engineering; Business; Geography; Marketing","score_opus":0.01602389775136318,"score_gpt":0.26258400199623533,"score_spread":0.24656010424487215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402567823","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985605,0.000073886105,0.000040582963,0.00018264589,0.0000030870046,0.00002358067,0.000088998204,0.0000015604378,0.0010251023],"genre_scores_gemma":[0.99893445,0.00014096328,0.00009678226,0.000051307914,0.0000020186396,0.000011581647,0.00008375439,0.0000026900734,0.0006765225],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9988034,0.00024081157,0.00004841384,0.00010086222,0.00024399965,0.00056250684],"domain_scores_gemma":[0.996305,0.00084901083,0.00042042776,0.000101403755,0.0012830714,0.001041065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009670252,0.0003500244,0.00047029645,0.0009259078,0.005116889,0.002799658,0.0010285734,0.0007160587,0.0019082024],"category_scores_gemma":[0.0033846484,0.00033195043,0.00065610925,0.0020845155,0.0016927884,0.0006904132,0.0009264166,0.0012763087,0.00016627327],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009736712,0.00054536515,0.9324123,0.000060699887,0.000046908954,0.0015789599,0.055282783,0.00034006883,0.00045412118,0.0005761012,0.0010428552,0.007562388],"study_design_scores_gemma":[0.000016142354,0.0001581012,0.80861026,0.0001115099,0.0000654323,0.00028420083,0.18572998,0.0019883073,0.00026616134,0.00009003706,0.0026319022,0.00004798625],"about_ca_topic_score_codex":0.9923929,"about_ca_topic_score_gemma":0.9965815,"teacher_disagreement_score":0.041327316,"about_ca_system_score_codex":0.041327316,"about_ca_system_score_gemma":0.031896263,"threshold_uncertainty_score":0.299852},"labels":[],"label_agreement":null},{"id":"W4402575766","doi":"10.1145/3641308.3677395","title":"First Workshop on Connected Micromobility for Safe and Sustainable Communities","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Business; Computer science","score_opus":0.01733710378419324,"score_gpt":0.24581678023326609,"score_spread":0.22847967644907285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402575766","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026393399,0.030067863,0.07264264,0.17832878,0.18779428,0.0017313538,0.002889816,0.0010026029,0.4991493],"genre_scores_gemma":[0.12721285,0.018698582,0.024331247,0.016567811,0.014392998,0.001496448,0.0032780843,0.0009224524,0.7930995],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99808025,0.0005909612,0.00006662731,0.00033752123,0.0004521433,0.00047249603],"domain_scores_gemma":[0.99724364,0.0004192622,0.00006147255,0.0001440645,0.000697082,0.0014344128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049416935,0.0014924662,0.00070616294,0.00071276724,0.0025192413,0.006431761,0.0031528012,0.004416009,0.04338859],"category_scores_gemma":[0.0028186296,0.00046186513,0.0014659397,0.0005698438,0.0014356251,0.0044265348,0.0076875486,0.0054612816,0.0122179175],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000309812,0.000493612,0.0006743988,0.0008422584,0.00005191441,0.0007455209,0.0030402215,0.002652729,0.005103459,0.052907117,0.85731286,0.07586605],"study_design_scores_gemma":[0.000017722408,0.00006451159,0.0002510446,0.00029419694,0.000010150679,0.000060398947,0.0011692981,0.0004877443,0.00072685606,0.0043914192,0.9925102,0.000016389045],"about_ca_topic_score_codex":0.0036904118,"about_ca_topic_score_gemma":0.007504651,"teacher_disagreement_score":0.04338859,"about_ca_system_score_codex":0.0024251495,"about_ca_system_score_gemma":0.007394368,"threshold_uncertainty_score":0.14514923},"labels":[],"label_agreement":null},{"id":"W4402637210","doi":"10.1016/j.eswa.2024.125412","title":"A multi-objective optimization approach for sustainable and personalized trip planning: A self-adaptive evolutionary algorithm with case study","year":2024,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Computer science; Evolutionary algorithm; Mathematical optimization; Genetic algorithm; Optimization algorithm; Artificial intelligence; Algorithm; Machine learning; Mathematics","score_opus":0.01669337235149348,"score_gpt":0.2626366321404224,"score_spread":0.2459432597889289,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402637210","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42638412,0.000682869,0.54639244,0.00061495963,0.00008353972,0.0003039515,0.00014923874,0.00033595692,0.025052857],"genre_scores_gemma":[0.84841883,0.0002174675,0.14593206,0.00004236306,0.000014183191,0.00016509618,0.00006748822,0.000035509634,0.00510703],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997639,0.00012295862,0.000009552097,0.000030791234,0.000042876454,0.000029911444],"domain_scores_gemma":[0.99940515,0.00041893695,0.000026666037,0.000036785554,0.00008523243,0.000027285783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000799736,0.00058527297,0.00056461606,0.0006889182,0.00052323606,0.0007777717,0.0009829496,0.0018002368,0.0022193347],"category_scores_gemma":[0.0015890835,0.00029344528,0.0006683691,0.0008395883,0.00034643552,0.00058387086,0.0005528743,0.000557262,0.00016938054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036540197,0.00010494837,0.00056758145,0.000045636883,0.000027078597,0.0002116139,0.00004396816,0.97503006,0.00059556274,0.0035871193,0.00036979895,0.019380076],"study_design_scores_gemma":[0.000007901695,0.000029742894,0.000117976284,0.0000027967828,0.0000071069867,0.000025061845,0.00001546565,0.99890196,0.00017280162,0.00046822472,0.00024818114,0.0000028284392],"about_ca_topic_score_codex":0.006834997,"about_ca_topic_score_gemma":0.006373848,"teacher_disagreement_score":0.006834997,"about_ca_system_score_codex":0.0005510038,"about_ca_system_score_gemma":0.0005529781,"threshold_uncertainty_score":0.013590395},"labels":[],"label_agreement":null},{"id":"W4402692437","doi":"10.1007/978-3-031-68634-4_14","title":"Toward Fair Ride Sharing Platforms: The Role of Regulations and Wait Time","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in networks and systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Business; Bike sharing; Sharing economy; Time-sharing; Internet privacy; Computer science; Transport engineering; Engineering; World Wide Web; Operating system","score_opus":0.01099613785630096,"score_gpt":0.19541411001976344,"score_spread":0.18441797216346248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402692437","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07513187,0.0027580785,0.41096255,0.022795247,0.0014677003,0.00012720405,0.00018575751,0.00052172114,0.4860498],"genre_scores_gemma":[0.8326748,0.0019901232,0.05456488,0.0010571742,0.0003903159,0.0001369378,0.00009759363,0.00028640396,0.10880179],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988456,0.00037718538,0.000025659176,0.00023051474,0.00029569643,0.00022548002],"domain_scores_gemma":[0.9965623,0.001825404,0.0003387463,0.0004754055,0.00044454334,0.00035368212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00400668,0.0005516599,0.00043721605,0.0006768239,0.0019167848,0.007995797,0.0021258995,0.002894743,0.018582558],"category_scores_gemma":[0.008754794,0.0005277163,0.0005260748,0.0009536811,0.0036952223,0.012736767,0.0032877561,0.004380284,0.0026712345],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003491599,0.00004338876,0.00032450797,0.000029169365,0.0000057257516,0.000033782275,0.0003673603,0.008295446,0.0005022401,0.9560639,0.0054211365,0.028878488],"study_design_scores_gemma":[0.000012553735,0.000039603492,0.00036799157,0.000067097746,0.000011873538,0.00003843374,0.0008120296,0.025436614,0.00067957985,0.93449473,0.038013365,0.00002608182],"about_ca_topic_score_codex":0.0038926662,"about_ca_topic_score_gemma":0.0041445703,"teacher_disagreement_score":0.018582558,"about_ca_system_score_codex":0.0021280148,"about_ca_system_score_gemma":0.0033333045,"threshold_uncertainty_score":0.062164843},"labels":[],"label_agreement":null},{"id":"W4402771965","doi":"10.1016/j.tbs.2024.100855","title":"Ridehailing use, travel patterns and multimodality: A latent-class cluster analysis of one-week GPS-based travel diaries in California","year":2024,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Environment and Climate Change Canada","funders":"California Department of Transportation; University of California, Davis; California Air Resources Board; U.S. Department of Transportation","keywords":"Latent class model; Multimodality; Cluster (spacecraft); Global Positioning System; Class (philosophy); Computer science; Psychology; Geography; Artificial intelligence; World Wide Web; Machine learning; Telecommunications","score_opus":0.030525532794168704,"score_gpt":0.2553847321547098,"score_spread":0.2248591993605411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402771965","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99809235,0.000039107883,0.00020792584,0.00003366167,0.000002380735,0.000018988305,0.0013041925,0.000009138552,0.00029216148],"genre_scores_gemma":[0.99492395,0.00007355947,0.0004203943,0.000008415763,0.000004017558,0.000030616287,0.004069853,0.000007172228,0.0004620002],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993456,0.000085507236,0.000045810822,0.00028726456,0.00012666133,0.0001091233],"domain_scores_gemma":[0.9986634,0.00022395133,0.0003521744,0.00016075002,0.00038291435,0.00021679957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082586915,0.00029612193,0.00044874015,0.0013532973,0.0011536127,0.0016205929,0.00077719154,0.0002967338,0.0015502394],"category_scores_gemma":[0.0016966114,0.00030943652,0.0006791118,0.002222912,0.0005001828,0.00051238143,0.00091995543,0.0006482358,0.0002544175],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013068569,0.00014673085,0.9884716,0.000041008116,0.00014085179,0.000053872496,0.0022223552,0.0009777173,0.0002864293,0.00014549222,0.0016535992,0.005729671],"study_design_scores_gemma":[0.000008182972,0.00002900864,0.99352866,0.000014127533,0.000037920952,0.000016940983,0.0026558996,0.002998187,0.00004109471,0.00003545908,0.0006231229,0.00001142373],"about_ca_topic_score_codex":0.43984294,"about_ca_topic_score_gemma":0.38785562,"teacher_disagreement_score":0.43984294,"about_ca_system_score_codex":0.002075891,"about_ca_system_score_gemma":0.0016080507,"threshold_uncertainty_score":0.87456554},"labels":[],"label_agreement":null},{"id":"W4402885256","doi":"10.1016/j.tre.2024.103782","title":"Express shipments with autonomous robots and public transportation","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part E Logistics and Transportation Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"H2020 European Research Council; European Research Council","keywords":"Robot; Transport engineering; Public transport; Business; Computer science; Engineering; Artificial intelligence","score_opus":0.09718733885247106,"score_gpt":0.34467593631627935,"score_spread":0.2474885974638083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402885256","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.060451336,0.001220402,0.92147106,0.00073511025,0.0001587156,0.000061919396,0.000104877894,0.00037527087,0.015421258],"genre_scores_gemma":[0.9179586,0.0011116406,0.06960394,0.0000898549,0.00009204225,0.00008394124,0.00012039531,0.000041884676,0.010897731],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971193,0.000118032214,0.000007408775,0.000066340086,0.00006439794,0.000031984964],"domain_scores_gemma":[0.9998332,0.000059659727,0.000039781913,0.000022035525,0.00003067741,0.000014634026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028585675,0.0006069856,0.00037747182,0.00028467397,0.00030872252,0.000682946,0.00080074294,0.00056089065,0.0022823536],"category_scores_gemma":[0.00046221347,0.00029360817,0.00060634845,0.000554547,0.0007346285,0.0010459262,0.0005964141,0.00066412473,0.00033804565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025850424,0.00002012208,0.0003251504,0.00004197735,0.00001736338,0.000049399132,0.000020842617,0.9625598,0.001024548,0.013623386,0.0006604893,0.021631053],"study_design_scores_gemma":[0.0000068001063,0.000041987296,0.00020080805,0.0000041381245,0.000006213945,0.00002027343,0.00002116461,0.99039876,0.00034853254,0.0060639475,0.0028817763,0.000005582301],"about_ca_topic_score_codex":0.010659081,"about_ca_topic_score_gemma":0.006500767,"teacher_disagreement_score":0.010659081,"about_ca_system_score_codex":0.00086954475,"about_ca_system_score_gemma":0.00074403355,"threshold_uncertainty_score":0.02119404},"labels":[],"label_agreement":null},{"id":"W4402937975","doi":"10.2139/ssrn.4968892","title":"The Impact of Ridesharing Platforms on Healthcare Access","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Business; Health care; Computer science; Internet privacy; Economics; Economic growth","score_opus":0.022064576688348055,"score_gpt":0.3294123428578889,"score_spread":0.30734776616954085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402937975","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89198864,0.0036530513,0.0015088251,0.01180142,0.0002514548,0.000057258356,0.0027934173,0.00006947939,0.087876394],"genre_scores_gemma":[0.9958758,0.00057099824,0.00011642232,0.00012262148,0.000085813495,0.000005354584,0.000172263,0.000009335951,0.0030414634],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977763,0.00090736116,0.00008395677,0.00019019813,0.0003635429,0.00067857734],"domain_scores_gemma":[0.9774984,0.014742705,0.0026401705,0.0008049823,0.0022413523,0.0020722933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015977086,0.00028813878,0.00032918534,0.0012875771,0.00085255323,0.00482127,0.00076108385,0.001386689,0.04902784],"category_scores_gemma":[0.026203271,0.0001509328,0.00077076274,0.0026389116,0.00082132017,0.0037547646,0.0021473416,0.0016698176,0.0024133322],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0055360585,0.002558294,0.46898735,0.0009936626,0.0008498448,0.002541373,0.0041835033,0.03960532,0.00402623,0.14470728,0.03617301,0.289838],"study_design_scores_gemma":[0.00029481106,0.003042493,0.71146506,0.00073810836,0.0015420163,0.0018415214,0.030636285,0.05464176,0.0038182745,0.124647446,0.067095585,0.00023655774],"about_ca_topic_score_codex":0.01556523,"about_ca_topic_score_gemma":0.013581262,"teacher_disagreement_score":0.04902784,"about_ca_system_score_codex":0.0015901135,"about_ca_system_score_gemma":0.0012567496,"threshold_uncertainty_score":0.16401446},"labels":[],"label_agreement":null},{"id":"W4403136856","doi":"10.1080/15472450.2024.2408024","title":"Optimizing dedicated lanes and tolling schemes for connected and autonomous vehicles to address bottleneck congestion considering morning commuter departure choices","year":2024,"lang":"en","type":"article","venue":"Journal of Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Bottleneck; Transport engineering; Traffic congestion; Computer science; Morning; Congestion pricing; Operations research; Engineering; Embedded system","score_opus":0.02664866800721479,"score_gpt":0.2697849228094237,"score_spread":0.24313625480220888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403136856","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7600928,0.00022028267,0.23349157,0.00025220873,0.00004950528,0.00013662475,0.0001487386,0.00021272463,0.005395696],"genre_scores_gemma":[0.9912588,0.000033706583,0.0079231905,0.000014024741,0.000003400639,0.000029657069,0.000035390556,0.000009229994,0.0006925742],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996275,0.00011983293,0.000010274325,0.0000666415,0.000027256763,0.00014854656],"domain_scores_gemma":[0.9989386,0.00054656353,0.00015872576,0.00004771269,0.00014281429,0.00016556072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000745426,0.0006887242,0.000705048,0.0005613498,0.00040348983,0.0008947111,0.0008759475,0.00078207446,0.0024858722],"category_scores_gemma":[0.002149652,0.0005272839,0.0005120187,0.00042055117,0.0006223859,0.0009244807,0.0007095693,0.00064637087,0.0001413407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080016274,0.000064307394,0.0010379741,0.000029191422,0.000019974672,0.00003278063,0.000024689387,0.9916991,0.000927621,0.00187136,0.00019434084,0.0040185936],"study_design_scores_gemma":[0.000014046682,0.000054253334,0.0003083164,0.000002420423,0.00001280786,0.0000050403296,0.00003850988,0.9982344,0.0002523331,0.00093704974,0.00013653394,0.0000042600036],"about_ca_topic_score_codex":0.013637355,"about_ca_topic_score_gemma":0.013224508,"teacher_disagreement_score":0.013637355,"about_ca_system_score_codex":0.0013209048,"about_ca_system_score_gemma":0.0017528448,"threshold_uncertainty_score":0.027116},"labels":[],"label_agreement":null},{"id":"W4403168684","doi":"10.3138/9781487553678-008","title":"5 Emerging Mobility Technologies and Transportation Systems in Canadian Cities","year":2024,"lang":"en","type":"book-chapter","venue":"University of Toronto Press eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Economic geography; Regional science; Business; Geography; Engineering","score_opus":0.011100267223525397,"score_gpt":0.18295884248492905,"score_spread":0.17185857526140366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403168684","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003412919,0.050819185,0.0009981423,0.013705539,0.0015310892,0.000053425203,0.0011691432,0.00008564151,0.92822504],"genre_scores_gemma":[0.053130936,0.065437265,0.001777004,0.0017607657,0.00029886136,0.00003215941,0.0007559249,0.00007876746,0.8767283],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993699,0.00004688805,0.000011965082,0.000049453516,0.00028866198,0.00023315352],"domain_scores_gemma":[0.99961025,0.000037151265,0.000010728806,0.000012258386,0.00024661154,0.000083034494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003938383,0.001198669,0.00037652603,0.0032770263,0.008035806,0.008150499,0.0011894448,0.0016131987,0.04476266],"category_scores_gemma":[0.00088193687,0.00045874104,0.00054330344,0.010593279,0.0022576454,0.0019454483,0.0010463618,0.0019694674,0.003284842],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014486125,0.000022235508,0.0010742551,0.0002366715,0.0000068330187,0.0002040415,0.003862665,0.001493147,0.00017834058,0.36074904,0.5528688,0.07928946],"study_design_scores_gemma":[0.0000019000497,0.0000027900116,0.001625022,0.00014736006,0.000006776073,0.00003093321,0.0016342895,0.00024508665,0.000046734443,0.005468017,0.99077904,0.000012077491],"about_ca_topic_score_codex":0.99423426,"about_ca_topic_score_gemma":0.9976992,"teacher_disagreement_score":0.11522395,"about_ca_system_score_codex":0.11522395,"about_ca_system_score_gemma":0.12260809,"threshold_uncertainty_score":0.8360122},"labels":[],"label_agreement":null},{"id":"W4403168709","doi":"10.3138/9781487553678-016","title":"13 The Evolution of Ride-Hailing Regulation in Canadian Cities: COVID-19 and Policy Convergence","year":2024,"lang":"en","type":"book-chapter","venue":"University of Toronto Press eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Convergence (economics); Economic geography; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Geography; Political science; Economics; Economic growth; Biology; Virology; Medicine","score_opus":0.014421394684143133,"score_gpt":0.20899319321100393,"score_spread":0.1945717985268608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403168709","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.087339364,0.008217646,0.0034536973,0.04673368,0.00032500675,0.00015670681,0.0012929373,0.00013107924,0.8523498],"genre_scores_gemma":[0.8074386,0.0043997364,0.0017752791,0.0043093725,0.0000900007,0.00008445637,0.00038233103,0.000091951195,0.1814283],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99214774,0.00077205664,0.00014743223,0.00072189054,0.0022390354,0.003971782],"domain_scores_gemma":[0.9957502,0.00064771797,0.00022083613,0.00022072514,0.0024324593,0.0007280617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003230804,0.0006229583,0.00071011356,0.004169981,0.017052509,0.016817573,0.0030109861,0.003817918,0.01969457],"category_scores_gemma":[0.0074148453,0.0005972565,0.000837378,0.008984907,0.013104155,0.003002404,0.0033973453,0.0041082767,0.00072469626],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029004252,0.000029030181,0.0043505034,0.000070801514,0.000015890004,0.00008977215,0.009151399,0.0019087192,0.00022520105,0.93209064,0.027987681,0.02405134],"study_design_scores_gemma":[0.000034386932,0.000044798446,0.07443217,0.00044156858,0.00007153653,0.000051611056,0.037004944,0.0027541902,0.0005921146,0.06654964,0.8178726,0.00015040007],"about_ca_topic_score_codex":0.99569184,"about_ca_topic_score_gemma":0.9972084,"teacher_disagreement_score":0.27941766,"about_ca_system_score_codex":0.27941766,"about_ca_system_score_gemma":0.30776623,"threshold_uncertainty_score":0.83577335},"labels":[],"label_agreement":null},{"id":"W4403171454","doi":"10.1038/s41598-024-74024-0","title":"An investigation of perceived risk dimensions in acceptability of shared autonomous vehicles, a mediation-moderation analysis","year":2024,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Moderation; Structural equation modeling; Mediation; Risk perception; Moderated mediation; Order (exchange); Psychology; Path analysis (statistics); Social psychology; Business; Marketing; Computer science; Finance; Political science","score_opus":0.01121873384519959,"score_gpt":0.24973198922218992,"score_spread":0.23851325537699034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403171454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99531376,0.0001851381,0.0021069602,0.0003637662,0.000015601694,0.00021105279,0.000106970016,0.0000086027985,0.0016881688],"genre_scores_gemma":[0.9979,0.0000975626,0.0012480834,0.000055876408,0.000007467779,0.00034389624,0.000059374146,0.000005383109,0.00028228093],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98468876,0.011054662,0.00085141946,0.0011040136,0.0013001583,0.0010009666],"domain_scores_gemma":[0.9198267,0.0645916,0.0070156693,0.0026028045,0.004357593,0.0016057128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.022150734,0.0008137058,0.0008214234,0.0015497613,0.0017601153,0.002563063,0.0010255006,0.001027707,0.00650873],"category_scores_gemma":[0.06041135,0.0005426477,0.0024462044,0.0011933282,0.0020005219,0.0037097477,0.004776122,0.0024956877,0.0002626482],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005645256,0.0010115226,0.8860167,0.00045929017,0.00095590914,0.00039533523,0.07339772,0.00043086306,0.0010414547,0.0053806063,0.0003855804,0.02996047],"study_design_scores_gemma":[0.00018306298,0.0021499288,0.87703514,0.0006865088,0.0021860003,0.00039362398,0.09432293,0.009611222,0.002038691,0.007447847,0.0038111834,0.00013377573],"about_ca_topic_score_codex":0.008804997,"about_ca_topic_score_gemma":0.006518067,"teacher_disagreement_score":0.022150734,"about_ca_system_score_codex":0.0017502893,"about_ca_system_score_gemma":0.0048825853,"threshold_uncertainty_score":0.11714572},"labels":[],"label_agreement":null},{"id":"W4403180983","doi":"10.1016/j.trd.2024.104444","title":"Rethinking automobility in the suburb: Experiences with carsharing in a Danish suburb","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia Hospital","funders":"Innovationsfonden","keywords":"Danish; Economic geography; Geography","score_opus":0.05089066400484437,"score_gpt":0.2872637488810048,"score_spread":0.23637308487616043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403180983","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99683857,0.00009549126,0.0003877754,0.00024365976,0.000009798458,0.000011429085,0.000014066813,0.0000050137446,0.0023942725],"genre_scores_gemma":[0.99764985,0.0001190795,0.00020248514,0.000047108108,0.000002429678,0.000006688223,0.000012213268,0.000007134434,0.0019530202],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9972512,0.0017390758,0.00006203787,0.00023794435,0.00020569991,0.00050406955],"domain_scores_gemma":[0.9981129,0.0009947435,0.00014679045,0.00013574371,0.00013997256,0.00046979307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025781107,0.00049025234,0.0005626163,0.00055547146,0.010451702,0.0032360046,0.0010726015,0.0013080374,0.0024450982],"category_scores_gemma":[0.0023518093,0.00045373946,0.00037271745,0.0009439317,0.009659372,0.0023528086,0.0056872037,0.0016765768,0.00032917623],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037243797,0.000050405713,0.005013499,0.000058651985,0.0000067854335,0.0012990559,0.98741674,0.00019488488,0.0012548943,0.001544234,0.00027272236,0.0028508466],"study_design_scores_gemma":[0.0000025851946,0.00005545368,0.002799963,0.000026243571,0.0000059814397,0.00016776298,0.9842867,0.0001119928,0.0003719719,0.00019456765,0.011962161,0.000014641726],"about_ca_topic_score_codex":0.045755375,"about_ca_topic_score_gemma":0.11732979,"teacher_disagreement_score":0.045755375,"about_ca_system_score_codex":0.0047764145,"about_ca_system_score_gemma":0.002774221,"threshold_uncertainty_score":0.090978146},"labels":[],"label_agreement":null},{"id":"W4403223029","doi":"10.1016/j.tbs.2024.100921","title":"Moderating effects of policy measures on intention to adopt autonomous vehicles: Evidence from China","year":2024,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministry of Education and Child Care","funders":"Fundamental Research Funds for the Central Universities; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"China; Psychology; Business; Political science; Law","score_opus":0.01886170248469723,"score_gpt":0.2677137968248426,"score_spread":0.24885209434014535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403223029","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986303,0.0003791242,0.00011462078,0.00014915944,0.000016173919,0.000008993046,0.00014998163,0.0000039595166,0.00054771476],"genre_scores_gemma":[0.99930346,0.00015261114,0.000052005442,0.000031564894,0.000007457315,0.000010824759,0.00016548556,0.0000023568514,0.000274122],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99606764,0.0017258554,0.0002941834,0.0007041694,0.00042642045,0.00078167435],"domain_scores_gemma":[0.9867643,0.0062011112,0.0031066574,0.0010785272,0.0014766046,0.0013727937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004076763,0.0008630768,0.00081993564,0.0015975656,0.001262253,0.0016493299,0.0009347506,0.0008944461,0.0031978546],"category_scores_gemma":[0.009048553,0.0004288923,0.0017918268,0.0031964716,0.0018044182,0.0010679465,0.0012915141,0.0013660756,0.00025961254],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022050056,0.00027744856,0.99267006,0.00005379335,0.0007024494,0.00009785996,0.001041492,0.0002835785,0.00016122212,0.00036519748,0.00017379815,0.0039525726],"study_design_scores_gemma":[0.000028343353,0.00014209883,0.99710697,0.000023942432,0.000439469,0.000012112369,0.0010763096,0.00056858774,0.00014505064,0.00011735329,0.00032563708,0.000014088486],"about_ca_topic_score_codex":0.15550251,"about_ca_topic_score_gemma":0.1343602,"teacher_disagreement_score":0.15550251,"about_ca_system_score_codex":0.0018305767,"about_ca_system_score_gemma":0.0037938287,"threshold_uncertainty_score":0.30919474},"labels":[],"label_agreement":null},{"id":"W4403226710","doi":"10.1016/j.cjca.2024.08.099","title":"AMUSEMENT PARK RIDES AND CARDIAC DEVICES: HEART DROPPER OR HEART STOPPER?","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Medicine; Theme park; Amusement; Cardiology; Internal medicine; Law","score_opus":0.016757832287039556,"score_gpt":0.23772762719108523,"score_spread":0.22096979490404567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403226710","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18989085,0.13628754,0.0010715683,0.5591843,0.00829036,0.0000616217,0.0009689103,0.00004564851,0.1041992],"genre_scores_gemma":[0.81170416,0.08334983,0.000914962,0.069987595,0.017559895,0.000044080854,0.00049851334,0.00003716397,0.015903693],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99861753,0.00026181433,0.00012673972,0.00021475981,0.00035002537,0.00042915012],"domain_scores_gemma":[0.99749005,0.0005527001,0.0006981292,0.000059224403,0.0004691933,0.0007306681],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011396533,0.000287859,0.0007363093,0.0011332528,0.0018146607,0.0031349072,0.00095284334,0.0065016323,0.031150332],"category_scores_gemma":[0.0068044765,0.00030193964,0.00078361644,0.0013117497,0.0018996603,0.003876547,0.0012228849,0.0043353327,0.0019391582],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012243364,0.0011597646,0.43205005,0.0015534795,0.00040358934,0.013950689,0.0067750416,0.00017524009,0.0007023324,0.040392976,0.20266917,0.2989433],"study_design_scores_gemma":[0.0003150323,0.00083477044,0.52322346,0.012224009,0.00082460965,0.03914648,0.095044225,0.0010895196,0.00030993795,0.040709168,0.28591383,0.00036508823],"about_ca_topic_score_codex":0.0465841,"about_ca_topic_score_gemma":0.10245307,"teacher_disagreement_score":0.0465841,"about_ca_system_score_codex":0.00168006,"about_ca_system_score_gemma":0.004457869,"threshold_uncertainty_score":0.10420829},"labels":[],"label_agreement":null},{"id":"W4403398983","doi":"10.31803/tg-20240411223559","title":"Understanding the Drivers of Adoption for Blockchain-enabled Intelligent Transportation Systems","year":2024,"lang":"en","type":"article","venue":"Tehnički glasnik","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Blockchain; Intelligent transportation system; Business; Computer science; Computer security; Transport engineering; Engineering","score_opus":0.057319220210898726,"score_gpt":0.2493708119104076,"score_spread":0.1920515916995089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403398983","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.988282,0.00030017272,0.0035966237,0.0012749953,0.0000078383,0.000055708086,0.00011386602,0.000012504764,0.0063561816],"genre_scores_gemma":[0.9989084,0.00027026908,0.00045033597,0.000019421757,0.000003410047,0.0000109540015,0.000042981887,0.0000014659395,0.00029270555],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99897695,0.0002927625,0.00006875623,0.000111741036,0.00023624669,0.00031362288],"domain_scores_gemma":[0.99253815,0.0039886055,0.0020416887,0.00016951693,0.0009260161,0.00033597418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018335851,0.000307967,0.00022290189,0.0017099304,0.00043162145,0.0021017871,0.00034947807,0.00071008445,0.0031612075],"category_scores_gemma":[0.0072355033,0.00023226858,0.00051693287,0.0017855341,0.0006035388,0.0034070718,0.000901102,0.0010000775,0.00022811398],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000071030685,0.0004125301,0.89393395,0.0002796626,0.00012400298,0.00055636273,0.008467644,0.009620303,0.0017250929,0.0368144,0.00073615747,0.04725892],"study_design_scores_gemma":[0.000021563952,0.0004143277,0.8503647,0.0004474071,0.00021475594,0.00041274543,0.042652614,0.07395769,0.0016626862,0.01708193,0.012696552,0.000072982264],"about_ca_topic_score_codex":0.00906757,"about_ca_topic_score_gemma":0.010398913,"teacher_disagreement_score":0.00906757,"about_ca_system_score_codex":0.0016507927,"about_ca_system_score_gemma":0.002256956,"threshold_uncertainty_score":0.01802957},"labels":[],"label_agreement":null},{"id":"W4403447394","doi":"10.1109/acit62333.2024.10712508","title":"Navigation and Communications Protocols for Autonomous Intelligent Mobility","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Solana Networks (Canada)","funders":"","keywords":"Computer science; Computer network; Telecommunications; Human–computer interaction","score_opus":0.04729850438603283,"score_gpt":0.34013957461143435,"score_spread":0.2928410702254015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403447394","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0053815246,0.003500264,0.90863705,0.005696455,0.00091698783,0.00043918847,0.00033586574,0.000614251,0.07447842],"genre_scores_gemma":[0.3227458,0.012195516,0.60988265,0.0029397544,0.0013068989,0.003202712,0.0012140634,0.0002663075,0.046246305],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99772984,0.0006342835,0.00024338548,0.0002457831,0.00097262237,0.00017409495],"domain_scores_gemma":[0.99743444,0.00091926294,0.00029693943,0.00058803573,0.00067803275,0.000083347964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002067739,0.0008803788,0.0005025252,0.0012132417,0.0017557758,0.0034283476,0.0012763056,0.0028979613,0.004796751],"category_scores_gemma":[0.0061433157,0.00056622986,0.0007496525,0.0015459388,0.0024581861,0.0058058235,0.002019922,0.0030023013,0.0017711906],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011188774,0.000013822604,0.00008328279,0.000068999034,0.0000062955287,0.0000891169,0.00018908014,0.006751203,0.0008321185,0.97421706,0.0045536733,0.013184221],"study_design_scores_gemma":[0.00004045146,0.00007728493,0.00023044835,0.0003120728,0.00003991242,0.00054639304,0.00027764606,0.085788846,0.0033053092,0.61370736,0.29561782,0.000056455625],"about_ca_topic_score_codex":0.0037724427,"about_ca_topic_score_gemma":0.0029316035,"teacher_disagreement_score":0.004796751,"about_ca_system_score_codex":0.0020723941,"about_ca_system_score_gemma":0.0031310858,"threshold_uncertainty_score":0.016046703},"labels":[],"label_agreement":null},{"id":"W4403465678","doi":"10.1155/2024/5841162","title":"Exploring Factors Affecting People’s Acceptance of Connected Vehicle Technology in China","year":2024,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"China; Transport engineering; Engineering; Business; Advertising; Geography","score_opus":0.018767942352825966,"score_gpt":0.24864928576791304,"score_spread":0.22988134341508706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403465678","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992575,0.000027554786,0.00006775875,0.00007643071,0.0000016458494,0.0000056393487,0.000024620907,0.0000013100336,0.00053747447],"genre_scores_gemma":[0.9997408,0.000028229357,0.000029412591,0.000012767886,0.0000010550677,0.000004093006,0.00003561898,5.4683284e-7,0.00014747347],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989905,0.0002059675,0.00011321338,0.0001491236,0.0003116064,0.00022955409],"domain_scores_gemma":[0.9973787,0.00070084824,0.00076745305,0.00014915447,0.00053304806,0.00047078356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013653057,0.00028774128,0.00025264663,0.0010240654,0.00079666614,0.000928242,0.00035501242,0.00046938844,0.0017173388],"category_scores_gemma":[0.0029186364,0.00019943474,0.0005216298,0.0012707271,0.00086505327,0.0006208029,0.0008065746,0.0005034608,0.00012716786],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017922508,0.00007038937,0.9877983,0.000027529433,0.000041032035,0.00014474717,0.004869519,0.00032291253,0.00042567725,0.000498056,0.00014323773,0.0056407005],"study_design_scores_gemma":[0.000002905829,0.00004938103,0.9934782,0.000013185459,0.0000166219,0.00003720543,0.0042710626,0.0014799631,0.0001034418,0.00013377583,0.00040201837,0.000012329973],"about_ca_topic_score_codex":0.071414396,"about_ca_topic_score_gemma":0.05685512,"teacher_disagreement_score":0.071414396,"about_ca_system_score_codex":0.0014188875,"about_ca_system_score_gemma":0.0016623156,"threshold_uncertainty_score":0.14199746},"labels":[],"label_agreement":null},{"id":"W4403487090","doi":"10.1287/mnsc.2022.03201","title":"Trading Flexibility for Adoption: From Dynamic to Static Walking in Ride-Sharing","year":2024,"lang":"en","type":"article","venue":"Management Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Flexibility (engineering); Computer science; Business; Microeconomics; Industrial organization; Economics; Management","score_opus":0.024047393026272852,"score_gpt":0.2963232654458374,"score_spread":0.2722758724195646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403487090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94363856,0.00058753684,0.044870477,0.0011818879,0.000040820494,0.00013926666,0.00043080613,0.00018476494,0.008925919],"genre_scores_gemma":[0.9958085,0.000057870064,0.003621297,0.000040816358,0.000005322464,0.000021165073,0.00006042452,0.000012656044,0.0003719265],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9978824,0.0010699865,0.00006731614,0.0004375371,0.00019700795,0.00034572376],"domain_scores_gemma":[0.9912709,0.0055492967,0.00097023946,0.0012046461,0.00042944992,0.00057551765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031661054,0.0006881456,0.0006817748,0.00073533034,0.0008651843,0.002528343,0.0015440565,0.0014167656,0.0045444313],"category_scores_gemma":[0.02253124,0.000440394,0.00072001,0.001215668,0.0014179338,0.004544062,0.0021981627,0.0017157879,0.00047647028],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017662421,0.0011386384,0.29091537,0.0005656785,0.00041168273,0.0010559587,0.0033937574,0.42438442,0.0068440875,0.07084076,0.0052886605,0.19339466],"study_design_scores_gemma":[0.00015200823,0.0010419429,0.08181474,0.00018116925,0.00029837742,0.00064794987,0.0043400647,0.8361822,0.0024511123,0.06446899,0.008161657,0.0002597923],"about_ca_topic_score_codex":0.012761506,"about_ca_topic_score_gemma":0.013635495,"teacher_disagreement_score":0.012761506,"about_ca_system_score_codex":0.0012929566,"about_ca_system_score_gemma":0.00084826705,"threshold_uncertainty_score":0.025374472},"labels":[],"label_agreement":null},{"id":"W4403598347","doi":"10.48550/arxiv.2409.04792","title":"Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Alliance de recherche numérique du Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research; Fonds Québécois de la Recherche sur la Nature et les Technologies; Nvidia","keywords":"Reinforcement learning; Reinforcement; Value (mathematics); Chain (unit); Computer science; Learning effect; Artificial intelligence; Microeconomics; Economics; Machine learning; Psychology; Social psychology; Physics","score_opus":0.013197840695021187,"score_gpt":0.17464169616511457,"score_spread":0.16144385547009338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403598347","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.044519167,0.0003793773,0.9515991,0.00032728317,0.000050636878,0.000057599278,0.000036171223,0.0010342204,0.0019964278],"genre_scores_gemma":[0.8749444,0.00019606561,0.12218794,0.00026618523,0.000060048984,0.00011686105,0.00010367118,0.0001960385,0.0019287906],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987332,0.00042368806,0.00006577933,0.00024949983,0.0003634542,0.00016433127],"domain_scores_gemma":[0.9934989,0.004347073,0.0006428537,0.0006656389,0.00059475796,0.00025079094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002792517,0.0011512268,0.001413933,0.0004724201,0.00046460706,0.001157735,0.0015170489,0.0013324058,0.0018276768],"category_scores_gemma":[0.015361691,0.0006878666,0.00054248737,0.00043435197,0.0013830075,0.002487043,0.0022346696,0.0030985198,0.0004787963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016181737,0.0001686162,0.0021986824,0.00008984497,0.000052676038,0.000098443896,0.00014862543,0.9112548,0.0027758467,0.012342699,0.0016509732,0.06905701],"study_design_scores_gemma":[0.000009279517,0.000022249604,0.0000612485,0.0000050403914,0.000004070071,0.000007809347,0.000004286227,0.9961184,0.00052493793,0.0030625332,0.00017742577,0.0000026781447],"about_ca_topic_score_codex":0.00425609,"about_ca_topic_score_gemma":0.0045285,"teacher_disagreement_score":0.00425609,"about_ca_system_score_codex":0.0013424314,"about_ca_system_score_gemma":0.0021546367,"threshold_uncertainty_score":0.014768422},"labels":[],"label_agreement":null},{"id":"W4403603330","doi":"10.3390/ijgi13100368","title":"Discovering Electric Vehicle Charging Locations Based on Clustering Techniques Applied to Vehicular Mobility Datasets","year":2024,"lang":"en","type":"article","venue":"ISPRS International Journal of Geo-Information","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of the Fraser Valley","funders":"","keywords":"Cluster analysis; Electric vehicle; Computer science; Data mining; Artificial intelligence; Physics","score_opus":0.005349292472257604,"score_gpt":0.24572705686394614,"score_spread":0.24037776439168854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403603330","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6594712,0.0010348113,0.31444106,0.0008658785,0.00021400224,0.0007322689,0.013554908,0.0041209497,0.0055649434],"genre_scores_gemma":[0.8207346,0.0003658437,0.15987416,0.00007979898,0.000041585263,0.00024279485,0.01772011,0.00008506271,0.0008560267],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916494,0.00019233102,0.00008020961,0.00027181258,0.0001754109,0.00011526613],"domain_scores_gemma":[0.9988952,0.00034306318,0.00012354179,0.00021365537,0.00037644696,0.000048150527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011347196,0.0010566319,0.0007738228,0.0039769267,0.0009662077,0.0009579458,0.0017550772,0.0009116586,0.0004553719],"category_scores_gemma":[0.0043044575,0.00035721678,0.0013324616,0.0031090735,0.00031938503,0.0009501935,0.0008627997,0.000756053,0.00050211005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024691358,0.00031955552,0.035099458,0.00029455574,0.00035994165,0.0003196651,0.000336279,0.81443435,0.004381031,0.004153206,0.0073752543,0.13267969],"study_design_scores_gemma":[0.000011382154,0.000038879047,0.0052577322,0.000021768068,0.000023506813,0.00009572051,0.0002137569,0.9886995,0.0017304026,0.002137891,0.0017452213,0.000024197161],"about_ca_topic_score_codex":0.029184546,"about_ca_topic_score_gemma":0.043389197,"teacher_disagreement_score":0.029184546,"about_ca_system_score_codex":0.00113657,"about_ca_system_score_gemma":0.00124765,"threshold_uncertainty_score":0.058029354},"labels":[],"label_agreement":null},{"id":"W4403627588","doi":"10.1016/j.tbs.2024.100930","title":"The landscape of contemporary paratransit research: A critical systematic review of the literature in the US and Canada","year":2024,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Environment and Climate Change Canada; McMaster University","funders":"","keywords":"Paratransit; Regional science; Engineering; Environmental planning; Geography; Transport engineering","score_opus":0.030272664527001385,"score_gpt":0.2976010081573875,"score_spread":0.2673283436303861,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403627588","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019465598,0.9908949,0.00037745674,0.0040066,0.00038212503,0.00062618556,0.0007960259,0.0000146655575,0.0009554353],"genre_scores_gemma":[0.041410673,0.9476908,0.0030056615,0.0045830733,0.0002211615,0.0021687322,0.0006654959,0.000024831032,0.00022964196],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.938193,0.024603814,0.017073384,0.0037570598,0.013667285,0.0027054995],"domain_scores_gemma":[0.7260046,0.18432492,0.022610089,0.004031597,0.059926327,0.0031023922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06431262,0.0014796717,0.0061022392,0.04721227,0.003965284,0.009731159,0.0038692676,0.00365965,0.0035948884],"category_scores_gemma":[0.24202582,0.0018638124,0.0052077225,0.050676137,0.0051590726,0.0066286107,0.0050782682,0.0032276195,0.00036672817],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002021314,0.00002541213,0.003113307,0.8775271,0.0024000653,0.0004204941,0.0075058034,0.00030783023,0.00020152815,0.0039899135,0.011966226,0.09234021],"study_design_scores_gemma":[0.000051966625,0.000046504243,0.003603934,0.9550182,0.003685151,0.00018776489,0.0041545457,0.000095822754,0.00008221933,0.0006443026,0.032387998,0.000041509044],"about_ca_topic_score_codex":0.361334,"about_ca_topic_score_gemma":0.60188246,"teacher_disagreement_score":0.63866603,"about_ca_system_score_codex":0.06310625,"about_ca_system_score_gemma":0.24100824,"threshold_uncertainty_score":0.71846163},"labels":[],"label_agreement":null},{"id":"W4403736841","doi":"10.18280/isi.290522","title":"Optimizing Urban Mobility: A Comparative Analysis of Taxi Demand Prediction Models","year":2024,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Universitas Gadjah Mada","keywords":"Computer science; Econometrics; Transport engineering; Economics; Engineering","score_opus":0.021891553564958137,"score_gpt":0.24078312496680968,"score_spread":0.21889157140185153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403736841","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8333381,0.0042651724,0.14435755,0.0013085582,0.00012996329,0.0001544009,0.0017631671,0.0012705572,0.013412521],"genre_scores_gemma":[0.97928166,0.0008361541,0.017763775,0.000044274537,0.000027970777,0.00005048096,0.0010223556,0.000046458652,0.00092681276],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960095,0.00014936182,0.000028119792,0.000078801124,0.00008247095,0.000060354825],"domain_scores_gemma":[0.99831796,0.0011354754,0.000108271124,0.00010193718,0.00028969106,0.000046671797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017482244,0.00081440696,0.0007987844,0.0012775509,0.00025138253,0.00061751896,0.0006751997,0.00067602843,0.0011055061],"category_scores_gemma":[0.0029706708,0.00021033104,0.00075914117,0.0013880731,0.0001836061,0.0008420388,0.00034350477,0.00048352976,0.00019333737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010310173,0.000090773574,0.008071863,0.00007815319,0.00007415367,0.000027548005,0.00002119182,0.9547892,0.00017167152,0.0010634172,0.0008919457,0.03461695],"study_design_scores_gemma":[0.0000025347208,0.0000384867,0.0017557376,0.0000062243657,0.000014019709,0.000007160826,0.000019335024,0.99756217,0.00011004233,0.00023571489,0.0002450056,0.0000035438995],"about_ca_topic_score_codex":0.031944107,"about_ca_topic_score_gemma":0.024530565,"teacher_disagreement_score":0.031944107,"about_ca_system_score_codex":0.001039414,"about_ca_system_score_gemma":0.0009266528,"threshold_uncertainty_score":0.06351632},"labels":[],"label_agreement":null},{"id":"W4403826543","doi":"10.1109/iotm.001.2400024","title":"Scenario Co-Design for Systemic Evaluation of Connected and Automated Mobility Setups","year":2024,"lang":"en","type":"article","venue":"IEEE Internet of Things Magazine","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science","score_opus":0.035012475440008205,"score_gpt":0.2992404658270663,"score_spread":0.26422799038705813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403826543","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.109735794,0.0001836094,0.85771626,0.00035855232,0.000096713935,0.008214376,0.0026377086,0.0013960025,0.019660996],"genre_scores_gemma":[0.3427082,0.00009868683,0.64530903,0.00005772322,0.0000140106995,0.009279793,0.0014459916,0.00013995549,0.000946677],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.97944564,0.016816065,0.0006634465,0.0012648612,0.0013330643,0.00047701527],"domain_scores_gemma":[0.959792,0.031249754,0.0019015354,0.0028814743,0.0035570941,0.00061825325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.021668985,0.0018627837,0.0009348419,0.0038441906,0.000900696,0.0029867922,0.0018158201,0.0012088531,0.011192602],"category_scores_gemma":[0.03932036,0.0007956252,0.0021326847,0.0021867403,0.0015738306,0.0030025598,0.0037396639,0.0016288031,0.00074550876],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014191004,0.00093261723,0.0070818807,0.0017053437,0.0006522196,0.00068445894,0.0030665435,0.7894761,0.0069974386,0.08048889,0.0030317712,0.10446367],"study_design_scores_gemma":[0.0003983096,0.0010081016,0.002076913,0.0002373444,0.00018577128,0.00010571591,0.0023791324,0.9467689,0.004847516,0.02971855,0.012189989,0.000083857776],"about_ca_topic_score_codex":0.003720266,"about_ca_topic_score_gemma":0.0047785523,"teacher_disagreement_score":0.021668985,"about_ca_system_score_codex":0.003965437,"about_ca_system_score_gemma":0.0032837507,"threshold_uncertainty_score":0.11459792},"labels":[],"label_agreement":null},{"id":"W4403918475","doi":"10.1109/sm63044.2024.10733430","title":"The SureStride: An Intermediate Mobility Solution for Seniors","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science","score_opus":0.01513475304286186,"score_gpt":0.2694194903287073,"score_spread":0.25428473728584544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403918475","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53186256,0.008121764,0.30663243,0.008874652,0.0029190946,0.0016485652,0.003317001,0.030637484,0.105986476],"genre_scores_gemma":[0.75154895,0.0031906923,0.12399407,0.0024549777,0.00032543833,0.0007880503,0.0034916417,0.00055834843,0.11364782],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996197,0.000054950742,0.000028346654,0.00006541176,0.0001438298,0.00008766661],"domain_scores_gemma":[0.99953043,0.000025052921,0.000033674663,0.000037695067,0.00014287425,0.00023020183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040408704,0.0008288461,0.00041416686,0.00054590846,0.00051570934,0.0008141893,0.0015539135,0.00087939634,0.016584044],"category_scores_gemma":[0.0010805257,0.00023527484,0.0005877057,0.00022850232,0.0002549714,0.0010675564,0.003195501,0.0006595898,0.0055141174],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011494452,0.0010355307,0.009819161,0.0011569937,0.000108335465,0.0010158262,0.001187798,0.0008558251,0.04480541,0.0038569488,0.09948896,0.8355199],"study_design_scores_gemma":[0.0013520184,0.015960906,0.057425696,0.0014795803,0.0006103924,0.014718864,0.004358716,0.022148758,0.03596092,0.006165903,0.8392469,0.0005713075],"about_ca_topic_score_codex":0.0009115526,"about_ca_topic_score_gemma":0.0024205293,"teacher_disagreement_score":0.016584044,"about_ca_system_score_codex":0.00019090071,"about_ca_system_score_gemma":0.0007590092,"threshold_uncertainty_score":0.05547911},"labels":[],"label_agreement":null},{"id":"W4403920087","doi":"10.1109/sm63044.2024.10733535","title":"Robot Wheelchair Convoys for Assistive Human Transportation","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; York University","funders":"","keywords":"Wheelchair; Robot; Computer science; Human–computer interaction; Human–robot interaction; Artificial intelligence; World Wide Web","score_opus":0.01772039263657451,"score_gpt":0.2691380128359439,"score_spread":0.2514176201993694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403920087","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2044744,0.0020058893,0.7669617,0.00041237014,0.0003031839,0.0003435399,0.0003520595,0.007901522,0.017245265],"genre_scores_gemma":[0.8981011,0.0005307193,0.08895793,0.00009000695,0.0000358137,0.00017047251,0.00044390562,0.00009842529,0.011571708],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99984884,0.00004039557,0.0000074555874,0.000033879533,0.000045147495,0.000024224692],"domain_scores_gemma":[0.9998869,0.00001522854,0.0000100677835,0.000021128162,0.00004070731,0.000025985579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016349697,0.0005792632,0.00029460806,0.00020003157,0.00042750547,0.00041447056,0.00073817564,0.00037933936,0.0038377882],"category_scores_gemma":[0.00025572296,0.0001544411,0.00023506767,0.00012446356,0.0002915151,0.00040427622,0.00081571494,0.00024840955,0.0010457669],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017499803,0.00040843943,0.0040882584,0.001033447,0.00016434064,0.0019280494,0.0012745562,0.053232245,0.36315048,0.014796076,0.01884494,0.5393292],"study_design_scores_gemma":[0.0003114795,0.0033817778,0.01307604,0.00023262754,0.000228585,0.0025248388,0.0010190886,0.5865569,0.12063303,0.008563424,0.2633002,0.00017200924],"about_ca_topic_score_codex":0.0057446714,"about_ca_topic_score_gemma":0.0074292165,"teacher_disagreement_score":0.0057446714,"about_ca_system_score_codex":0.0002071048,"about_ca_system_score_gemma":0.0004965045,"threshold_uncertainty_score":0.012838721},"labels":[],"label_agreement":null},{"id":"W4403930853","doi":"10.1016/j.jebo.2024.106756","title":"People do not demand commitment devices because they might not work","year":2024,"lang":"en","type":"article","venue":"Journal of Economic Behavior & Organization","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"American Economic Association; University of Ottawa; Boston College; Russell Sage Foundation; Epsilon Sigma Alpha","keywords":"Work (physics); Business; Psychology; Engineering; Mechanical engineering","score_opus":0.014400188430169995,"score_gpt":0.2386810184252176,"score_spread":0.22428082999504761,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403930853","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68231183,0.00032725546,0.009130557,0.008786375,0.0005273364,0.00011760855,0.00069299806,0.00025089644,0.29785508],"genre_scores_gemma":[0.96978104,0.000114862254,0.0013676278,0.0016810378,0.00006259644,0.00011683095,0.0003203063,0.000042445732,0.026513245],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99906236,0.00024376332,0.000042075426,0.000090105335,0.00021745199,0.00034424034],"domain_scores_gemma":[0.99426794,0.00090977823,0.0010464245,0.0011228462,0.00095108914,0.0017019442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087775977,0.00029314245,0.00030784344,0.0003314233,0.0018745699,0.0020443178,0.0007267943,0.0019596498,0.05948575],"category_scores_gemma":[0.0067757014,0.00031054774,0.00041756072,0.0003211618,0.00083530316,0.0015841532,0.0014553409,0.0015581183,0.018316664],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021423069,0.005559085,0.3571564,0.0010998956,0.0005537882,0.0029788134,0.021241004,0.0011345374,0.023164468,0.09195765,0.13410684,0.35890514],"study_design_scores_gemma":[0.00091746886,0.0025419297,0.5008793,0.0008161231,0.00034438993,0.004403244,0.0654872,0.004109952,0.008829159,0.098691806,0.31266773,0.00031174876],"about_ca_topic_score_codex":0.0008625642,"about_ca_topic_score_gemma":0.0015488347,"teacher_disagreement_score":0.05948575,"about_ca_system_score_codex":0.00030124752,"about_ca_system_score_gemma":0.0004818993,"threshold_uncertainty_score":0.19899964},"labels":[],"label_agreement":null},{"id":"W4403946247","doi":"10.1111/1468-2427.13278","title":"<scp>UBER IN EXURBIA</scp>: Peripheral Platformization, Post‐Suburbanization and the Public–Private Ridehail Partnership in the Toronto City Region","year":2024,"lang":"en","type":"article","venue":"International Journal of Urban and Regional Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Arts and Humanities Research Council; Studienstiftung des Deutschen Volkes; Deutsche Forschungsgemeinschaft","keywords":"Suburbanization; General partnership; Economic geography; Public–private partnership; Regional science; Political science; Geography; Sociology; Demography","score_opus":0.06249647191484095,"score_gpt":0.3275982939127033,"score_spread":0.26510182199786236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403946247","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9743326,0.00021236691,0.00013161612,0.0016233261,0.000008399538,0.000014779008,0.00013229264,0.0000066033435,0.02353809],"genre_scores_gemma":[0.9952443,0.00012404726,0.00004154354,0.00006554541,0.000002830197,0.000005601038,0.000043961274,0.0000032256025,0.00446892],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.99937385,0.0001319484,0.000008969752,0.000059226066,0.00011706558,0.00030892188],"domain_scores_gemma":[0.9988141,0.00015587398,0.0003474331,0.00006933879,0.00017211508,0.00044113258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006912948,0.00009493925,0.00011408038,0.00046243359,0.0037123605,0.003409064,0.00042579282,0.00034416348,0.005270928],"category_scores_gemma":[0.0011112172,0.00009422115,0.00010586085,0.0012134146,0.004488647,0.001080114,0.0024204878,0.00059902837,0.00026874995],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018584247,0.00016086131,0.37929386,0.00019643341,0.00003515168,0.0025782313,0.47901535,0.001042535,0.002045881,0.07113012,0.023841053,0.04047467],"study_design_scores_gemma":[0.0000058160867,0.00004087275,0.54391783,0.0000674646,0.000011119517,0.000117030984,0.40774214,0.00026774663,0.00040028087,0.00047209524,0.046939347,0.000018186673],"about_ca_topic_score_codex":0.7846379,"about_ca_topic_score_gemma":0.9282587,"teacher_disagreement_score":0.21536207,"about_ca_system_score_codex":0.015869621,"about_ca_system_score_gemma":0.011488627,"threshold_uncertainty_score":0.43326074},"labels":[],"label_agreement":null},{"id":"W4403971315","doi":"10.2139/ssrn.5007501","title":"A Track Slot Auction Serious Game","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Engineering Link (Canada)","funders":"","keywords":"Track (disk drive); Computer science; Computer security; Operating system","score_opus":0.006994656986017499,"score_gpt":0.23143921573117165,"score_spread":0.22444455874515415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403971315","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23443809,0.00021447909,0.59121203,0.0022834917,0.00031971498,0.0004842935,0.0005955776,0.00079609384,0.16965625],"genre_scores_gemma":[0.9014129,0.00015109245,0.042616326,0.00024451257,0.00007082574,0.00016399195,0.00027541406,0.00012883949,0.05493614],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991381,0.00031171218,0.000040010305,0.00014625603,0.00018520295,0.00017869065],"domain_scores_gemma":[0.9978859,0.0012294711,0.00011288261,0.00021294013,0.00017142281,0.00038736867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011203559,0.00074342795,0.0011959968,0.00045293957,0.0014452657,0.0033946019,0.0018850043,0.0024502082,0.023417866],"category_scores_gemma":[0.006115882,0.0004988924,0.00097555446,0.00074596284,0.0015061708,0.0039598416,0.0020861023,0.0019864447,0.0014754484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083846075,0.00030137657,0.00058524474,0.00013289365,0.00006050384,0.00026744368,0.00026368359,0.061950114,0.0019039469,0.89748585,0.013221507,0.022988958],"study_design_scores_gemma":[0.00027460957,0.00019592792,0.00018806048,0.0000150018495,0.000028679697,0.000115827665,0.00012045402,0.3108407,0.00048371658,0.6819973,0.005715288,0.000024428626],"about_ca_topic_score_codex":0.0026231036,"about_ca_topic_score_gemma":0.0027110067,"teacher_disagreement_score":0.023417866,"about_ca_system_score_codex":0.0011291143,"about_ca_system_score_gemma":0.0022249266,"threshold_uncertainty_score":0.07834053},"labels":[],"label_agreement":null},{"id":"W4404024665","doi":"10.1007/978-3-031-73122-8_14","title":"A Policy-Based Autonomic Management System for Smart Cities Leveraging Off-The-Shelf Platforms","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in networks and systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Off the shelf; Computer science; Business; Process management; Software engineering","score_opus":0.013964611997346891,"score_gpt":0.21242967650845043,"score_spread":0.19846506451110354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404024665","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0857809,0.00082565326,0.7882509,0.0013902159,0.0010967171,0.0005015023,0.00046597607,0.08275624,0.038931802],"genre_scores_gemma":[0.79792213,0.0004892962,0.1724679,0.0009646228,0.0002860244,0.00028530599,0.001021794,0.0020052278,0.024557604],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996012,0.00006479935,0.000045886343,0.00008728442,0.00013512197,0.00006569061],"domain_scores_gemma":[0.99942744,0.00008382499,0.00004033671,0.00019181747,0.000114270064,0.00014226756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088950986,0.00047032605,0.00055450975,0.00045493888,0.00071414676,0.0021296162,0.0015167767,0.00088658294,0.0042392435],"category_scores_gemma":[0.001025079,0.00034324877,0.00028937185,0.0004049313,0.0004431796,0.0018618273,0.0017448673,0.0012684875,0.0017433879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018124807,0.0017654753,0.006291848,0.00030533882,0.0003636263,0.001350483,0.0010689201,0.114077576,0.115485914,0.063549735,0.12388534,0.57004327],"study_design_scores_gemma":[0.00013120897,0.00026452693,0.0018285603,0.000041133695,0.00009552668,0.00028173736,0.00014533666,0.86935925,0.032768752,0.023087926,0.071911424,0.00008455353],"about_ca_topic_score_codex":0.0023412572,"about_ca_topic_score_gemma":0.0024980665,"teacher_disagreement_score":0.0042392435,"about_ca_system_score_codex":0.0005005839,"about_ca_system_score_gemma":0.00083701295,"threshold_uncertainty_score":0.014181614},"labels":[],"label_agreement":null},{"id":"W4404160337","doi":"10.1515/rne-2024-0047","title":"Effects of Shoe-Leather Cost on Consumer Cash Withdrawal Behavior","year":2024,"lang":"en","type":"article","venue":"Review of Network Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Cash; Business; Work (physics); Finance; Engineering","score_opus":0.008287821902134828,"score_gpt":0.2378034726207934,"score_spread":0.22951565071865856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404160337","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9951159,0.00026477868,0.0022533957,0.0003020533,0.0000111438685,0.000028574588,0.00021186458,0.000021300302,0.0017908845],"genre_scores_gemma":[0.9984328,0.00010564625,0.00025376666,0.000025039519,0.000005990978,0.000014700558,0.00011853266,0.0000033678593,0.0010401937],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988123,0.00056270347,0.000051263345,0.00017026067,0.00016176706,0.00024156056],"domain_scores_gemma":[0.9760557,0.017727813,0.0039232406,0.0008438272,0.00079707516,0.0006524037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001962998,0.00047160775,0.0005618816,0.0006702266,0.00038759768,0.0017087782,0.0009359573,0.0011649805,0.008003464],"category_scores_gemma":[0.011547956,0.0003090102,0.0010649916,0.00082200015,0.0007314169,0.0012850165,0.00077203003,0.0016101119,0.0004448258],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025716065,0.0015475663,0.85343385,0.00026470097,0.00070729904,0.0010353222,0.00058276963,0.1034825,0.0018501295,0.00989161,0.0014908576,0.023141786],"study_design_scores_gemma":[0.00009458349,0.001123698,0.687438,0.000096379925,0.0006387056,0.00022202494,0.0020441387,0.29879645,0.00092009397,0.0068691787,0.0016315015,0.00012520135],"about_ca_topic_score_codex":0.022820277,"about_ca_topic_score_gemma":0.016503647,"teacher_disagreement_score":0.022820277,"about_ca_system_score_codex":0.0019639435,"about_ca_system_score_gemma":0.0007196564,"threshold_uncertainty_score":0.04537487},"labels":[],"label_agreement":null},{"id":"W4404179575","doi":"10.1109/tiv.2024.3494873","title":"Vehicle-Specific Virtual Traffic Control Strategy to Reduce the Start-Up Delay for Autonomous Heavy Trucks","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Vehicles","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"British Columbia Institute of Technology; University of Windsor","funders":"","keywords":"Truck; Control (management); Automotive engineering; Computer science; Aeronautics; Transport engineering; Engineering","score_opus":0.029794587522929107,"score_gpt":0.2652304623690429,"score_spread":0.2354358748461138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404179575","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30862203,0.0001608485,0.6806516,0.00012027161,0.0000937569,0.00007487702,0.000046995974,0.0011922923,0.009037351],"genre_scores_gemma":[0.99232304,0.000019584246,0.0068419883,0.000013659756,0.0000053124204,0.000012049015,0.000021679398,0.000009606038,0.0007530707],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998078,0.00002626555,0.0000070865026,0.000044470908,0.000052441832,0.00006203875],"domain_scores_gemma":[0.99974877,0.000029603792,0.00004640129,0.000024738196,0.000097183154,0.000053360007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001791504,0.0004944665,0.00032010686,0.00042821578,0.0004353296,0.0005073294,0.00070750614,0.00023346127,0.0012525145],"category_scores_gemma":[0.00033611816,0.00014781886,0.00023827325,0.00018729153,0.00037643235,0.0004760165,0.0006222527,0.00031095717,0.00023469457],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038633615,0.00022900161,0.002746839,0.00007406549,0.000039942533,0.00025835424,0.00016437507,0.81433916,0.08654374,0.010732937,0.0018190378,0.082666114],"study_design_scores_gemma":[0.000015729873,0.00020650036,0.0006461268,0.0000031650536,0.000017042294,0.000054618507,0.000058547503,0.9878862,0.00829978,0.0013465849,0.0014547104,0.000010955499],"about_ca_topic_score_codex":0.0043165116,"about_ca_topic_score_gemma":0.0046620504,"teacher_disagreement_score":0.0043165116,"about_ca_system_score_codex":0.0003882204,"about_ca_system_score_gemma":0.0009841073,"threshold_uncertainty_score":0.008582771},"labels":[],"label_agreement":null},{"id":"W4404290061","doi":"10.1155/2024/2977018","title":"The Impact of Dockless Bike‐Sharing and Built Environment on Ride‐Sourcing Trips","year":2024,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"China Scholarship Council; Government of Jiangsu Province; National Natural Science Foundation of China","keywords":"TRIPS architecture; Transport engineering; Bike sharing; Business; Engineering","score_opus":0.009962001050820572,"score_gpt":0.2606428126651965,"score_spread":0.25068081161437594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404290061","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9959551,0.00012365318,0.0012899927,0.00007369978,0.0000057436137,0.000015211886,0.00030941507,0.000011418226,0.0022157854],"genre_scores_gemma":[0.99923253,0.000042220432,0.00025827065,0.0000046848286,0.0000015881061,0.000004574546,0.00010976891,0.0000026590624,0.00034375157],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99938405,0.00019185414,0.000035140805,0.000111739675,0.00013706493,0.00014013077],"domain_scores_gemma":[0.99795216,0.0008365221,0.00042648593,0.00017623107,0.00036089643,0.00024767197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071418047,0.00028422108,0.00027904168,0.0007593934,0.00041891687,0.0011747283,0.00040102564,0.00031991405,0.0027095296],"category_scores_gemma":[0.0029497817,0.00015410983,0.00059009955,0.0011590895,0.0006669899,0.0007896755,0.0011842152,0.00045452907,0.00025248312],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013898361,0.00007501093,0.95701414,0.000072677714,0.00017684477,0.00028024687,0.00055779004,0.017862717,0.001301912,0.0013676919,0.00033803936,0.02081405],"study_design_scores_gemma":[0.0000025740146,0.00007490353,0.9806518,0.000019408117,0.000070964124,0.000046456218,0.0015195503,0.015723469,0.0003612241,0.00053990184,0.0009734081,0.000016345253],"about_ca_topic_score_codex":0.033925448,"about_ca_topic_score_gemma":0.088430904,"teacher_disagreement_score":0.033925448,"about_ca_system_score_codex":0.0008722624,"about_ca_system_score_gemma":0.00095730805,"threshold_uncertainty_score":0.06745595},"labels":[],"label_agreement":null},{"id":"W4404314997","doi":"10.1016/j.commtr.2024.100149","title":"Bridging the gap: Toward a holistic understanding of shared micromobility fleet development dynamics","year":2024,"lang":"en","type":"article","venue":"Communications in Transportation Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Encana (Canada)","funders":"Kementerian Pendidikan dan Kebudayaan; OeAD-GmbH; Bundesministerium für Klimaschutz, Umwelt, Energie, Mobilität, Innovation und Technologie","keywords":"Bridging (networking); Sociology; Computer science; Computer network","score_opus":0.33476097760117646,"score_gpt":0.4202710507484132,"score_spread":0.08551007314723674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404314997","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24307576,0.0037818544,0.65105635,0.02036729,0.00018168511,0.00017752801,0.00086765323,0.000176489,0.0803154],"genre_scores_gemma":[0.95800185,0.002356823,0.036702644,0.0004358076,0.000053004154,0.00011835542,0.00016240893,0.000047422443,0.00212166],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99924517,0.0003197038,0.000029965544,0.00015796268,0.00012971852,0.00011741935],"domain_scores_gemma":[0.99769646,0.0013727158,0.0003562789,0.00022640481,0.00018543517,0.00016265872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016284077,0.00060671376,0.0006477692,0.0014255607,0.0010284911,0.004919496,0.0014794271,0.0018288472,0.0046539526],"category_scores_gemma":[0.0047320668,0.00049614493,0.0008611562,0.0012179357,0.0023688101,0.012266374,0.0038244962,0.0018527543,0.00025231924],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021774717,0.000052179264,0.006539496,0.00016610694,0.000043366683,0.00022765942,0.0016843593,0.13531633,0.0007343205,0.8353092,0.0011520742,0.0187531],"study_design_scores_gemma":[0.0000046078294,0.00003261051,0.0029100736,0.00025483436,0.000020741907,0.00010348092,0.0032420098,0.22046614,0.00027890384,0.7541326,0.018521553,0.000032394153],"about_ca_topic_score_codex":0.007107464,"about_ca_topic_score_gemma":0.0054080207,"teacher_disagreement_score":0.007107464,"about_ca_system_score_codex":0.0033306584,"about_ca_system_score_gemma":0.003280921,"threshold_uncertainty_score":0.02416575},"labels":[],"label_agreement":null},{"id":"W4404354661","doi":"10.1016/j.trc.2024.104916","title":"Reinforced stable matching for Crowd-Sourced Delivery Systems under stochastic driver acceptance behavior","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part C Emerging Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Matching (statistics); Computer science; Transport engineering; Engineering; Simulation; Mathematics; Statistics","score_opus":0.05844482951933686,"score_gpt":0.33879531300436383,"score_spread":0.28035048348502695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404354661","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15897065,0.0003777896,0.8328353,0.00048662792,0.00009227203,0.00017835037,0.00022175963,0.0003323864,0.006504859],"genre_scores_gemma":[0.9787016,0.00017161827,0.018481104,0.000074041294,0.000021402882,0.00006768213,0.00007354832,0.00003541523,0.0023736733],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984326,0.0006072243,0.0000635014,0.00030341922,0.00026875015,0.00032441213],"domain_scores_gemma":[0.99372476,0.003752576,0.0010003992,0.00034642578,0.0006678805,0.00050790777],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035476729,0.0011219126,0.0012585291,0.0011267896,0.0009147353,0.0013690419,0.0018937421,0.00134448,0.005639897],"category_scores_gemma":[0.012225275,0.00049174554,0.00097577664,0.0009594684,0.0011580759,0.00193621,0.0020450095,0.0012970065,0.0005667218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003234415,0.00012214862,0.0017321105,0.00013274315,0.000106032094,0.0002497332,0.00015312222,0.9099019,0.0028661217,0.060069967,0.0019330303,0.02240972],"study_design_scores_gemma":[0.000019294019,0.00007644035,0.0002630143,0.000008661715,0.000016719952,0.000040332394,0.000043522512,0.9790896,0.00031431476,0.019726815,0.00038733118,0.000013994286],"about_ca_topic_score_codex":0.0038529066,"about_ca_topic_score_gemma":0.0022634217,"teacher_disagreement_score":0.005639897,"about_ca_system_score_codex":0.0019412219,"about_ca_system_score_gemma":0.0014474391,"threshold_uncertainty_score":0.018867373},"labels":[],"label_agreement":null},{"id":"W4404633920","doi":"10.1016/j.ejtl.2024.100147","title":"Dynamic rebalancing for Bike-sharing systems under inventory interval and target predictions","year":2024,"lang":"en","type":"article","venue":"EURO Journal on Transportation and Logistics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Polytechnique Montréal; Group for Research in Decision Analysis; Transport Canada","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Bike sharing; Interval (graph theory); Environmental science; Computer science; Engineering; Mathematics; Transport engineering","score_opus":0.025212255535546114,"score_gpt":0.26165148600368143,"score_spread":0.2364392304681353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404633920","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.69987893,0.0004459402,0.29085192,0.00025064018,0.000051406936,0.00010276677,0.00038793983,0.00071501755,0.0073154946],"genre_scores_gemma":[0.9934128,0.000038786424,0.0060442383,0.000010480202,0.0000032009239,0.000016601525,0.000062360996,0.000021790622,0.00038978228],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997061,0.00008391627,0.000012998067,0.00005738923,0.000056204022,0.000083333936],"domain_scores_gemma":[0.9992343,0.00045340965,0.000103273924,0.00006907453,0.00008312716,0.000056763212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000692783,0.00088214054,0.0006987329,0.00036431628,0.00039485822,0.00104427,0.0007342058,0.0006291889,0.0018507306],"category_scores_gemma":[0.0018321056,0.00033502994,0.0003949288,0.00040001175,0.00038926565,0.0010090243,0.0006728454,0.0007422404,0.00015266801],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000541628,0.000019330953,0.00036447204,0.000015093718,0.0000071739237,0.000014734345,0.00001291746,0.9952342,0.0006475923,0.00042617763,0.00008220502,0.0031220245],"study_design_scores_gemma":[0.0000041529493,0.000023584806,0.0002030052,0.0000016595272,0.0000030625838,0.000004149964,0.0000125019515,0.99899286,0.0003472766,0.00033781564,0.00006742332,0.0000025237312],"about_ca_topic_score_codex":0.012918843,"about_ca_topic_score_gemma":0.0074100355,"teacher_disagreement_score":0.012918843,"about_ca_system_score_codex":0.0008037503,"about_ca_system_score_gemma":0.00090158556,"threshold_uncertainty_score":0.025687277},"labels":[],"label_agreement":null},{"id":"W4404636053","doi":"10.1016/j.cie.2024.110711","title":"MERCI: Multi-agent reinforcement learning for enhancing on-demand Electric taxi operation in terms of Rebalancing, Charging, and Informing Orders","year":2024,"lang":"en","type":"article","venue":"Computers & Industrial Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Heilongjiang Province; Natural Sciences and Engineering Research Council of Canada; Mitacs; National Natural Science Foundation of China; Canada Foundation for Innovation","keywords":"Reinforcement learning; Reinforcement; On demand; Automotive engineering; Computer science; Engineering; Business; Artificial intelligence; Structural engineering; Multimedia","score_opus":0.01918843082513213,"score_gpt":0.23391289331148532,"score_spread":0.21472446248635318,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404636053","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.080185145,0.0004887768,0.89305335,0.0006585238,0.00028569606,0.0002306539,0.000208353,0.009587433,0.015302084],"genre_scores_gemma":[0.9041208,0.00008351628,0.08868715,0.00020211373,0.000038062448,0.00015738937,0.000116549534,0.00013888834,0.0064555863],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978787,0.00006546839,0.000007493568,0.000037264967,0.00006147353,0.000040464976],"domain_scores_gemma":[0.99935263,0.00032230277,0.00008053213,0.000050477975,0.00012677474,0.0000672467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083311315,0.0009049334,0.00075559353,0.00037432858,0.00038134478,0.0005722724,0.001204945,0.0009959907,0.0044654366],"category_scores_gemma":[0.002012468,0.00034571497,0.00039410178,0.00019501515,0.00040465832,0.00052547385,0.00095323427,0.0015905898,0.00054489425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030941336,0.00029844008,0.000995315,0.00009225883,0.0000811534,0.00011149859,0.000059230177,0.91342056,0.003155073,0.004152489,0.00541281,0.071911715],"study_design_scores_gemma":[0.000019792262,0.00004025072,0.00007894662,0.0000024898354,0.0000049697105,0.00000661873,0.0000023638393,0.99867696,0.0004043565,0.0003847832,0.00037531237,0.0000030815168],"about_ca_topic_score_codex":0.0065265885,"about_ca_topic_score_gemma":0.0097487,"teacher_disagreement_score":0.0065265885,"about_ca_system_score_codex":0.00069714594,"about_ca_system_score_gemma":0.000898872,"threshold_uncertainty_score":0.0149383545},"labels":[],"label_agreement":null},{"id":"W4404644576","doi":"10.1145/3678717.3691272","title":"FleetWiz: An Intelligent Platform for Spatio-Temporal Multi-Resource Truckload Fleet Dispatching","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; University of Calgary","funders":"","keywords":"Resource (disambiguation); Computer science; Fleet management; Resource management (computing); Telecommunications; Computer network","score_opus":0.03506246363580157,"score_gpt":0.2874985627204784,"score_spread":0.25243609908467685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404644576","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015186263,0.00021423033,0.7615133,0.00037168653,0.00012129759,0.00035211002,0.0050762724,0.2074259,0.009738894],"genre_scores_gemma":[0.34239766,0.0005599585,0.6131404,0.00041539743,0.000048793216,0.0009453216,0.016232226,0.0121892085,0.014071076],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995956,0.00007834332,0.00003988892,0.0001204239,0.000117840325,0.000047925674],"domain_scores_gemma":[0.9994443,0.00024361895,0.000056424182,0.00011882419,0.00006594221,0.00007090933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011100882,0.0015617529,0.00065172673,0.00089805014,0.0005539102,0.0015162937,0.0026251487,0.0010519725,0.012669261],"category_scores_gemma":[0.0023232466,0.00071992807,0.0014794897,0.00043447892,0.00059408543,0.002136262,0.0027087077,0.0016592338,0.003108336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015736133,0.000496267,0.0046424693,0.000862449,0.0004119919,0.0010005634,0.0011779583,0.6399592,0.02943826,0.05454857,0.105067946,0.16082066],"study_design_scores_gemma":[0.00010847916,0.00006550111,0.0004283275,0.000047895508,0.000034780744,0.00006867706,0.0000719625,0.9417943,0.0053303656,0.011877065,0.04010283,0.00006973129],"about_ca_topic_score_codex":0.015000383,"about_ca_topic_score_gemma":0.018648421,"teacher_disagreement_score":0.015000383,"about_ca_system_score_codex":0.0013868693,"about_ca_system_score_gemma":0.0015046434,"threshold_uncertainty_score":0.042382896},"labels":[],"label_agreement":null},{"id":"W4404647587","doi":"10.1139/cjce-2023-0539","title":"Measuring safety benefits of a connected cruise control–equipped vehicle in a connected road environment","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Motor Association Foundation for Traffic Safety; Alberta Innovates","keywords":"Cruise control; Automotive engineering; Cruise; Vehicle safety; Transport engineering; Control (management); Computer science; Engineering; Aeronautics; Aerospace engineering","score_opus":0.011275917494557992,"score_gpt":0.17083467879638942,"score_spread":0.15955876130183141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404647587","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99885666,0.0000098762575,0.0007975469,0.0000029178739,0.000002333776,0.000013631248,0.00003199929,0.000010759733,0.00027416853],"genre_scores_gemma":[0.9990225,0.000017793482,0.00069061836,0.000003112561,0.0000018621432,0.000011610803,0.00009892005,0.0000025150434,0.00015098632],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996221,0.000088642286,0.000020237016,0.000074615746,0.00014795379,0.000046380057],"domain_scores_gemma":[0.99910283,0.0002686686,0.00019818355,0.00006810092,0.00023977949,0.00012249834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023351895,0.000415673,0.00016298969,0.0006148835,0.00020009073,0.00035187005,0.00029952693,0.00035943085,0.00084846915],"category_scores_gemma":[0.0018257067,0.00011465926,0.00024028498,0.0003133615,0.00024971468,0.0004547397,0.0005885448,0.00018721297,0.00019191836],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0048637213,0.0019052239,0.6532959,0.0004101979,0.000445578,0.0008930065,0.0017467425,0.06911558,0.1881932,0.0006641744,0.0003942796,0.07807236],"study_design_scores_gemma":[0.00006139525,0.014177182,0.87300545,0.00005203307,0.00035834132,0.00044985136,0.0023774656,0.06266644,0.04495527,0.000610906,0.0011962106,0.00008944618],"about_ca_topic_score_codex":0.0024037664,"about_ca_topic_score_gemma":0.0033900943,"teacher_disagreement_score":0.0024037664,"about_ca_system_score_codex":0.00022536844,"about_ca_system_score_gemma":0.00026718128,"threshold_uncertainty_score":0.004779637},"labels":[],"label_agreement":null},{"id":"W4404687420","doi":"10.1063/5.0240016","title":"Analysis of optimal location of motorcycle taxi shelter online in the Tegal station area","year":2024,"lang":"en","type":"article","venue":"AIP conference proceedings","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministry of Transportation of Ontario","funders":"","keywords":"Computer science; Transport engineering; Engineering","score_opus":0.02330237305096217,"score_gpt":0.26303234375292395,"score_spread":0.23972997070196178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404687420","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.927601,0.00041467452,0.055141207,0.00054217613,0.000047767924,0.00013143918,0.0005706758,0.00012353683,0.015427627],"genre_scores_gemma":[0.9928154,0.000098856166,0.004407734,0.000014828248,0.000011356567,0.000020034493,0.0001103442,0.000020795022,0.0025005664],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997222,0.00008082055,0.0000061640176,0.0000453932,0.00003511497,0.000110174115],"domain_scores_gemma":[0.99901927,0.000575444,0.00011221801,0.00003108672,0.0001677106,0.000094284784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067081227,0.0005206443,0.00085932587,0.0009030642,0.0005511257,0.0014452037,0.0010108777,0.0010973368,0.0057295514],"category_scores_gemma":[0.0022408501,0.0007593293,0.00086065836,0.0007798939,0.0005575983,0.0009517528,0.00055426906,0.00055774185,0.0002693004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001561605,0.00007825159,0.004428723,0.0000507154,0.000039694685,0.00020047544,0.00004124934,0.9854897,0.0011185062,0.0035489486,0.0008664818,0.0039809803],"study_design_scores_gemma":[0.00000966552,0.000037897986,0.001806708,0.0000049677833,0.000018318178,0.000012757028,0.0000987334,0.99711657,0.00024457547,0.0005116756,0.00013293966,0.0000051263723],"about_ca_topic_score_codex":0.051547874,"about_ca_topic_score_gemma":0.034680083,"teacher_disagreement_score":0.051547874,"about_ca_system_score_codex":0.002272244,"about_ca_system_score_gemma":0.0022120725,"threshold_uncertainty_score":0.10249567},"labels":[],"label_agreement":null},{"id":"W4404717201","doi":"10.2139/ssrn.5034583","title":"Integrated Mobile Inventory and Fleet Management for an On-Demand Delivery System","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Fleet management; Inventory management; Business; Delivery system; Operations management; Computer science; Telecommunications; Engineering","score_opus":0.011259321318687942,"score_gpt":0.23821250598931829,"score_spread":0.22695318467063033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404717201","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38884285,0.0005473491,0.59377855,0.000526391,0.00015296531,0.00039905647,0.0006512412,0.00088059966,0.014220984],"genre_scores_gemma":[0.97569865,0.0001287189,0.019463258,0.000026704654,0.00003224002,0.00005903626,0.000172802,0.000035322526,0.0043832655],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995865,0.00009070368,0.000021071857,0.0000797034,0.000098992416,0.00012294183],"domain_scores_gemma":[0.99971646,0.00008775892,0.00004069843,0.000029785946,0.00008608056,0.000039183065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060293626,0.00082634063,0.0010354236,0.0005876091,0.00069414405,0.0018528452,0.0010965567,0.0008071709,0.003447562],"category_scores_gemma":[0.0008751695,0.0004992737,0.0006867851,0.0007820969,0.00028546975,0.0011051513,0.0009132826,0.0006321119,0.0003950619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023443389,0.00015495726,0.0015911818,0.00005454004,0.000040653667,0.000119679244,0.000051824347,0.9503675,0.003945771,0.0025362847,0.00085342117,0.040049765],"study_design_scores_gemma":[0.000008236355,0.00007879053,0.0005481538,0.0000025411127,0.000015698526,0.000016189333,0.000022726217,0.9980483,0.0003898304,0.00058441947,0.00027965335,0.000005602417],"about_ca_topic_score_codex":0.020260822,"about_ca_topic_score_gemma":0.016783373,"teacher_disagreement_score":0.020260822,"about_ca_system_score_codex":0.0014702786,"about_ca_system_score_gemma":0.0014088993,"threshold_uncertainty_score":0.040285766},"labels":[],"label_agreement":null},{"id":"W4404748985","doi":"10.1080/07352166.2024.2427643","title":"From ride hailing to food hailing: Understanding on-demand food delivery through platform urbanism and urban policy in Canadian cities","year":2024,"lang":"en","type":"article","venue":"Journal of Urban Affairs","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University; University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Urbanism; Food delivery; Business; Urban policy; Marketing; Urban planning; Geography; Engineering; Architecture; Civil engineering","score_opus":0.03775094512675631,"score_gpt":0.23938527934596476,"score_spread":0.20163433421920846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404748985","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7323629,0.0025771256,0.0032269324,0.02121317,0.000056376222,0.000121266894,0.0005192529,0.000026025586,0.239897],"genre_scores_gemma":[0.9938008,0.0011105996,0.00053265435,0.00026396266,0.0000049599694,0.000021924625,0.000059129346,0.000009792235,0.004196201],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9984321,0.00033870703,0.000030623494,0.00016392773,0.00024524523,0.00078951626],"domain_scores_gemma":[0.99774003,0.00062945153,0.000308581,0.000108289896,0.0006250813,0.00058870495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016279528,0.0004316642,0.00029081723,0.0027918108,0.015652632,0.010003011,0.0016912525,0.001418518,0.006148034],"category_scores_gemma":[0.004064876,0.000336039,0.0004413705,0.004865062,0.012875167,0.004083933,0.0051950603,0.0016433524,0.0002522216],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000084626445,0.00013458656,0.0843902,0.0003031019,0.00004153898,0.0010235705,0.29081723,0.006278651,0.000634149,0.57122487,0.009073999,0.035993554],"study_design_scores_gemma":[0.000014832516,0.00002849064,0.0690395,0.00047689214,0.000054297478,0.00009973159,0.760342,0.0058641336,0.00032841755,0.03451762,0.12914848,0.00008560232],"about_ca_topic_score_codex":0.9917157,"about_ca_topic_score_gemma":0.99478525,"teacher_disagreement_score":0.19329731,"about_ca_system_score_codex":0.19329731,"about_ca_system_score_gemma":0.106320225,"threshold_uncertainty_score":0.9356608},"labels":[],"label_agreement":null},{"id":"W4404781324","doi":"10.18653/v1/2024.nllp-1.27","title":"Empowering Air Travelers: A Chatbot for Canadian Air Passenger Rights","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Alliance de recherche numérique du Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Chatbot; Air travel; Aeronautics; Computer science; Business; Aviation; Internet privacy; World Wide Web; Engineering; Aerospace engineering","score_opus":0.011659491713722075,"score_gpt":0.2504366419675655,"score_spread":0.2387771502538434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404781324","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6171223,0.0028315482,0.18033212,0.0072347056,0.0011041792,0.0027986171,0.0037490122,0.059502438,0.12532511],"genre_scores_gemma":[0.8569067,0.00071776065,0.084456936,0.0009055368,0.0002064305,0.00066957896,0.0023390646,0.00062303094,0.053174965],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993617,0.00024440113,0.00003096911,0.00009836539,0.0001345736,0.0001299512],"domain_scores_gemma":[0.99690056,0.0016184772,0.00009410448,0.00016815419,0.0005232189,0.00069541886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011486241,0.0010422951,0.0003329266,0.0009075518,0.0028660875,0.0012313625,0.0011151321,0.0013114155,0.014700712],"category_scores_gemma":[0.004768777,0.00020652347,0.000307972,0.00044268012,0.00082589046,0.0019589085,0.0018159938,0.000815989,0.0022191396],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029338805,0.0014928317,0.01853929,0.0030557772,0.00013045203,0.0058580856,0.07643107,0.004421478,0.12763578,0.010763491,0.2063438,0.54239416],"study_design_scores_gemma":[0.00064170593,0.002751377,0.049352273,0.0011249521,0.00046903192,0.0034144996,0.048136994,0.1043128,0.049506865,0.006339054,0.73309773,0.00085267826],"about_ca_topic_score_codex":0.15341702,"about_ca_topic_score_gemma":0.25278866,"teacher_disagreement_score":0.846583,"about_ca_system_score_codex":0.0021839475,"about_ca_system_score_gemma":0.0031667931,"threshold_uncertainty_score":0.30504805},"labels":[],"label_agreement":null},{"id":"W4404787921","doi":"10.1109/tnse.2024.3507545","title":"QPoS: Decentralized Stake-Based Leader and Voter Selection in a PBFT System With Mobile Voters","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Network Science and Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Selection (genetic algorithm); Voter model; Computer science; Artificial intelligence; Mathematics; Statistics","score_opus":0.006583386807191674,"score_gpt":0.1948719971657569,"score_spread":0.18828861035856523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404787921","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23430128,0.00010479666,0.7611124,0.00035882127,0.00006146628,0.0002634153,0.0001064494,0.00035064993,0.0033407041],"genre_scores_gemma":[0.9847483,0.000024898829,0.013933884,0.000025128671,0.000013294606,0.00006842528,0.000026836053,0.00000928608,0.0011500181],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99818796,0.0007265209,0.00007496128,0.00033989348,0.0003320433,0.0003386134],"domain_scores_gemma":[0.9959377,0.0021217165,0.0005826538,0.000552578,0.0004057463,0.0003995318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002481272,0.00041628373,0.00086609204,0.00038253888,0.0010003375,0.001076234,0.0015803507,0.0008683623,0.0026945125],"category_scores_gemma":[0.0062139262,0.0002699909,0.00046290708,0.0003826649,0.0014074751,0.0015852631,0.0021357494,0.00085434393,0.00034758946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020875796,0.00023721825,0.0066648005,0.00027088771,0.0001325649,0.0015161451,0.0012828399,0.72631073,0.031825367,0.1519507,0.002113519,0.07560768],"study_design_scores_gemma":[0.00011054073,0.00018507252,0.00030672335,0.000010621381,0.000015505006,0.00011977714,0.00007446436,0.9705273,0.0026260635,0.025240395,0.0007659763,0.000017468728],"about_ca_topic_score_codex":0.0019503707,"about_ca_topic_score_gemma":0.0019211199,"teacher_disagreement_score":0.0026945125,"about_ca_system_score_codex":0.00085740583,"about_ca_system_score_gemma":0.0013775247,"threshold_uncertainty_score":0.01312238},"labels":[],"label_agreement":null},{"id":"W4404795724","doi":"10.1109/tiv.2024.3509315","title":"Improving Takeover Requests in Automated Vehicles: The Role of Dynamic Alerts and Cognitive State","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Vehicles","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"State (computer science); Cognition; Computer science; Computer security; Business; Internet privacy; Psychology; Neuroscience","score_opus":0.007762492682576885,"score_gpt":0.24119095997968915,"score_spread":0.23342846729711225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404795724","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99934465,0.000028192804,0.00042900944,0.000009318277,0.0000012350416,0.0000055660917,0.0000058604587,0.0000063633365,0.00016988807],"genre_scores_gemma":[0.99963224,0.000022043852,0.0002441416,0.000005928752,0.0000028000286,0.000004556248,0.000014133571,0.000001813481,0.0000723996],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999361,0.000235723,0.000045888573,0.00008050393,0.00019042338,0.000086551336],"domain_scores_gemma":[0.9959986,0.0021014295,0.0010362895,0.00016168562,0.00041178157,0.0002901664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000618875,0.00041341185,0.00019324616,0.00034008778,0.00016183534,0.00059399795,0.00019661598,0.00026679717,0.00067634997],"category_scores_gemma":[0.007636715,0.00011881018,0.0001916532,0.0001280436,0.00015305456,0.00037831784,0.0004793169,0.00021956576,0.00010878482],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023615581,0.0017516828,0.7358085,0.00030498786,0.0002743552,0.0003193156,0.0056528402,0.0029979825,0.087593414,0.00012691254,0.00021758638,0.16259097],"study_design_scores_gemma":[0.000015912025,0.0018241428,0.9853821,0.000017946713,0.00007981981,0.00011860157,0.0015233806,0.003936651,0.006676998,0.00015003573,0.00025082967,0.000023500666],"about_ca_topic_score_codex":0.0010940222,"about_ca_topic_score_gemma":0.0015359598,"teacher_disagreement_score":0.0010940222,"about_ca_system_score_codex":0.00018869434,"about_ca_system_score_gemma":0.0002142766,"threshold_uncertainty_score":0.0032729506},"labels":[],"label_agreement":null},{"id":"W4405099770","doi":"10.1080/00207543.2024.2436652","title":"Dynamically dealing with requests in a stochastic multi-period home healthcare problem with consistency constraints","year":2024,"lang":"en","type":"article","venue":"International Journal of Production Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Revenue; Operations research; Consistency (knowledge bases); Computer science; Health care; Agency (philosophy); Profit (economics); Operations management; Service provider; Rule of thumb; Service (business); Business; Marketing; Economics; Engineering; Microeconomics; Artificial intelligence; Finance","score_opus":0.05140990102300406,"score_gpt":0.3714518967494734,"score_spread":0.3200419957264693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405099770","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37712768,0.000840299,0.6141903,0.0018637481,0.00015365792,0.0003347755,0.0007370152,0.00035322807,0.004399295],"genre_scores_gemma":[0.95162225,0.000254617,0.045413565,0.000135129,0.00006626573,0.00018560704,0.0003339044,0.000080959835,0.0019077528],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977392,0.0010936528,0.00012050534,0.00039973418,0.00021765206,0.00042929433],"domain_scores_gemma":[0.9939382,0.0045844642,0.0006422658,0.0001666091,0.00026566914,0.00040273153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038416493,0.0012514264,0.0019567125,0.00070053386,0.0007821382,0.0019556307,0.0021538814,0.0024052397,0.002714971],"category_scores_gemma":[0.0077681807,0.0011603173,0.0011039323,0.0011721106,0.0009210562,0.0019447395,0.001162488,0.0014851693,0.00020568866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000978867,0.000052057534,0.00089296204,0.000047097074,0.000048274866,0.0001292182,0.00004614083,0.99205536,0.00033542077,0.0028057785,0.00032858545,0.003161241],"study_design_scores_gemma":[0.0000228875,0.000052474214,0.00036343167,0.0000068818586,0.000015198455,0.000046188892,0.00006358863,0.99595296,0.00017519001,0.0030689852,0.0002231936,0.0000090668045],"about_ca_topic_score_codex":0.0072878147,"about_ca_topic_score_gemma":0.0038041777,"teacher_disagreement_score":0.0072878147,"about_ca_system_score_codex":0.0014011787,"about_ca_system_score_gemma":0.0017190916,"threshold_uncertainty_score":0.02031684},"labels":[],"label_agreement":null},{"id":"W4405122745","doi":"10.5267/j.ijiec.2024.10.006","title":"Green pickup and delivery problem with private drivers for crowd-shipping distribution considering traffic congestion","year":2024,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Pickup; Traffic congestion; Transport engineering; Distribution (mathematics); Business; Computer science; Automotive engineering; Computer security; Engineering; Mathematics; Artificial intelligence","score_opus":0.02292143232867713,"score_gpt":0.235166849413481,"score_spread":0.21224541708480388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405122745","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4599379,0.00075658935,0.5299215,0.0010169013,0.00012452019,0.00023005556,0.00040767493,0.0002975383,0.0073073795],"genre_scores_gemma":[0.97573507,0.00018520204,0.020517062,0.00005736826,0.000016212385,0.000096706935,0.00015865192,0.000025219528,0.003208461],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99949,0.00014288946,0.000022715958,0.00012540548,0.000056992245,0.00016199311],"domain_scores_gemma":[0.9991818,0.00042460256,0.000121865254,0.000027020891,0.00009913208,0.00014558736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094255904,0.0011534024,0.0019623674,0.0005719199,0.0008359955,0.0014197938,0.001383902,0.0017580136,0.0020819146],"category_scores_gemma":[0.0015351606,0.0007802589,0.0012498683,0.00063396594,0.00079973985,0.0010011651,0.0013696939,0.0010378852,0.00014697909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006215691,0.00002847597,0.00055740826,0.000036498473,0.000021718628,0.0001440645,0.000026241398,0.9942941,0.0003891597,0.00190057,0.00024768407,0.0022919448],"study_design_scores_gemma":[0.000011504835,0.000024976582,0.00010254431,0.0000025704096,0.00000936528,0.000010886161,0.000029568211,0.99858814,0.00008889861,0.0009995773,0.00012809435,0.000003846191],"about_ca_topic_score_codex":0.018625034,"about_ca_topic_score_gemma":0.008130771,"teacher_disagreement_score":0.018625034,"about_ca_system_score_codex":0.0016033028,"about_ca_system_score_gemma":0.0017262215,"threshold_uncertainty_score":0.0370332},"labels":[],"label_agreement":null},{"id":"W4405135848","doi":"10.1016/j.trip.2024.101289","title":"Optimizing travel costs of feeder-integrated public transport system: A methodology","year":2024,"lang":"en","type":"article","venue":"Transportation Research Interdisciplinary Perspectives","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; UK Research and Innovation","keywords":"Public transport; Transport engineering; Business; Computer science; Operations research; Engineering","score_opus":0.1171599430972618,"score_gpt":0.3994606062827081,"score_spread":0.2823006631854463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405135848","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047030147,0.00068212656,0.94238085,0.00046010097,0.000056018853,0.00030100727,0.0003997265,0.00016401104,0.00852603],"genre_scores_gemma":[0.5229378,0.0009353608,0.46753404,0.00018750833,0.00007853047,0.00091853424,0.00061039644,0.000111331414,0.006686511],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996432,0.0001478693,0.00001551077,0.000071272705,0.00006536777,0.00005671738],"domain_scores_gemma":[0.9994143,0.0003463731,0.00006310299,0.000024053605,0.000117882686,0.00003432611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001227926,0.0010903255,0.000974216,0.0012474023,0.00047474046,0.0011634224,0.001460235,0.0013889101,0.004205198],"category_scores_gemma":[0.0017897605,0.0006573253,0.0012940002,0.0016449013,0.00045483134,0.0007323774,0.00077372143,0.000992554,0.00023368887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009993951,0.00003053611,0.00026308477,0.00004378687,0.000024983578,0.000035640525,0.00001016408,0.986809,0.00019446055,0.0031195437,0.00035182483,0.009106923],"study_design_scores_gemma":[0.00000606632,0.00001710806,0.000085157015,0.0000075678013,0.0000103138555,0.000007851966,0.000011868039,0.9980697,0.00008589099,0.0013350304,0.00036096544,0.0000025747263],"about_ca_topic_score_codex":0.015051611,"about_ca_topic_score_gemma":0.009519154,"teacher_disagreement_score":0.015051611,"about_ca_system_score_codex":0.0015565531,"about_ca_system_score_gemma":0.0029063814,"threshold_uncertainty_score":0.029927969},"labels":[],"label_agreement":null},{"id":"W4405299765","doi":"10.4230/lipics.mfcs.2024.19","title":"The Canadian Traveller Problem on Outerplanar Graphs","year":2024,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Agence Nationale de la Recherche","keywords":"Outerplanar graph; Computer science; Combinatorics; Mathematics; Discrete mathematics; Pathwidth; Graph; Line graph","score_opus":0.00835453155064097,"score_gpt":0.19910095488260074,"score_spread":0.19074642333195976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405299765","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5902467,0.0015374979,0.30959246,0.0045017665,0.00014320147,0.0007329013,0.0027275993,0.0011724844,0.08934535],"genre_scores_gemma":[0.835848,0.0017169238,0.120824486,0.0004277321,0.00008682578,0.0002261572,0.0027724837,0.00033527034,0.037762213],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99893373,0.00023547464,0.000024082217,0.00022065277,0.00018941844,0.00039660133],"domain_scores_gemma":[0.99767417,0.0012087737,0.00027901822,0.00014261801,0.00022278754,0.0004726183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007587904,0.0013626252,0.0010667696,0.0009956093,0.002311401,0.0020499425,0.0032110813,0.0018862985,0.010650329],"category_scores_gemma":[0.005450011,0.00053096004,0.000696683,0.002908745,0.0016409571,0.0044437596,0.0019031578,0.0015386905,0.00090680626],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010706905,0.00043940838,0.0031051086,0.0006697086,0.0001558482,0.00063107815,0.0010645067,0.5378795,0.0058222287,0.31824434,0.032818712,0.09809887],"study_design_scores_gemma":[0.00019739155,0.00025393383,0.0016728129,0.000053903976,0.00008804641,0.0004567733,0.0011239853,0.79680735,0.0045921924,0.159034,0.035642255,0.00007738653],"about_ca_topic_score_codex":0.15932105,"about_ca_topic_score_gemma":0.13798216,"teacher_disagreement_score":0.15932105,"about_ca_system_score_codex":0.0053079436,"about_ca_system_score_gemma":0.004978945,"threshold_uncertainty_score":0.31678742},"labels":[],"label_agreement":null},{"id":"W4405334776","doi":"10.1051/shsconf/202420801022","title":"Study on the Impact of Autonomous Driving Technology on the Economy and Society","year":2024,"lang":"en","type":"article","venue":"SHS Web of Conferences","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Economy; Economics; Business; Economic system","score_opus":0.022366313605854775,"score_gpt":0.2732636110945066,"score_spread":0.2508972974886518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405334776","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91947967,0.00063388865,0.00072599703,0.0013254862,0.000026430269,0.000028356135,0.000047826234,0.000004690389,0.077727675],"genre_scores_gemma":[0.99637324,0.0005268723,0.000137829,0.000113357855,0.000010109991,0.0000083780715,0.000017703342,0.0000017237104,0.0028108994],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996222,0.0001264282,0.000008823195,0.000034550954,0.00012916175,0.000078798446],"domain_scores_gemma":[0.9988682,0.00052698853,0.00016039153,0.000037366568,0.00027588624,0.00013114093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042080463,0.00011257077,0.00009331058,0.00068507076,0.00094190356,0.001583633,0.00020587073,0.00039459518,0.0033412217],"category_scores_gemma":[0.0013817272,0.00004711237,0.00018216883,0.0010207517,0.0007619017,0.0018516787,0.00057522405,0.000462494,0.0003060694],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018306077,0.0012982605,0.43509042,0.0006845757,0.000100248966,0.0025204367,0.059695184,0.0049554813,0.006718931,0.22420675,0.00860968,0.255937],"study_design_scores_gemma":[0.000017060558,0.0009386176,0.5813691,0.00035504482,0.000099864395,0.00097212027,0.18863066,0.0116758365,0.0041515795,0.029741604,0.18197925,0.000069224334],"about_ca_topic_score_codex":0.005596412,"about_ca_topic_score_gemma":0.0076445863,"teacher_disagreement_score":0.005596412,"about_ca_system_score_codex":0.0011164242,"about_ca_system_score_gemma":0.0010988729,"threshold_uncertainty_score":0.01117754},"labels":[],"label_agreement":null},{"id":"W4405487342","doi":"10.1145/3670865.3673446","title":"Pricing Shared Rides","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science","score_opus":0.01124696836800215,"score_gpt":0.22721928721800067,"score_spread":0.2159723188499985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405487342","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2377196,0.0016714613,0.4119549,0.0054847538,0.0016278863,0.00062084914,0.0009971071,0.0009148426,0.33900866],"genre_scores_gemma":[0.96258205,0.00032519715,0.011635246,0.00017387338,0.000141899,0.00010626923,0.00014527499,0.00007279022,0.024817241],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99727327,0.0006044428,0.00009629825,0.00046459155,0.0010846383,0.00047676617],"domain_scores_gemma":[0.9968665,0.001087013,0.00032233016,0.00066272536,0.00074685307,0.00031456238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018565448,0.0007975461,0.0007065517,0.00059991964,0.0011095416,0.004279655,0.0027032183,0.0022980683,0.02186214],"category_scores_gemma":[0.013976487,0.00044524155,0.000769109,0.00093785283,0.001599778,0.00683568,0.0018909456,0.0021376966,0.002174333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002738184,0.0002958298,0.0025048254,0.00018349914,0.00008096273,0.00021042455,0.00032013105,0.07043867,0.0025664384,0.8001515,0.014480389,0.10849352],"study_design_scores_gemma":[0.00016567326,0.00073310104,0.0048359646,0.00018019129,0.000105355844,0.00046034507,0.0009783802,0.40901375,0.0040048985,0.48521897,0.09415748,0.00014596457],"about_ca_topic_score_codex":0.0030878098,"about_ca_topic_score_gemma":0.0027666062,"teacher_disagreement_score":0.02186214,"about_ca_system_score_codex":0.0021984158,"about_ca_system_score_gemma":0.0017314901,"threshold_uncertainty_score":0.07313615},"labels":[],"label_agreement":null},{"id":"W4405487704","doi":"10.1016/j.rtbm.2024.101277","title":"Will you still drive or are you ready to ride? Exploring readiness to use demand-responsive transport in the City of Vienna","year":2024,"lang":"en","type":"article","venue":"Research in Transportation Business & Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Österreichische Forschungsförderungsgesellschaft; Bundesministerium für Klimaschutz, Umwelt, Energie, Mobilität, Innovation und Technologie","keywords":"Transport engineering; Business; Engineering","score_opus":0.15778732460289158,"score_gpt":0.35854162965406267,"score_spread":0.2007543050511711,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405487704","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99886864,0.00004931717,0.0002090495,0.000104148574,0.0000019310385,0.000008174087,0.00007383324,0.0000015074955,0.00068337226],"genre_scores_gemma":[0.9994222,0.00007431927,0.00019413084,0.00001496905,8.8829495e-7,0.00001131818,0.00006391824,0.0000018081632,0.00021649986],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991161,0.00043308822,0.000042439795,0.0000933993,0.00009635511,0.00021858772],"domain_scores_gemma":[0.99890125,0.00050600944,0.00023909683,0.00004510742,0.00013595085,0.00017256268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012261565,0.00016591551,0.0002922414,0.00070238084,0.0005603507,0.0016707567,0.00047409197,0.0005744266,0.0018591691],"category_scores_gemma":[0.0027807849,0.00026186233,0.00044462932,0.0007944866,0.00063916645,0.00092340715,0.0012886144,0.00074079965,0.00028518846],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034368277,0.00040472177,0.86457205,0.00035587745,0.00018818563,0.0013189503,0.083924346,0.0036642454,0.0027215264,0.004153818,0.0018947972,0.03645795],"study_design_scores_gemma":[0.000009124116,0.00028286822,0.7678894,0.0002045735,0.00005634975,0.00034253704,0.2179997,0.005550349,0.00054241467,0.0010052992,0.006038459,0.00007888215],"about_ca_topic_score_codex":0.038954392,"about_ca_topic_score_gemma":0.06317804,"teacher_disagreement_score":0.038954392,"about_ca_system_score_codex":0.0019703787,"about_ca_system_score_gemma":0.0009915002,"threshold_uncertainty_score":0.07745528},"labels":[],"label_agreement":null},{"id":"W4405709710","doi":"10.1109/iceccme62383.2024.10797134","title":"Optimizing the Location of Opportunity Chargers for Urban Buses Using a Multi-Criteria Decision-Making Approach","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Computer science","score_opus":0.07757310096000351,"score_gpt":0.3275395432793212,"score_spread":0.2499664423193177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405709710","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10030956,0.00027827994,0.89212245,0.00036211516,0.000051905787,0.00035322702,0.00012568684,0.00011953784,0.006277152],"genre_scores_gemma":[0.854871,0.00018538487,0.14229177,0.00006229153,0.000020461483,0.00028809122,0.000092227085,0.000024935498,0.0021637804],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989519,0.0005057449,0.0000407881,0.0001403206,0.00016326757,0.00019785187],"domain_scores_gemma":[0.99868757,0.0008229088,0.00014072686,0.000029980027,0.00018761889,0.00013115835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021139674,0.0012551162,0.0012245319,0.0015164042,0.0008061612,0.0022984082,0.0013860759,0.0016087765,0.0031059047],"category_scores_gemma":[0.002840733,0.00075043266,0.0010638823,0.0012350532,0.0007504845,0.0011541425,0.00111246,0.0009749064,0.00024170913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057363217,0.00006447878,0.0004730476,0.000053893564,0.000029937386,0.00008502778,0.000050161365,0.9848734,0.0007501132,0.003341589,0.00022780366,0.009993273],"study_design_scores_gemma":[0.000016513817,0.00007238594,0.00015823274,0.000012990318,0.000018047744,0.000012081444,0.0000711389,0.9964134,0.00044893622,0.0024832913,0.00028263722,0.000010413953],"about_ca_topic_score_codex":0.0051116752,"about_ca_topic_score_gemma":0.005523973,"teacher_disagreement_score":0.0051116752,"about_ca_system_score_codex":0.0015851635,"about_ca_system_score_gemma":0.002297562,"threshold_uncertainty_score":0.011501253},"labels":[],"label_agreement":null},{"id":"W4405801380","doi":"10.1155/atr/9210901","title":"Understanding the Spatial Variation of Integrated Use of Ride‐Hailing Services With the Metro","year":2024,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Research of Jiangsu Higher Education Institutions of China; Ministry of Education of the People's Republic of China; National Natural Science Foundation of China; Nanjing Forestry University","keywords":"Variation (astronomy); Transport engineering; Spatial variability; Engineering; Computer science; Geography; Statistics; Mathematics","score_opus":0.026048803387646043,"score_gpt":0.2363361492804229,"score_spread":0.21028734589277687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405801380","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99696213,0.00020426972,0.0013205308,0.000067357076,0.000005896962,0.00000934962,0.00028716403,0.000008239004,0.0011350184],"genre_scores_gemma":[0.9993118,0.00007009491,0.00020632161,0.000005214595,0.0000042215265,0.000004103015,0.00021591967,0.00000154118,0.0001808062],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991843,0.000171349,0.000061302286,0.00023680285,0.00016398412,0.00018218903],"domain_scores_gemma":[0.9982741,0.0004786768,0.0005486429,0.00018135026,0.0003703096,0.00014697484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007498168,0.00027106365,0.00033911667,0.0015499752,0.00039303454,0.000846976,0.00048336663,0.00022616294,0.0013216309],"category_scores_gemma":[0.0034310792,0.00015627057,0.0005346073,0.0027377608,0.00044754302,0.00088302145,0.0010121568,0.00030467837,0.0001624324],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001737353,0.000020234262,0.9887672,0.00003054085,0.000111293324,0.00014220034,0.0009260969,0.0011179761,0.0003951068,0.00058911904,0.00016291038,0.0077199675],"study_design_scores_gemma":[8.642497e-7,0.000014005988,0.99468875,0.000009361694,0.00003726214,0.00005447398,0.0016457698,0.002616576,0.00008300858,0.00018080925,0.00066263485,0.0000065464073],"about_ca_topic_score_codex":0.059913848,"about_ca_topic_score_gemma":0.07627309,"teacher_disagreement_score":0.059913848,"about_ca_system_score_codex":0.0005873988,"about_ca_system_score_gemma":0.00075706997,"threshold_uncertainty_score":0.119130194},"labels":[],"label_agreement":null},{"id":"W4405887423","doi":"10.1016/j.cities.2024.105683","title":"Impact of attitudinal factors and mode-specific transportation policies on the intention to adopt MaaS: The moderating role of urban scale","year":2024,"lang":"en","type":"article","venue":"Cities","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministry of Education and Child Care","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Scale (ratio); Mode (computer interface); Psychology; Business; Mode choice; Social psychology; Political science; Public transport; Geography; Computer science; Law","score_opus":0.02212665876306723,"score_gpt":0.2563382168975664,"score_spread":0.23421155813449918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405887423","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976705,0.00008292443,0.00015547725,0.00020279043,0.000013382265,0.000012990654,0.00007117032,0.000004456505,0.0017862457],"genre_scores_gemma":[0.99898666,0.00004107342,0.00009666713,0.000033613847,0.0000066748166,0.000012302817,0.00005098617,0.0000035804123,0.0007684067],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979024,0.00095667364,0.000112549096,0.00031755609,0.00019623539,0.0005145078],"domain_scores_gemma":[0.9857757,0.0076423464,0.0025007427,0.001151258,0.0007237426,0.0022062832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024519688,0.0003965529,0.00036688845,0.00047768012,0.00081395125,0.0019718148,0.0007010074,0.0011601996,0.012783704],"category_scores_gemma":[0.009432707,0.00039209818,0.0012194779,0.000642522,0.0010601893,0.0009090283,0.0014032745,0.0018281125,0.00056561845],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005430266,0.0011015759,0.99084103,0.000026832076,0.0003216932,0.00009383597,0.0012722479,0.00033979403,0.0005677126,0.0007619087,0.00019430254,0.0039360304],"study_design_scores_gemma":[0.000019685831,0.0003116632,0.99444324,0.000024939796,0.00020548743,0.000026620428,0.002773796,0.0011210211,0.00021759029,0.0003300609,0.0005141389,0.000011774997],"about_ca_topic_score_codex":0.022966148,"about_ca_topic_score_gemma":0.027627222,"teacher_disagreement_score":0.022966148,"about_ca_system_score_codex":0.00073235715,"about_ca_system_score_gemma":0.0019980168,"threshold_uncertainty_score":0.045664966},"labels":[],"label_agreement":null},{"id":"W4405908699","doi":"10.1109/wf-iot62078.2024.10811331","title":"Legal considerations for the transportation of unaccompanied minors in autonomous vehicles","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Computer security; Transport engineering; Business; Engineering","score_opus":0.02085860114025121,"score_gpt":0.24820705801642162,"score_spread":0.22734845687617042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405908699","genre_codex":"other","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20912951,0.008047129,0.023335334,0.21227384,0.0044396515,0.001012379,0.0013949082,0.000569047,0.5397983],"genre_scores_gemma":[0.76952624,0.0073772487,0.019017369,0.07965712,0.00083904556,0.00059563096,0.000741832,0.00014705982,0.122098476],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99077094,0.0012814747,0.00057200965,0.000506167,0.0047108512,0.002158509],"domain_scores_gemma":[0.9904156,0.0026334466,0.00085174403,0.0004305279,0.0045297085,0.0011389967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004376301,0.00039946835,0.0002939143,0.0014282403,0.009605536,0.003331429,0.0031140815,0.0049458994,0.0053789676],"category_scores_gemma":[0.0144559555,0.0005269028,0.0007677821,0.0007351387,0.0057855705,0.0020017617,0.0027097822,0.0042330567,0.0008435216],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011888071,0.0002201001,0.04643583,0.0005593722,0.000054475582,0.0047171856,0.03501714,0.002913529,0.004627286,0.6115208,0.2014295,0.092385806],"study_design_scores_gemma":[0.000057476293,0.0001786548,0.0365993,0.002720471,0.0001070352,0.0027272848,0.026109545,0.0014032936,0.0019220785,0.021223284,0.90671617,0.00023545777],"about_ca_topic_score_codex":0.7415445,"about_ca_topic_score_gemma":0.85797584,"teacher_disagreement_score":0.7415445,"about_ca_system_score_codex":0.013588214,"about_ca_system_score_gemma":0.054691672,"threshold_uncertainty_score":0.51995516},"labels":[],"label_agreement":null},{"id":"W4405957417","doi":"10.1016/j.trb.2024.103146","title":"Investment and financing of roadway digital infrastructure for automated driving","year":2025,"lang":"en","type":"article","venue":"Transportation Research Part B Methodological","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Science Foundation","keywords":"Finance; Investment (military); Transport engineering; Business; Computer science; Engineering; Politics","score_opus":0.1553383962284856,"score_gpt":0.43041796763843987,"score_spread":0.27507957140995426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405957417","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8852838,0.0010387943,0.0663792,0.0046886983,0.00009345555,0.00018459871,0.0009742435,0.00018847456,0.0411686],"genre_scores_gemma":[0.9963558,0.00021272963,0.0015914703,0.000033093937,0.00001292134,0.000031340627,0.00008903974,0.0000069780967,0.0016665977],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99906605,0.000402127,0.000023753215,0.00008369819,0.00011026006,0.00031411904],"domain_scores_gemma":[0.9975556,0.0013475709,0.00046593437,0.00011372597,0.00018542756,0.00033176682],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015566362,0.00036988253,0.0003565562,0.0006876135,0.0003268481,0.00201168,0.00079958927,0.0014697011,0.0057044956],"category_scores_gemma":[0.008180822,0.00038496783,0.0003964896,0.00056685763,0.00080171454,0.0026225708,0.0010187383,0.0010418459,0.00029530152],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006442646,0.00029066837,0.022111427,0.00034288844,0.000109503984,0.00073890557,0.0002953537,0.49643397,0.002685445,0.38204253,0.007272554,0.08703257],"study_design_scores_gemma":[0.00016210998,0.00054153614,0.02000886,0.00027610836,0.0001785393,0.00057890447,0.0015033449,0.7962174,0.004204813,0.15337351,0.022874601,0.00008018026],"about_ca_topic_score_codex":0.0033119111,"about_ca_topic_score_gemma":0.00279081,"teacher_disagreement_score":0.0057044956,"about_ca_system_score_codex":0.0032139125,"about_ca_system_score_gemma":0.0025458012,"threshold_uncertainty_score":0.023318648},"labels":[],"label_agreement":null},{"id":"W4405961022","doi":"10.1093/geroni/igae098.1113","title":"END-USER PERSPECTIVES ON POLICIES FOR SOCIAL ROBOTICS WITH AGING APPLICATIONS","year":2024,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Robotics; Artificial intelligence; Computer science; Human–computer interaction; Robot","score_opus":0.020297538378892224,"score_gpt":0.2955455717468233,"score_spread":0.2752480333679311,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405961022","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80387235,0.0011189819,0.02602573,0.052353453,0.0003639823,0.0004783287,0.00014780961,0.00016288762,0.115476616],"genre_scores_gemma":[0.98875797,0.00032331966,0.0040695127,0.0040969155,0.000044480694,0.00021366886,0.00002559925,0.000029874745,0.002438665],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.94033855,0.04907797,0.0019499534,0.0014040997,0.0038666083,0.0033628934],"domain_scores_gemma":[0.8938808,0.08583876,0.0055681085,0.0031752246,0.008079591,0.0034575083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06433105,0.0005743806,0.00037257926,0.0013847016,0.008150973,0.0130915735,0.001477706,0.0064402344,0.0044851005],"category_scores_gemma":[0.08269954,0.00039267878,0.00066686625,0.00087576226,0.0114467405,0.010165607,0.008558541,0.004767659,0.00069186056],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020173292,0.00032760648,0.018712834,0.00057669246,0.000023871024,0.0011571667,0.8029251,0.001093527,0.0028815134,0.1257277,0.0058790324,0.0404932],"study_design_scores_gemma":[0.00003750592,0.000331732,0.006696759,0.0016128173,0.00003744081,0.00047612088,0.77167207,0.0023695023,0.0028736447,0.020098671,0.19367324,0.000120547986],"about_ca_topic_score_codex":0.004019904,"about_ca_topic_score_gemma":0.003234627,"teacher_disagreement_score":0.06433105,"about_ca_system_score_codex":0.008876279,"about_ca_system_score_gemma":0.007303797,"threshold_uncertainty_score":0.34021914},"labels":[],"label_agreement":null},{"id":"W4406064172","doi":"10.1016/j.trc.2024.104987","title":"Two-echelon prize-collecting vehicle routing with time windows and vehicle synchronization: A branch-and-price approach","year":2025,"lang":"en","type":"article","venue":"Transportation Research Part C Emerging Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Vehicle routing problem; Synchronization (alternating current); Computer science; Time synchronization; Real-time computing; Routing (electronic design automation); Operations research; Engineering; Computer network","score_opus":0.025061015596330834,"score_gpt":0.2965486321030091,"score_spread":0.27148761650667824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406064172","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04230732,0.00074476615,0.9445318,0.00075736357,0.000097125114,0.00022014299,0.00022101495,0.00038950288,0.010730908],"genre_scores_gemma":[0.54109675,0.0009832403,0.44409686,0.00025893573,0.00018497661,0.00036238218,0.0005835045,0.00031425484,0.012119191],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989839,0.00041163873,0.000035722052,0.00018453215,0.00016761576,0.00021654776],"domain_scores_gemma":[0.99829787,0.0011635397,0.00016268043,0.000084031424,0.00013376265,0.00015814709],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002322233,0.0013466201,0.0024187337,0.0011829755,0.00085002533,0.002069543,0.0021948977,0.0015101358,0.0076225623],"category_scores_gemma":[0.0036151786,0.0008879488,0.0011284191,0.0022657649,0.00094380445,0.0025536048,0.0014063583,0.0017767857,0.00063533476],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013133371,0.00011132432,0.00044261216,0.000095646865,0.000057382065,0.0001062017,0.000056299898,0.92971164,0.0004935022,0.035281315,0.0022344443,0.031278275],"study_design_scores_gemma":[0.000015891634,0.00002909511,0.00004845193,0.0000046087334,0.000008871484,0.000012838215,0.000015408827,0.9875339,0.00011753991,0.011609201,0.000600113,0.000004005],"about_ca_topic_score_codex":0.0061773877,"about_ca_topic_score_gemma":0.0059360676,"teacher_disagreement_score":0.0076225623,"about_ca_system_score_codex":0.002290902,"about_ca_system_score_gemma":0.0023685836,"threshold_uncertainty_score":0.02550006},"labels":[],"label_agreement":null},{"id":"W4406226687","doi":"10.1016/j.trpro.2024.12.134","title":"Development and implementation of equity: implication for Mobility-as-a-Service in Japan","year":2025,"lang":"en","type":"article","venue":"Transportation research procedia","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Equity (law); Business; Transport engineering; Service (business); Telecommunications; Computer security; Computer science; Marketing; Engineering; Political science","score_opus":0.06541641524687401,"score_gpt":0.4275874528384389,"score_spread":0.3621710375915649,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406226687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8412935,0.0020977007,0.010675276,0.021267734,0.00013749745,0.00032923973,0.000056052373,0.000030692496,0.12411234],"genre_scores_gemma":[0.9962845,0.00035150602,0.00152323,0.00030944514,0.000015315189,0.00004079648,0.0000105701565,0.0000033095087,0.0014612643],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99556917,0.0019724546,0.00018987914,0.0002775761,0.0006458812,0.0013450079],"domain_scores_gemma":[0.99589807,0.00082942395,0.0006510729,0.00017440654,0.0012012621,0.0012458522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0058381287,0.0002753773,0.00022351436,0.0008611763,0.0031126966,0.0052470462,0.00075321714,0.0009066966,0.0023638704],"category_scores_gemma":[0.007523377,0.00017090602,0.00033208562,0.00096806407,0.0039613065,0.0048131477,0.0070055504,0.0011333757,0.00008607104],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014636233,0.00056755415,0.25810277,0.0007395122,0.00007719965,0.0013993676,0.06053377,0.0023849937,0.0033407996,0.42686185,0.005128566,0.24071732],"study_design_scores_gemma":[0.000057555277,0.00082501036,0.4811397,0.001442435,0.00019976584,0.000586375,0.27615914,0.007654496,0.0031883593,0.09509787,0.13354465,0.000104694416],"about_ca_topic_score_codex":0.029751414,"about_ca_topic_score_gemma":0.03731122,"teacher_disagreement_score":0.029751414,"about_ca_system_score_codex":0.008898199,"about_ca_system_score_gemma":0.0142958965,"threshold_uncertainty_score":0.06456125},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"medium"}],"label_agreement":"split"},{"id":"W4406230562","doi":"10.1016/j.trpro.2024.12.061","title":"Impact of Life-course events on hierarchical Vehicle transaction durations: Case of a Developing country.","year":2025,"lang":"en","type":"article","venue":"Transportation research procedia","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Calgary","keywords":"Life course approach; Course (navigation); Database transaction; Developing country; Computer security; Computer science; Business; Engineering; Forensic engineering; Psychology; Economics; Economic growth; Database; Developmental psychology","score_opus":0.035081078293931395,"score_gpt":0.3794066919984146,"score_spread":0.3443256137044832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406230562","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974408,0.00015079486,0.00026655346,0.00024862107,0.00000471125,0.000011941028,0.0006591259,0.000004468228,0.0012128911],"genre_scores_gemma":[0.99899966,0.00013583308,0.00016000807,0.0000171996,0.0000026634825,0.000008240079,0.0003872476,0.0000025092409,0.00028674284],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994042,0.00024384719,0.000024536568,0.0000656322,0.000046990157,0.00021482694],"domain_scores_gemma":[0.9960658,0.0019698124,0.00095557614,0.00015585612,0.0003190725,0.0005338243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012503702,0.00025562107,0.0003032037,0.0010866977,0.0009988429,0.0011331679,0.0007043446,0.0007371728,0.004406244],"category_scores_gemma":[0.0047515905,0.0002308146,0.0005078367,0.001954555,0.00058763317,0.001116763,0.0012825326,0.0013478865,0.000422522],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003141151,0.00037911566,0.9637308,0.000097490854,0.000105190804,0.0051620686,0.0031999114,0.0116406195,0.0002944929,0.0028292292,0.0016069455,0.010639997],"study_design_scores_gemma":[0.000024419829,0.0002264017,0.9243623,0.0000850019,0.00012513729,0.0012540772,0.031041475,0.038116872,0.00036301216,0.0014852849,0.0028629822,0.00005303601],"about_ca_topic_score_codex":0.083269134,"about_ca_topic_score_gemma":0.070689686,"teacher_disagreement_score":0.083269134,"about_ca_system_score_codex":0.0015812666,"about_ca_system_score_gemma":0.00072662253,"threshold_uncertainty_score":0.16556889},"labels":[],"label_agreement":null},{"id":"W4406383638","doi":"10.1016/s0967-0653(97)85066-1","title":"10.1016/s0967-0653(97)85066-1","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Negotiation; Business; Computer science; Sociology; Social science","score_opus":0.006604953601666713,"score_gpt":0.1678893115943601,"score_spread":0.1612843579926934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406383638","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00046686182,0.0003967612,0.0005729304,0.0003798351,0.00033667093,0.00010393101,0.0005630054,0.00070395804,0.996476],"genre_scores_gemma":[0.000512148,0.00019124518,0.00025542153,0.00018760626,0.00005633386,0.00005018931,0.00029245234,0.000117120646,0.9983375],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992849,0.000044490655,0.000060150862,0.0002729196,0.00017866032,0.00015886349],"domain_scores_gemma":[0.9979504,0.00047849352,0.00012991145,0.00022090823,0.0005247353,0.00069553935],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0010522036,0.0029745277,0.0018708683,0.0028165583,0.0025797603,0.0043426873,0.0033411442,0.0063094627,0.98888576],"category_scores_gemma":[0.0016559582,0.0009464965,0.0014198938,0.0024383513,0.0019975225,0.005797918,0.0031096174,0.0026048694,0.99237716],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000349649,0.00023478197,0.0009167079,0.00066183484,0.000035441775,0.00030243993,0.00014476394,0.000408087,0.0020710574,0.0060925493,0.3710542,0.6177285],"study_design_scores_gemma":[0.000043140648,0.00012919657,0.00062178064,0.00034868723,0.000014397264,0.00036995235,0.00014488137,0.00017473262,0.00029201852,0.0005817714,0.99725866,0.000020766887],"about_ca_topic_score_codex":0.0037404331,"about_ca_topic_score_gemma":0.0032900996,"teacher_disagreement_score":0.01111424,"about_ca_system_score_codex":0.0012017487,"about_ca_system_score_gemma":0.0012382263,"threshold_uncertainty_score":0.015853047},"labels":[],"label_agreement":null},{"id":"W4406455536","doi":"10.1016/s0029-7437(10)70388-8","title":"10.1016/s0029-7437(10)70388-8","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Medicine; Urinary incontinence; Business; Urology","score_opus":0.005968262649232386,"score_gpt":0.17049949795100877,"score_spread":0.16453123530177638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406455536","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00042852137,0.0004376559,0.00067499315,0.00030727332,0.00029044563,0.000085129854,0.00066274137,0.00069780025,0.9964154],"genre_scores_gemma":[0.00060101086,0.00019429217,0.00029033638,0.00012481319,0.000059792095,0.00005121156,0.00034913624,0.00014650762,0.99818295],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993333,0.000043328873,0.00005168778,0.00024103954,0.0001856684,0.00014483316],"domain_scores_gemma":[0.9980286,0.0005606144,0.00013657701,0.00021629054,0.00042516176,0.00063264696],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00111117,0.0030564913,0.0020933074,0.0033487075,0.0025737481,0.004749246,0.003901922,0.0063309195,0.9883741],"category_scores_gemma":[0.0015352996,0.0010163956,0.0014551952,0.0032023115,0.0024029831,0.005412927,0.0030978865,0.0028966155,0.99212474],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029933802,0.0002412255,0.00082856923,0.00082020607,0.0000456471,0.00029442346,0.00014409507,0.00052001624,0.0027403596,0.008513756,0.3351115,0.6504409],"study_design_scores_gemma":[0.00004135539,0.000112554844,0.00062539923,0.00035496047,0.000013296654,0.00028176507,0.00012781276,0.00023816842,0.00042368943,0.00068643875,0.9970734,0.000021156236],"about_ca_topic_score_codex":0.003933131,"about_ca_topic_score_gemma":0.0029738038,"teacher_disagreement_score":0.011625886,"about_ca_system_score_codex":0.0013597712,"about_ca_system_score_gemma":0.0014864249,"threshold_uncertainty_score":0.016582847},"labels":[],"label_agreement":null},{"id":"W4406509236","doi":"10.1016/s0197-2510(05)70182-0","title":"10.1016/s0197-2510(05)70182-0","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Style (visual arts); Psychology; Business; Art; Literature","score_opus":0.004584965472018148,"score_gpt":0.15882833104177116,"score_spread":0.15424336556975302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406509236","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00033850435,0.00027384516,0.0004912211,0.00032531426,0.00022749852,0.000071324655,0.00046403852,0.00063570676,0.99717253],"genre_scores_gemma":[0.0004521147,0.00012404895,0.0002163411,0.00013640038,0.00004051047,0.000035371388,0.0002650492,0.000104596766,0.9986255],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993543,0.00004375942,0.000053479427,0.00021560352,0.00019112365,0.00014174618],"domain_scores_gemma":[0.99811006,0.00044429427,0.00012388043,0.00019936066,0.00044662805,0.0006758181],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009793498,0.0022900705,0.0015210167,0.0027618743,0.0023010187,0.0040987614,0.0029434983,0.0061686235,0.98809075],"category_scores_gemma":[0.001740407,0.00077154534,0.0012502528,0.0024698009,0.0015768876,0.004686878,0.0028095974,0.0022080652,0.9914131],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023595731,0.00020772137,0.0008832175,0.00050887425,0.000028653018,0.00023207805,0.00012878208,0.00035529112,0.0016830463,0.0072470913,0.3448664,0.6436229],"study_design_scores_gemma":[0.000029008344,0.00008191928,0.00053900003,0.00024022323,0.0000089764135,0.00022061601,0.00010910052,0.00015151151,0.00025043785,0.0005266479,0.99782854,0.000014030047],"about_ca_topic_score_codex":0.004760594,"about_ca_topic_score_gemma":0.0037629658,"teacher_disagreement_score":0.011909246,"about_ca_system_score_codex":0.0012435433,"about_ca_system_score_gemma":0.0015702171,"threshold_uncertainty_score":0.016987026},"labels":[],"label_agreement":null},{"id":"W4406638487","doi":"10.1016/b978-0-7506-3993-4.50150-3","title":"10.1016/b978-0-7506-3993-4.50150-3","year":2000,"lang":"en","type":"book-chapter","venue":"Time to knit","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.007737549174752337,"score_gpt":0.1635101002514176,"score_spread":0.15577255107666527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406638487","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019195915,0.0003690084,0.00093051966,0.00021689119,0.00013887802,0.000041735664,0.0005527582,0.0007920933,0.9967662],"genre_scores_gemma":[0.00046237913,0.00021117821,0.00031008048,0.000085798034,0.000025405134,0.000028478107,0.00033947747,0.00017761768,0.9983596],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99952817,0.000025276026,0.000027371216,0.00017561109,0.00015574285,0.00008786021],"domain_scores_gemma":[0.9985973,0.0004651663,0.00009399095,0.0001995204,0.00028344398,0.00036045257],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008479163,0.0021530953,0.0013404009,0.001953706,0.0014488988,0.0043086265,0.002742419,0.004370645,0.9803382],"category_scores_gemma":[0.0014421304,0.00081298803,0.0008199707,0.0018741846,0.001200001,0.0049068164,0.0031140388,0.0020493632,0.98934525],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001396389,0.00013824561,0.0004068309,0.00046514618,0.000015949521,0.00014404528,0.00010436481,0.00037907032,0.002813854,0.0073476187,0.35867506,0.62937015],"study_design_scores_gemma":[0.000014992616,0.00004639673,0.0004341749,0.00025445275,0.000007366535,0.0001851907,0.000091449445,0.00013033721,0.00037062465,0.0011086637,0.9973442,0.000012164362],"about_ca_topic_score_codex":0.0031501814,"about_ca_topic_score_gemma":0.0030762749,"teacher_disagreement_score":0.019661784,"about_ca_system_score_codex":0.0009248886,"about_ca_system_score_gemma":0.00076903636,"threshold_uncertainty_score":0.028045058},"labels":[],"label_agreement":null},{"id":"W4406736466","doi":"10.1115/imece2024-144185","title":"Hybrid Locomotive Consists: Balancing Operational and Embodied Carbon Effects","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Embodied cognition; Automotive engineering; Engineering","score_opus":0.004289988086556713,"score_gpt":0.20676899341779117,"score_spread":0.20247900533123447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406736466","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9917359,0.000016632785,0.00654081,0.0000075074936,0.0000019096726,0.000020446349,0.000045045093,0.000023989545,0.0016077354],"genre_scores_gemma":[0.998672,0.000009090942,0.00071103673,0.0000011071517,2.973528e-7,0.0000057516086,0.000027757276,0.000003155104,0.00056986994],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.999806,0.000051254385,0.000010185043,0.000034222976,0.000052814394,0.0000456006],"domain_scores_gemma":[0.9995665,0.00020008616,0.00005524153,0.000067334004,0.00008004183,0.000030758416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043311118,0.000353507,0.00038938108,0.00047989222,0.0002880064,0.0005619148,0.00057785126,0.00032147882,0.0020414821],"category_scores_gemma":[0.0008245219,0.00018945131,0.00036408054,0.00045281264,0.00049954694,0.0005409363,0.00045869205,0.00018282329,0.00016779316],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011160901,0.00018615273,0.040819917,0.00017609767,0.00016714366,0.0006109691,0.00020071246,0.875052,0.050421376,0.002419613,0.00015171754,0.028678196],"study_design_scores_gemma":[0.0000666514,0.0021923897,0.097714245,0.000021958014,0.00016653343,0.00037612516,0.0011011865,0.8508115,0.04343833,0.002230876,0.0018252915,0.00005489595],"about_ca_topic_score_codex":0.004824696,"about_ca_topic_score_gemma":0.010263776,"teacher_disagreement_score":0.004824696,"about_ca_system_score_codex":0.00052224495,"about_ca_system_score_gemma":0.00024511182,"threshold_uncertainty_score":0.009593248},"labels":[],"label_agreement":null},{"id":"W4407128605","doi":"10.1109/tits.2025.3534836","title":"Enhancing the Collaborative Decision-Making Performance of Connected and Autonomous Vehicles: A Multi-Modal Failure-Aware Graph Representation Approach","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Modal; Computer science; Representation (politics); Graph; Theoretical computer science","score_opus":0.013671673008791466,"score_gpt":0.2594996012435245,"score_spread":0.24582792823473304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407128605","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023143848,0.00010576876,0.97521317,0.00014879131,0.000016077385,0.000025717254,0.000026882091,0.00024296892,0.0010767968],"genre_scores_gemma":[0.8838284,0.000141355,0.11427671,0.000104009894,0.000029860867,0.00010849211,0.00012675379,0.00005465471,0.001329852],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933845,0.00019046993,0.000026155909,0.00018938082,0.0001648405,0.00009054775],"domain_scores_gemma":[0.99881697,0.000543033,0.00022667185,0.000117136675,0.0002074216,0.00008874244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009549841,0.0009999598,0.0008686073,0.00093500625,0.0005071333,0.0008201821,0.0016208437,0.0009937448,0.0012123233],"category_scores_gemma":[0.0030518235,0.000377488,0.0008952002,0.00062358327,0.00070781197,0.0016585822,0.0014529459,0.0010375442,0.00020785337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035486886,0.00003124803,0.0005843708,0.000029793006,0.000029437817,0.0000593023,0.000074328564,0.9619329,0.0018020103,0.006105787,0.00034305867,0.028972194],"study_design_scores_gemma":[0.0000024019666,0.000011824563,0.000056776204,0.0000015154058,0.0000043640957,0.000006296584,0.0000071506997,0.9968766,0.00019451091,0.002725072,0.00011025937,0.0000032499877],"about_ca_topic_score_codex":0.0069017564,"about_ca_topic_score_gemma":0.004216543,"teacher_disagreement_score":0.0069017564,"about_ca_system_score_codex":0.00094706437,"about_ca_system_score_gemma":0.0011694222,"threshold_uncertainty_score":0.013723195},"labels":[],"label_agreement":null},{"id":"W4407162067","doi":"10.1190/4d-forum2024-026.1","title":"Determining the value of 4D: An East Coast Canada example","year":2025,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Value (mathematics); Computer science","score_opus":0.013323623950826617,"score_gpt":0.216251577686503,"score_spread":0.20292795373567638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407162067","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6104555,0.00090307137,0.17857824,0.0070855008,0.000089945665,0.0006228159,0.0066396394,0.00072856375,0.19489674],"genre_scores_gemma":[0.86631554,0.0004960379,0.10972491,0.00017913822,0.000007156978,0.0001028824,0.00074263476,0.00009562844,0.022336055],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9988667,0.00022829702,0.000035261426,0.000105458676,0.000540235,0.00022411485],"domain_scores_gemma":[0.9973435,0.001093741,0.00009745344,0.00014499764,0.0011925639,0.00012771187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014294819,0.0005338442,0.00039460027,0.0021413807,0.0020847498,0.0022198765,0.0013162286,0.001104253,0.0055677094],"category_scores_gemma":[0.0060089678,0.00038818948,0.00074054656,0.0030684932,0.0013627185,0.001288064,0.0012325734,0.0011082339,0.00038504842],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031915685,0.00022346429,0.049704146,0.00024097656,0.000100551835,0.0011608613,0.00097268994,0.5720449,0.0026172916,0.25372425,0.012833699,0.10605803],"study_design_scores_gemma":[0.00008535133,0.00009555386,0.014593776,0.00010571977,0.000067838526,0.00017951154,0.0025283396,0.88315517,0.0037131486,0.060374238,0.03498826,0.00011302178],"about_ca_topic_score_codex":0.90086657,"about_ca_topic_score_gemma":0.9263674,"teacher_disagreement_score":0.09913343,"about_ca_system_score_codex":0.023900101,"about_ca_system_score_gemma":0.016141517,"threshold_uncertainty_score":0.19943446},"labels":[],"label_agreement":null},{"id":"W4407194486","doi":"10.1007/s10479-025-06477-z","title":"Sustainable ridesharing routing and scheduling problem: an efficient multi-objective adaptive large neighborhood search","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Hebei Province Outstanding Youth Fund; Humanities and Social Sciences Youth Foundation, Ministry of Education of the People's Republic of China","keywords":"Computer science; Theory of computation; Scheduling (production processes); Vehicle routing problem; Mathematical optimization; Job shop scheduling; Routing (electronic design automation); Distributed computing; Computer network; Mathematics; Algorithm","score_opus":0.10301871189886422,"score_gpt":0.40639415954148794,"score_spread":0.3033754476426237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407194486","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11361797,0.0010008549,0.87332475,0.00078794727,0.00013771569,0.00022138191,0.0002699126,0.00025011995,0.010389285],"genre_scores_gemma":[0.7809259,0.00051023264,0.20919527,0.00017052724,0.00008609917,0.00033217954,0.0003249065,0.00009283598,0.008361947],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994684,0.00024194433,0.00001957281,0.00010892002,0.00009238238,0.000068857924],"domain_scores_gemma":[0.9993098,0.00046845968,0.000070817405,0.000028209462,0.00007428427,0.000048460148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012268767,0.0007406104,0.0018469276,0.000989591,0.0005578035,0.0009825502,0.0018175616,0.0017090508,0.002483037],"category_scores_gemma":[0.0022208116,0.0005634704,0.0007979334,0.0010889367,0.0006294526,0.0012336511,0.0011052085,0.0007758811,0.00020099054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006372675,0.00006264292,0.00023573401,0.000061324405,0.000033538814,0.00004806738,0.0000191403,0.982534,0.00043242026,0.004145094,0.00085257925,0.011511725],"study_design_scores_gemma":[0.000010401856,0.000024234772,0.00004006578,0.0000023959246,0.0000061249098,0.000007925407,0.000007725153,0.9987198,0.000051308973,0.0009666827,0.0001612106,0.0000021302033],"about_ca_topic_score_codex":0.0077071832,"about_ca_topic_score_gemma":0.0060238927,"teacher_disagreement_score":0.0077071832,"about_ca_system_score_codex":0.0008710494,"about_ca_system_score_gemma":0.0015458511,"threshold_uncertainty_score":0.015324652},"labels":[],"label_agreement":null},{"id":"W4407572216","doi":"10.1007/s11116-025-10590-0","title":"Agent-based modelling of older adult needs for autonomous mobility-on-demand: a case study in Winnipeg, Canada","year":2025,"lang":"en","type":"article","venue":"Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Economic and Social Research Council; University of Leeds","keywords":"Transport engineering; Geography; Gerontology; Engineering; Medicine","score_opus":0.01712668110204327,"score_gpt":0.24442048730345217,"score_spread":0.2272938062014089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407572216","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9657358,0.00044341298,0.012647482,0.0015069968,0.00004735213,0.00044427646,0.0030919458,0.00012022465,0.015962588],"genre_scores_gemma":[0.98430586,0.00030657565,0.008222406,0.000078748206,0.0000052398836,0.00011396366,0.001093086,0.000024265397,0.005849757],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961215,0.000115998046,0.000020509951,0.00005528885,0.000071348215,0.00012469545],"domain_scores_gemma":[0.9989718,0.000364564,0.000049787952,0.000038225007,0.00038110258,0.00019449432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000777296,0.00079029024,0.00047277307,0.00073382986,0.0022406944,0.0017523699,0.001975823,0.0012398238,0.003045719],"category_scores_gemma":[0.0021613466,0.0004663439,0.0007449637,0.0012574136,0.0008909242,0.0005320573,0.0011220826,0.000786192,0.0002436037],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029932908,0.00036641286,0.06577179,0.00020764374,0.00010833137,0.0023976206,0.001938311,0.8957448,0.0010337008,0.013889325,0.005926725,0.012315944],"study_design_scores_gemma":[0.00009339025,0.00006690902,0.019210229,0.00006578029,0.0000557303,0.00008881529,0.0040863105,0.96540505,0.0004056038,0.0012377923,0.00922738,0.000056978064],"about_ca_topic_score_codex":0.9886486,"about_ca_topic_score_gemma":0.98541707,"teacher_disagreement_score":0.026287168,"about_ca_system_score_codex":0.026287168,"about_ca_system_score_gemma":0.020028459,"threshold_uncertainty_score":0.19072765},"labels":[],"label_agreement":null},{"id":"W4407584849","doi":"10.3390/futuretransp5010019","title":"Planning and Economic Feasibility of Electric-Connected Automated Microtransit First/Last Mile Service Under Uncertainty","year":2025,"lang":"en","type":"article","venue":"Future Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mile; Last mile (transportation); Service (business); Computer science; Operations research; Aeronautics; Business; Engineering; Geography; Marketing; Geodesy","score_opus":0.009251236311526433,"score_gpt":0.24222742803555639,"score_spread":0.23297619172402995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407584849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.794079,0.00046774693,0.17339411,0.00085771474,0.00004490899,0.0004493999,0.0010579189,0.00013747788,0.029511657],"genre_scores_gemma":[0.99116397,0.00014255127,0.006497989,0.000012650432,0.000005439783,0.00009042724,0.00013335772,0.000016271724,0.001937339],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999159,0.00039791674,0.000023658975,0.000091017486,0.00013299983,0.00019538526],"domain_scores_gemma":[0.99763036,0.0017219471,0.00021009422,0.00004697888,0.00019449412,0.00019606481],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015095767,0.00070001365,0.00063602783,0.00079855265,0.000670509,0.0019335386,0.00081541296,0.0010963394,0.0035725913],"category_scores_gemma":[0.0032892819,0.000764323,0.00093407935,0.0008565072,0.00091331045,0.001324451,0.0009225515,0.0010036707,0.00021921055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059769067,0.0000114119575,0.0006240551,0.000013100592,0.000007804538,0.00005331715,0.000011607023,0.9956475,0.000113441005,0.0021315007,0.00008331521,0.0012430912],"study_design_scores_gemma":[0.00000814311,0.00005656294,0.0007256816,0.0000068590366,0.000011242754,0.000015259044,0.00008657221,0.996407,0.0002547439,0.0021421947,0.00027682504,0.000008901405],"about_ca_topic_score_codex":0.030267762,"about_ca_topic_score_gemma":0.021450335,"teacher_disagreement_score":0.030267762,"about_ca_system_score_codex":0.003669858,"about_ca_system_score_gemma":0.003337654,"threshold_uncertainty_score":0.060183167},"labels":[],"label_agreement":null},{"id":"W4407783213","doi":"10.1109/ispa63168.2024.00110","title":"Dependency-aware Task Offloading and Resource Pricing in Vehicular Edge Computing: A Stackelberg Game Approach","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Stackelberg competition; Computer science; Dependency (UML); Task (project management); Enhanced Data Rates for GSM Evolution; Game theory; Resource management (computing); Edge computing; Resource (disambiguation); Distributed computing; Computer network; Artificial intelligence; Microeconomics; Economics","score_opus":0.009605567641186087,"score_gpt":0.218953289093893,"score_spread":0.20934772145270691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407783213","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05562317,0.0002915883,0.9372918,0.0004885472,0.00008705994,0.00014536729,0.00006973216,0.00011042246,0.005892333],"genre_scores_gemma":[0.94395596,0.00032086982,0.05268201,0.000139362,0.000037750902,0.00011335163,0.000043518077,0.000028274902,0.0026790125],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989242,0.00037651966,0.000034482175,0.00016737255,0.00017129479,0.00032614003],"domain_scores_gemma":[0.99923575,0.00039905417,0.00007976605,0.000036340185,0.000115549796,0.00013348137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014880162,0.001449402,0.0012687438,0.00071911345,0.0009801063,0.0015386591,0.0020014457,0.0014502918,0.0018099085],"category_scores_gemma":[0.0022109214,0.0004897292,0.0008682221,0.00072147476,0.0013910208,0.0018961582,0.001647853,0.0014847888,0.00015306272],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008605077,0.00007651537,0.0005498016,0.000045125817,0.000040707713,0.000153476,0.00008107123,0.9526953,0.0016256577,0.03234871,0.000810795,0.011486838],"study_design_scores_gemma":[0.000007932975,0.000027967299,0.00005440917,0.000002739153,0.0000090572,0.000017227883,0.000022447442,0.99178046,0.00023035293,0.007580982,0.0002599338,0.000006443597],"about_ca_topic_score_codex":0.012185646,"about_ca_topic_score_gemma":0.010244666,"teacher_disagreement_score":0.012185646,"about_ca_system_score_codex":0.0021185463,"about_ca_system_score_gemma":0.003278678,"threshold_uncertainty_score":0.024229407},"labels":[],"label_agreement":null},{"id":"W4407810764","doi":"10.1007/978-3-031-70973-9_35","title":"Heterotaxy and Isomerism","year":2024,"lang":"en","type":"book-chapter","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; University of Toronto; Hospital for Sick Children","funders":"","keywords":"Heterotaxy; Medicine; Internal medicine","score_opus":0.009036612430784999,"score_gpt":0.19043638308168176,"score_spread":0.18139977065089677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407810764","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0051900805,0.0025407625,0.009330856,0.0012242501,0.00044881398,0.000011379411,0.000056239925,0.000057322315,0.9811404],"genre_scores_gemma":[0.17509623,0.0074241175,0.0073178294,0.0010647683,0.0004818289,0.00007228578,0.00015902394,0.0001589589,0.80822486],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998493,0.00002350681,0.0000039862593,0.00004224569,0.00005750034,0.000023551374],"domain_scores_gemma":[0.99994564,0.000015813077,0.0000057038205,0.00001719449,0.0000097775055,0.000005817606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014919727,0.00031863106,0.00026622394,0.00045762403,0.0007131097,0.0013091598,0.0004675388,0.000708987,0.019715842],"category_scores_gemma":[0.0002424877,0.00014313546,0.00023056299,0.0005422067,0.0029887864,0.002090589,0.0009339361,0.0019745051,0.003928934],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004682712,0.0000034966297,0.000017961374,0.000013030293,8.993243e-7,0.000027277121,0.00006840851,0.00014586453,0.0007340222,0.9781254,0.0047630984,0.016095884],"study_design_scores_gemma":[0.0000032927778,0.000017730381,0.0001787956,0.000027633323,0.0000026909343,0.0003490011,0.00016866486,0.00038756622,0.0015369015,0.6698273,0.3274928,0.000007684049],"about_ca_topic_score_codex":0.0012360634,"about_ca_topic_score_gemma":0.0014812145,"teacher_disagreement_score":0.019715842,"about_ca_system_score_codex":0.0014927868,"about_ca_system_score_gemma":0.00046908134,"threshold_uncertainty_score":0.065956056},"labels":[],"label_agreement":null},{"id":"W4407949388","doi":"10.1109/cdc56724.2024.10886682","title":"Coverage Control with Heterogeneous Robot Teams via Multi-Marginal Optimal Transport","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Computer science; Robot; Control (management); Distributed computing; Artificial intelligence","score_opus":0.005692203934263281,"score_gpt":0.2073425543861468,"score_spread":0.2016503504518835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407949388","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05140344,0.00033286613,0.9424105,0.00037484348,0.000052990108,0.00004150489,0.000072275296,0.00018658479,0.0051250425],"genre_scores_gemma":[0.9624479,0.00016159336,0.033506714,0.00007669929,0.000029317802,0.00012766165,0.000082971026,0.00005944642,0.0035076234],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999529,0.0001712926,0.000014663406,0.00010171046,0.0000773824,0.000106013686],"domain_scores_gemma":[0.99899334,0.0006153958,0.00014571947,0.00005554293,0.00010193116,0.000087964305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001202129,0.0009327289,0.0012042525,0.00073037774,0.0006547031,0.0010909068,0.0011292633,0.0010052372,0.0019432637],"category_scores_gemma":[0.002964662,0.00053956266,0.0010255289,0.0005319359,0.0014890161,0.001141998,0.002037436,0.00091166684,0.00019407635],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041459283,0.00001049115,0.00017380378,0.000018317265,0.000011965386,0.000035304216,0.00002875646,0.9836769,0.00045819243,0.012592124,0.00028417382,0.00266844],"study_design_scores_gemma":[0.0000069331163,0.0000126535615,0.00003794362,0.0000018984767,0.0000024050064,0.0000038222524,0.0000074412987,0.99480164,0.00009359565,0.0048980857,0.00013127222,0.0000022127747],"about_ca_topic_score_codex":0.007923385,"about_ca_topic_score_gemma":0.0031769895,"teacher_disagreement_score":0.007923385,"about_ca_system_score_codex":0.0017505151,"about_ca_system_score_gemma":0.0008139539,"threshold_uncertainty_score":0.01575452},"labels":[],"label_agreement":null},{"id":"W4408011605","doi":"10.1016/j.cie.2025.110991","title":"Last-mile delivery optimization: Leveraging electric vehicles and parcel lockers for prime customer service","year":2025,"lang":"en","type":"article","venue":"Computers & Industrial Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Mile; Last mile (transportation); Prime (order theory); Service (business); Customer service; Engineering; Transport engineering; Business; Operations management; Computer science; Marketing; Mathematics; Geography","score_opus":0.01711334052917129,"score_gpt":0.20616225536921404,"score_spread":0.18904891484004274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408011605","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44202092,0.0012656932,0.5177933,0.001319628,0.00026115094,0.0001566751,0.00025181097,0.0020180875,0.034912717],"genre_scores_gemma":[0.97081155,0.00012381499,0.02378649,0.00010521388,0.000033502864,0.000015931739,0.00008506985,0.00010908694,0.004929411],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99963725,0.00007057379,0.000007806418,0.00007069524,0.000059799197,0.00015377394],"domain_scores_gemma":[0.9996302,0.0001514515,0.00004614937,0.000030085293,0.000085791864,0.000056320478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005851396,0.0010919377,0.00087141094,0.0005430893,0.00046323988,0.001355802,0.0009455983,0.0008156738,0.005857941],"category_scores_gemma":[0.0014861128,0.00038364966,0.00041552645,0.0005470114,0.00029961893,0.0012733054,0.00077548594,0.0008429242,0.0006909229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030035136,0.00024550088,0.0013209248,0.00005326567,0.000040135164,0.00009609406,0.0000398833,0.91748714,0.004880094,0.0028630975,0.003393917,0.06927957],"study_design_scores_gemma":[0.0000074866302,0.00008584057,0.00017074677,0.000002515938,0.000011744429,0.000012485568,0.000034767076,0.9977836,0.0006327798,0.0007300518,0.0005240853,0.0000038493827],"about_ca_topic_score_codex":0.0062721665,"about_ca_topic_score_gemma":0.0071762595,"teacher_disagreement_score":0.0062721665,"about_ca_system_score_codex":0.00070163497,"about_ca_system_score_gemma":0.0012013334,"threshold_uncertainty_score":0.019596756},"labels":[],"label_agreement":null},{"id":"W4408069003","doi":"10.2139/ssrn.5152056","title":"Quantifying the Triple-Win Potential of Sustainable Mobility","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Natural Resources Canada; HEC Montréal","funders":"","keywords":"Business; Natural resource economics; Economics","score_opus":0.012189379509735695,"score_gpt":0.25937622693332363,"score_spread":0.24718684742358793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408069003","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6209514,0.0021107,0.22083719,0.0048803976,0.00026407864,0.0001396252,0.00096479163,0.00017876909,0.14967296],"genre_scores_gemma":[0.9938014,0.00034573395,0.0026849553,0.000040955227,0.00003126487,0.000027508338,0.00005151462,0.0000217252,0.002994903],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989422,0.00038407324,0.000025292497,0.00015746303,0.00018543756,0.0003056191],"domain_scores_gemma":[0.99529403,0.003304255,0.00036491532,0.00024400018,0.00033358252,0.0004590624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002212961,0.0006697024,0.00075370754,0.001165239,0.00081028073,0.003585285,0.001008625,0.0020317333,0.01295189],"category_scores_gemma":[0.013763825,0.00042007313,0.0005155393,0.0012571939,0.0016384255,0.0075025554,0.002918736,0.001445603,0.0006529802],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013735359,0.000045731354,0.0027832042,0.00011859095,0.00005472366,0.00015117528,0.00016472233,0.1857672,0.00065821793,0.7935851,0.0022681733,0.014265804],"study_design_scores_gemma":[0.000008930384,0.000056436,0.0008388384,0.00004190701,0.000023557928,0.00007604013,0.00040470815,0.23864843,0.00035174214,0.7573358,0.0021946493,0.000019005263],"about_ca_topic_score_codex":0.0020533986,"about_ca_topic_score_gemma":0.0017296695,"teacher_disagreement_score":0.01295189,"about_ca_system_score_codex":0.0017669533,"about_ca_system_score_gemma":0.0014605472,"threshold_uncertainty_score":0.043328345},"labels":[],"label_agreement":null},{"id":"W4408069401","doi":"10.1016/j.tra.2025.104430","title":"Exploring the potential adoption of Mobility-as-a-Service in Beijing: A spatial agent-based model","year":2025,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Beijing; Transport engineering; Service (business); Agent-based model; Computer science; Business; Environmental economics; China; Geography; Engineering; Marketing; Economics","score_opus":0.17248903049822514,"score_gpt":0.4013323827443277,"score_spread":0.22884335224610255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408069401","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95054036,0.00040518318,0.016766004,0.0037454988,0.00003066636,0.00008044067,0.00037950548,0.00006972416,0.027982555],"genre_scores_gemma":[0.99644333,0.00017353632,0.0005822245,0.000024624567,0.0000044269113,0.00001838291,0.000046625762,0.0000049273226,0.0027020525],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99954695,0.00018200313,0.000017634233,0.000081451035,0.00003560953,0.00013633537],"domain_scores_gemma":[0.99856913,0.0007732321,0.00026085187,0.00005777626,0.00013787494,0.00020113768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092539936,0.00048591275,0.00069499697,0.00081827585,0.0009883464,0.0032037531,0.0020355918,0.0021826427,0.007534005],"category_scores_gemma":[0.0040709497,0.00046344262,0.00066704967,0.0015459233,0.0014740869,0.003940706,0.0019077783,0.0011719626,0.00039208028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002544773,0.00026077504,0.030439585,0.00010493825,0.0001220667,0.0008545352,0.00085409364,0.7408044,0.0008171006,0.21396346,0.0014649576,0.010059548],"study_design_scores_gemma":[0.000054039425,0.00008826243,0.004572713,0.00001801054,0.00007983738,0.000045339075,0.00095904636,0.9700318,0.00013344336,0.022150477,0.0018412372,0.000025819532],"about_ca_topic_score_codex":0.11115284,"about_ca_topic_score_gemma":0.075330734,"teacher_disagreement_score":0.11115284,"about_ca_system_score_codex":0.005224691,"about_ca_system_score_gemma":0.0028857521,"threshold_uncertainty_score":0.2210117},"labels":[],"label_agreement":null},{"id":"W4408257875","doi":"10.24908/cpp-apc.v2025i1.17930","title":"Cultivating Bus Rapid Transit (BRT) Station Areas within Freight Rail Corridors","year":2025,"lang":"en","type":"article","venue":"Canadian Planning and Policy / Aménagement et politique au Canada","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Bus rapid transit; Transport engineering; Transit (satellite); Rail transit; Light rail transit; Business; Automotive engineering; Engineering; Public transport","score_opus":0.00924497406630798,"score_gpt":0.24090953631652068,"score_spread":0.2316645622502127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408257875","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9925385,0.000051392326,0.00052260014,0.00012174086,0.0000021705778,0.000049550512,0.000053015498,0.000009040513,0.0066520125],"genre_scores_gemma":[0.99586135,0.00017542382,0.001835501,0.00002498041,0.0000018918084,0.000027630078,0.00008457892,0.0000034869229,0.0019851637],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99935013,0.00018368784,0.000013781502,0.00008273863,0.00014044066,0.0002291583],"domain_scores_gemma":[0.99865854,0.00018935018,0.00037926325,0.0000768521,0.00027127092,0.00042468586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008462669,0.00016423242,0.00011752876,0.000513741,0.0012753742,0.001086719,0.0005367438,0.00015700945,0.0032766184],"category_scores_gemma":[0.0023901751,0.00013901565,0.00015496729,0.0008739699,0.0009431411,0.00052882783,0.0011019947,0.00032980888,0.0002290437],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022132999,0.0007017485,0.7708777,0.0003959302,0.00007083948,0.00093269564,0.030418081,0.004537308,0.017091552,0.007409984,0.0027753538,0.16456752],"study_design_scores_gemma":[0.000021569615,0.00060946227,0.9195742,0.00013730481,0.00004354025,0.00015283926,0.04341164,0.001080715,0.0014090295,0.00050323264,0.033034056,0.000022266831],"about_ca_topic_score_codex":0.48192903,"about_ca_topic_score_gemma":0.8668267,"teacher_disagreement_score":0.51807094,"about_ca_system_score_codex":0.0068075834,"about_ca_system_score_gemma":0.010560464,"threshold_uncertainty_score":0.9582478},"labels":[],"label_agreement":null},{"id":"W4408310159","doi":"10.1155/atr/4250568","title":"Enhancing Random Regret Minimization With Perception and Demographic Heterogeneity Insights: A Taxi‐Hailing Case Study in Chengdu, China","year":2025,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Regret; China; Perception; Operations research; Computer science; Engineering; Statistics; Geography; Mathematics; Psychology","score_opus":0.006143713311457969,"score_gpt":0.24264530854880564,"score_spread":0.23650159523734768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408310159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9968491,0.000055786535,0.0019956192,0.00017480234,0.0000030316257,0.000028886525,0.000052326748,0.000010192041,0.0008301713],"genre_scores_gemma":[0.9985221,0.000046702316,0.0009636001,0.000011692448,0.0000026131936,0.000015625528,0.00004308808,0.0000031456507,0.0003914975],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989446,0.0006084675,0.000035333487,0.00010378941,0.000081370206,0.00022648818],"domain_scores_gemma":[0.9973699,0.0016605906,0.00029752371,0.00019273045,0.0002579683,0.00022134917],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026806633,0.00068541657,0.0005969452,0.0007616269,0.0015377912,0.0011075363,0.0016373495,0.0011658213,0.0017485132],"category_scores_gemma":[0.0042093894,0.0003039797,0.00083335536,0.0013932223,0.0007898637,0.0013984177,0.0010299698,0.00095287926,0.00010287781],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000770534,0.0019837387,0.28428465,0.00029402276,0.00034952545,0.01031227,0.0057977512,0.63324314,0.0016542275,0.021488054,0.0028318583,0.036990225],"study_design_scores_gemma":[0.00007191422,0.00032673817,0.058682743,0.000024823232,0.00009506529,0.000286872,0.006205951,0.9274665,0.0006176284,0.00485779,0.0012866369,0.0000773415],"about_ca_topic_score_codex":0.13284238,"about_ca_topic_score_gemma":0.119803876,"teacher_disagreement_score":0.13284238,"about_ca_system_score_codex":0.0047665755,"about_ca_system_score_gemma":0.0018640786,"threshold_uncertainty_score":0.26413828},"labels":[],"label_agreement":null},{"id":"W4408325404","doi":"10.1109/globecom52923.2024.10901015","title":"Joint Model Assignment and Resource Allocation for Cost-Effective Mobile Generative Services","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Resource allocation; Joint (building); Resource management (computing); Mobile telephony; Resource (disambiguation); Distributed computing; Computer network; Mobile radio; Engineering","score_opus":0.016763263956691702,"score_gpt":0.257392496173308,"score_spread":0.2406292322166163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408325404","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06686036,0.00016155731,0.9280068,0.00015763298,0.000025511446,0.00009396175,0.000048540925,0.0023659666,0.0022795612],"genre_scores_gemma":[0.8793398,0.000069038986,0.1188971,0.00007559576,0.000017754197,0.00007312305,0.00011605999,0.00015901432,0.0012525589],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993131,0.00020760423,0.000026905582,0.00010602931,0.00017697178,0.00016925928],"domain_scores_gemma":[0.9992593,0.00028495278,0.00006159704,0.00016476821,0.00013829561,0.00009109905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000743823,0.0007824099,0.00056103204,0.00050504407,0.0006694797,0.00090838625,0.0015932779,0.00057687424,0.0023801075],"category_scores_gemma":[0.0026692066,0.00035947643,0.00037987967,0.0005812687,0.0005036722,0.0014964938,0.0018806563,0.0009263857,0.00071142457],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046938178,0.00036087536,0.0030771815,0.00010533132,0.000050903185,0.00035418393,0.0003706319,0.7270389,0.023460587,0.013338481,0.0050207623,0.2263528],"study_design_scores_gemma":[0.0000064671567,0.000017781604,0.00011197496,0.0000014981131,0.0000050201784,0.000028405466,0.000029498222,0.99529845,0.0017898898,0.0022857685,0.0004204579,0.000004799772],"about_ca_topic_score_codex":0.00507248,"about_ca_topic_score_gemma":0.0063105295,"teacher_disagreement_score":0.00507248,"about_ca_system_score_codex":0.0008353359,"about_ca_system_score_gemma":0.0009833782,"threshold_uncertainty_score":0.010085881},"labels":[],"label_agreement":null},{"id":"W4408326101","doi":"10.1109/globecom52923.2024.10901142","title":"A New Online Evolutive Optimization Method for Driving Agents","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"National Natural Science Foundation of China","keywords":"Computer science","score_opus":0.021522513348475547,"score_gpt":0.31521593740372195,"score_spread":0.2936934240552464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408326101","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008081475,0.00018464848,0.988209,0.00010886793,0.00007319126,0.000032453932,0.000014187258,0.00038802566,0.0029081868],"genre_scores_gemma":[0.64136994,0.00029738573,0.34634107,0.00025850322,0.000100846024,0.00029531075,0.00011871341,0.00018902555,0.011029197],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996891,0.000059807087,0.000018899533,0.0000932248,0.00009951971,0.000039418264],"domain_scores_gemma":[0.99976236,0.00006809221,0.000028581777,0.000025268882,0.0000879888,0.00002768355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000522979,0.0009388309,0.00070919207,0.00051460305,0.00058132096,0.00075304706,0.0014592579,0.0009128028,0.0022335364],"category_scores_gemma":[0.00090633164,0.00037154162,0.0006186851,0.0003342974,0.00062035606,0.0008323534,0.001167147,0.0009160483,0.00051882793],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010364953,0.00008650371,0.0009264686,0.00010131803,0.00006875884,0.0001664595,0.00020294986,0.75181544,0.010809732,0.023930438,0.0024325005,0.20935573],"study_design_scores_gemma":[0.000005472868,0.000022252249,0.000036175054,0.0000023941225,0.0000037585535,0.000016758271,0.000004463018,0.99713326,0.00043103186,0.0013225535,0.001017311,0.000004566834],"about_ca_topic_score_codex":0.0037994555,"about_ca_topic_score_gemma":0.0028029694,"teacher_disagreement_score":0.0037994555,"about_ca_system_score_codex":0.0005020179,"about_ca_system_score_gemma":0.00076213916,"threshold_uncertainty_score":0.00755471},"labels":[],"label_agreement":null},{"id":"W4408677959","doi":"10.55041/ijsrem42635","title":"A Comparative Study of GST Implementation Across Countries","year":2025,"lang":"en","type":"article","venue":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Political science; Regional science; Geography","score_opus":0.05785905645678118,"score_gpt":0.4288320085841584,"score_spread":0.3709729521273772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408677959","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.970841,0.0015298369,0.0005176699,0.00057432434,0.00003418893,0.0000571968,0.0009118631,0.000017715463,0.025516244],"genre_scores_gemma":[0.9966755,0.001236554,0.00035288365,0.0001024998,0.000006297145,0.000019291787,0.00062268454,0.000010080559,0.0009742672],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975497,0.0010514054,0.00020475299,0.00019998585,0.0005127881,0.00048138364],"domain_scores_gemma":[0.9955289,0.0014579173,0.0010259411,0.00032936945,0.001475988,0.00018194955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002730685,0.00016957382,0.00034461642,0.0029321262,0.0008883901,0.0022770218,0.00046086963,0.00036551492,0.0022474504],"category_scores_gemma":[0.007952912,0.00017429338,0.0004384698,0.008803608,0.0010390383,0.0013892085,0.0014762488,0.00070813653,0.00020575419],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001288954,0.00049600995,0.60211885,0.0021678011,0.0007120637,0.0016100454,0.035163604,0.008264689,0.0022517801,0.116830125,0.009791703,0.21930441],"study_design_scores_gemma":[0.00003585829,0.0004972789,0.8829427,0.00062653935,0.0002093209,0.0004233111,0.048828986,0.0009095894,0.0014868117,0.0011260824,0.0628487,0.000064946835],"about_ca_topic_score_codex":0.031708002,"about_ca_topic_score_gemma":0.027254542,"teacher_disagreement_score":0.031708002,"about_ca_system_score_codex":0.0039490024,"about_ca_system_score_gemma":0.0024363108,"threshold_uncertainty_score":0.06304687},"labels":[],"label_agreement":null},{"id":"W4408696798","doi":"10.1109/itsc58415.2024.10919661","title":"Modelling Link-Level Shared Micromobility Demand: Regression and Neural Network Approaches","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Artificial neural network; Computer network; Link (geometry); Artificial intelligence","score_opus":0.08756493789090866,"score_gpt":0.24410771134219125,"score_spread":0.1565427734512826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408696798","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6057435,0.0011318768,0.38419092,0.0015779941,0.00011937132,0.00017688738,0.0013067808,0.00057192706,0.0051807435],"genre_scores_gemma":[0.9583652,0.00045673078,0.036724728,0.000075587384,0.0000663521,0.0001472184,0.00082598464,0.000040608604,0.0032975737],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907184,0.00047896386,0.000045700326,0.0001936533,0.00009028572,0.000119512566],"domain_scores_gemma":[0.99570185,0.003463444,0.0003277289,0.000090765214,0.0003372951,0.000078893085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025458534,0.0012193606,0.00078576326,0.0014348235,0.0003593286,0.0012640294,0.0015169277,0.0012993879,0.002686103],"category_scores_gemma":[0.008451067,0.0005957002,0.0008968795,0.0017550105,0.00039744982,0.0018247537,0.0010446142,0.0016037669,0.00045645924],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010538079,0.00019427242,0.019536277,0.000044934943,0.00016642692,0.00007933339,0.00007489982,0.9528729,0.00019858358,0.0022162434,0.0004965658,0.024014227],"study_design_scores_gemma":[0.000002054887,0.000011310754,0.0008810996,0.000003406734,0.0000060588945,0.0000029503049,0.000022029759,0.9983607,0.000026231488,0.00062596815,0.00005451856,0.0000037645764],"about_ca_topic_score_codex":0.058890197,"about_ca_topic_score_gemma":0.033429336,"teacher_disagreement_score":0.058890197,"about_ca_system_score_codex":0.0013878146,"about_ca_system_score_gemma":0.0008695041,"threshold_uncertainty_score":0.117094815},"labels":[],"label_agreement":null},{"id":"W4408696902","doi":"10.1109/itsc58415.2024.10920253","title":"Optimizing Station Placement for Integrated Shared Micromobility and Public Transit Networks","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Alberta Innovates","keywords":"Computer science; Computer network; Public transport; Engineering; Transport engineering","score_opus":0.019392577059640398,"score_gpt":0.2405479269356163,"score_spread":0.2211553498759759,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408696902","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2844184,0.00050023396,0.7019273,0.00035487936,0.00007099175,0.00017335376,0.0006353881,0.00042836292,0.01149117],"genre_scores_gemma":[0.9572093,0.00015509309,0.038011856,0.00003089253,0.000011906747,0.000102361686,0.00026042305,0.00004442114,0.004173886],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999529,0.00011808863,0.000012964942,0.00012524806,0.00006200867,0.00015278759],"domain_scores_gemma":[0.9995117,0.00020530328,0.000093642884,0.000037877384,0.000071941875,0.00007944632],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006142117,0.0014333628,0.0014050953,0.0006899682,0.00055847433,0.001426182,0.0014611189,0.001429497,0.0048379293],"category_scores_gemma":[0.0014575849,0.0008244197,0.0009430283,0.0011265208,0.0006605863,0.0013333865,0.0014536586,0.00079213665,0.0004232942],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028073795,0.000015057993,0.00038711313,0.000013092996,0.000011020583,0.0000242756,0.000009432159,0.9946508,0.00024144357,0.001381585,0.00015922872,0.0030788444],"study_design_scores_gemma":[0.0000062209624,0.000031402687,0.00026497274,0.0000037853144,0.000011995314,0.000011457115,0.00003074319,0.9975817,0.00015261839,0.0016134111,0.00028807126,0.0000036369215],"about_ca_topic_score_codex":0.019379305,"about_ca_topic_score_gemma":0.022639591,"teacher_disagreement_score":0.019379305,"about_ca_system_score_codex":0.0020406991,"about_ca_system_score_gemma":0.0019404071,"threshold_uncertainty_score":0.038533032},"labels":[],"label_agreement":null},{"id":"W4408712249","doi":"10.1109/itsc58415.2024.10919739","title":"Dynamic Predictive Matching Framework for Crowd-Sourced Delivery Service","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Matching (statistics); Service delivery framework; Service (business); Business; Mathematics; Statistics","score_opus":0.0085428458057704,"score_gpt":0.24677005686769884,"score_spread":0.23822721106192846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408712249","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024560528,0.00076487905,0.9688487,0.0006291882,0.0001859163,0.00012635514,0.00034798458,0.0009266854,0.0036097765],"genre_scores_gemma":[0.89607054,0.00069338473,0.093446665,0.00038238478,0.00022805839,0.00022802467,0.0006293226,0.00019646967,0.008125138],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987324,0.00030225152,0.00004851203,0.00032298986,0.00030167127,0.00029217184],"domain_scores_gemma":[0.99828607,0.00093562173,0.00020321591,0.00010949501,0.00030346497,0.0001620214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022974506,0.0012309819,0.0018311467,0.0010675539,0.0007684588,0.001510586,0.003751867,0.0018291702,0.0047256076],"category_scores_gemma":[0.00458818,0.0007779785,0.0010863065,0.0015133814,0.0008539679,0.0018407088,0.0019716432,0.0019139961,0.0008747748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010281066,0.00007938118,0.00084628444,0.00006341313,0.0000379048,0.00012097212,0.00007213415,0.95845544,0.0006228344,0.00998282,0.002177704,0.027438318],"study_design_scores_gemma":[0.000003574228,0.000009695423,0.00005932442,0.0000024506458,0.0000049061578,0.000009432043,0.000009937087,0.99678755,0.00008745851,0.0026944347,0.0003270931,0.00000417644],"about_ca_topic_score_codex":0.02300917,"about_ca_topic_score_gemma":0.012409758,"teacher_disagreement_score":0.02300917,"about_ca_system_score_codex":0.0021749143,"about_ca_system_score_gemma":0.0023601456,"threshold_uncertainty_score":0.0457505},"labels":[],"label_agreement":null},{"id":"W4408712308","doi":"10.1109/itsc58415.2024.10919641","title":"Optimization-based Control Algorithm: Development and Testing for Dynamic On-Demand SAV Operation","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Control (management); Development (topology); Algorithm; Artificial intelligence; Mathematics","score_opus":0.01115384781960358,"score_gpt":0.23097372402577757,"score_spread":0.219819876206174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408712308","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13491513,0.0001678797,0.853541,0.00019441688,0.000058750848,0.00034913849,0.00005759297,0.0011995784,0.009516531],"genre_scores_gemma":[0.920496,0.00005775453,0.07774853,0.00005194407,0.00000784096,0.00022320241,0.000062428604,0.000061598636,0.001290778],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993118,0.00019457313,0.000039576018,0.00012107468,0.00023222396,0.000100852565],"domain_scores_gemma":[0.99802774,0.0011715713,0.0001582627,0.00011618755,0.00048323197,0.000042999443],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014871478,0.00062615867,0.00065168826,0.00033012,0.0003475997,0.00074642507,0.0008095047,0.00094546005,0.0020808112],"category_scores_gemma":[0.004220615,0.00030906853,0.00036850042,0.00020784841,0.0005010226,0.00055966264,0.00060762,0.0008221619,0.000253753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000075383236,0.00007869543,0.00059400056,0.000044946468,0.000015751475,0.000025575557,0.000030439809,0.9773775,0.0012262063,0.0016034957,0.00019122289,0.018736888],"study_design_scores_gemma":[0.000005705634,0.000022199209,0.000056341003,0.0000012975836,0.0000015252499,0.00000206157,0.0000026753146,0.9994616,0.00031619737,0.00006153335,0.000067973706,0.0000010145541],"about_ca_topic_score_codex":0.011623452,"about_ca_topic_score_gemma":0.0045051817,"teacher_disagreement_score":0.011623452,"about_ca_system_score_codex":0.0005886638,"about_ca_system_score_gemma":0.0012965143,"threshold_uncertainty_score":0.023111582},"labels":[],"label_agreement":null},{"id":"W4408789181","doi":"10.1016/j.commtr.2025.100172","title":"Modular AI agents for transportation surveys and interviews: Advancing engagement, transparency, and cost efficiency","year":2025,"lang":"en","type":"article","venue":"Communications in Transportation Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Environment and Climate Change Canada; McGill University; University of Sydney; Concordia University; National Research Foundation Singapore; Singapore-MIT Alliance for Research and Technology Centre; Massachusetts Institute of Technology","keywords":"Transparency (behavior); Modular design; Business; Computer science; Computer security","score_opus":0.14701349435280095,"score_gpt":0.4417383472024958,"score_spread":0.29472485284969485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408789181","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03485555,0.00010835422,0.95434344,0.0017962884,0.000043467837,0.001973743,0.00009162735,0.0013750186,0.0054126065],"genre_scores_gemma":[0.14707425,0.000085792715,0.84717727,0.00030516484,0.00003695047,0.0036657504,0.00011962242,0.0001820345,0.0013531649],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.91215473,0.07681749,0.002090115,0.0043177935,0.0034851453,0.0011347205],"domain_scores_gemma":[0.87468445,0.09438433,0.006827371,0.016360119,0.0051285163,0.0026152167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.058769777,0.0013426661,0.00051311334,0.0026209573,0.0024486785,0.005366003,0.0031400346,0.0024958942,0.0045236517],"category_scores_gemma":[0.09207703,0.0012801553,0.0008364166,0.0012362277,0.0049507194,0.0082297595,0.0147944605,0.0023390772,0.0019773063],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008308709,0.0013969268,0.016408246,0.0015139251,0.00016642785,0.0009230129,0.18262024,0.018159999,0.06688713,0.1445107,0.0059781787,0.5606043],"study_design_scores_gemma":[0.00080642494,0.0019535427,0.012657333,0.0018340341,0.00031876375,0.0010888263,0.053851213,0.27738404,0.044333663,0.28705257,0.31827745,0.00044211035],"about_ca_topic_score_codex":0.0010233169,"about_ca_topic_score_gemma":0.0020577759,"teacher_disagreement_score":0.058769777,"about_ca_system_score_codex":0.0026937246,"about_ca_system_score_gemma":0.004832498,"threshold_uncertainty_score":0.310808},"labels":[],"label_agreement":null},{"id":"W4408862224","doi":"10.1109/icca62237.2024.10927778","title":"Bridging the Accessibility Gap in Online Shopping with AI - Driven Solutions","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Algoma University","funders":"","keywords":"Bridging (networking); Computer science; Computer security","score_opus":0.03321686690625168,"score_gpt":0.28422195540568296,"score_spread":0.25100508849943126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408862224","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1849465,0.0034610222,0.74835086,0.003619882,0.00022919521,0.00040733034,0.00016309871,0.0060094353,0.0528127],"genre_scores_gemma":[0.62306607,0.0018293026,0.36387354,0.0010501421,0.00009911914,0.0002657559,0.00027780366,0.00034700992,0.009191267],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987662,0.0005278199,0.00007750083,0.00014268619,0.00039289048,0.00009294867],"domain_scores_gemma":[0.99582714,0.002527356,0.00023005475,0.00042664612,0.00072836416,0.00026037532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017858655,0.00052577927,0.00030011006,0.0008761241,0.0005837996,0.0034739082,0.00166209,0.0012463743,0.0049530733],"category_scores_gemma":[0.007199225,0.0003089787,0.0004323979,0.0004437727,0.0011401322,0.004660575,0.0040611536,0.0009949617,0.0014083567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066709873,0.0010754428,0.0059571043,0.0026808477,0.000117256975,0.0014519611,0.011271225,0.006473008,0.053188797,0.03900787,0.0121712,0.8659382],"study_design_scores_gemma":[0.00034477396,0.001970996,0.016803246,0.0027512154,0.00040486263,0.007992075,0.021428505,0.18997118,0.07201112,0.2585501,0.4272625,0.0005093864],"about_ca_topic_score_codex":0.00090293086,"about_ca_topic_score_gemma":0.0013317373,"teacher_disagreement_score":0.0049530733,"about_ca_system_score_codex":0.00041581056,"about_ca_system_score_gemma":0.00070902245,"threshold_uncertainty_score":0.016569734},"labels":[],"label_agreement":null},{"id":"W4408953237","doi":"10.3138/uhr-2024-0023","title":"Taxi Wars 2.0: Digital Ride-Hailing and the Long Arc of “Disruption” in the Canadian Private Taxi Industry","year":2025,"lang":"en","type":"article","venue":"Urban History Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Carleton University; York University","funders":"","keywords":"Business; Arc (geometry); Advertising; Engineering; Mechanical engineering","score_opus":0.015454636395460164,"score_gpt":0.2229504310290025,"score_spread":0.20749579463354234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408953237","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.051378064,0.47584972,0.0017706814,0.09267153,0.001674439,0.00005345684,0.00046169225,0.00007064383,0.37606987],"genre_scores_gemma":[0.46529597,0.47902828,0.0010685262,0.009098042,0.0006517452,0.000024755784,0.00027368712,0.00006010497,0.04449889],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9978149,0.00027822878,0.000045335382,0.00016115994,0.001194937,0.00050544343],"domain_scores_gemma":[0.9969015,0.00087619,0.00029027273,0.0000958579,0.0015217937,0.00031440277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020033256,0.00041673577,0.00030958434,0.0047884383,0.009302623,0.010089816,0.0011097477,0.0020483725,0.0055557517],"category_scores_gemma":[0.0034747978,0.00021700124,0.00022761688,0.010848438,0.015689645,0.0036553198,0.0018768124,0.0029882668,0.0004192838],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004582737,0.000034041626,0.003750882,0.0020388935,0.000027393547,0.00060095696,0.052222088,0.0008485381,0.00062834687,0.5986864,0.08141722,0.2596994],"study_design_scores_gemma":[0.0000020983216,0.000012102862,0.006203296,0.0011052272,0.000015852616,0.00016263172,0.020886807,0.00011116568,0.00029285435,0.0037677966,0.96740997,0.000030222216],"about_ca_topic_score_codex":0.95630836,"about_ca_topic_score_gemma":0.97511387,"teacher_disagreement_score":0.0779646,"about_ca_system_score_codex":0.0779646,"about_ca_system_score_gemma":0.09593048,"threshold_uncertainty_score":0.5656754},"labels":[],"label_agreement":null},{"id":"W4409075262","doi":"10.1016/j.tre.2025.104095","title":"Data-driven optimization for drone delivery service planning with online demand","year":2025,"lang":"en","type":"article","venue":"Transportation Research Part E Logistics and Transportation Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"Australian Research Council","keywords":"Drone; Service (business); Computer science; Business; On demand; Operations research; Engineering; Marketing; Multimedia","score_opus":0.15473409662634108,"score_gpt":0.3941651740985153,"score_spread":0.23943107747217424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409075262","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018025735,0.0005115454,0.9775277,0.00048486743,0.000067860354,0.00007173028,0.00018256366,0.00013135742,0.0029966116],"genre_scores_gemma":[0.8481389,0.00067819044,0.1467267,0.00026987283,0.00008453753,0.0003087247,0.00043557322,0.000110434936,0.0032470154],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99943846,0.00022990575,0.000024942268,0.00011680116,0.00012849194,0.00006146472],"domain_scores_gemma":[0.99723476,0.002128832,0.0002216381,0.000098659824,0.0002454443,0.000070711816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016070312,0.0010215903,0.0013017997,0.0005196096,0.00032294012,0.0012906374,0.0010589886,0.0013764034,0.0018630809],"category_scores_gemma":[0.0044045183,0.00094679196,0.00091650884,0.00066189986,0.0009230728,0.0012454191,0.0007960962,0.0019472305,0.00022653479],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000070579135,0.000009644302,0.000076294564,0.000021137335,0.000007409458,0.000007878186,0.000006199277,0.9957704,0.000071465234,0.002414283,0.000080155885,0.001528093],"study_design_scores_gemma":[0.0000023393366,0.000006748603,0.000020684962,0.0000032296268,0.0000015503383,0.0000017706652,0.0000027612373,0.9981675,0.000054530472,0.0015995324,0.0001378116,0.000001525153],"about_ca_topic_score_codex":0.007878976,"about_ca_topic_score_gemma":0.0054879524,"teacher_disagreement_score":0.007878976,"about_ca_system_score_codex":0.0015254937,"about_ca_system_score_gemma":0.0018427207,"threshold_uncertainty_score":0.015666246},"labels":[],"label_agreement":null},{"id":"W4409175778","doi":"10.38124/ijisrt/25feb803","title":"Evaluating the Influence of Ride Sourcing Services on Travel Patterns and Transportation Networks in Toronto","year":2025,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Business; Computer science; Advertising; Telecommunications; Engineering","score_opus":0.011279241360568588,"score_gpt":0.28708418600181257,"score_spread":0.275804944641244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409175778","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99319166,0.0002557585,0.00027974995,0.0001666277,0.0000039181587,0.000018843568,0.003345958,0.000014124438,0.0027234086],"genre_scores_gemma":[0.9978377,0.0001787901,0.00016271308,0.000011641801,0.0000024667595,0.000009304607,0.0011506528,0.000003825244,0.00064287416],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99943537,0.00011581704,0.00003769828,0.000077408295,0.00017259041,0.00016109982],"domain_scores_gemma":[0.9978604,0.00040832104,0.00058675196,0.00011837763,0.00064634206,0.0003797072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005270663,0.0002498671,0.00017261766,0.0013049982,0.00077465025,0.0012098247,0.0004453411,0.00021049434,0.0019932569],"category_scores_gemma":[0.0035630544,0.00017598471,0.0003459507,0.0038205779,0.00047707718,0.00058325374,0.0009977521,0.00024039407,0.00024983945],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005808829,0.000019761359,0.98424613,0.000059532773,0.00006510266,0.00018133153,0.0021914518,0.003407044,0.0004926334,0.00052170444,0.0010668397,0.0076903095],"study_design_scores_gemma":[0.0000016376388,0.000021737531,0.9920855,0.00002186008,0.000021675243,0.000026619844,0.0034409044,0.0024966914,0.00015511774,0.00003278662,0.0016875538,0.000007824764],"about_ca_topic_score_codex":0.94734603,"about_ca_topic_score_gemma":0.9725734,"teacher_disagreement_score":0.05265397,"about_ca_system_score_codex":0.012543041,"about_ca_system_score_gemma":0.007027503,"threshold_uncertainty_score":0.10592806},"labels":[],"label_agreement":null},{"id":"W4409233654","doi":"10.1109/tits.2025.3553077","title":"Decision Making in Urban Traffic: A Game Theoretic Approach for Autonomous Vehicles Adhering to Traffic Rules","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Game theory; Computer science; Transport engineering; Engineering; Operations research; Mathematical economics; Economics","score_opus":0.018097615335129644,"score_gpt":0.2642156403016896,"score_spread":0.24611802496655993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409233654","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026217833,0.00016649626,0.9607346,0.00063250505,0.00005848795,0.00011474386,0.00006458942,0.000046897265,0.011963856],"genre_scores_gemma":[0.8853696,0.00035128088,0.10960122,0.00015340895,0.000060722843,0.0002812963,0.00005739798,0.00002493791,0.0041001663],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988508,0.0005834059,0.00004223676,0.00015534146,0.00024697048,0.00012117948],"domain_scores_gemma":[0.99901557,0.0005910709,0.00011435169,0.00003859232,0.00014867295,0.00009178057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016561387,0.0008277833,0.00079345686,0.00062784983,0.0007338893,0.0018101016,0.0015593561,0.0012794617,0.0016030967],"category_scores_gemma":[0.0024414593,0.00040461202,0.0009540261,0.00059900177,0.002386652,0.0016646698,0.0012982814,0.0015430988,0.00017247467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020285383,0.000038048227,0.0003000026,0.00003700034,0.000028052462,0.00008674818,0.00013857706,0.84517777,0.00071219023,0.14860876,0.0003054816,0.0045471652],"study_design_scores_gemma":[0.0000075068083,0.000024147745,0.000056556622,0.000006078004,0.0000065966415,0.000010743605,0.000043437307,0.95533353,0.000106629326,0.043825928,0.00057133276,0.0000075199914],"about_ca_topic_score_codex":0.008478402,"about_ca_topic_score_gemma":0.0059567643,"teacher_disagreement_score":0.008478402,"about_ca_system_score_codex":0.001894484,"about_ca_system_score_gemma":0.0022662005,"threshold_uncertainty_score":0.0168581},"labels":[],"label_agreement":null},{"id":"W4409267555","doi":"10.1155/atr/6687585","title":"Solving the Electric Share‐A‐Ride Problem Using a Hybrid Variable Neighborhood Search Algorithm","year":2025,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"University of Illinois at Urbana-Champaign; National Taiwan University of Science and Technology; National Taiwan University; Ministry of Education; Fu Jen Catholic University; National Science and Technology Council","keywords":"Variable neighborhood search; Variable (mathematics); Computer science; Mathematical optimization; Algorithm; Metaheuristic; Mathematics","score_opus":0.00862728909110099,"score_gpt":0.2465540579961367,"score_spread":0.2379267689050357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409267555","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07816444,0.00035013224,0.91091895,0.00025345758,0.00003964728,0.00012296681,0.00010354499,0.0003329782,0.009713844],"genre_scores_gemma":[0.6471782,0.00020499404,0.34639052,0.000093737006,0.00002816461,0.00029480993,0.000229351,0.00008077122,0.005499626],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996669,0.00013811223,0.000011161829,0.000073651354,0.000059184873,0.000050932504],"domain_scores_gemma":[0.9995585,0.00031088036,0.000039429433,0.00002025465,0.000048745624,0.000022161023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058695447,0.0006281982,0.0008827956,0.00045169046,0.00036894437,0.00058865,0.0010132833,0.0007681578,0.002444847],"category_scores_gemma":[0.0010438035,0.00036753874,0.000569806,0.00058590836,0.00031552862,0.0006278755,0.00061934616,0.0004952455,0.00020736542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047834597,0.000056341058,0.00043953198,0.00003925629,0.0000260881,0.000040327737,0.000027752609,0.9716879,0.0005675309,0.0047799987,0.00073949364,0.021548005],"study_design_scores_gemma":[0.000011996257,0.00002123928,0.000060569622,0.0000020675502,0.000003998792,0.000008760902,0.000009549249,0.9983683,0.00013782973,0.0010477451,0.00032598124,0.0000018490819],"about_ca_topic_score_codex":0.009330085,"about_ca_topic_score_gemma":0.009277747,"teacher_disagreement_score":0.009330085,"about_ca_system_score_codex":0.0005114987,"about_ca_system_score_gemma":0.0013004371,"threshold_uncertainty_score":0.018551588},"labels":[],"label_agreement":null},{"id":"W4409348269","doi":"10.4018/979-8-3693-7625-6.ch002","title":"Secondary Drivers","year":2025,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Geography","score_opus":0.008530426292979634,"score_gpt":0.2119290061430656,"score_spread":0.20339857985008597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409348269","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048418548,0.0034129887,0.006533011,0.005726824,0.0023587525,0.000711415,0.005083699,0.0004397756,0.92731494],"genre_scores_gemma":[0.14257687,0.006350409,0.0018352801,0.001794188,0.0004788573,0.00038972634,0.0038407173,0.0002836784,0.8424503],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99908864,0.00010239504,0.00003946393,0.00012120139,0.00042862844,0.00021963676],"domain_scores_gemma":[0.9986381,0.00033111795,0.000120292265,0.00008101821,0.000577342,0.00025209086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074533647,0.0005786719,0.00027566124,0.0017857491,0.0014958789,0.0033839776,0.0008217711,0.00087394664,0.14820138],"category_scores_gemma":[0.0018624903,0.00022216562,0.0006413296,0.0016812538,0.00047335523,0.0028563046,0.002261864,0.0012996595,0.03073712],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009402455,0.00023395503,0.027026325,0.0017886093,0.00001817956,0.0011504765,0.013697814,0.0003892379,0.0022269243,0.30300304,0.33956027,0.31081122],"study_design_scores_gemma":[0.0000023391224,0.00002516624,0.005166524,0.00015993394,0.0000028185268,0.00030096088,0.0032769546,0.00008128908,0.0002523537,0.0030696497,0.98765314,0.000008915781],"about_ca_topic_score_codex":0.0074248053,"about_ca_topic_score_gemma":0.009629359,"teacher_disagreement_score":0.14820138,"about_ca_system_score_codex":0.002273599,"about_ca_system_score_gemma":0.002640097,"threshold_uncertainty_score":0.49578297},"labels":[],"label_agreement":null},{"id":"W4409385083","doi":"10.1016/j.geits.2025.100310","title":"A comparative review of user acceptance factors for drones and sidewalk robots in autonomous last mile delivery","year":2025,"lang":"en","type":"review","venue":"Green Energy and Intelligent Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Research Foundation","keywords":"Drone; Mile; Last mile (transportation); Robot; Computer science; Engineering; Aeronautics; Human–computer interaction; Transport engineering; Geography; Artificial intelligence","score_opus":0.03942568433456641,"score_gpt":0.2962953598964439,"score_spread":0.2568696755618775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409385083","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010807303,0.99766433,0.00011759034,0.0001562169,0.00005689476,0.000026533568,0.000072253766,0.000004147521,0.0008213706],"genre_scores_gemma":[0.005907264,0.9934534,0.00026721184,0.00011907598,0.000026773872,0.000032016913,0.000065473774,0.0000021378803,0.00012669095],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99834895,0.00056387315,0.00042650214,0.00015357621,0.00044099294,0.00006611992],"domain_scores_gemma":[0.9924764,0.0053538545,0.0007578203,0.0000811079,0.0012199583,0.00011088039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034035163,0.00069069775,0.0018173392,0.006132826,0.00038215617,0.0016268695,0.0007912796,0.00084422366,0.0026449263],"category_scores_gemma":[0.007784649,0.0003692114,0.0019007237,0.007165967,0.00040595036,0.001579536,0.00063087593,0.0007897019,0.00041193742],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017609553,0.000118423784,0.0018298951,0.32429683,0.0008688641,0.00019379564,0.0009145773,0.00023005236,0.0009409231,0.0016830396,0.0071933027,0.6615542],"study_design_scores_gemma":[0.00008823634,0.0010796111,0.02997573,0.35844016,0.009328485,0.002276205,0.0029764317,0.00035815928,0.0016246242,0.0013023422,0.59240216,0.00014783542],"about_ca_topic_score_codex":0.0039455416,"about_ca_topic_score_gemma":0.009164382,"teacher_disagreement_score":0.006132826,"about_ca_system_score_codex":0.0009955225,"about_ca_system_score_gemma":0.0035070395,"threshold_uncertainty_score":0.017999709},"labels":[],"label_agreement":null},{"id":"W4409387533","doi":"10.1016/j.cstp.2025.101452","title":"Discrepancies between initial applicants and actual users of a new microtransit service: The case of FlexRide Milwaukee","year":2025,"lang":"en","type":"article","venue":"Case Studies on Transport Policy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Service (business); Transport engineering; Business; Operations research; Computer science; Engineering; Marketing","score_opus":0.03478367131628438,"score_gpt":0.3382317012696693,"score_spread":0.3034480299533849,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409387533","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99879706,0.000033212724,0.000056255292,0.0003537817,0.000005877705,0.000024047302,0.000080934726,0.0000028310942,0.0006460625],"genre_scores_gemma":[0.9989605,0.00006319457,0.00013432202,0.00017672386,0.0000052249857,0.000030890085,0.000083852894,0.0000050530953,0.0005402257],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977234,0.0007559219,0.00014391898,0.00029802907,0.00034256544,0.00073612726],"domain_scores_gemma":[0.9952226,0.0009252488,0.0012841092,0.00022024539,0.0008389554,0.0015087932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024442307,0.00031082763,0.00028055182,0.0014250368,0.00442502,0.0019851972,0.0012679658,0.0008941857,0.0032151467],"category_scores_gemma":[0.007240012,0.00035670292,0.00031923465,0.0018754748,0.0014367097,0.0014923242,0.002581497,0.0013859775,0.0005235411],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018418948,0.00035833163,0.93097335,0.000044904005,0.000029090694,0.0025724452,0.048743933,0.00017443285,0.0006072821,0.00067186065,0.002813193,0.012826998],"study_design_scores_gemma":[0.000010677853,0.00021659558,0.7872205,0.000077885816,0.00002076831,0.0011511365,0.20569202,0.0014730612,0.0002728177,0.00018194214,0.0036296116,0.00005304234],"about_ca_topic_score_codex":0.19974399,"about_ca_topic_score_gemma":0.35450423,"teacher_disagreement_score":0.19974399,"about_ca_system_score_codex":0.0038019721,"about_ca_system_score_gemma":0.0033280696,"threshold_uncertainty_score":0.39716268},"labels":[],"label_agreement":null},{"id":"W4409458628","doi":"10.1016/j.tre.2025.104126","title":"Emerging AI-driven smart and sustainable mobility","year":2025,"lang":"en","type":"article","venue":"Transportation Research Part E Logistics and Transportation Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Business; Computer science; Engineering; Transport engineering","score_opus":0.04357292873988734,"score_gpt":0.36248398624213407,"score_spread":0.31891105750224674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409458628","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008284253,0.6770645,0.034344885,0.060923185,0.0071935686,0.00003981938,0.00018313262,0.00014340343,0.21182337],"genre_scores_gemma":[0.22766927,0.7096266,0.013633654,0.010168916,0.006148097,0.000096821976,0.00022711144,0.00005587239,0.03237365],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994722,0.00010878693,0.0000290299,0.00007350321,0.00022760105,0.000088849614],"domain_scores_gemma":[0.9984059,0.0008701637,0.00010778427,0.000084903615,0.00043020066,0.000101010424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015256171,0.0004976919,0.00045558554,0.00086320017,0.00054171873,0.0028182154,0.0012388256,0.0022554414,0.007391247],"category_scores_gemma":[0.0022271855,0.00016480831,0.00035963993,0.0013667373,0.003122121,0.005295933,0.0014461543,0.00238621,0.0013544526],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020828893,0.000047734044,0.00032296116,0.0018219267,0.00003238471,0.00008419708,0.00022139524,0.002603319,0.0011318509,0.8118783,0.019883858,0.16195124],"study_design_scores_gemma":[0.000007862684,0.00007524369,0.00056061463,0.0008626764,0.000021415592,0.00017771928,0.0005581559,0.004124766,0.0010206363,0.33720952,0.6553566,0.000024811647],"about_ca_topic_score_codex":0.002043112,"about_ca_topic_score_gemma":0.002514002,"teacher_disagreement_score":0.007391247,"about_ca_system_score_codex":0.002125756,"about_ca_system_score_gemma":0.0021350028,"threshold_uncertainty_score":0.024726152},"labels":[],"label_agreement":null},{"id":"W4409571748","doi":"10.1016/j.trd.2025.104765","title":"Can transportation network companies improve the sustainability of urban transportation?","year":2025,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Sustainability; Transport engineering; Business; Urban sustainability; Sustainable transport; Flow network; Environmental economics; Environmental planning; Engineering; Environmental science; Urban planning; Civil engineering; Economics","score_opus":0.016472782975522043,"score_gpt":0.2690633593945821,"score_spread":0.25259057641906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409571748","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46794832,0.022860918,0.010290386,0.39230374,0.0017260349,0.00025006948,0.0006916855,0.00032185068,0.10360696],"genre_scores_gemma":[0.9747488,0.010431738,0.0024735099,0.006310046,0.00026523034,0.000042928816,0.000119503195,0.000020139145,0.005588139],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99926466,0.0003718946,0.000015236753,0.00005311813,0.00010815387,0.00018695515],"domain_scores_gemma":[0.9980946,0.00046308877,0.00041721342,0.000084782005,0.0005525024,0.00038768348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001517843,0.0003661917,0.00018090973,0.0005073558,0.00049306185,0.0022730422,0.00048394065,0.0015904101,0.0073105083],"category_scores_gemma":[0.004756064,0.00008176955,0.0003875177,0.0007491844,0.000611799,0.0037419866,0.0009545448,0.0005598179,0.00070365786],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028557688,0.0014161485,0.10396375,0.0022019467,0.00038593987,0.00045545318,0.0011680981,0.0140221445,0.0054134214,0.065596305,0.0711247,0.73396665],"study_design_scores_gemma":[0.00024198473,0.001750012,0.20960723,0.003299183,0.0005901789,0.00044210962,0.022162577,0.020825988,0.010519276,0.077864535,0.65256095,0.00013587934],"about_ca_topic_score_codex":0.0068496494,"about_ca_topic_score_gemma":0.0120675005,"teacher_disagreement_score":0.0073105083,"about_ca_system_score_codex":0.0017604504,"about_ca_system_score_gemma":0.0036323918,"threshold_uncertainty_score":0.024456084},"labels":[],"label_agreement":null},{"id":"W4409603140","doi":"10.61091/jcmcc127b-107","title":"Advances in self-driving driverless electric vehicles: a comparative analysis of subsystem and prototype development","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Electric cars; Development (topology); Computer science; Self driving; Automotive engineering; Engineering; Systems engineering; Mathematics","score_opus":0.008607776658538738,"score_gpt":0.2558277553045759,"score_spread":0.24721997864603718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409603140","genre_codex":"empirical","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85985935,0.0033075367,0.018559087,0.0003818862,0.000026854155,0.00015486042,0.00012478228,0.00017494215,0.11741064],"genre_scores_gemma":[0.9766634,0.0028850047,0.011349682,0.000038519236,0.000011062553,0.00006502983,0.00020956961,0.00005120276,0.008726428],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99841356,0.0005309443,0.00008039311,0.00013754617,0.0006316621,0.00020599623],"domain_scores_gemma":[0.99487877,0.0021950866,0.00043675833,0.00050217385,0.0017556498,0.00023157355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027194214,0.00027664332,0.00021655335,0.0024094745,0.0005423718,0.0019340889,0.0007016082,0.0005262443,0.0046115327],"category_scores_gemma":[0.0066589825,0.00018532998,0.00030271988,0.0014799028,0.00094620034,0.002601584,0.0011891111,0.00042585577,0.0006350235],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073257607,0.0006661338,0.08400258,0.0019166842,0.00009133491,0.0018740286,0.03173334,0.016720733,0.032983165,0.21006963,0.0035444715,0.61566526],"study_design_scores_gemma":[0.000080178914,0.008342131,0.29197922,0.0010534943,0.0004422817,0.0067084376,0.04813786,0.04734238,0.08787856,0.041071076,0.46679372,0.00017062871],"about_ca_topic_score_codex":0.0016504916,"about_ca_topic_score_gemma":0.001518858,"teacher_disagreement_score":0.0046115327,"about_ca_system_score_codex":0.0015451971,"about_ca_system_score_gemma":0.0012144321,"threshold_uncertainty_score":0.015427053},"labels":[],"label_agreement":null},{"id":"W4409678303","doi":"10.2139/ssrn.5225976","title":"Agent-Based Modellng of Driver Behaviour in Ride-Hailing: A Supply-Side Simulation Study","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Supply side; Computer science; Business; Demand side; Simulation; Economics; Microeconomics; Commerce","score_opus":0.016863992028325794,"score_gpt":0.28326093710688977,"score_spread":0.266396945078564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409678303","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96147656,0.00020288698,0.026014784,0.00069484516,0.000042660613,0.00009316638,0.0005328351,0.00008369758,0.010858578],"genre_scores_gemma":[0.9944243,0.000106766434,0.002257824,0.000030778687,0.000007639883,0.000055954282,0.00015721242,0.000014041619,0.0029456113],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996338,0.00018873047,0.000014233446,0.00004193684,0.000035376586,0.00008591121],"domain_scores_gemma":[0.99651414,0.0025425977,0.00022974388,0.00012231326,0.00033369154,0.00025753438],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011783403,0.0005572687,0.0011485416,0.0006790613,0.00072239497,0.0014641066,0.0015753516,0.0025212215,0.0055917013],"category_scores_gemma":[0.0040494753,0.00068832625,0.0009749839,0.0007370544,0.0008804833,0.0013449499,0.0009309714,0.0016016337,0.00044308705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000081781545,0.00011823977,0.0019745335,0.00001878154,0.00002800815,0.00005499221,0.000052569554,0.9944917,0.00014600118,0.002261178,0.00017709564,0.0005952195],"study_design_scores_gemma":[0.000021995646,0.00003468006,0.00034377314,0.0000024090164,0.000008877607,0.0000043631467,0.00003977435,0.99895597,0.000050419843,0.00043073928,0.000102734324,0.0000043113764],"about_ca_topic_score_codex":0.06795351,"about_ca_topic_score_gemma":0.0322708,"teacher_disagreement_score":0.06795351,"about_ca_system_score_codex":0.0017455958,"about_ca_system_score_gemma":0.0017808601,"threshold_uncertainty_score":0.13511598},"labels":[],"label_agreement":null},{"id":"W4409795136","doi":"10.61091/jcmcc127b-400","title":"Subsidy Strategies of Ride-Hailing Platforms Considering Taxi Street-Hailing during Order Overflow","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Social Science Fund of China","keywords":"Subsidy; Order (exchange); Business; Taxis; Advertising; Economics; Transport engineering; Engineering; Finance; Market economy","score_opus":0.009631696809578323,"score_gpt":0.23867803988692657,"score_spread":0.22904634307734825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409795136","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96729547,0.0000841737,0.023243647,0.0001661054,0.000016882941,0.00011715273,0.0000735697,0.00004078659,0.008962244],"genre_scores_gemma":[0.99711764,0.000038346516,0.001399137,0.000010175778,0.0000015675058,0.000018317833,0.00001676015,0.0000045755855,0.0013934675],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995421,0.00012493678,0.000013710796,0.00005176582,0.000045281522,0.00022218886],"domain_scores_gemma":[0.9982905,0.00079433335,0.0003080016,0.0000723474,0.00017275974,0.0003620856],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009232576,0.0006043579,0.00072994665,0.0006896536,0.0008304869,0.0015655757,0.0011322598,0.0010409282,0.0054484867],"category_scores_gemma":[0.0031128665,0.00033620195,0.00062233314,0.00042604216,0.0008211648,0.0016147608,0.0010463863,0.0007952656,0.000262513],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005721275,0.0002494813,0.0114788925,0.00007227064,0.000047157595,0.0014028206,0.00032551843,0.93983495,0.004361149,0.028373728,0.00096243114,0.012319442],"study_design_scores_gemma":[0.000022358834,0.00015937688,0.0023442935,0.00000814163,0.000031335505,0.000076553195,0.00049084873,0.99223423,0.00064260507,0.0035787188,0.00039304144,0.0000184217],"about_ca_topic_score_codex":0.009858324,"about_ca_topic_score_gemma":0.008280262,"teacher_disagreement_score":0.009858324,"about_ca_system_score_codex":0.0019321312,"about_ca_system_score_gemma":0.0012218113,"threshold_uncertainty_score":0.019601882},"labels":[],"label_agreement":null},{"id":"W4409841782","doi":"10.1016/j.cstp.2025.101463","title":"Unveiling Inequalities in the gig Economy: Analyzing driver earnings in Toronto’s ridehailing industry","year":2025,"lang":"en","type":"article","venue":"Case Studies on Transport Policy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"The Scarborough Hospital; University of Toronto; Institut National de la Recherche Scientifique","funders":"","keywords":"Earnings; Inequality; Gig economy; Labour economics; Economics; Business; Finance; Mathematics","score_opus":0.027430714418493807,"score_gpt":0.3216020906780711,"score_spread":0.2941713762595773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409841782","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97638386,0.00038605565,0.00034030003,0.000401371,0.000009371856,0.000021316813,0.01935055,0.000013323474,0.0030937619],"genre_scores_gemma":[0.9819901,0.00027142977,0.00030774946,0.000046284636,0.000009074853,0.000016344255,0.01541705,0.000006046245,0.0019359889],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99973196,0.000030833387,0.000015386178,0.000040380874,0.00007873423,0.00010260666],"domain_scores_gemma":[0.9990753,0.00011650778,0.0002413508,0.00006990497,0.0003124718,0.00018450046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003068232,0.00025412004,0.00017406202,0.0015733308,0.0007244487,0.0010349251,0.00041560034,0.0002545524,0.0017158673],"category_scores_gemma":[0.0013514877,0.00013952653,0.00033688874,0.0037501066,0.0002993211,0.00038226732,0.001013853,0.0003418739,0.00033139865],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033938122,0.000019362715,0.98661894,0.000045463497,0.000068947935,0.00017542246,0.0012704883,0.0015448614,0.00020007163,0.00056197617,0.004692778,0.0047677816],"study_design_scores_gemma":[0.0000016224379,0.000007893076,0.9925195,0.000021526665,0.000014283223,0.00001550002,0.00228459,0.0015298802,0.000058538262,0.000060758804,0.0034794817,0.000006424748],"about_ca_topic_score_codex":0.9564869,"about_ca_topic_score_gemma":0.98032147,"teacher_disagreement_score":0.04351312,"about_ca_system_score_codex":0.006294947,"about_ca_system_score_gemma":0.0046100556,"threshold_uncertainty_score":0.08753872},"labels":[],"label_agreement":null},{"id":"W4409881148","doi":"10.1080/10630732.2025.2477993","title":"To “In-House” or To Outsource? Artificial Intelligence in Canadian Local Governments","year":2025,"lang":"en","type":"article","venue":"Journal of Urban Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University","funders":"","keywords":"Outsourcing; Business; Marketing","score_opus":0.010303543029828227,"score_gpt":0.25197236652430893,"score_spread":0.2416688234944807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409881148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9539678,0.00079889054,0.000591075,0.007894635,0.000022326283,0.00006431874,0.0001811777,0.0000297854,0.036450017],"genre_scores_gemma":[0.9919817,0.00072077295,0.00052402477,0.0003816583,0.0000031093025,0.000019180072,0.00009736589,0.00001474927,0.006257325],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.99471647,0.0013863071,0.00014665874,0.00038488428,0.001388275,0.0019774004],"domain_scores_gemma":[0.99397683,0.0013124385,0.00058299425,0.00027144296,0.001937169,0.0019190243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004273665,0.0002225362,0.0003670506,0.0014940418,0.01668461,0.006129778,0.0016450384,0.00075203524,0.0032674542],"category_scores_gemma":[0.010038029,0.00031029203,0.0002972324,0.006137138,0.00609467,0.0017835967,0.0036471388,0.0011796318,0.00026288116],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024758847,0.00021519682,0.2215923,0.0004605077,0.00005696044,0.0019612543,0.51032686,0.0028731327,0.0019917928,0.07789798,0.029446721,0.15292972],"study_design_scores_gemma":[0.000014483585,0.000049726186,0.16984974,0.00033780705,0.000036925572,0.00016926172,0.6982994,0.002179567,0.00043847167,0.003021922,0.12549825,0.00010443777],"about_ca_topic_score_codex":0.99195343,"about_ca_topic_score_gemma":0.9964623,"teacher_disagreement_score":0.14513542,"about_ca_system_score_codex":0.14513542,"about_ca_system_score_gemma":0.16479172,"threshold_uncertainty_score":0.9915217},"labels":[],"label_agreement":null},{"id":"W4409889403","doi":"10.61737/olrg2214","title":"Harmoniser la gouvernance de la mobilité servicielle : trois clés pour passer de la compétition à la collaboration","year":2025,"lang":"fr","type":"report","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Political science; Humanities; Philosophy","score_opus":0.010946442682553148,"score_gpt":0.2736630233167329,"score_spread":0.2627165806341798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409889403","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.101561315,0.0041297083,0.7095579,0.019880991,0.0005297479,0.0008418909,0.0003844461,0.00092175294,0.16219227],"genre_scores_gemma":[0.6819007,0.0029162064,0.2655061,0.0016639609,0.00020176856,0.001057705,0.0005446448,0.0006262686,0.04558265],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99156135,0.0036110037,0.0003761093,0.0014740012,0.002036253,0.00094119326],"domain_scores_gemma":[0.9916249,0.002968151,0.0006816328,0.0017168995,0.0020008506,0.001007585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009530635,0.0013794308,0.0013843713,0.0017817994,0.0033154371,0.0106631955,0.0032697327,0.0037833238,0.019182146],"category_scores_gemma":[0.01765526,0.00074078725,0.0016850685,0.002620967,0.0043471283,0.010476964,0.0103390515,0.0034948708,0.0033641176],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003498874,0.0005135635,0.01505801,0.0017800066,0.00047787715,0.00065844174,0.01070729,0.121263705,0.01479614,0.45390218,0.014348027,0.36614498],"study_design_scores_gemma":[0.00017948369,0.0010771744,0.019099355,0.0016648493,0.00027773646,0.0006955735,0.020007392,0.18446481,0.009876682,0.38892782,0.37338597,0.00034317534],"about_ca_topic_score_codex":0.02199719,"about_ca_topic_score_gemma":0.022425123,"teacher_disagreement_score":0.02199719,"about_ca_system_score_codex":0.005292689,"about_ca_system_score_gemma":0.013138732,"threshold_uncertainty_score":0.06417066},"labels":[],"label_agreement":null},{"id":"W4409917551","doi":"10.1109/wacvw65960.2025.00113","title":"OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Driving","year":2025,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"End-to-end principle; Computer science; Open source; Artificial intelligence; Operating system; Software","score_opus":0.019601352746413607,"score_gpt":0.2780642105251702,"score_spread":0.2584628577787566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409917551","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007248154,0.00059230044,0.9366991,0.00050212216,0.00040649172,0.0002029742,0.002937097,0.04598883,0.005422914],"genre_scores_gemma":[0.32620767,0.0007946797,0.6312902,0.0010476215,0.00023924638,0.0010340171,0.014720157,0.005801624,0.018864777],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99964166,0.00007564249,0.000019742498,0.0001254123,0.000086716034,0.000050759176],"domain_scores_gemma":[0.9994993,0.00018259771,0.000023352966,0.00009359243,0.00015265254,0.000048452886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008119727,0.0014988732,0.0008568419,0.0005510983,0.0006755576,0.0014616408,0.0033195193,0.0021348922,0.013509494],"category_scores_gemma":[0.0040149754,0.0006690874,0.0015529868,0.00046390248,0.0005669333,0.0022775019,0.0028656267,0.002912793,0.0061396775],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042981515,0.0003597041,0.0023627798,0.00055398565,0.00033611496,0.0005029109,0.00046005542,0.5382062,0.0063803364,0.025392614,0.08734174,0.33767375],"study_design_scores_gemma":[0.000027493614,0.000028088061,0.00013089228,0.000022971817,0.000014222287,0.000050357707,0.000024634399,0.9718004,0.0017004133,0.014176457,0.011999216,0.000024836467],"about_ca_topic_score_codex":0.011560743,"about_ca_topic_score_gemma":0.023507763,"teacher_disagreement_score":0.013509494,"about_ca_system_score_codex":0.00081627513,"about_ca_system_score_gemma":0.0015299821,"threshold_uncertainty_score":0.04519373},"labels":[],"label_agreement":null},{"id":"W4409997932","doi":"10.2139/ssrn.5238788","title":"Does Micro-Mobility Impacts Trip Generation Rates and Modal Split?","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Modal; Environmental science; Econometrics; Computer science; Transport engineering; Economics; Engineering; Materials science","score_opus":0.009228410560404625,"score_gpt":0.2523258611390356,"score_spread":0.24309745057863097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409997932","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98632556,0.0004944394,0.0009421542,0.0031585838,0.000051946656,0.0000134310285,0.0015335156,0.00003081682,0.0074495426],"genre_scores_gemma":[0.9975725,0.00010606015,0.00006227538,0.00007359278,0.000026313362,0.0000032400035,0.00020400394,0.0000090092335,0.0019429792],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995111,0.000117664735,0.000022223843,0.0001127415,0.00004696996,0.00018924291],"domain_scores_gemma":[0.9945064,0.0026323674,0.001219114,0.00030700446,0.0004077366,0.0009273721],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008081745,0.00021169755,0.0004435678,0.00042633363,0.00051421917,0.0022161093,0.0007491661,0.0012632399,0.032115467],"category_scores_gemma":[0.0063620275,0.00029974978,0.0009026711,0.0008587095,0.00060132245,0.002002339,0.0009342222,0.0009799751,0.0030533688],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007568954,0.00029106348,0.96499676,0.000097475095,0.00073764,0.0005511302,0.0007627616,0.0077983467,0.0011604562,0.0057552885,0.003121091,0.013971008],"study_design_scores_gemma":[0.000025289395,0.00017610393,0.9808899,0.000036201833,0.00032282565,0.00013006704,0.003064816,0.0055899275,0.00040739772,0.0060879337,0.003244502,0.000025031597],"about_ca_topic_score_codex":0.021766827,"about_ca_topic_score_gemma":0.021884486,"teacher_disagreement_score":0.032115467,"about_ca_system_score_codex":0.00047417742,"about_ca_system_score_gemma":0.0005993873,"threshold_uncertainty_score":0.107436895},"labels":[],"label_agreement":null},{"id":"W4410016326","doi":"10.1016/j.trf.2025.04.019","title":"From first ride to regular user: Understanding the factors influencing continuous use intention of autonomous taxis","year":2025,"lang":"en","type":"article","venue":"Transportation Research Part F Traffic Psychology and Behaviour","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"National Natural Science Foundation of China","keywords":"Taxis; Transport engineering; Human factors and ergonomics; Poison control; Engineering; Computer science; Business; Computer security; Environmental health; Medicine","score_opus":0.0859722271544542,"score_gpt":0.35536889841966235,"score_spread":0.26939667126520817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410016326","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992194,0.000026667463,0.00006247816,0.00007830951,0.0000028024729,0.000009842603,0.000023714847,0.0000013359686,0.0005753807],"genre_scores_gemma":[0.9994809,0.000036860965,0.00009863772,0.000028870654,0.0000022932666,0.000010395309,0.000051527175,0.0000018327333,0.00028881544],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991598,0.00026248366,0.000066385444,0.00011382524,0.00017098896,0.00022652508],"domain_scores_gemma":[0.9902096,0.0042658616,0.0022878482,0.00036959013,0.0011543223,0.0017126941],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015563234,0.0002698962,0.0003448241,0.000901281,0.0007932281,0.0026862144,0.00059002364,0.0012421848,0.003068496],"category_scores_gemma":[0.009855564,0.00041510008,0.00079946435,0.0006303498,0.0008302024,0.0013786737,0.000924689,0.00202609,0.00036446133],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001460734,0.000880146,0.9851939,0.000027366217,0.000084332154,0.000052430034,0.008368171,0.000109895394,0.00056363246,0.00021909484,0.00012654625,0.004228413],"study_design_scores_gemma":[0.000005406868,0.00014317349,0.9870078,0.000023533219,0.00004417047,0.000028298879,0.0114702545,0.00085025677,0.00011601367,0.00013813803,0.00016266348,0.000010429407],"about_ca_topic_score_codex":0.03737701,"about_ca_topic_score_gemma":0.061858907,"teacher_disagreement_score":0.03737701,"about_ca_system_score_codex":0.0011279891,"about_ca_system_score_gemma":0.001847025,"threshold_uncertainty_score":0.074318886},"labels":[],"label_agreement":null},{"id":"W4410133754","doi":"10.1007/978-3-031-88653-9_71","title":"Navigating the Future: Artificial Intelligence and Sustainable Transportation in Morocco","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in networks and systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Geography; Business","score_opus":0.010588922500338072,"score_gpt":0.23050839693961878,"score_spread":0.2199194744392807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410133754","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13871026,0.25713432,0.0047538774,0.07001467,0.0029156583,0.000057148187,0.0003453824,0.00010577509,0.525963],"genre_scores_gemma":[0.8497259,0.06570626,0.0026621658,0.0017437675,0.0005219301,0.00003976872,0.0001316735,0.00002735246,0.079441175],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99987984,0.000035950037,0.0000034547847,0.0000121335715,0.000018622695,0.000050044426],"domain_scores_gemma":[0.9999517,0.000018993207,0.000007858128,0.0000028162176,0.000009519876,0.000009114092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023695224,0.00041240224,0.0001976671,0.00050611293,0.0015063875,0.002033368,0.00028981443,0.0007223175,0.002197251],"category_scores_gemma":[0.0002809994,0.00009539908,0.00016686505,0.0010669363,0.0013437055,0.0013315844,0.000854635,0.0005854947,0.000256086],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000862662,0.00004680096,0.0048187817,0.0006604442,0.000031113253,0.001680679,0.013877969,0.00455375,0.001472853,0.65081275,0.076893166,0.24506547],"study_design_scores_gemma":[0.00000527191,0.000040997093,0.0133748995,0.0005629533,0.000020251877,0.00042649728,0.009278475,0.0022879278,0.00049913325,0.053179726,0.9202996,0.000024382764],"about_ca_topic_score_codex":0.083151035,"about_ca_topic_score_gemma":0.14328888,"teacher_disagreement_score":0.083151035,"about_ca_system_score_codex":0.0048723114,"about_ca_system_score_gemma":0.0023937388,"threshold_uncertainty_score":0.1653341},"labels":[],"label_agreement":null},{"id":"W4410359207","doi":"10.1109/icoin63865.2025.10993163","title":"Optimizing Task Offloading Migration Decisions: An Advantage Actor-Critic Approach","year":2025,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Task (project management); Human–computer interaction; Distributed computing; Systems engineering; Engineering","score_opus":0.016005532185446106,"score_gpt":0.2674755383228914,"score_spread":0.2514700061374453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410359207","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.046481565,0.00078888854,0.94396234,0.0008646334,0.00015377234,0.00008079443,0.0000472133,0.00034657758,0.007274228],"genre_scores_gemma":[0.9564957,0.00029995613,0.038535204,0.00017477042,0.00007629753,0.00009611773,0.00005411064,0.000059115977,0.0042087506],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951494,0.00019622511,0.000020660704,0.000104992876,0.000081843034,0.00008138181],"domain_scores_gemma":[0.9985026,0.0009625995,0.00015427603,0.00005636091,0.00022045766,0.00010376823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013795188,0.0012882572,0.0010913304,0.00039927496,0.00034925525,0.0009924741,0.0011274902,0.0011793975,0.0015506336],"category_scores_gemma":[0.0033775256,0.0004779873,0.00040800677,0.00035244433,0.0007039034,0.000785585,0.00077148,0.001432201,0.000244643],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057704376,0.000027594919,0.00026948654,0.00003052379,0.000026463369,0.00005373543,0.00002151186,0.9896741,0.0004983598,0.0016362857,0.00041842237,0.007285754],"study_design_scores_gemma":[0.0000053444423,0.000012678599,0.000030404313,0.000002690039,0.0000038076116,0.000004357379,0.0000034635323,0.99928087,0.00008164452,0.00048064056,0.00009237905,0.0000016590308],"about_ca_topic_score_codex":0.006363504,"about_ca_topic_score_gemma":0.0044612437,"teacher_disagreement_score":0.006363504,"about_ca_system_score_codex":0.0006947215,"about_ca_system_score_gemma":0.0012786144,"threshold_uncertainty_score":0.012652934},"labels":[],"label_agreement":null},{"id":"W4410445584","doi":"10.3390/electronics14102026","title":"Machine Learning-Driven Truck–Drone Collaborative Delivery for Time- and Energy-Efficient Last-Mile Deliveries","year":2025,"lang":"en","type":"article","venue":"Electronics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Drone; Mile; Last mile (transportation); Truck; Aeronautics; Engineering; Computer science; Transport engineering; Automotive engineering; Simulation; Geography","score_opus":0.0029789686691043572,"score_gpt":0.197245977545763,"score_spread":0.19426700887665865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410445584","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27067843,0.00014882958,0.7208408,0.00029324947,0.000050966937,0.00008368695,0.00014372534,0.00053400366,0.007226244],"genre_scores_gemma":[0.9810387,0.000033941054,0.017662652,0.000021091226,0.000004711329,0.000031331332,0.00006738072,0.000019548319,0.0011206142],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985504,0.00003937468,0.000005857002,0.00003326062,0.00003134808,0.000035121073],"domain_scores_gemma":[0.99953747,0.00026008487,0.000050492796,0.00003427015,0.00007722205,0.00004049255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047703806,0.00039954053,0.00046912604,0.00025491332,0.00034814462,0.00062352914,0.0007155839,0.0005066437,0.0016757383],"category_scores_gemma":[0.0014695969,0.0002611226,0.0003456273,0.00030028063,0.00027503906,0.00077954325,0.00058486866,0.0006960114,0.00024107783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014744018,0.000015294667,0.0003995555,0.000007910252,0.000004279136,0.000015510952,0.000012301338,0.9945815,0.00033849303,0.0006512704,0.00008977054,0.0038693468],"study_design_scores_gemma":[0.0000013488512,0.000007775179,0.000057645848,6.6541895e-7,8.4215975e-7,0.0000024634867,0.0000071324084,0.999408,0.00013922418,0.0002836081,0.00009036261,9.591889e-7],"about_ca_topic_score_codex":0.008125508,"about_ca_topic_score_gemma":0.00713635,"teacher_disagreement_score":0.008125508,"about_ca_system_score_codex":0.0005734234,"about_ca_system_score_gemma":0.00086091587,"threshold_uncertainty_score":0.016156435},"labels":[],"label_agreement":null},{"id":"W4410887692","doi":"10.1109/syscon64521.2025.11014875","title":"Optimizing Ticket Assignment Through Group Role Assignment with Agents' Busyness Degree","year":2025,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nipissing University","funders":"","keywords":"Ticket; Computer science; Group (periodic table); Degree (music); Computer security; Chemistry","score_opus":0.01913113587904778,"score_gpt":0.23771325731662285,"score_spread":0.21858212143757508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410887692","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25047198,0.0003507101,0.7420467,0.0003781935,0.00012632464,0.00022792125,0.00008186781,0.0007761159,0.0055402806],"genre_scores_gemma":[0.8257501,0.00010054883,0.17127202,0.000075132055,0.00002788492,0.00012242797,0.00011639034,0.00006768947,0.002467825],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993555,0.00019038927,0.000038165508,0.0001400581,0.000101632795,0.00017431377],"domain_scores_gemma":[0.9988607,0.00043092645,0.0001465759,0.00012182586,0.00018315596,0.00025680213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011959637,0.0010904814,0.0009131669,0.0007683768,0.0008239312,0.0009363225,0.0013995729,0.00067899434,0.0034050145],"category_scores_gemma":[0.0029745856,0.00034394782,0.0005170228,0.0006459118,0.0004710318,0.001413894,0.0011188611,0.00066850096,0.0005579144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046906932,0.0003972808,0.00681347,0.0001364683,0.000065212604,0.00012140531,0.0003140305,0.74221593,0.009673969,0.008578055,0.0032673697,0.22794776],"study_design_scores_gemma":[0.000038523347,0.00011371749,0.0005599688,0.000007400786,0.000022289798,0.000040551746,0.00012929642,0.9930269,0.0017376912,0.0033498148,0.00096266775,0.0000110701085],"about_ca_topic_score_codex":0.0039112903,"about_ca_topic_score_gemma":0.004390081,"teacher_disagreement_score":0.0039112903,"about_ca_system_score_codex":0.0006615203,"about_ca_system_score_gemma":0.0017406879,"threshold_uncertainty_score":0.011390865},"labels":[],"label_agreement":null},{"id":"W4410956842","doi":"10.1080/15568318.2025.2508843","title":"A regional cost-benefit analysis of replacing motorized modes by a shared automated electric vehicle service","year":2025,"lang":"en","type":"article","venue":"International Journal of Sustainable Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"Fuel Cell Technologies Program; European Regional Development Fund; Fundação para a Ciência e a Tecnologia; Ministério da Ciência, Tecnologia e Ensino Superior; European Commission; Goldman Sachs Group","keywords":"Electric vehicle; Service (business); Transport engineering; Automotive engineering; Computer science; Business; Engineering; Marketing","score_opus":0.00696439942708346,"score_gpt":0.255745451780683,"score_spread":0.2487810523535995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410956842","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.921401,0.0010036721,0.050045058,0.00056547654,0.00005784325,0.00048518452,0.0027637992,0.00012571544,0.023552109],"genre_scores_gemma":[0.9909142,0.00026160918,0.006616238,0.000038080158,0.0000067876317,0.00009724507,0.00033593972,0.000018317169,0.0017116212],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884427,0.0006801545,0.000023493441,0.000120565426,0.00013701258,0.00019446465],"domain_scores_gemma":[0.99834263,0.0010418266,0.0001743488,0.00009733436,0.0002450507,0.00009876802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021337292,0.0010363513,0.00073469436,0.0010305498,0.00031362093,0.0016564613,0.001283133,0.0010915394,0.0051644817],"category_scores_gemma":[0.0036306644,0.0005057091,0.0020974292,0.0010919294,0.000508219,0.0013612703,0.0010378808,0.0010222386,0.00031404398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005721018,0.00015559373,0.0027933305,0.00019587034,0.0001777726,0.00022023321,0.000043295993,0.97850275,0.002067245,0.005928201,0.0005568161,0.008786679],"study_design_scores_gemma":[0.00014259887,0.0018576713,0.00985768,0.00010079829,0.0006532331,0.000182072,0.00057663914,0.9771524,0.0022833268,0.003846188,0.0032826138,0.0000647978],"about_ca_topic_score_codex":0.019938404,"about_ca_topic_score_gemma":0.013076391,"teacher_disagreement_score":0.019938404,"about_ca_system_score_codex":0.0034523455,"about_ca_system_score_gemma":0.0018936971,"threshold_uncertainty_score":0.03964472},"labels":[],"label_agreement":null},{"id":"W4411025495","doi":"10.1145/3727120","title":"Online Allocation with Multi-Class Arrivals: Group Fairness vs Individual Welfare","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Measurement and Analysis of Computing Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Alberta","funders":"Universitas Brawijaya","keywords":"Welfare; Class (philosophy); Max-min fairness; Group (periodic table); Fairness measure; Computer science; Economics; Microeconomics; Resource allocation; Computer network; Artificial intelligence; Telecommunications; Physics","score_opus":0.030009689757875057,"score_gpt":0.24479841646630401,"score_spread":0.21478872670842897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411025495","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048866235,0.00023968607,0.9465274,0.0008318021,0.000086811844,0.0001525254,0.00009636295,0.00019755843,0.0030015637],"genre_scores_gemma":[0.8550892,0.00021842586,0.139913,0.00035064228,0.00020684287,0.00028102094,0.000109013505,0.00014715777,0.0036847417],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9958973,0.001777887,0.00013737535,0.0008752523,0.00062571984,0.00068645243],"domain_scores_gemma":[0.98720014,0.008846908,0.001146836,0.0012542296,0.0007095486,0.0008423849],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007844454,0.0011493936,0.0026248007,0.0007988818,0.0013618317,0.0030505368,0.0039784494,0.0026725105,0.003215734],"category_scores_gemma":[0.018522207,0.0004892092,0.0008703542,0.001508374,0.0018833338,0.00528747,0.0019491675,0.0022328545,0.00045417476],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057432964,0.000552355,0.0030307763,0.00015710262,0.0001053993,0.00021794197,0.000288177,0.81159246,0.0022802213,0.111943945,0.0033608638,0.06589647],"study_design_scores_gemma":[0.000027601629,0.000051766732,0.00022507898,0.000007725311,0.000010092497,0.00004933058,0.000039339295,0.96519053,0.000528009,0.033220414,0.00064104697,0.000009043793],"about_ca_topic_score_codex":0.0027951805,"about_ca_topic_score_gemma":0.0017704859,"teacher_disagreement_score":0.007844454,"about_ca_system_score_codex":0.002692088,"about_ca_system_score_gemma":0.0024295035,"threshold_uncertainty_score":0.041485906},"labels":[],"label_agreement":null},{"id":"W4411026006","doi":"10.1007/s43615-025-00623-2","title":"The Sustainable Shared Reverse Logistics Framework: A Blueprint for EV Battery Recovery","year":2025,"lang":"en","type":"article","venue":"Circular Economy and Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Blueprint; Reverse logistics; Battery (electricity); Business; Process management; Manufacturing engineering; Computer science; Engineering; Mechanical engineering; Supply chain; Marketing; Physics","score_opus":0.00741421412005993,"score_gpt":0.23612197931369316,"score_spread":0.22870776519363323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411026006","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00834491,0.0022694627,0.6336818,0.10074378,0.0022112695,0.0004469045,0.0002899523,0.00083729497,0.25117472],"genre_scores_gemma":[0.47636655,0.0052005006,0.40007722,0.015065517,0.0012587149,0.001041821,0.0005673153,0.000731085,0.099691354],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.990044,0.00401876,0.00038640166,0.0009926027,0.0033283315,0.0012299264],"domain_scores_gemma":[0.9916255,0.0018147596,0.00040584695,0.0021360153,0.0027166258,0.0013013467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013509323,0.0013293353,0.00092623517,0.0020374293,0.004123369,0.017123012,0.0061931363,0.010486582,0.009981647],"category_scores_gemma":[0.010543746,0.0006017198,0.001719866,0.0021408165,0.019608978,0.019355293,0.018462082,0.0096752,0.0024887742],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028519703,0.000018665376,0.00003378893,0.000034586814,0.000003415061,0.000029730687,0.00017088022,0.0018587539,0.000094320974,0.9893979,0.003336068,0.005019102],"study_design_scores_gemma":[0.0000050560184,0.00001974897,0.000052611063,0.00016343885,0.0000046012397,0.000047909314,0.00075472635,0.0035185087,0.00027148897,0.8982819,0.096854225,0.00002597573],"about_ca_topic_score_codex":0.0096625155,"about_ca_topic_score_gemma":0.013215259,"teacher_disagreement_score":0.017123012,"about_ca_system_score_codex":0.008946956,"about_ca_system_score_gemma":0.027673088,"threshold_uncertainty_score":0.07144493},"labels":[],"label_agreement":null},{"id":"W4411047196","doi":"10.1016/j.retrec.2025.101583","title":"Establishing a framework of support to scale in mobility as a Service: Consolidated insights from the literature on potential governance frameworks","year":2025,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Crohn's and Colitis Canada; Canadian Foundation for Pharmacy; Cooperative Research Centres, Australian Government Department of Industry","keywords":"Corporate governance; Process management; Scale (ratio); Business; Service (business); Risk analysis (engineering); Transport engineering; Industrial organization; Engineering; Marketing; Finance; Geography","score_opus":0.01391464450378224,"score_gpt":0.30008067123633514,"score_spread":0.2861660267325529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411047196","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11163219,0.0016625171,0.34903893,0.06472258,0.00032174334,0.00036254938,0.00022472808,0.00019488439,0.47183987],"genre_scores_gemma":[0.9858649,0.00028474972,0.010113861,0.00048028608,0.0001042463,0.00017687729,0.00003142655,0.000030391206,0.0029132618],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99077386,0.0041232225,0.00046072598,0.0015204031,0.0016148258,0.0015069802],"domain_scores_gemma":[0.9856995,0.0069488892,0.0018056959,0.0022512295,0.0019333014,0.0013613922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011133314,0.0007435877,0.0010440095,0.002450721,0.0044994093,0.014017334,0.0026636412,0.006934838,0.007595838],"category_scores_gemma":[0.025703592,0.0005189355,0.0011675406,0.0027713845,0.034530964,0.017098095,0.009158776,0.0049052266,0.0006103311],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002011559,0.000004559114,0.00012571653,0.0000064214887,0.0000025071192,0.000014091248,0.00025047967,0.0005364096,0.000018609604,0.99799514,0.0002037751,0.00084045454],"study_design_scores_gemma":[0.000014717396,0.000012006686,0.00030468774,0.00005646599,0.0000068404725,0.000020342533,0.0006889421,0.0026723314,0.00004542261,0.99028265,0.005886863,0.000008640079],"about_ca_topic_score_codex":0.0050229034,"about_ca_topic_score_gemma":0.0054852464,"teacher_disagreement_score":0.014017334,"about_ca_system_score_codex":0.006768472,"about_ca_system_score_gemma":0.008924879,"threshold_uncertainty_score":0.058879316},"labels":[],"label_agreement":null},{"id":"W4411080375","doi":"10.1016/j.jth.2025.102080","title":"Inclusive autonomous shuttles as public transportation options for older people: A qualitative study of user and service provider perspectives","year":2025,"lang":"en","type":"article","venue":"Journal of Transport & Health","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Service provider; Public transport; Qualitative research; Business; Service (business); Process management; Public relations; Internet privacy; Marketing; Computer science; Transport engineering; Sociology; Engineering; Political science","score_opus":0.0183066356280869,"score_gpt":0.3485605789450947,"score_spread":0.3302539433170078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411080375","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963523,0.00048444403,0.00088712096,0.00080121437,0.000022656375,0.0000952075,0.000073325005,0.0000070734022,0.0012765913],"genre_scores_gemma":[0.99718165,0.0006563803,0.00063169876,0.0004998948,0.000010469319,0.0001712254,0.000034286157,0.000009710279,0.0008047748],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9938133,0.004417398,0.00027663689,0.0003256773,0.00036406383,0.00080297823],"domain_scores_gemma":[0.9876165,0.008650931,0.0009955554,0.0002825053,0.0010773626,0.0013772117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0119419815,0.00042520833,0.000784543,0.001137112,0.0054836883,0.0026942678,0.0010094778,0.0012918118,0.0023774381],"category_scores_gemma":[0.013676788,0.00067481917,0.00042114512,0.0014025545,0.0043223705,0.003938352,0.004643095,0.0020631156,0.00020400036],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025494632,0.000028031525,0.003788082,0.00009060172,0.0000030438891,0.00029146858,0.9923097,0.0000140901775,0.0003672358,0.00042755797,0.00017624022,0.0024784068],"study_design_scores_gemma":[0.0000026333323,0.000039494433,0.0013086838,0.00008772255,0.0000039415545,0.00010320946,0.9960549,0.000048018057,0.00008782777,0.00008760944,0.0021704037,0.000005620948],"about_ca_topic_score_codex":0.013335753,"about_ca_topic_score_gemma":0.02078804,"teacher_disagreement_score":0.013335753,"about_ca_system_score_codex":0.0034090965,"about_ca_system_score_gemma":0.0044595455,"threshold_uncertainty_score":0.06315601},"labels":[],"label_agreement":null},{"id":"W4411118917","doi":"10.1016/j.cstp.2025.101512","title":"Spatial impacts of on-demand transit service for transit stop and neighborhood ridership","year":2025,"lang":"en","type":"article","venue":"Case Studies on Transport Policy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Western University; University of Regina","funders":"Social Sciences and Humanities Research Council","keywords":"Transit (satellite); Transport engineering; Service (business); Business; Public transport; Engineering; Marketing","score_opus":0.02429931797214261,"score_gpt":0.30366068594575973,"score_spread":0.2793613679736171,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411118917","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22213763,0.0010143745,0.7485764,0.001983209,0.00013334841,0.0008450583,0.011389606,0.00047348463,0.013446838],"genre_scores_gemma":[0.8650733,0.00072918297,0.1257512,0.00012719985,0.000047713907,0.0005277094,0.004426875,0.0000629793,0.0032538373],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9971169,0.0013837424,0.00016366495,0.00059317093,0.00049958314,0.0002429052],"domain_scores_gemma":[0.99561834,0.0019938063,0.00075052,0.00064337166,0.00086089777,0.00013293652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029667825,0.0006301924,0.0006067048,0.0031510794,0.0005721437,0.002364759,0.0019467989,0.0009949796,0.0033664221],"category_scores_gemma":[0.008717543,0.00045942285,0.0025979546,0.0033465088,0.00086287456,0.001892388,0.0031254457,0.0009908949,0.00032024636],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008376371,0.00032186808,0.2974802,0.00043608574,0.00093378057,0.00064932136,0.0009834361,0.43136054,0.0010424275,0.18055896,0.0059923893,0.08015725],"study_design_scores_gemma":[0.00002373742,0.00017687278,0.13484791,0.00021480373,0.0005138848,0.00020115443,0.0017726913,0.7953154,0.00087193237,0.050312378,0.015655568,0.00009369852],"about_ca_topic_score_codex":0.14030297,"about_ca_topic_score_gemma":0.16093755,"teacher_disagreement_score":0.14030297,"about_ca_system_score_codex":0.003944697,"about_ca_system_score_gemma":0.0037012028,"threshold_uncertainty_score":0.27897263},"labels":[],"label_agreement":null},{"id":"W4411146462","doi":"10.1287/ijoc.2024.0637","title":"Learning-Based Online Optimization for Autonomous Mobility-on-Demand Fleet Control","year":2025,"lang":"en","type":"article","venue":"INFORMS journal on computing","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Control (management); Operations research; Fleet management; Mathematical optimization; Artificial intelligence; Engineering; Telecommunications; Mathematics","score_opus":0.008515457155003322,"score_gpt":0.2545853614221791,"score_spread":0.24606990426717576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411146462","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021635847,0.00033131853,0.97092617,0.00041456346,0.00006956241,0.0000923449,0.00016413348,0.0012293218,0.0051367567],"genre_scores_gemma":[0.8796185,0.00020595167,0.11467715,0.00027900387,0.000060086903,0.00027737863,0.00039247514,0.00025742658,0.0042319703],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995895,0.00009541606,0.000021393143,0.00009638761,0.00009777859,0.000099474506],"domain_scores_gemma":[0.9982502,0.0012155422,0.00015603936,0.00009186492,0.00019462648,0.00009169948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011316641,0.0012524239,0.0012665608,0.000500551,0.00039784712,0.0009885634,0.0013610667,0.0012953356,0.004969334],"category_scores_gemma":[0.0038670832,0.0006358375,0.0006798471,0.0005686561,0.0008865154,0.0010185539,0.0013203494,0.001895339,0.0006139501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020460478,0.000021678174,0.00014606367,0.000027336799,0.000008711382,0.000012622151,0.00000826443,0.98993707,0.00019394429,0.0016672924,0.00047735893,0.007479287],"study_design_scores_gemma":[0.0000031905072,0.0000054183456,0.00001626503,0.0000013733381,0.0000010226729,0.0000011301491,0.000001242684,0.9991479,0.000043947137,0.0006914319,0.00008634855,7.9758803e-7],"about_ca_topic_score_codex":0.009837443,"about_ca_topic_score_gemma":0.007966241,"teacher_disagreement_score":0.009837443,"about_ca_system_score_codex":0.0012882284,"about_ca_system_score_gemma":0.0019139324,"threshold_uncertainty_score":0.019560397},"labels":[],"label_agreement":null},{"id":"W4411179308","doi":"10.3311/pptr.38371","title":"Revenue Alterations of Shared Automated Mobility Services Integrated into Mobility as a Service","year":2025,"lang":"en","type":"article","venue":"Periodica Polytechnica Transportation Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Service (business); Revenue; Business; Computer science; Telecommunications; Marketing; Finance","score_opus":0.004892756765113563,"score_gpt":0.23506124778468937,"score_spread":0.23016849101957582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411179308","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88148546,0.0005124136,0.08197197,0.0009484753,0.00015155962,0.00022726208,0.00075943687,0.00032193863,0.03362153],"genre_scores_gemma":[0.9940095,0.00006160189,0.0041693253,0.000025749869,0.000016474307,0.000021489703,0.00020328867,0.0000275062,0.0014650875],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9953499,0.0016789177,0.00014957594,0.0004887982,0.0013876423,0.00094503904],"domain_scores_gemma":[0.9903628,0.0040383483,0.0017143588,0.0011633006,0.0021969723,0.00052420417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038389026,0.0005546424,0.00045074485,0.0014005916,0.00080721313,0.003180714,0.001511743,0.00066160946,0.0051831147],"category_scores_gemma":[0.018539842,0.00031342843,0.0013087883,0.0015616213,0.0009309229,0.0045926794,0.002644549,0.0016935179,0.00053379615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00092838804,0.0007453251,0.08536924,0.00021519001,0.00024256414,0.0018876524,0.0007939647,0.5316923,0.006684601,0.23993692,0.0050594355,0.12644443],"study_design_scores_gemma":[0.000042813997,0.00064492674,0.041767757,0.00009022517,0.00017157951,0.0005236241,0.0017175411,0.88775223,0.006996135,0.04654303,0.013632028,0.000118105505],"about_ca_topic_score_codex":0.009356544,"about_ca_topic_score_gemma":0.007061856,"teacher_disagreement_score":0.009356544,"about_ca_system_score_codex":0.0057067135,"about_ca_system_score_gemma":0.0027732684,"threshold_uncertainty_score":0.04140532},"labels":[],"label_agreement":null},{"id":"W4411236843","doi":"10.1016/j.tra.2025.104566","title":"Analyzing the influence of transit pass ownership on the determinants of ride-sourcing frequency in Metro Vancouver: Implications for policy and urban mobility planning","year":2025,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Transport engineering; Urban transit; Transit (satellite); Business; Public transport; Car ownership; Transportation planning; Urban planning; Transit-oriented development; Rail transit; Economic geography; Regional science; Environmental planning; Engineering; Geography; Civil engineering","score_opus":0.08554556917153998,"score_gpt":0.41775269042160945,"score_spread":0.33220712125006946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411236843","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958884,0.00027805383,0.00051305944,0.0004773735,0.0000059446647,0.000028214597,0.00040319187,0.000008577208,0.00239719],"genre_scores_gemma":[0.99803704,0.00028506873,0.00029456246,0.00002905827,0.0000050384533,0.00001676706,0.00024139241,0.0000042963425,0.0010868191],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990089,0.00036635422,0.000035671947,0.000107974716,0.00015577627,0.00032525446],"domain_scores_gemma":[0.99422246,0.0028829982,0.0009855893,0.00025718217,0.0009283097,0.00072342425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013971978,0.00034103694,0.00050714327,0.0010594508,0.001033753,0.0021223077,0.0008136627,0.0004796021,0.003690145],"category_scores_gemma":[0.0074655353,0.00025972867,0.00072598574,0.0027063657,0.0007980946,0.0008455322,0.0013812273,0.0010251118,0.000329835],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006340277,0.00008587816,0.9818217,0.00008918417,0.00012497559,0.0003213499,0.0016247099,0.003078025,0.00027909008,0.00096157927,0.0005015187,0.011048648],"study_design_scores_gemma":[0.0000069676953,0.00007197788,0.97516394,0.000107638974,0.000094604125,0.000058670215,0.012039936,0.009410441,0.00014722272,0.0005503544,0.0023287612,0.00001940311],"about_ca_topic_score_codex":0.8148417,"about_ca_topic_score_gemma":0.8539042,"teacher_disagreement_score":0.18515831,"about_ca_system_score_codex":0.004716005,"about_ca_system_score_gemma":0.007456407,"threshold_uncertainty_score":0.37249744},"labels":[],"label_agreement":null},{"id":"W4411334088","doi":"10.1016/j.cstp.2025.101533","title":"Understanding the spatiotemporal dynamics of ride-hailing services: A study of demand and supply patterns using a large-scale driver activity dataset","year":2025,"lang":"en","type":"article","venue":"Case Studies on Transport Policy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"University of Toronto","keywords":"Scale (ratio); Dynamics (music); Computer science; Transport engineering; Business; Geography; Cartography; Engineering","score_opus":0.049397280894101635,"score_gpt":0.3205646157060931,"score_spread":0.2711673348119915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411334088","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9293684,0.0002850057,0.0016456408,0.000583965,0.000026095851,0.000031566946,0.066742085,0.0000974922,0.0012198021],"genre_scores_gemma":[0.8597747,0.0002907024,0.003010136,0.000108533735,0.000032820466,0.00007051152,0.13525611,0.00003934533,0.00141719],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996489,0.000073299816,0.00003668563,0.00011260424,0.000058495578,0.00006996612],"domain_scores_gemma":[0.99861586,0.00051400723,0.00030384155,0.0001991192,0.00023877948,0.00012841349],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006449193,0.00029113152,0.00041018616,0.0018096389,0.0003323637,0.00081869814,0.00072029105,0.00078119553,0.0013665115],"category_scores_gemma":[0.00264473,0.0002300915,0.0007710419,0.0036960037,0.00025053264,0.0010918571,0.0007506365,0.00070159714,0.0008548842],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032572466,0.00048487328,0.92886084,0.00027350558,0.00047678527,0.0005780634,0.0013671792,0.015281127,0.002489932,0.002146937,0.028908337,0.018806748],"study_design_scores_gemma":[0.00003796085,0.00009881629,0.910863,0.00006361795,0.000108312975,0.00029335817,0.0041025667,0.058251772,0.0008685229,0.0010251654,0.024230933,0.000056006225],"about_ca_topic_score_codex":0.081100665,"about_ca_topic_score_gemma":0.12029843,"teacher_disagreement_score":0.081100665,"about_ca_system_score_codex":0.00072002446,"about_ca_system_score_gemma":0.00073286257,"threshold_uncertainty_score":0.1612572},"labels":[],"label_agreement":null},{"id":"W4411337166","doi":"10.1109/tvt.2025.3579331","title":"Socially Game-Theoretic Lane-Change for Autonomous Heavy Vehicle Based on Asymmetric Driving Aggressiveness","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Game theory; Vehicle dynamics; Automotive engineering; Computer science; Simulation; Engineering; Transport engineering; Economics; Microeconomics","score_opus":0.010434970954730142,"score_gpt":0.24431482512205616,"score_spread":0.233879854167326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411337166","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.082120724,0.00010605149,0.9135719,0.0002243278,0.00003230208,0.00009566838,0.00007884295,0.00009662832,0.0036736517],"genre_scores_gemma":[0.96731555,0.0000611321,0.031067297,0.0000487462,0.000013843492,0.00009206723,0.00007680813,0.000016320333,0.0013082254],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898785,0.00037408576,0.000041895357,0.00024220215,0.00020530979,0.00014866458],"domain_scores_gemma":[0.99818474,0.001028432,0.000249023,0.000088434914,0.00029796365,0.00015138676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012925664,0.00086500164,0.0007923537,0.0007363026,0.00060253957,0.0013263039,0.0013543352,0.00079017907,0.001813741],"category_scores_gemma":[0.0031602385,0.00044084634,0.0008884273,0.0004261081,0.0011723662,0.0014870018,0.0011601284,0.0011354408,0.00017020201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006420518,0.000048066187,0.0018370139,0.000050382976,0.00004288055,0.00012107947,0.00014714384,0.9636871,0.0013671834,0.021362826,0.0003261535,0.010945976],"study_design_scores_gemma":[0.0000037788895,0.000019851905,0.00014158018,0.0000023470775,0.0000068165473,0.000010289932,0.000017705092,0.9943568,0.00018009938,0.0051547154,0.00009872519,0.0000072361304],"about_ca_topic_score_codex":0.010407931,"about_ca_topic_score_gemma":0.0077888304,"teacher_disagreement_score":0.010407931,"about_ca_system_score_codex":0.0018847263,"about_ca_system_score_gemma":0.0018001572,"threshold_uncertainty_score":0.020694673},"labels":[],"label_agreement":null},{"id":"W4411355543","doi":"10.21203/rs.3.rs-6866050/v1","title":"Balancing Energy Resilience and Mobility: A Multi-Objective Strategy for Deploying Shared Autonomous Electric Vehicles in Urban Disruptions","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Environment and Climate Change Canada","keywords":"Resilience (materials science); Urban resilience; Computer science; Energy (signal processing); Business; Transport engineering; Environmental economics; Urban planning; Engineering; Civil engineering; Economics","score_opus":0.04680858426317986,"score_gpt":0.35802470512804363,"score_spread":0.3112161208648638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411355543","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38398445,0.00040260932,0.60364115,0.0009798057,0.000091614806,0.00013810169,0.00009956317,0.00027102043,0.010391752],"genre_scores_gemma":[0.9935408,0.00003043647,0.005551284,0.000022336497,0.000007995327,0.000019938085,0.000011995061,0.000007704503,0.00080745516],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996939,0.00009426031,0.000011297001,0.000055122677,0.000041010913,0.000104483224],"domain_scores_gemma":[0.9994338,0.00027937684,0.00009652878,0.000029088755,0.00007644733,0.00008467389],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008206102,0.0010245295,0.000807557,0.00049866945,0.00049268274,0.0009930511,0.0008527072,0.00089168694,0.0016451449],"category_scores_gemma":[0.0015893058,0.00027018096,0.00034478644,0.0003804691,0.00056003587,0.0010580356,0.0015614354,0.0005111273,0.00012531827],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006984508,0.000024388686,0.00029836808,0.000021130214,0.00003394411,0.00004955101,0.000030947074,0.9882669,0.0015900851,0.0021811845,0.00020712578,0.0072265915],"study_design_scores_gemma":[0.000007842038,0.00006571678,0.00017923466,0.0000037011066,0.000012033228,0.000012166738,0.00005692207,0.99761415,0.00028610657,0.0015836074,0.00017471507,0.000003769414],"about_ca_topic_score_codex":0.0037128439,"about_ca_topic_score_gemma":0.003481179,"teacher_disagreement_score":0.0037128439,"about_ca_system_score_codex":0.00071107986,"about_ca_system_score_gemma":0.0007103623,"threshold_uncertainty_score":0.0073824525},"labels":[],"label_agreement":null},{"id":"W4411465327","doi":"10.1155/atr/1680317","title":"Optimization Methods for Customized Bus Routes in Random Environments","year":2025,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Randomness; Reservation; Computer science; Sorting; Genetic algorithm; Mathematical optimization; Heuristic; Path (computing); Service (business); Stochastic programming; Variable neighborhood search; Operations research; Algorithm; Engineering; Metaheuristic; Mathematics; Artificial intelligence; Computer network","score_opus":0.007357633920769358,"score_gpt":0.294825450585935,"score_spread":0.28746781666516563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411465327","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009011864,0.00031382404,0.9879821,0.000121009216,0.000034481902,0.000047960613,0.000059110203,0.00010162591,0.0023280035],"genre_scores_gemma":[0.5936583,0.0010821511,0.3952805,0.00015787479,0.000094682466,0.00058687764,0.00034668125,0.00028293516,0.008509936],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992675,0.0003600041,0.000027901764,0.00013068797,0.0001211237,0.00009279962],"domain_scores_gemma":[0.9984713,0.0010404263,0.00019122266,0.00005374177,0.00018848132,0.00005467842],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016136619,0.001324478,0.0012772012,0.0009962764,0.00044185884,0.00095320155,0.0010456209,0.0010844232,0.0026625572],"category_scores_gemma":[0.0030515885,0.00079813076,0.0012489555,0.0010587627,0.00073925237,0.0008601279,0.0010825348,0.0009505919,0.00032958383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006269964,0.0000062800955,0.00007933861,0.000015760043,0.000012207708,0.00001565069,0.000007270442,0.9937125,0.00009908931,0.003585001,0.00013508648,0.0023254612],"study_design_scores_gemma":[0.0000031497973,0.000008033584,0.000028220671,0.0000026009643,0.0000025476354,0.0000042545853,0.0000054459338,0.9976972,0.000037012116,0.00200884,0.00020030804,0.0000023430446],"about_ca_topic_score_codex":0.008289141,"about_ca_topic_score_gemma":0.006094996,"teacher_disagreement_score":0.008289141,"about_ca_system_score_codex":0.001171659,"about_ca_system_score_gemma":0.0015513004,"threshold_uncertainty_score":0.016481757},"labels":[],"label_agreement":null},{"id":"W4411536522","doi":"10.1016/j.trip.2025.101504","title":"Accessibility of third-party transit apps and the role of transit agencies and their open data","year":2025,"lang":"en","type":"article","venue":"Transportation Research Interdisciplinary Perspectives","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"York University; Carnegie Mellon University","keywords":"Transit (satellite); Business; Third party; Transport engineering; Computer science; Internet privacy; Computer security; Public transport; Engineering","score_opus":0.05712892081520379,"score_gpt":0.3910408978298088,"score_spread":0.33391197701460495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411536522","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8421964,0.0014956614,0.018041741,0.019019015,0.0001285317,0.00017672166,0.00017789856,0.0000978563,0.11866618],"genre_scores_gemma":[0.9950972,0.00039735308,0.0014387821,0.0005664358,0.00001853231,0.0000689133,0.000031445103,0.000028338525,0.00235289],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.9684623,0.021925736,0.0012965982,0.0017848607,0.004610118,0.0019203816],"domain_scores_gemma":[0.9301756,0.0484616,0.007348371,0.0047777486,0.006536505,0.002700238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.018259473,0.0002729823,0.0003469222,0.0024301545,0.007095058,0.014786505,0.0011250178,0.0020125534,0.00501653],"category_scores_gemma":[0.047371443,0.00038522834,0.0005013394,0.0027870568,0.016657986,0.014039112,0.009077279,0.0033346845,0.00042186797],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008046893,0.00012205995,0.036036104,0.00036485653,0.000022972345,0.0009873651,0.76304704,0.00020241119,0.0013394273,0.14742956,0.0029132955,0.047454406],"study_design_scores_gemma":[0.000016392461,0.00012146861,0.02764326,0.0010313308,0.000033970897,0.000839186,0.79881245,0.0007672932,0.0011459166,0.023472752,0.14604446,0.00007155523],"about_ca_topic_score_codex":0.017194273,"about_ca_topic_score_gemma":0.013376025,"teacher_disagreement_score":0.018259473,"about_ca_system_score_codex":0.005183562,"about_ca_system_score_gemma":0.007134502,"threshold_uncertainty_score":0.0965665},"labels":[],"label_agreement":null},{"id":"W4411557825","doi":"10.3390/su17135730","title":"Understanding Consumers’ Adoption Behavior of Driverless Delivery Vehicles: Insights from the Combined Use of NCA and PLS-SEM","year":2025,"lang":"en","type":"article","venue":"Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; Cape Breton University","funders":"Sichuan University of Science and Engineering","keywords":"Business; Marketing; Computer science","score_opus":0.038449057246689455,"score_gpt":0.2422640947224714,"score_spread":0.20381503747578195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411557825","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938896,0.00003576613,0.0045330427,0.000092043076,0.0000014149368,0.00007694096,0.00007978421,0.000016091904,0.0012752941],"genre_scores_gemma":[0.99269897,0.00009456674,0.0065476117,0.000027238884,0.0000015089371,0.00011901995,0.0001599958,0.0000049568757,0.00034616288],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987417,0.0006221554,0.00009918863,0.000156456,0.00030220102,0.000078424266],"domain_scores_gemma":[0.9946143,0.003515165,0.0005840189,0.00022007023,0.0009871487,0.00007921985],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038320282,0.0004368386,0.00032959357,0.0013499479,0.0004771395,0.0013924139,0.000473207,0.00045130783,0.001230077],"category_scores_gemma":[0.007672929,0.00028989042,0.0008366382,0.0015394079,0.0004699617,0.0016728935,0.0007226318,0.00063593296,0.00014684153],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000107626096,0.0008131824,0.82918346,0.00031439806,0.0001778032,0.00032408806,0.045512825,0.0052738353,0.004030529,0.004018657,0.0005368518,0.10970676],"study_design_scores_gemma":[0.000034072855,0.0005357844,0.811955,0.00022949364,0.0002779483,0.00017886436,0.078348435,0.09696549,0.0024769849,0.004507601,0.004398498,0.000091856964],"about_ca_topic_score_codex":0.018114518,"about_ca_topic_score_gemma":0.023329303,"teacher_disagreement_score":0.018114518,"about_ca_system_score_codex":0.001413892,"about_ca_system_score_gemma":0.0016401659,"threshold_uncertainty_score":0.036018133},"labels":[],"label_agreement":null},{"id":"W4411599731","doi":"10.1109/tmc.2025.3582864","title":"Embodied AI-Enhanced Vehicular Networks: An Integrated Vision Language Models and Reinforcement Learning Method","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Chiang Mai University; Ministry of Science and ICT, South Korea; Ministry of Education - Singapore; National Research Foundation","keywords":"Embodied cognition; Computer science; Reinforcement learning; Human–computer interaction; Artificial intelligence; Cognitive science; Psychology","score_opus":0.008551245628869705,"score_gpt":0.28536783881716715,"score_spread":0.27681659318829743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411599731","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023642821,0.00022874457,0.9732592,0.00020268757,0.000036787533,0.000026071097,0.000021160631,0.00016543997,0.0024171155],"genre_scores_gemma":[0.93575704,0.00016170541,0.061098147,0.000114632094,0.000025753077,0.00007224227,0.000035031764,0.000032053278,0.0027034644],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996458,0.00012045466,0.000013690659,0.00007399082,0.00008710952,0.000058873273],"domain_scores_gemma":[0.99920195,0.000476004,0.00009591888,0.00004291206,0.00013335203,0.0000498797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073804654,0.0006097235,0.00061975035,0.00033758543,0.0002634088,0.0007790004,0.0012330842,0.00073589326,0.0009997283],"category_scores_gemma":[0.0025279906,0.00033095223,0.0004081725,0.00033159967,0.00076822995,0.0010779907,0.0010882885,0.0010406228,0.00018656292],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028989793,0.000022566013,0.00023120118,0.000024637971,0.000015922436,0.000046186862,0.00005392633,0.97553885,0.0013059299,0.007543496,0.00025429632,0.014934071],"study_design_scores_gemma":[0.0000024260091,0.000010647527,0.000018454757,0.0000013849227,0.000002230492,0.0000043730925,0.0000036388053,0.9980166,0.00016923083,0.0016659516,0.00010303353,0.0000021056678],"about_ca_topic_score_codex":0.0071511026,"about_ca_topic_score_gemma":0.004120087,"teacher_disagreement_score":0.0071511026,"about_ca_system_score_codex":0.00090327725,"about_ca_system_score_gemma":0.001009085,"threshold_uncertainty_score":0.014218926},"labels":[],"label_agreement":null},{"id":"W4411616840","doi":"10.1177/03611981251335892","title":"Exploring the Effects of Information and Communication Technology on Travel Within an Activity-Based Travel Demand Modeling System","year":2025,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Dalhousie University","funders":"Environment and Climate Change Canada","keywords":"Travel behavior; Computer science; Geography; Economic geography; Transport engineering; Engineering","score_opus":0.0815015218661069,"score_gpt":0.3361942314094959,"score_spread":0.25469270954338896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411616840","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93724364,0.00009263914,0.056808136,0.0003449962,0.0000113314945,0.00011976064,0.00076439034,0.00014051051,0.0044746785],"genre_scores_gemma":[0.9892152,0.00006474185,0.009033306,0.000019814019,0.0000032219516,0.000061830804,0.0003205133,0.000011740134,0.0012697235],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957365,0.00023313481,0.000017617776,0.00006653643,0.00004169227,0.000067357345],"domain_scores_gemma":[0.9991115,0.00060804264,0.00007816042,0.000038371047,0.000114135386,0.000049821418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007510565,0.00061769463,0.00041376334,0.0004087883,0.00037828885,0.0010717834,0.0008043066,0.0007677027,0.0012707271],"category_scores_gemma":[0.0016260187,0.0004249812,0.00064892194,0.000703128,0.00027061897,0.00086467335,0.00067869964,0.00060042564,0.00015720345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043169697,0.00007610453,0.0049997107,0.00001856387,0.000022802917,0.000026589994,0.00005573329,0.99029654,0.00040549712,0.0011709806,0.00009523932,0.0027890669],"study_design_scores_gemma":[0.0000020888685,0.000018337545,0.00080953276,0.0000010590496,0.0000046387354,0.0000021831945,0.0000308785,0.9988182,0.000071547096,0.00014007882,0.00009935434,0.0000020634225],"about_ca_topic_score_codex":0.13309734,"about_ca_topic_score_gemma":0.08207077,"teacher_disagreement_score":0.13309734,"about_ca_system_score_codex":0.0023445417,"about_ca_system_score_gemma":0.0015914144,"threshold_uncertainty_score":0.26464528},"labels":[],"label_agreement":null},{"id":"W4411634490","doi":"10.2139/ssrn.5321003","title":"Transport Modal Shift: Do Riders Prefer E-Bike Sharing Over E-Scooter Sharing in Canadian Cities?","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Modal shift; Modal; Business; Bike sharing; Transport engineering; Advertising; Marketing; Public transport; Engineering; Chemistry","score_opus":0.009927226175160982,"score_gpt":0.23586581531628367,"score_spread":0.2259385891411227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411634490","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9886529,0.00045559937,0.00006844619,0.003100051,0.000028727454,0.00003436561,0.00084118097,0.000005265053,0.006813417],"genre_scores_gemma":[0.99665666,0.00020946964,0.000043415643,0.00040344402,0.000008080577,0.00001086637,0.000361037,0.0000049144055,0.0023020697],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979044,0.00015024698,0.000047349055,0.00025435322,0.00036197543,0.0012817029],"domain_scores_gemma":[0.99333537,0.0007732469,0.0013639185,0.00021429619,0.0021116938,0.0022014715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015899416,0.00033481218,0.0006816841,0.0013912196,0.0070764553,0.0042657224,0.0030710076,0.0026239506,0.014845632],"category_scores_gemma":[0.0065719,0.00043307774,0.00094429957,0.004661267,0.0030123778,0.0026434425,0.0016484815,0.0024128843,0.0007238287],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00092540996,0.0005042128,0.9439776,0.000100803765,0.00016255835,0.00026410774,0.022709798,0.00059518963,0.00032861784,0.003485074,0.011554201,0.015392514],"study_design_scores_gemma":[0.00004631906,0.00005092619,0.9074509,0.00009235184,0.00007445688,0.00003125523,0.086687595,0.00060897105,0.000093561095,0.0005315368,0.004278279,0.00005380766],"about_ca_topic_score_codex":0.995598,"about_ca_topic_score_gemma":0.9978929,"teacher_disagreement_score":0.033329956,"about_ca_system_score_codex":0.033329956,"about_ca_system_score_gemma":0.041287273,"threshold_uncertainty_score":0.24182689},"labels":[],"label_agreement":null},{"id":"W4411811653","doi":"10.1007/978-981-96-8889-0_36","title":"Towards Predicting Complex Carpooling Trajectories with Context-Augmented BERT-LLM in Chaotic Environments","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Université du Québec à Montréal","funders":"","keywords":"Computer science; Chaotic; Context (archaeology); Artificial intelligence; Geography","score_opus":0.014394527585051723,"score_gpt":0.21905596261982868,"score_spread":0.20466143503477696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411811653","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3701145,0.0010829751,0.62112063,0.00027681954,0.00022083915,0.00008447882,0.0008857515,0.003100854,0.003113139],"genre_scores_gemma":[0.923624,0.00020213277,0.07335833,0.00005811877,0.00006169618,0.000043186617,0.00088046776,0.000096459145,0.0016756909],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998666,0.000019413412,0.000005587427,0.000044467502,0.000025302264,0.000038637903],"domain_scores_gemma":[0.99965835,0.00014947199,0.000038458085,0.000040520707,0.000055213106,0.00005794567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026104393,0.0011028296,0.0009172462,0.00094873516,0.00042253706,0.0009282243,0.0011386848,0.0013043929,0.0014676326],"category_scores_gemma":[0.0011580543,0.0005879595,0.00075942336,0.0009355909,0.00043313514,0.00086492876,0.001221823,0.0014237548,0.0008107217],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031593995,0.00015500892,0.0060144113,0.00007745167,0.00007781957,0.00019805344,0.000083817766,0.9130322,0.005256156,0.0009454166,0.0015140885,0.0723296],"study_design_scores_gemma":[0.0000017948579,0.000008659907,0.00036052935,0.0000028465872,0.0000022220593,0.0000067540873,0.000009010771,0.99905103,0.00018998906,0.0002822499,0.00008203638,0.0000029042428],"about_ca_topic_score_codex":0.016276117,"about_ca_topic_score_gemma":0.01769544,"teacher_disagreement_score":0.016276117,"about_ca_system_score_codex":0.00038112872,"about_ca_system_score_gemma":0.0006685179,"threshold_uncertainty_score":0.03236276},"labels":[],"label_agreement":null},{"id":"W4411865174","doi":"10.1016/j.trc.2025.105217","title":"Data-driven optimization for ride-sourcing vehicle dispatching and relocation under demand and travel time uncertainty","year":2025,"lang":"en","type":"article","venue":"Transportation Research Part C Emerging Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Research Grants Council, University Grants Committee; National Natural Science Foundation of China","keywords":"Relocation; Transport engineering; Travel time; Automatic vehicle location; Computer science; Operations research; Engineering; Global Positioning System; Telecommunications","score_opus":0.05237858306981703,"score_gpt":0.34239826666077566,"score_spread":0.29001968359095864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411865174","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050264683,0.0010202569,0.9382332,0.001809361,0.00042367243,0.000398153,0.0016441615,0.00063813163,0.005568408],"genre_scores_gemma":[0.893671,0.00045838772,0.095940955,0.0003912465,0.00019136911,0.0006138189,0.0014318054,0.0003506071,0.0069508743],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980751,0.00079981,0.00010432916,0.00036657456,0.00030641098,0.00034780338],"domain_scores_gemma":[0.9914507,0.0066425996,0.00045809944,0.00022361142,0.00088522385,0.00033977782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055989893,0.002541695,0.004867581,0.0015553035,0.0009649824,0.003202348,0.0030930028,0.0036221102,0.005191515],"category_scores_gemma":[0.012155583,0.0031073713,0.0021141968,0.0019335459,0.0019168385,0.0023945097,0.0028573885,0.0034604853,0.0006058317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003676849,0.000021038912,0.00007403508,0.000032355565,0.000016144715,0.00001750952,0.000009766961,0.997021,0.00007525405,0.0011781239,0.0002765844,0.0012412491],"study_design_scores_gemma":[0.0000052484397,0.000005221122,0.000014306768,0.0000016156553,0.0000015036617,8.9400083e-7,0.000002931626,0.99923337,0.00002073879,0.0006725635,0.00003986218,0.0000017510264],"about_ca_topic_score_codex":0.034416776,"about_ca_topic_score_gemma":0.015262726,"teacher_disagreement_score":0.034416776,"about_ca_system_score_codex":0.0032535982,"about_ca_system_score_gemma":0.004209585,"threshold_uncertainty_score":0.06843287},"labels":[],"label_agreement":null},{"id":"W4411987668","doi":"10.1016/j.tranpol.2025.07.001","title":"Service area identification for robotaxi deployment: A GIS-based spatio-temporal multi-criteria decision support framework","year":2025,"lang":"en","type":"article","venue":"Transport Policy","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Hong Kong Polytechnic University; National Natural Science Foundation of China","keywords":"Software deployment; Identification (biology); Computer science; Service (business); Decision support system; Transport engineering; Geographic information system; Engineering; Data mining; Business; Geography; Remote sensing","score_opus":0.02948998269097617,"score_gpt":0.3245446039478543,"score_spread":0.2950546212568781,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411987668","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022989864,0.0001986677,0.9721634,0.0003334923,0.00003890042,0.00017557996,0.00048572064,0.00054617965,0.0030682185],"genre_scores_gemma":[0.7345477,0.00020291297,0.26170433,0.00010910295,0.00005285079,0.00044261006,0.00072965183,0.00009214476,0.0021187617],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99860305,0.0004112021,0.00009866225,0.00030424504,0.00034352174,0.00023925464],"domain_scores_gemma":[0.99802667,0.00096654904,0.00025890046,0.000064773965,0.00047698803,0.000206151],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002941955,0.0013895432,0.002049808,0.002735611,0.0009951409,0.0029202546,0.0025053525,0.0018684524,0.0041984865],"category_scores_gemma":[0.003524013,0.0008449861,0.0017187062,0.002083857,0.0009053365,0.0019981738,0.0020853877,0.0012056959,0.00052981114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005361351,0.000069770525,0.0005864058,0.000071527604,0.00004174429,0.000098870616,0.000056885285,0.97716147,0.0007206469,0.0053480277,0.00074851245,0.015042457],"study_design_scores_gemma":[0.000003324755,0.000012782118,0.00006658896,0.000004826504,0.000005525736,0.0000067928895,0.00001988399,0.99834037,0.00009423634,0.0012963352,0.00014518175,0.0000040765326],"about_ca_topic_score_codex":0.031122651,"about_ca_topic_score_gemma":0.0205561,"teacher_disagreement_score":0.031122651,"about_ca_system_score_codex":0.0025969332,"about_ca_system_score_gemma":0.0038539993,"threshold_uncertainty_score":0.061882973},"labels":[],"label_agreement":null},{"id":"W4412189802","doi":"10.54254/2753-7048/2024.24821","title":"Moral Hazard in Ride Hailing Services: Provide Disincentives from Ratings System Failures","year":2025,"lang":"en","type":"article","venue":"Lecture Notes in Education Psychology and Public Media","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Moral hazard; Business; Actuarial science; Economics; Microeconomics; Incentive","score_opus":0.009014750436122255,"score_gpt":0.27320424696399837,"score_spread":0.2641894965278761,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412189802","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8994367,0.0005173901,0.070807874,0.0044637243,0.0002343848,0.00034283343,0.00023338912,0.0006252363,0.023338549],"genre_scores_gemma":[0.9949189,0.000051391384,0.0035165902,0.00014497201,0.000047148722,0.00006424982,0.000046454596,0.00003499441,0.0011752341],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.97585005,0.012674641,0.0012218795,0.0021401078,0.0056144632,0.0024988225],"domain_scores_gemma":[0.8778925,0.07218516,0.020145584,0.0106660165,0.013926041,0.0051846234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.026117219,0.00075817964,0.00091150915,0.0014656403,0.0022247636,0.0048452187,0.0021272656,0.0018128641,0.011330707],"category_scores_gemma":[0.13262965,0.00069946615,0.00069646025,0.0008518087,0.0015818125,0.004781073,0.0037065782,0.0026145084,0.0017991567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024759858,0.0020719022,0.4705098,0.00084522105,0.00033649968,0.0008102855,0.011165895,0.029533774,0.010026939,0.033096176,0.012842823,0.4262847],"study_design_scores_gemma":[0.0003954038,0.005345712,0.56926125,0.0010093423,0.0004311016,0.0022399053,0.02201869,0.2797987,0.01150868,0.06725248,0.04019658,0.0005421406],"about_ca_topic_score_codex":0.0036282388,"about_ca_topic_score_gemma":0.0030882838,"teacher_disagreement_score":0.026117219,"about_ca_system_score_codex":0.0022536821,"about_ca_system_score_gemma":0.0026926605,"threshold_uncertainty_score":0.13812274},"labels":[],"label_agreement":null},{"id":"W4412209921","doi":"","title":"Exploring the extent of and motivations for using social media across the travel planning process.","year":2024,"lang":"en","type":"article","venue":"University of Southern Denmark Research Portal (University of Southern Denmark)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Innovation Cluster (Canada)","funders":"","keywords":"Social media; Process (computing); Advertising; Business; Marketing; Computer science; World Wide Web","score_opus":0.12826052199313667,"score_gpt":0.30392886001431124,"score_spread":0.17566833802117457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412209921","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9972511,0.000118725344,0.00028539132,0.00016972612,0.0000031974569,0.000025939506,0.0000402056,0.000005687453,0.0021000486],"genre_scores_gemma":[0.99901855,0.00009301375,0.000348559,0.000024121066,0.0000020235032,0.000018111798,0.000034813525,0.000002290414,0.00045847968],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99907565,0.00049175747,0.0000442656,0.000066616776,0.00016407108,0.00015754429],"domain_scores_gemma":[0.9937186,0.0037212716,0.0013686053,0.00018339156,0.0004026616,0.00060552964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013941015,0.00019042876,0.00012023182,0.0010427872,0.00096765,0.0022662263,0.0004081437,0.00053828413,0.002523285],"category_scores_gemma":[0.008129444,0.00022923901,0.00023186962,0.00074331916,0.0006793688,0.0015510471,0.0015058712,0.0006265312,0.00024674],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029782686,0.00054538855,0.6860113,0.00068713975,0.0001420207,0.0010961916,0.20947535,0.00044761502,0.0042711883,0.0016098825,0.001276812,0.09413927],"study_design_scores_gemma":[0.0000089471505,0.00029889337,0.52037615,0.00019563192,0.00006155948,0.00068469986,0.46570918,0.00091973715,0.0010144745,0.00062025833,0.010065686,0.00004470061],"about_ca_topic_score_codex":0.005502454,"about_ca_topic_score_gemma":0.01236166,"teacher_disagreement_score":0.005502454,"about_ca_system_score_codex":0.0006095251,"about_ca_system_score_gemma":0.0010416459,"threshold_uncertainty_score":0.01094085},"labels":[],"label_agreement":null},{"id":"W4412393454","doi":"10.1155/atr/5516034","title":"Exploring Commuter’s Preferences and Future Intentions to Use Ride‐Sharing: A Case Study From a Developing Country","year":2025,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Qatar National Library","keywords":"Developing country; Transport engineering; Business; Advertising; Marketing; Economics; Engineering; Economic growth","score_opus":0.06868284251314048,"score_gpt":0.2933144608455418,"score_spread":0.2246316183324013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412393454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99962103,0.000022222092,0.000050907347,0.00003361133,7.97882e-7,0.000009765255,0.000021696596,3.8098977e-7,0.00023948644],"genre_scores_gemma":[0.9989343,0.00024706038,0.00026066942,0.00004474703,0.0000021104338,0.000020395897,0.000036225985,0.0000015835359,0.00045288377],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996138,0.000152179,0.000025785317,0.00004958201,0.000039591232,0.00011919428],"domain_scores_gemma":[0.99902785,0.00041258358,0.00020659273,0.000055296805,0.00012425809,0.00017342137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092919904,0.00031255087,0.0003916337,0.0008517316,0.0026791056,0.0011064537,0.0005086474,0.0007144487,0.0022251161],"category_scores_gemma":[0.0016026405,0.0004412767,0.00043852607,0.0010370155,0.0008343955,0.0010199754,0.0009683444,0.00096337666,0.00029258625],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000095198004,0.0010194352,0.7590398,0.0002128282,0.000039603976,0.022538874,0.20169123,0.00025107083,0.0013615699,0.00045920457,0.0004436592,0.012847583],"study_design_scores_gemma":[0.000011787401,0.0007146836,0.36149803,0.00012304125,0.00005764639,0.0074588805,0.6256885,0.00072651304,0.0006282005,0.00014356953,0.002892781,0.00005643402],"about_ca_topic_score_codex":0.030095521,"about_ca_topic_score_gemma":0.05454457,"teacher_disagreement_score":0.030095521,"about_ca_system_score_codex":0.0009168639,"about_ca_system_score_gemma":0.0009647318,"threshold_uncertainty_score":0.05984068},"labels":[],"label_agreement":null},{"id":"W4412404326","doi":"10.1109/tvt.2025.3589019","title":"KLOTSKI: Towards Consensus Enabled Collaborative Vehicles in Intelligent Transportation","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Intelligent transportation system; Transport engineering; Computer science; Systems engineering; Engineering","score_opus":0.007530128440758633,"score_gpt":0.23800386106761875,"score_spread":0.23047373262686013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412404326","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015174092,0.00038578382,0.97127444,0.0006203833,0.00014412017,0.00023209263,0.00009400563,0.0023399382,0.009735134],"genre_scores_gemma":[0.42475858,0.00089185237,0.5471539,0.00035621008,0.000077485216,0.0005396836,0.000502572,0.0003030823,0.025416672],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990233,0.00026439095,0.000071396826,0.00019408262,0.0003163012,0.00013040757],"domain_scores_gemma":[0.99932027,0.00015413313,0.0000645129,0.00014002057,0.00017912559,0.00014186416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015631373,0.000772511,0.0005753658,0.0006392027,0.0011638225,0.00224077,0.0019731545,0.0013643418,0.0030439529],"category_scores_gemma":[0.0024540501,0.00045020334,0.0005916672,0.000584071,0.0014825983,0.003059374,0.003507846,0.001723824,0.0016939879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041824376,0.00023951239,0.0009677756,0.00042744042,0.000080364014,0.00046330082,0.0009913911,0.44133645,0.030432172,0.3543486,0.013399497,0.15689532],"study_design_scores_gemma":[0.0000870902,0.00014495592,0.0002487349,0.000049945542,0.00003115902,0.000089718684,0.00026211428,0.85039926,0.015692059,0.07810875,0.054836247,0.00005002319],"about_ca_topic_score_codex":0.008076197,"about_ca_topic_score_gemma":0.007011132,"teacher_disagreement_score":0.008076197,"about_ca_system_score_codex":0.0016338619,"about_ca_system_score_gemma":0.0034351659,"threshold_uncertainty_score":0.016058385},"labels":[],"label_agreement":null},{"id":"W4412408588","doi":"10.1080/10447318.2025.2526596","title":"Examining the Adoption of Autonomous Vehicles in China, Considering Factors Related to Human Behavior, Automation, and the Environment","year":2025,"lang":"en","type":"article","venue":"International Journal of Human-Computer Interaction","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Fundamental Research Funds for Central Universities of the Central South University; Hunan Provincial Innovation Foundation for Postgraduate; National Natural Science Foundation of China","keywords":"China; Automation; Computer science; Business; Engineering; Geography","score_opus":0.017612075361574116,"score_gpt":0.27729762348540354,"score_spread":0.25968554812382943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412408588","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994696,0.000060336075,0.00007538557,0.000052273266,0.0000014107109,0.000006242586,0.00004650456,0.0000010452385,0.0002872706],"genre_scores_gemma":[0.99959046,0.00007467603,0.00006060665,0.000016026926,0.000001778012,0.0000053262306,0.00006867849,4.3877463e-7,0.00018195255],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994272,0.00011658906,0.000065486354,0.00009918537,0.00016146348,0.00013012864],"domain_scores_gemma":[0.99826556,0.00039126686,0.00065170485,0.00007708798,0.0003646801,0.0002498613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012713495,0.00029716836,0.0002011495,0.0012334496,0.00066389155,0.00067150564,0.00030500532,0.00031655218,0.00105378],"category_scores_gemma":[0.0021692552,0.00019865851,0.00043343334,0.0015841555,0.000403703,0.0007084926,0.0005428112,0.0003096608,0.00010108712],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000140146485,0.00004471747,0.99259466,0.000025373765,0.00002144553,0.00008517732,0.0012568175,0.00022086469,0.00021582413,0.00011247568,0.000068916364,0.005339628],"study_design_scores_gemma":[0.0000015354984,0.00005236581,0.99658823,0.000008366792,0.000013112619,0.000032764186,0.0019321501,0.0010142814,0.00006495983,0.0000434887,0.00024373496,0.000004895951],"about_ca_topic_score_codex":0.07922154,"about_ca_topic_score_gemma":0.104269095,"teacher_disagreement_score":0.07922154,"about_ca_system_score_codex":0.0013994063,"about_ca_system_score_gemma":0.0021571931,"threshold_uncertainty_score":0.15752083},"labels":[],"label_agreement":null},{"id":"W4412430448","doi":"10.1016/j.knosys.2025.114106","title":"A hybrid genetic algorithm for the vehicle relocation problem with ride-sharing options in one-way car-sharing systems","year":2025,"lang":"en","type":"article","venue":"Knowledge-Based Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Anhui Normal University; Anhui Provincial Department of Education; National Natural Science Foundation of China","keywords":"Relocation; Genetic algorithm; Car sharing; Computer science; Algorithm; Mathematical optimization; Engineering; Transport engineering; Mathematics; Machine learning; Operating system","score_opus":0.020818445742256532,"score_gpt":0.2421968920053268,"score_spread":0.22137844626307027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412430448","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.054742653,0.00051480083,0.9372737,0.00026791292,0.000054304288,0.0001468249,0.000071030554,0.00027993723,0.0066488227],"genre_scores_gemma":[0.6164065,0.00038599005,0.3780073,0.0002046654,0.0000462533,0.00048345185,0.00020396842,0.000073796626,0.0041881567],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996611,0.00011781321,0.000013418702,0.00006548838,0.00007371803,0.00006841531],"domain_scores_gemma":[0.99955374,0.0002912396,0.000043043594,0.000015315658,0.000066114226,0.000030576724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008299312,0.0009683149,0.0010635752,0.0009867807,0.00057145295,0.0009447312,0.0015044407,0.0016823066,0.0021149535],"category_scores_gemma":[0.0015253687,0.0004931053,0.0007813296,0.0010894419,0.00062140374,0.0007535575,0.00089494855,0.0008593402,0.00023403182],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021808733,0.000027076698,0.00024608828,0.00002245994,0.000020743108,0.000034033994,0.000024366645,0.9816483,0.00029759938,0.002740456,0.0002701875,0.014646811],"study_design_scores_gemma":[0.000015587499,0.00001991169,0.000038258655,0.000004043793,0.0000059367107,0.000008252973,0.000009589132,0.99845624,0.00007696554,0.0011300294,0.0002320362,0.0000031281822],"about_ca_topic_score_codex":0.013229624,"about_ca_topic_score_gemma":0.009215302,"teacher_disagreement_score":0.013229624,"about_ca_system_score_codex":0.0010486301,"about_ca_system_score_gemma":0.0017136974,"threshold_uncertainty_score":0.026305258},"labels":[],"label_agreement":null},{"id":"W4412486350","doi":"10.1139/dsa-2024-0068","title":"Framework for truck–RPAS hybrid models in last-mile delivery","year":2025,"lang":"en","type":"article","venue":"Drone Systems and Applications","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Truck; Mile; Last mile (transportation); Environmental science; Computer science; Transport engineering; Engineering; Automotive engineering; Geography","score_opus":0.013233469041325269,"score_gpt":0.24541882973730042,"score_spread":0.23218536069597515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412486350","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01158286,0.00033185116,0.9723762,0.00031700553,0.00006811118,0.00010294853,0.00016907202,0.00021669026,0.014835253],"genre_scores_gemma":[0.7648914,0.0010481144,0.20735313,0.0002814491,0.00008915533,0.0009285371,0.00056543876,0.00024631582,0.024596501],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996946,0.00010987529,0.000011252387,0.0000505986,0.00007946161,0.00005422492],"domain_scores_gemma":[0.9996954,0.00014830356,0.00003794719,0.000019333089,0.00007362157,0.000025478772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072674407,0.0010732189,0.0007459941,0.0006715655,0.00055977254,0.0012562703,0.0016812835,0.0013319365,0.0043699355],"category_scores_gemma":[0.0010778604,0.00054092443,0.0012524305,0.00060718495,0.00062143424,0.0008580949,0.0012595688,0.0013305766,0.0006123859],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004909487,0.000008732897,0.00006378218,0.000010854221,0.0000075176026,0.000016518858,0.000008283508,0.9903437,0.0001443154,0.0078147035,0.00022042605,0.0013562388],"study_design_scores_gemma":[0.0000017565685,0.0000048408965,0.000012121028,0.0000021883336,0.000001868558,0.000002466005,0.0000046034233,0.9979873,0.00003192083,0.0015331698,0.00041627808,0.0000015366747],"about_ca_topic_score_codex":0.016349314,"about_ca_topic_score_gemma":0.010895162,"teacher_disagreement_score":0.016349314,"about_ca_system_score_codex":0.0012297537,"about_ca_system_score_gemma":0.0017017032,"threshold_uncertainty_score":0.032508314},"labels":[],"label_agreement":null},{"id":"W4412686285","doi":"10.1016/j.jclepro.2025.146252","title":"Greenhouse gas emissions trends and fleet renewal of ride-hailing in Toronto, Canada","year":2025,"lang":"en","type":"article","venue":"Journal of Cleaner Production","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Hudbay Minerals (Canada); Street Contxt (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Greenhouse gas; Environmental science; Business; Engineering; Oceanography","score_opus":0.006156641479640977,"score_gpt":0.23523361324897335,"score_spread":0.22907697176933237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412686285","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9742672,0.0013322431,0.00023468226,0.00036283102,0.000012650654,0.00002296972,0.01885316,0.000035677993,0.0048785643],"genre_scores_gemma":[0.99129885,0.00065707724,0.00014622249,0.00003871873,0.0000037614311,0.000009611336,0.0054112077,0.0000061589094,0.0024284099],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99963856,0.000014883542,0.000023972701,0.000057828263,0.00014784395,0.000116861425],"domain_scores_gemma":[0.9985421,0.00007089668,0.00030390747,0.000038485912,0.00077309756,0.00027148332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025565104,0.00029103912,0.00020345607,0.0015950447,0.00089856377,0.0011289261,0.00058197463,0.0003002895,0.0020546683],"category_scores_gemma":[0.0010661738,0.00019784698,0.00046643327,0.0039184773,0.00035779038,0.00050260324,0.0005602303,0.0003821795,0.0002544357],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007757485,0.000016380167,0.98388875,0.00010020529,0.0000782178,0.00023830424,0.0015945197,0.0013918895,0.00074307265,0.0003283434,0.002645556,0.0088971155],"study_design_scores_gemma":[8.861274e-7,0.000008591045,0.99621177,0.000016178663,0.00000943181,0.000036081834,0.0010132022,0.0004265145,0.000068154026,0.000010396941,0.0021913697,0.000007427695],"about_ca_topic_score_codex":0.98922694,"about_ca_topic_score_gemma":0.9941466,"teacher_disagreement_score":0.019773053,"about_ca_system_score_codex":0.019773053,"about_ca_system_score_gemma":0.010471492,"threshold_uncertainty_score":0.14346421},"labels":[],"label_agreement":null},{"id":"W4412691658","doi":"10.63682/jns.v14i32s.8501","title":"Surrogacy Explored: The Impact on Carriers and Their Experiences Internationally","year":2025,"lang":"en","type":"article","venue":"Journal of Neonatal Surgery","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Environmental planning; Environmental science","score_opus":0.013423873026064594,"score_gpt":0.2531761682038494,"score_spread":0.23975229517778482,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412691658","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9765694,0.0013551153,0.00036409288,0.004783536,0.00013259421,0.000019514682,0.00003357988,0.0000067881074,0.016735403],"genre_scores_gemma":[0.994787,0.00091963395,0.00014236188,0.0005166918,0.000021608277,0.00001125861,0.00001809973,0.000007123133,0.0035762666],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9974367,0.0016537486,0.00007690015,0.00012425972,0.00033033098,0.00037805294],"domain_scores_gemma":[0.99718314,0.0010665383,0.00052496383,0.00011490515,0.00019269364,0.00091770187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037349695,0.00019643552,0.0003143849,0.0006995722,0.004773063,0.004038716,0.00050007174,0.0010343057,0.005379932],"category_scores_gemma":[0.00897935,0.00018483285,0.00025625894,0.00075812114,0.005500884,0.002494895,0.006785737,0.0020496177,0.00030041064],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011043397,0.00010289083,0.07508339,0.000059225313,0.000016020089,0.0041944864,0.8581044,0.00008736946,0.00068792683,0.013892549,0.002993015,0.044668283],"study_design_scores_gemma":[0.000008292155,0.00016690267,0.019387843,0.00023630344,0.000016922466,0.0036033604,0.9311967,0.000090646194,0.00018822314,0.001608849,0.043460317,0.000035726225],"about_ca_topic_score_codex":0.008180184,"about_ca_topic_score_gemma":0.0106708435,"teacher_disagreement_score":0.008180184,"about_ca_system_score_codex":0.0022302056,"about_ca_system_score_gemma":0.0033806264,"threshold_uncertainty_score":0.019752681},"labels":[],"label_agreement":null},{"id":"W4412754835","doi":"10.11159/iccste25.295","title":"Spatiotemporal Analysis of Chicago Ridesharing Demand using Modified Spatial Error Model","year":2025,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Civil, Structural and Transportation Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.02529613741503851,"score_gpt":0.2547457160886655,"score_spread":0.22944957867362697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412754835","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9870134,0.00007618999,0.009549642,0.00012447232,0.000013708594,0.000027676757,0.0022721512,0.00012894349,0.00079370296],"genre_scores_gemma":[0.9928617,0.00004849099,0.0036919778,0.000011377259,0.000005852112,0.00004501811,0.0028028737,0.000013535953,0.00051923806],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99924386,0.00030286203,0.00006139581,0.0001994233,0.000105594125,0.0000870334],"domain_scores_gemma":[0.9978035,0.0011883372,0.0003021663,0.00021012488,0.00042201712,0.00007387601],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013476695,0.00043700167,0.0003536422,0.0015806457,0.00021509435,0.00077503204,0.00074437185,0.00043016102,0.0018509686],"category_scores_gemma":[0.0038840834,0.0001816393,0.0008273803,0.0022388392,0.0003332184,0.0005714295,0.0006684293,0.00041950072,0.00024137682],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032563883,0.00017864563,0.662172,0.00009291872,0.0002565588,0.00033296423,0.00044300855,0.31305602,0.0013334844,0.0032699986,0.0021628896,0.016375968],"study_design_scores_gemma":[0.000009700873,0.000093150906,0.101133406,0.000012670073,0.000041977033,0.000063825195,0.00047968247,0.89604235,0.0004149291,0.0007362728,0.00094390375,0.000028158807],"about_ca_topic_score_codex":0.0774994,"about_ca_topic_score_gemma":0.054123484,"teacher_disagreement_score":0.0774994,"about_ca_system_score_codex":0.0010538012,"about_ca_system_score_gemma":0.00075015594,"threshold_uncertainty_score":0.1540966},"labels":[],"label_agreement":null},{"id":"W4412754882","doi":"10.11159/iccste25.275","title":"Design of a circular express route with limited stops derived from a conventional route for the BRS system","year":2025,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Civil, Structural and Transportation Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.017372152532257653,"score_gpt":0.21300667803157694,"score_spread":0.19563452549931928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412754882","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27529663,0.00038357585,0.69204676,0.00028129108,0.00019723413,0.00048830203,0.00053729676,0.0022495198,0.028519375],"genre_scores_gemma":[0.8755346,0.00015283971,0.11753761,0.00003848762,0.000015228573,0.00017750831,0.000336405,0.00010050734,0.006106809],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997056,0.00009670229,0.000013386565,0.00006719786,0.000060499344,0.000056570367],"domain_scores_gemma":[0.99976045,0.000027108934,0.000034728255,0.000038702725,0.000097506534,0.000041515865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026417614,0.0006357551,0.00042576485,0.0005048934,0.0005783695,0.00081351853,0.0009512378,0.0005186766,0.0037615376],"category_scores_gemma":[0.00040213738,0.00028057292,0.0006170089,0.00031223873,0.0003477759,0.00040621264,0.0005500548,0.00032024848,0.0010375343],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006410691,0.00022144307,0.004677208,0.00031766665,0.000093650866,0.0006270075,0.00030213333,0.8345353,0.057587076,0.014205293,0.002973383,0.083818786],"study_design_scores_gemma":[0.00009530209,0.00073919044,0.0015272894,0.00002402107,0.00010075598,0.00029006973,0.00020574144,0.9727951,0.008983567,0.0013184006,0.0138750505,0.000045565113],"about_ca_topic_score_codex":0.006131914,"about_ca_topic_score_gemma":0.0065723457,"teacher_disagreement_score":0.006131914,"about_ca_system_score_codex":0.00055745774,"about_ca_system_score_gemma":0.00119466,"threshold_uncertainty_score":0.012583554},"labels":[],"label_agreement":null},{"id":"W4412976168","doi":"10.1007/978-981-96-7441-1_22","title":"HR Management for the Next Generation of Smart Mobility","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in electrical engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Canada West","funders":"","keywords":"Computer science","score_opus":0.022873266186821176,"score_gpt":0.22567061784342035,"score_spread":0.20279735165659918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412976168","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019672617,0.042532362,0.13732865,0.08035484,0.009370188,0.00021293598,0.00089001964,0.002240815,0.7073975],"genre_scores_gemma":[0.27756765,0.03047128,0.047851942,0.0085747475,0.004190796,0.0001716549,0.00096581905,0.00020384329,0.63000226],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99969304,0.000060369366,0.0000100045145,0.000038492515,0.00012550323,0.000072652874],"domain_scores_gemma":[0.99963963,0.00006995573,0.000035627403,0.000048964284,0.00007790822,0.00012789913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075343036,0.00027213385,0.00021978881,0.0003027372,0.0005722506,0.0027963612,0.0008118396,0.0013161985,0.0327194],"category_scores_gemma":[0.0007657537,0.000109284716,0.00024100795,0.0005267105,0.00045874037,0.0026057,0.0013922866,0.0011451332,0.005374607],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043740565,0.000091226226,0.0009309522,0.0002456528,0.000014404051,0.000090750014,0.00050742994,0.0025137556,0.0016781176,0.14497767,0.28384554,0.5650608],"study_design_scores_gemma":[0.0000099502895,0.00007528324,0.0027185737,0.0002923107,0.000013584075,0.00015051804,0.0010568035,0.0069221724,0.0006861763,0.04486891,0.9431836,0.000022072209],"about_ca_topic_score_codex":0.0030650832,"about_ca_topic_score_gemma":0.0038445573,"teacher_disagreement_score":0.0327194,"about_ca_system_score_codex":0.000902331,"about_ca_system_score_gemma":0.001682587,"threshold_uncertainty_score":0.109457314},"labels":[],"label_agreement":null},{"id":"W4412992603","doi":"10.31387/oscm0620481","title":"Truck-Sharing Constraints: Two Case Studies","year":2025,"lang":"en","type":"article","venue":"Operations and Supply Chain Management An International Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Truck; Computer science; Business; Engineering; Automotive engineering","score_opus":0.016130464304999703,"score_gpt":0.30985558179781636,"score_spread":0.29372511749281666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412992603","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9103789,0.0004693158,0.0250744,0.0011767303,0.000059853566,0.0011304747,0.00065552763,0.000039654205,0.0610152],"genre_scores_gemma":[0.9712099,0.0007855167,0.017272176,0.00013235914,0.000015854548,0.00054813514,0.00033130837,0.000021992324,0.009682842],"study_design_codex":"simulation_or_modeling","study_design_gemma":"qualitative","domain_scores_codex":[0.9962059,0.00218615,0.00016120743,0.00021103557,0.0006384576,0.0005972146],"domain_scores_gemma":[0.9851361,0.011820121,0.0007690072,0.00063826545,0.0009878025,0.00064881396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036759428,0.00078525575,0.0005003227,0.0014035894,0.0033367008,0.002713381,0.002285346,0.004606018,0.00904586],"category_scores_gemma":[0.009504311,0.00050699705,0.0009485494,0.003370642,0.0016838883,0.0032408147,0.0022192101,0.0020614746,0.0004479666],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022994087,0.010641993,0.06420139,0.002528971,0.0003346472,0.0798685,0.042299043,0.42103183,0.006384884,0.2589926,0.017298054,0.09411873],"study_design_scores_gemma":[0.0010646852,0.0031078868,0.03834683,0.0012236906,0.00033429282,0.0150883645,0.2791715,0.39649698,0.018980732,0.062162597,0.18353325,0.0004892529],"about_ca_topic_score_codex":0.02628584,"about_ca_topic_score_gemma":0.03529911,"teacher_disagreement_score":0.02628584,"about_ca_system_score_codex":0.003815777,"about_ca_system_score_gemma":0.002624496,"threshold_uncertainty_score":0.052265644},"labels":[],"label_agreement":null},{"id":"W4413005174","doi":"10.1080/03155986.2025.2541148","title":"Collaboration between carrier companies using truck platooning: an application in the forestry industry","year":2025,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université de Montréal; Université Laval; Center for Interuniversity Research and Analysis on Organizations","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Truck; Business; Forestry; Engineering; Automotive engineering","score_opus":0.0634636556856399,"score_gpt":0.36968737436016397,"score_spread":0.3062237186745241,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413005174","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8362075,0.000991233,0.14220053,0.0013199323,0.00005650615,0.0004268895,0.00012527652,0.00014513287,0.018527059],"genre_scores_gemma":[0.9638338,0.00040394833,0.03387003,0.000042173684,0.000017459704,0.000059595244,0.00005081173,0.000011631614,0.0017104567],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99811894,0.0011030539,0.00003622145,0.00016376539,0.00029457395,0.0002834171],"domain_scores_gemma":[0.993543,0.004804723,0.00037552597,0.0002747711,0.0004421774,0.00055975356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025881268,0.00076795224,0.00070983375,0.0009707928,0.002064963,0.0012741011,0.001150683,0.0020971678,0.0038190337],"category_scores_gemma":[0.0037629446,0.0002827626,0.0008331005,0.0021096205,0.00079352263,0.0025616528,0.0016482405,0.0008967513,0.0001952883],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00077832653,0.002352833,0.015146303,0.00035212314,0.00022591958,0.0031029982,0.0011792685,0.823803,0.0047038803,0.038513914,0.0018923898,0.10794909],"study_design_scores_gemma":[0.00021279819,0.0009669509,0.005245825,0.000056157773,0.00012515725,0.0004950597,0.003032513,0.96205074,0.0033073912,0.018871685,0.0055730348,0.00006261812],"about_ca_topic_score_codex":0.017439371,"about_ca_topic_score_gemma":0.017837616,"teacher_disagreement_score":0.017439371,"about_ca_system_score_codex":0.0022692052,"about_ca_system_score_gemma":0.0024541155,"threshold_uncertainty_score":0.034675717},"labels":[],"label_agreement":null},{"id":"W4413071331","doi":"10.1007/978-3-031-98740-3_30","title":"Exact Set Packing in Multimodal Transportation with Ridesharing System for First/Last Mile","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Mile; Last mile (transportation); Set (abstract data type); Programming language; Geography","score_opus":0.012285131425248657,"score_gpt":0.2248702768440449,"score_spread":0.21258514541879625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413071331","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18200512,0.0018983256,0.7871224,0.0005281771,0.00035510183,0.000247664,0.0012143977,0.002327456,0.024301346],"genre_scores_gemma":[0.7890555,0.0006337572,0.19587743,0.00012393662,0.00013860891,0.00012451001,0.0011448844,0.00028849594,0.012612768],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992612,0.000127128,0.00003261858,0.00017278365,0.00015248598,0.00025381037],"domain_scores_gemma":[0.99944705,0.00022011045,0.000038447095,0.00014125463,0.00008957146,0.00006353786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045003428,0.00103778,0.002576571,0.0007853777,0.0013164135,0.0018402936,0.0019002,0.0011784503,0.009712314],"category_scores_gemma":[0.0013494529,0.0007654692,0.0011351602,0.0017935358,0.0005631673,0.002462213,0.0017214426,0.00095268,0.00093423284],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065732445,0.00021837604,0.00089946593,0.0002791047,0.00007520025,0.0002398817,0.00015091049,0.8147202,0.0035789218,0.021327842,0.016087733,0.1417651],"study_design_scores_gemma":[0.0000117477775,0.00006009223,0.00022013023,0.000008252566,0.000014866367,0.00006186804,0.000049579045,0.98680437,0.0004924189,0.011180267,0.001085684,0.000010737109],"about_ca_topic_score_codex":0.012621627,"about_ca_topic_score_gemma":0.008018442,"teacher_disagreement_score":0.012621627,"about_ca_system_score_codex":0.0013477292,"about_ca_system_score_gemma":0.0013693548,"threshold_uncertainty_score":0.03249091},"labels":[],"label_agreement":null},{"id":"W4413276146","doi":"10.1016/j.trb.2025.103290","title":"Optimal matching for ridesharing systems with endogenous and flexible user participation","year":2025,"lang":"en","type":"article","venue":"Transportation Research Part B Methodological","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministry of Transportation of Ontario","funders":"","keywords":"Matching (statistics); Computer science; Mathematical optimization; Transport engineering; Operations research; Engineering; Mathematics; Statistics","score_opus":0.42553377902809314,"score_gpt":0.46038628323845443,"score_spread":0.03485250421036129,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413276146","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52309996,0.00033988964,0.46663758,0.00039901098,0.000039858536,0.0004995656,0.00026513878,0.0002816567,0.00843737],"genre_scores_gemma":[0.98060405,0.000099926954,0.01615461,0.00004068653,0.000008497526,0.000107180924,0.000062747815,0.00003079633,0.0028914963],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99751484,0.001068795,0.00010273513,0.00048233668,0.00015612796,0.0006751855],"domain_scores_gemma":[0.9953424,0.0029290174,0.000631407,0.00027438387,0.00032183705,0.00050104683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032218655,0.0011798779,0.0023368727,0.0009418847,0.0009965712,0.0024208492,0.0018793555,0.0019956725,0.005108761],"category_scores_gemma":[0.0102599505,0.0010855374,0.001039415,0.001067649,0.0016125622,0.002400937,0.0027366038,0.0011916186,0.00059335376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037819284,0.0002026049,0.0019907784,0.00010461381,0.00008259526,0.00022942646,0.0002251611,0.96422774,0.0028071236,0.018540174,0.0005686437,0.010642794],"study_design_scores_gemma":[0.000035362373,0.00013191548,0.000510542,0.000008111222,0.00002040126,0.000035678222,0.00015599308,0.9868978,0.00040879875,0.011465471,0.00031274115,0.000017043989],"about_ca_topic_score_codex":0.009562844,"about_ca_topic_score_gemma":0.005395186,"teacher_disagreement_score":0.009562844,"about_ca_system_score_codex":0.0021727,"about_ca_system_score_gemma":0.0014858942,"threshold_uncertainty_score":0.019014359},"labels":[],"label_agreement":null},{"id":"W4413510182","doi":"10.64628/aam.suh9hg9qm","title":"As people continue working from home, the monthly transit pass needs to change to remain worth it","year":2021,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Transit (satellite); Business; Transport engineering; Engineering; Public transport","score_opus":0.02185263033983309,"score_gpt":0.22401436902037924,"score_spread":0.20216173868054615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413510182","genre_codex":"other","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2104351,0.0037211846,0.03203899,0.2053334,0.014206021,0.00027713965,0.0007892738,0.003362036,0.5298369],"genre_scores_gemma":[0.41454455,0.004034696,0.02262323,0.022826921,0.0028311796,0.0002093125,0.00073313905,0.0008457634,0.53135127],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988086,0.00020924075,0.00004154506,0.00013530925,0.00056495494,0.00024029275],"domain_scores_gemma":[0.9966948,0.00022051984,0.00021725138,0.00022494579,0.0010036716,0.0016389231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011283547,0.00040496318,0.00035095445,0.0005502019,0.0032946279,0.005322841,0.0008559471,0.0014574447,0.055380207],"category_scores_gemma":[0.0031562168,0.00016267467,0.00045601022,0.00054197875,0.0015815503,0.0038931782,0.0024056595,0.0021740121,0.025928834],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001400012,0.0006445573,0.013885585,0.00039718847,0.00005395818,0.0004322024,0.008889179,0.00042543316,0.0059462674,0.026908252,0.43148732,0.51078993],"study_design_scores_gemma":[0.000019923033,0.00033341502,0.0182692,0.0002048537,0.00002993347,0.0005561734,0.026798459,0.00036531658,0.0007619198,0.008860358,0.9437513,0.000049149035],"about_ca_topic_score_codex":0.005463551,"about_ca_topic_score_gemma":0.012169122,"teacher_disagreement_score":0.055380207,"about_ca_system_score_codex":0.0011119626,"about_ca_system_score_gemma":0.0024293396,"threshold_uncertainty_score":0.18526524},"labels":[],"label_agreement":null},{"id":"W4413517174","doi":"10.64628/aam.tyrqyju3a","title":"Bike sharing isn’t just for rich hipsters – ‘super users’ have lower incomes","year":2019,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Business","score_opus":0.022311305723645924,"score_gpt":0.24734574629369224,"score_spread":0.22503444057004632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413517174","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8759829,0.000725388,0.0012505184,0.010988695,0.00036722684,0.000043205484,0.0012551553,0.000069611684,0.10931732],"genre_scores_gemma":[0.9651375,0.00048741585,0.0006041579,0.0025962945,0.000112421585,0.00006087736,0.0006634437,0.00005696559,0.030280842],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992047,0.0001621606,0.000029841362,0.00008101843,0.0001446016,0.00037770014],"domain_scores_gemma":[0.9979134,0.00023771799,0.0003176686,0.0001321158,0.000337459,0.001061678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054549624,0.00024243245,0.00034013283,0.00074648624,0.0025468464,0.0033395262,0.00037613016,0.0005685184,0.054218482],"category_scores_gemma":[0.0034014697,0.0002246677,0.000268731,0.001495993,0.0011725695,0.0023628394,0.0021746682,0.0014076494,0.0060618785],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046496157,0.00047219178,0.59855074,0.00035996875,0.00031083132,0.0007644281,0.028735671,0.0002663247,0.0024783586,0.040977217,0.122386076,0.20423324],"study_design_scores_gemma":[0.0000695681,0.00028740187,0.639735,0.00048427246,0.00017533357,0.0013242676,0.09139034,0.00036095263,0.0008958687,0.016260313,0.24891147,0.00010525709],"about_ca_topic_score_codex":0.01955243,"about_ca_topic_score_gemma":0.032661848,"teacher_disagreement_score":0.054218482,"about_ca_system_score_codex":0.00061658124,"about_ca_system_score_gemma":0.0009510208,"threshold_uncertainty_score":0.1813789},"labels":[],"label_agreement":null},{"id":"W4413549380","doi":"10.64628/aam.rjkteyxmj","title":"Self-driving cars will not fix our transportation woes","year":2020,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Self driving; Transport engineering; Business; Aeronautics; Engineering","score_opus":0.01293242977637952,"score_gpt":0.21290973758085802,"score_spread":0.1999773078044785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413549380","genre_codex":"other","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07397247,0.0045920764,0.0076699704,0.28452766,0.020365192,0.00007125103,0.0004196919,0.00071284705,0.6076689],"genre_scores_gemma":[0.44440016,0.005134212,0.0062482134,0.071163274,0.002255897,0.000099662175,0.0005428353,0.00043258216,0.46972325],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983475,0.0003050922,0.00006254699,0.00022110387,0.00066425133,0.00039942993],"domain_scores_gemma":[0.99565685,0.00041125654,0.00024759202,0.00044075883,0.0018518398,0.001391738],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019063397,0.00061035785,0.00026214233,0.0005992451,0.0032645885,0.005852937,0.00078360375,0.0031878976,0.04674485],"category_scores_gemma":[0.0061849537,0.0001749162,0.0005901215,0.00044109332,0.0030784837,0.004913284,0.0027076325,0.004019102,0.015272627],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015069096,0.0004909435,0.010358335,0.0002833525,0.00010578825,0.00030344256,0.0030616769,0.00059309433,0.003471741,0.37277347,0.433785,0.1746225],"study_design_scores_gemma":[0.0000133617505,0.00011660256,0.0044871457,0.0001861643,0.000041791187,0.0002397129,0.0036438042,0.0002447205,0.0011312576,0.024456087,0.96540725,0.000031979616],"about_ca_topic_score_codex":0.0045653246,"about_ca_topic_score_gemma":0.00909587,"teacher_disagreement_score":0.04674485,"about_ca_system_score_codex":0.0017784879,"about_ca_system_score_gemma":0.0026588787,"threshold_uncertainty_score":0.15637714},"labels":[],"label_agreement":null},{"id":"W4413584861","doi":"10.64628/aam.rngays3f9","title":"Using gaming tactics in apps raises new legal issues","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Internet privacy; Computer science; Business; Computer security","score_opus":0.07417376459140432,"score_gpt":0.3351515054733251,"score_spread":0.2609777408819208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413584861","genre_codex":"other","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06374772,0.0018257715,0.04967164,0.10290774,0.0012989548,0.00010776433,0.00035136845,0.00034879672,0.7797403],"genre_scores_gemma":[0.84182537,0.0014712325,0.023214791,0.01834924,0.0016599271,0.00028185904,0.00022165416,0.0005278818,0.11244804],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9860006,0.00403562,0.0005986903,0.001652508,0.006175861,0.0015368272],"domain_scores_gemma":[0.94045526,0.043681633,0.0015376289,0.0069310535,0.0062181754,0.0011762962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009823879,0.00057048886,0.00069965544,0.002253278,0.0069742105,0.014923269,0.002758766,0.011492402,0.03185165],"category_scores_gemma":[0.056620605,0.0007059809,0.0008509868,0.0017593438,0.010138577,0.018493406,0.0054098777,0.011472566,0.003731889],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014049228,0.00003211248,0.0009267722,0.000035471792,0.000006236603,0.00025233527,0.0024757779,0.00011570172,0.00021161298,0.96652144,0.011433097,0.017975288],"study_design_scores_gemma":[0.000025511212,0.000038336402,0.0026592636,0.00046769573,0.000046901227,0.00081785995,0.004927616,0.0030678555,0.0017790082,0.7942095,0.19189577,0.00006475227],"about_ca_topic_score_codex":0.008983263,"about_ca_topic_score_gemma":0.01176509,"teacher_disagreement_score":0.03185165,"about_ca_system_score_codex":0.0024466433,"about_ca_system_score_gemma":0.0035239644,"threshold_uncertainty_score":0.10655439},"labels":[],"label_agreement":null},{"id":"W4413604524","doi":"10.64628/aam.y9ytpvnwq","title":"Transportation apps can help people with disabilities navigate public transit but accessibility lags behind","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Public transport; Internet privacy; Transit (satellite); Business; Transport engineering; Advertising; Computer science; Engineering","score_opus":0.03834667657247814,"score_gpt":0.2567679256393412,"score_spread":0.21842124906686305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413604524","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3134976,0.0044236267,0.0834798,0.021016864,0.0035403138,0.0008211995,0.007684666,0.010461733,0.5550742],"genre_scores_gemma":[0.7447051,0.005745216,0.046868864,0.0022266032,0.0010313417,0.00068705645,0.004425936,0.0009324872,0.19337747],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997162,0.000066175635,0.00001242826,0.000033749926,0.00010738795,0.000064096515],"domain_scores_gemma":[0.99893004,0.00047044095,0.000057881036,0.000113644295,0.00032898496,0.000098952405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004167328,0.00077280693,0.0002379967,0.00094658224,0.00059613015,0.0022641767,0.0002974436,0.0011824421,0.057274755],"category_scores_gemma":[0.0041960725,0.00017128239,0.00046246382,0.00073414773,0.00029886974,0.0030048857,0.0017948261,0.00057515444,0.009954358],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054079806,0.00076953747,0.012997108,0.0011336528,0.00007772141,0.00092322554,0.0029936598,0.0008593682,0.0065163146,0.022226397,0.24136579,0.70959646],"study_design_scores_gemma":[0.00024916208,0.0008406551,0.044928405,0.0014945691,0.00061521446,0.001788053,0.010560384,0.011135676,0.011644829,0.088405125,0.82822096,0.000117025185],"about_ca_topic_score_codex":0.003194016,"about_ca_topic_score_gemma":0.0062132464,"teacher_disagreement_score":0.057274755,"about_ca_system_score_codex":0.0002167002,"about_ca_system_score_gemma":0.0006923467,"threshold_uncertainty_score":0.19160318},"labels":[],"label_agreement":null},{"id":"W4413626286","doi":"10.64628/aam.vmumkhna9","title":"Safety on the line: Drivers who juggle multiple jobs are more likely to take risks on the road","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Line (geometry); Business; Transport engineering; Operations management; Engineering; Mathematics","score_opus":0.051058486933987304,"score_gpt":0.27128145031644324,"score_spread":0.22022296338245595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413626286","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99368227,0.00026194245,0.00028524923,0.0020554452,0.000094942676,0.000017470351,0.00021204152,0.0000081330245,0.0033825457],"genre_scores_gemma":[0.9967738,0.00018156863,0.00014057805,0.00037340476,0.000078016215,0.000009178098,0.00019898915,0.000009177888,0.0022351926],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990257,0.00016712541,0.0000701686,0.00024002681,0.0002190736,0.00027791495],"domain_scores_gemma":[0.99385035,0.0008796249,0.00252027,0.00025493084,0.00074637495,0.0017483991],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007366384,0.0003767643,0.00037099654,0.0008672105,0.0015640343,0.0024521926,0.00066344,0.0019523472,0.017641116],"category_scores_gemma":[0.0070394455,0.00034567577,0.001131585,0.000815704,0.0004991181,0.0016761713,0.0011803168,0.0021383506,0.0018076565],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002203171,0.00038232777,0.9868493,0.000030016248,0.00009924667,0.00027402176,0.000814342,0.000071508555,0.00022465199,0.00020088033,0.0019273341,0.008906027],"study_design_scores_gemma":[0.000035746165,0.0003708326,0.9824889,0.00011417193,0.0002730317,0.0013619661,0.008555297,0.0008294117,0.00029603866,0.0015465291,0.004073563,0.00005448238],"about_ca_topic_score_codex":0.01629173,"about_ca_topic_score_gemma":0.016155222,"teacher_disagreement_score":0.017641116,"about_ca_system_score_codex":0.00043562893,"about_ca_system_score_gemma":0.0014187524,"threshold_uncertainty_score":0.059015453},"labels":[],"label_agreement":null},{"id":"W4413632901","doi":"10.64628/aam.kj4nktwqh","title":"Using smart devices to schedule on-demand public transportation can save time and money","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Schedule; Public transport; Business; Computer science; Transport engineering; Engineering; Operating system","score_opus":0.028191249752879895,"score_gpt":0.25511042051171784,"score_spread":0.22691917075883794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413632901","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19816975,0.0033725621,0.26265383,0.0077793137,0.0056791464,0.00047893287,0.0031634949,0.010862863,0.50784016],"genre_scores_gemma":[0.83079237,0.0026808956,0.047489982,0.0012834918,0.00057250034,0.00017203664,0.0018414563,0.0004524065,0.11471481],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997762,0.00003415909,0.0000099795025,0.000042829164,0.00009565464,0.000041126466],"domain_scores_gemma":[0.99949944,0.00010103517,0.00006933762,0.00010362012,0.00017533613,0.000051178995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018457818,0.0006386763,0.00020660146,0.0005615911,0.00041138195,0.0012267571,0.0007298844,0.00062208343,0.029662617],"category_scores_gemma":[0.0010024331,0.00019107043,0.00034812736,0.000833973,0.00023076839,0.0014361714,0.00070572196,0.0005113454,0.00909395],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040813,0.00054672116,0.010367038,0.00036868095,0.000092567265,0.000273919,0.00034079276,0.012817739,0.038700633,0.023172667,0.14445041,0.76846063],"study_design_scores_gemma":[0.00015504124,0.0007472061,0.025661409,0.0003044626,0.00024758017,0.0004897137,0.0021607066,0.062142365,0.047007423,0.030208506,0.8306956,0.00017995237],"about_ca_topic_score_codex":0.003013485,"about_ca_topic_score_gemma":0.006427533,"teacher_disagreement_score":0.029662617,"about_ca_system_score_codex":0.0004173285,"about_ca_system_score_gemma":0.00043928376,"threshold_uncertainty_score":0.0992313},"labels":[],"label_agreement":null},{"id":"W4413883065","doi":"10.1080/17450101.2025.2551692","title":"Putting the car in context: a call for a situated technopolitical transition in global automobilities","year":2025,"lang":"en","type":"article","venue":"Mobilities","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Kwantlen Polytechnic University","funders":"","keywords":"Situated; Context (archaeology); Transition (genetics); Sociology; Public relations; Political science; Computer science; Geography","score_opus":0.007026069600631776,"score_gpt":0.2469653231728883,"score_spread":0.23993925357225654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413883065","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43768173,0.0049380665,0.06870644,0.10306325,0.0006728633,0.0001463867,0.000050240495,0.00034064648,0.38440043],"genre_scores_gemma":[0.9926779,0.000592469,0.0029644773,0.00082461996,0.000035649427,0.000026508678,0.000006459388,0.000031793308,0.0028400663],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9965814,0.002042287,0.00006912839,0.00038311072,0.00036413677,0.0005599859],"domain_scores_gemma":[0.99714077,0.0013796405,0.00025312934,0.00055580883,0.00024069264,0.00043006422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048735025,0.00041526236,0.0003327175,0.0013040048,0.010127601,0.014486598,0.001304419,0.0028844567,0.004243197],"category_scores_gemma":[0.0039155376,0.00034474538,0.0004486157,0.0017569915,0.0656279,0.012558538,0.011901259,0.0051134797,0.0004910008],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020231531,0.000028884391,0.0020915954,0.00012257809,0.0000080756245,0.00051643053,0.18943305,0.00062544073,0.00067165337,0.78798664,0.0014972185,0.01699822],"study_design_scores_gemma":[0.0000098860555,0.00008638686,0.0035954195,0.00047744767,0.000019872654,0.00056917866,0.45735955,0.001045196,0.0011649288,0.3228427,0.21277231,0.000057113535],"about_ca_topic_score_codex":0.008035046,"about_ca_topic_score_gemma":0.017363034,"teacher_disagreement_score":0.014486598,"about_ca_system_score_codex":0.008399153,"about_ca_system_score_gemma":0.007846399,"threshold_uncertainty_score":0.060940444},"labels":[],"label_agreement":null},{"id":"W4413893301","doi":"10.1007/s44257-025-00039-0","title":"Agency specific insights into bus ridership determinants using a Bayesian framework","year":2025,"lang":"en","type":"article","venue":"Discover Analytics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Agency (philosophy); Bayesian probability; Computer science; Business; Transport engineering; Engineering; Artificial intelligence; Sociology","score_opus":0.022751809053307755,"score_gpt":0.28271422616895736,"score_spread":0.2599624171156496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413893301","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2658942,0.001192019,0.7164902,0.0028463446,0.00006075775,0.00025483742,0.0031631286,0.00027865768,0.009819851],"genre_scores_gemma":[0.92436564,0.0008895604,0.06963298,0.00017727069,0.000088473826,0.00023015827,0.0015302027,0.00004736395,0.003038324],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965425,0.002062118,0.00013748612,0.0006323315,0.0003863863,0.00023921177],"domain_scores_gemma":[0.98288304,0.0136932535,0.0012613757,0.0007625667,0.0010396253,0.00036016843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006820766,0.00055118685,0.0011506513,0.0030923777,0.0008012544,0.0024656493,0.0011319203,0.0010676378,0.005473784],"category_scores_gemma":[0.028546795,0.0008836826,0.0017767999,0.002611743,0.00092095224,0.0023871004,0.0017310212,0.0017321282,0.0005091082],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019797825,0.00054352824,0.28656006,0.00034632644,0.0009564414,0.0004712445,0.0027109652,0.3777374,0.0010318791,0.21667306,0.0075217425,0.10524935],"study_design_scores_gemma":[0.000033967604,0.00009684834,0.041047867,0.0002051226,0.0002863824,0.00013751724,0.0009680983,0.8243152,0.00029111875,0.12223677,0.01030645,0.00007476305],"about_ca_topic_score_codex":0.060496867,"about_ca_topic_score_gemma":0.06808143,"teacher_disagreement_score":0.060496867,"about_ca_system_score_codex":0.0013274349,"about_ca_system_score_gemma":0.0021864676,"threshold_uncertainty_score":0.120289445},"labels":[],"label_agreement":null},{"id":"W4413942131","doi":"10.1080/21650020.2025.2551837","title":"The ongoing evolution of EVTOLs: urban transport potential and the security dimension","year":2025,"lang":"en","type":"article","venue":"Urban Planning and Transport Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Dimension (graph theory); Mathematics","score_opus":0.01297450502661836,"score_gpt":0.2806117888514835,"score_spread":0.2676372838248652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413942131","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10104167,0.60971767,0.045706555,0.0458706,0.0037170548,0.000066838744,0.00063940306,0.00019455256,0.19304557],"genre_scores_gemma":[0.42073163,0.54784733,0.008848086,0.0022283357,0.0016289601,0.00006919457,0.00044307645,0.00007281034,0.018130552],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99965084,0.00009048885,0.000013919806,0.00005955517,0.00010558585,0.000079635276],"domain_scores_gemma":[0.9995402,0.00020130102,0.000061886894,0.000027691289,0.00012119664,0.000047843605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005532443,0.00042362968,0.00033683717,0.0008685949,0.0005050734,0.0030837334,0.0006164158,0.0010963508,0.006009882],"category_scores_gemma":[0.0006942645,0.0001722656,0.00034072806,0.0015451631,0.002042342,0.0040747616,0.0017601764,0.0012543603,0.0006850378],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000071935814,0.000037113172,0.0037224835,0.002636147,0.00004363165,0.00050292455,0.0010659227,0.009403116,0.0031685375,0.54337883,0.0141078355,0.42186156],"study_design_scores_gemma":[0.0000038265116,0.00013387905,0.0023057421,0.0012211003,0.00002447694,0.0007524975,0.0038164263,0.0026079458,0.0020237307,0.063853845,0.92322004,0.000036480204],"about_ca_topic_score_codex":0.0024219078,"about_ca_topic_score_gemma":0.003163715,"teacher_disagreement_score":0.006009882,"about_ca_system_score_codex":0.0015698846,"about_ca_system_score_gemma":0.0013774235,"threshold_uncertainty_score":0.020105064},"labels":[],"label_agreement":null},{"id":"W4413958753","doi":"10.5267/j.jpm.2025.8.007","title":"API-based dynamic programming model and optimization of vehicle routing: Cases of fluctuations in demand, traffic, capacity, and availability","year":2025,"lang":"en","type":"article","venue":"Journal of Project Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Dynamic programming; Routing (electronic design automation); Computer science; Vehicle routing problem; On demand; Computer network; Algorithm","score_opus":0.016698694146787072,"score_gpt":0.2610771206123618,"score_spread":0.24437842646557476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413958753","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13602589,0.00051178737,0.8318574,0.0010546407,0.0001299989,0.00013209054,0.00092929637,0.0004017879,0.028957104],"genre_scores_gemma":[0.9424494,0.00036662663,0.043759383,0.00009367305,0.000035245987,0.00024995304,0.0003989331,0.000091885086,0.012554897],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940896,0.00023601146,0.000020930733,0.00010163347,0.000096356234,0.000136059],"domain_scores_gemma":[0.9990802,0.00058456976,0.00010238811,0.00002679153,0.00015656784,0.000049359565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001106925,0.0009835656,0.0010866274,0.0007269778,0.00054663746,0.0019016303,0.0013666612,0.0013022728,0.0030656324],"category_scores_gemma":[0.0020117268,0.0006201675,0.0010188688,0.001349395,0.0007193177,0.0009763649,0.0009661402,0.0017527329,0.00028714247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017488263,0.000012201638,0.00017544765,0.000012634712,0.000007176216,0.000034179313,0.000012812963,0.9946203,0.00010101675,0.003606359,0.00017780466,0.0012226064],"study_design_scores_gemma":[0.0000012013858,0.0000046916543,0.000040076433,8.929576e-7,0.0000013105451,0.0000028604852,0.0000059532977,0.9992884,0.00001985131,0.0005573784,0.00007606731,0.0000013402619],"about_ca_topic_score_codex":0.029569216,"about_ca_topic_score_gemma":0.017869221,"teacher_disagreement_score":0.029569216,"about_ca_system_score_codex":0.0016193026,"about_ca_system_score_gemma":0.0015970574,"threshold_uncertainty_score":0.0587942},"labels":[],"label_agreement":null},{"id":"W4414033356","doi":"10.1080/21680566.2025.2551913","title":"An enhanced approximate dynamic programming approach to on-demand ride-Pooling","year":2025,"lang":"en","type":"article","venue":"Transportmetrica B Transport Dynamics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Pooling; Dynamic programming; Computer science; On demand; Computer security; Artificial intelligence; Algorithm; Multimedia","score_opus":0.007258102807373965,"score_gpt":0.24661696842520117,"score_spread":0.2393588656178272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414033356","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020433621,0.00064306706,0.9720035,0.00044865796,0.00007558766,0.00008111469,0.00030687777,0.00035333645,0.0056542726],"genre_scores_gemma":[0.8019446,0.00068596925,0.18802294,0.00035097028,0.00010191201,0.00031488956,0.0006753027,0.0002019525,0.0077013983],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992237,0.0002998573,0.00003648716,0.00016126764,0.00013834768,0.00014042706],"domain_scores_gemma":[0.99839216,0.0011144173,0.000111418405,0.00007406651,0.00023106694,0.00007695568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016702047,0.0012917405,0.0018719576,0.0006298117,0.00043593798,0.0018173081,0.0019723845,0.001625792,0.0042825677],"category_scores_gemma":[0.0043672104,0.0008586903,0.0010666562,0.0012592407,0.00071375247,0.0015898432,0.001413886,0.0019746237,0.00043744783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022319675,0.000017990587,0.00015364152,0.00002997186,0.000015152251,0.000024265079,0.000015378802,0.98858833,0.00011258559,0.0034150262,0.00045367843,0.007151672],"study_design_scores_gemma":[0.0000024357519,0.000007048539,0.000018828863,0.0000024193816,0.0000022330453,0.000003014578,0.000003819381,0.99821043,0.000029139195,0.0015454856,0.00017381374,0.0000014295305],"about_ca_topic_score_codex":0.02031383,"about_ca_topic_score_gemma":0.012914605,"teacher_disagreement_score":0.02031383,"about_ca_system_score_codex":0.001509711,"about_ca_system_score_gemma":0.0018296386,"threshold_uncertainty_score":0.040391207},"labels":[],"label_agreement":null},{"id":"W4414052208","doi":"10.2139/ssrn.5414574","title":"A Systematic Literature Review on Skyline Operator in Decision Support System: A Taxi Dispatch Perspective","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Saint Mary's University","funders":"","keywords":"Skyline; Decision support system; Systematic review; Perspective (graphical); Operator (biology); Multiple-criteria decision analysis","score_opus":0.005193579623833253,"score_gpt":0.26278204242610653,"score_spread":0.25758846280227327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414052208","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016017858,0.9958813,0.00029042567,0.0010045251,0.00021128473,0.0002493199,0.00032908347,0.000005004537,0.00042724467],"genre_scores_gemma":[0.027146598,0.9684946,0.0015201462,0.0017588604,0.00018470039,0.0005002823,0.00025664468,0.0000067780984,0.00013143542],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.98160166,0.007416643,0.0067588966,0.0013973068,0.0022890219,0.0005365077],"domain_scores_gemma":[0.9043565,0.07790721,0.009582873,0.0009959543,0.0061696866,0.0009877454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020144943,0.0013871521,0.006171986,0.02061937,0.0009916051,0.0052071987,0.0018075231,0.003743494,0.0047071124],"category_scores_gemma":[0.08392654,0.0012131857,0.005802964,0.01703697,0.0018092782,0.004320891,0.0024909119,0.0023902797,0.00037891144],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025290865,0.000041635056,0.001580312,0.93668365,0.007114942,0.00017402225,0.00056082284,0.00018677129,0.00021668019,0.0008303072,0.00207327,0.05028465],"study_design_scores_gemma":[0.000182271,0.00023499965,0.0033528223,0.9376695,0.038414005,0.00030926993,0.000937398,0.00009181723,0.0001303947,0.00066867133,0.017973673,0.000035227113],"about_ca_topic_score_codex":0.009814951,"about_ca_topic_score_gemma":0.03967545,"teacher_disagreement_score":0.02061937,"about_ca_system_score_codex":0.00615775,"about_ca_system_score_gemma":0.027584169,"threshold_uncertainty_score":0.10653788},"labels":[],"label_agreement":null},{"id":"W4414111398","doi":"10.1177/2694104x251378449","title":"Buy Now, Pay Later: AI, Inherent Tensions, and Implications","year":2025,"lang":"en","type":"article","venue":"Management and business review.","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Key (lock); Government (linguistics); Payment; Work (physics)","score_opus":0.012807939592503936,"score_gpt":0.26387065376263946,"score_spread":0.25106271417013554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414111398","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0072350525,0.3662435,0.0061992304,0.54760176,0.0026970778,0.000025042833,0.000045207158,0.000028484836,0.06992473],"genre_scores_gemma":[0.36315173,0.49950108,0.007197865,0.11542105,0.0065884762,0.00011558719,0.0000625579,0.000052250292,0.007909452],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9919878,0.00411092,0.00039031246,0.00064680167,0.0024439495,0.00042012153],"domain_scores_gemma":[0.9565123,0.037121784,0.0016350031,0.0005973758,0.003349307,0.00078433345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01814396,0.00028404608,0.00072814233,0.0027890482,0.0019775154,0.008757197,0.001517557,0.004699066,0.0027741285],"category_scores_gemma":[0.021879798,0.0002809777,0.00040844944,0.0041084583,0.011788809,0.009916858,0.0017441316,0.008467922,0.0006269248],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007681872,0.000087762615,0.0017183766,0.001205672,0.00006688105,0.0003771077,0.0021164874,0.0010435326,0.00026899754,0.6977037,0.049929094,0.24540561],"study_design_scores_gemma":[0.00002552793,0.00005678752,0.0020394027,0.002030133,0.000028898701,0.00041206717,0.005936506,0.0017167279,0.00021000399,0.77060133,0.21689025,0.00005237442],"about_ca_topic_score_codex":0.007564687,"about_ca_topic_score_gemma":0.012712212,"teacher_disagreement_score":0.01814396,"about_ca_system_score_codex":0.0055460446,"about_ca_system_score_gemma":0.0042125406,"threshold_uncertainty_score":0.09595561},"labels":[],"label_agreement":null},{"id":"W4414151078","doi":"10.3982/ecta19106","title":"Who Benefits From Surge Pricing?","year":2025,"lang":"en","type":"article","venue":"Econometrica","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Network of European Institutes for Advanced Study; Digital Technology Supercluster; Stanford Institute for Economic Policy Research; University of Pennsylvania; John S. and James L. Knight Foundation; Charles Warren Center for Studies in American History, Harvard University; Stanford University","keywords":"Boom; Welfare; Counterfactual thinking; Surge; Matching (statistics); Salient","score_opus":0.009121869285237104,"score_gpt":0.20196561072937264,"score_spread":0.19284374144413552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414151078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7029827,0.019477477,0.002808397,0.16438778,0.000872945,0.00006644569,0.001324685,0.00011614055,0.10796331],"genre_scores_gemma":[0.99243754,0.0017101073,0.00011563795,0.0031858583,0.0004258773,0.000007832351,0.000084665655,0.000010248703,0.0020222738],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99920017,0.00032177515,0.000020165411,0.00006889416,0.00010764753,0.00028142543],"domain_scores_gemma":[0.9958364,0.002197319,0.0007559024,0.00016946369,0.0002958505,0.0007451441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014659272,0.00011810385,0.00044158578,0.00047081293,0.0005220728,0.0018545672,0.00048230577,0.0014477383,0.018796],"category_scores_gemma":[0.008965367,0.00015369804,0.0005251126,0.00059559866,0.001044898,0.0027983603,0.00068658125,0.0013099887,0.0016744105],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088055653,0.0011489512,0.35069174,0.00048615038,0.00046274508,0.0012438608,0.0017255478,0.0017497458,0.0009354539,0.059638966,0.11593462,0.46510178],"study_design_scores_gemma":[0.00039958523,0.0009640842,0.5022911,0.0012622001,0.00070574885,0.0038542338,0.024868106,0.010956061,0.0016126212,0.31343675,0.13952717,0.0001222989],"about_ca_topic_score_codex":0.0017657359,"about_ca_topic_score_gemma":0.0033618577,"teacher_disagreement_score":0.018796,"about_ca_system_score_codex":0.0006376344,"about_ca_system_score_gemma":0.00092968077,"threshold_uncertainty_score":0.06287885},"labels":[],"label_agreement":null},{"id":"W4414179217","doi":"10.3390/modelling6030103","title":"Evaluating Carsharing Fleet Management Strategies Using Discrete Event Simulation: A Case Study","year":2025,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University","funders":"","keywords":"Fleet management; Discrete event simulation; Event (particle physics); Measure (data warehouse); Quality (philosophy); Incident management","score_opus":0.1654793898955486,"score_gpt":0.4738706523335897,"score_spread":0.3083912624380411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414179217","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98671734,0.000061676554,0.010016006,0.00010863934,0.000016048987,0.00019208297,0.00022933635,0.000065386535,0.002593521],"genre_scores_gemma":[0.9928566,0.00006182896,0.006073625,0.000015992044,0.0000036411714,0.00008916712,0.00014592499,0.0000068696754,0.00074630306],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917275,0.00038230905,0.00003279019,0.000089742236,0.00013431981,0.00018807524],"domain_scores_gemma":[0.99443394,0.0041952576,0.0003718751,0.00020892757,0.000462581,0.00032744958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017861981,0.0010767889,0.0007142393,0.0007987916,0.0006553324,0.001291898,0.0013170481,0.0016008881,0.0015421303],"category_scores_gemma":[0.0030530554,0.00036797978,0.0008760176,0.00080359343,0.00055551884,0.0008037649,0.000529432,0.0009663809,0.00013128945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001693545,0.00046188824,0.005151481,0.000043047545,0.000040646784,0.00016789722,0.000073086034,0.98921835,0.0008813985,0.00082388794,0.00017185978,0.002797157],"study_design_scores_gemma":[0.00004009719,0.00030532668,0.0014421161,0.000005851299,0.00001893239,0.000016996606,0.00018835116,0.9966995,0.00084230833,0.0002313809,0.0001959252,0.000013212024],"about_ca_topic_score_codex":0.03903077,"about_ca_topic_score_gemma":0.029131385,"teacher_disagreement_score":0.03903077,"about_ca_system_score_codex":0.0025085576,"about_ca_system_score_gemma":0.0016057089,"threshold_uncertainty_score":0.077607155},"labels":[],"label_agreement":null},{"id":"W4414229223","doi":"10.1109/tmc.2025.3610915","title":"Accelerating Stable Matching Between Workers and Spatial-Temporal Tasks for Dynamic MCS: A Stagewise Service Trading Approach","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Aeronautical Science Foundation of China; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Matching (statistics); Futures contract; Key (lock); Service (business); Task (project management); Incentive; Software deployment; Path (computing); Pareto principle","score_opus":0.020129966484849562,"score_gpt":0.2632609947721499,"score_spread":0.24313102828730038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414229223","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023232935,0.00010132058,0.97456914,0.00020187204,0.000029753757,0.00008012596,0.00004379976,0.0001784143,0.0015626538],"genre_scores_gemma":[0.85932404,0.00011412671,0.13717455,0.00015607353,0.000040661133,0.00017477757,0.000070434515,0.000052873085,0.0028925284],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986174,0.0004095974,0.00006343482,0.00033893777,0.00027549546,0.00029509963],"domain_scores_gemma":[0.9973086,0.0014477452,0.00029744554,0.0003293807,0.00027926333,0.0003374842],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024463232,0.0007873703,0.0011478438,0.00050508115,0.00084205205,0.0010522908,0.0029813559,0.0014717656,0.0035449956],"category_scores_gemma":[0.006047347,0.00052201084,0.0007883264,0.0006412697,0.00115892,0.001945004,0.0029600707,0.0013945702,0.0004192922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037431603,0.0002453446,0.0023099044,0.000156711,0.00006407011,0.00022292633,0.0003580363,0.82972944,0.009945255,0.07022876,0.0019537662,0.08441137],"study_design_scores_gemma":[0.000013843156,0.000051989744,0.00011596603,0.0000037226168,0.000006724056,0.000029648272,0.00002489794,0.9823729,0.0006265652,0.016181767,0.00056452584,0.000007522109],"about_ca_topic_score_codex":0.003929186,"about_ca_topic_score_gemma":0.0034407992,"teacher_disagreement_score":0.003929186,"about_ca_system_score_codex":0.0010920537,"about_ca_system_score_gemma":0.002235076,"threshold_uncertainty_score":0.012937546},"labels":[],"label_agreement":null},{"id":"W4414423944","doi":"10.1016/j.tra.2025.104626","title":"An investigation of the factors that affect the use of pooled ridehailing services in California","year":2025,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"California Department of Transportation; University of California, Davis; California Air Resources Board; Southern California Association of Governments","keywords":"TRIPS architecture; Metropolitan area; Openness to experience; Affect (linguistics); Mode choice; Data collection; Competition (biology); Work (physics); Travel behavior; Logit","score_opus":0.13274396248613735,"score_gpt":0.39986730702331674,"score_spread":0.2671233445371794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414423944","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9956098,0.00018865803,0.00013443442,0.00017301703,0.0000045103316,0.000030015488,0.00077429606,0.000008358418,0.0030767606],"genre_scores_gemma":[0.997416,0.00030382775,0.00033397158,0.000060125974,0.000008620236,0.000030075733,0.0008903068,0.000005314234,0.000951675],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989095,0.00022001914,0.000073341624,0.00031182726,0.00031022046,0.00017509933],"domain_scores_gemma":[0.9960031,0.0013839331,0.0011453612,0.00020035829,0.0008824972,0.00038465986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015135573,0.00022492449,0.00030971278,0.0009552048,0.0010791328,0.0019046639,0.00096299127,0.0003247973,0.0025248816],"category_scores_gemma":[0.005716375,0.0002733855,0.0004653856,0.0018259794,0.0004326845,0.0007668351,0.0008342818,0.0006747797,0.00019671292],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000528562,0.00019405909,0.9874605,0.000073093564,0.00009157047,0.00011613342,0.0017265315,0.0008379544,0.0001528793,0.00031386962,0.001916155,0.007064387],"study_design_scores_gemma":[0.000009613278,0.00007501755,0.9891248,0.000058950947,0.00007222008,0.000049221366,0.0052453917,0.0022919823,0.000080306665,0.000072811374,0.00290327,0.000016521199],"about_ca_topic_score_codex":0.49453622,"about_ca_topic_score_gemma":0.6196631,"teacher_disagreement_score":0.49453622,"about_ca_system_score_codex":0.002727032,"about_ca_system_score_gemma":0.0022539804,"threshold_uncertainty_score":0.9833154},"labels":[],"label_agreement":null},{"id":"W4414491826","doi":"10.34647/jmv.nr25.id224","title":"Mobilitätsarmut im ländlichen Raum – Was können On-Demand-Verkehre leisten?","year":2025,"lang":"de","type":"article","venue":"Journal für Mobilität und Verkehr","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nutrasource","funders":"","keywords":"Context (archaeology); Long-term prediction; Time line","score_opus":0.013092277308469761,"score_gpt":0.3030817439955149,"score_spread":0.28998946668704517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414491826","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49301854,0.12291239,0.03998846,0.05506785,0.0026626387,0.0013861166,0.004887411,0.00037697298,0.27969956],"genre_scores_gemma":[0.9214025,0.041205857,0.010476504,0.0022623402,0.00042195694,0.0006310174,0.0016784241,0.00015643908,0.021764822],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99463624,0.0028526792,0.00020530458,0.00034134302,0.0012095408,0.0007548003],"domain_scores_gemma":[0.989689,0.0054548853,0.0011720962,0.0005938277,0.0021295093,0.0009605493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006702225,0.00073315774,0.0011241164,0.0011736075,0.0012127709,0.0073989606,0.0018194201,0.0019392597,0.0353879],"category_scores_gemma":[0.016688732,0.00037254533,0.0012230666,0.0016420096,0.0018496678,0.0072782235,0.0030718513,0.0019381829,0.0051727393],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030660208,0.0017628112,0.0472729,0.012867954,0.00097119954,0.00077691814,0.005267106,0.019983016,0.0055389977,0.076875485,0.036097012,0.7895207],"study_design_scores_gemma":[0.00049984624,0.007008325,0.09998212,0.019860173,0.0016810966,0.0012165561,0.043522943,0.016509691,0.01411446,0.12742597,0.66763735,0.0005414552],"about_ca_topic_score_codex":0.009106892,"about_ca_topic_score_gemma":0.013769938,"teacher_disagreement_score":0.0353879,"about_ca_system_score_codex":0.004155812,"about_ca_system_score_gemma":0.004765101,"threshold_uncertainty_score":0.1183843},"labels":[],"label_agreement":null},{"id":"W4414572273","doi":"10.1016/j.jth.2025.102177","title":"Obstacles and facilitators to access to paratransit for people with disabilities: A scoping review","year":2025,"lang":"en","type":"article","venue":"Journal of Transport & Health","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centres Intégré Universitaires de Santé et de Services Sociaux; Centre for Interdisciplinary Research in Rehabilitation; Université Laval","funders":"Fonds de Recherche du Québec - Santé","keywords":"Paratransit; Punctuality; Service (business); Key (lock); Face (sociological concept); Usability","score_opus":0.031573992532681464,"score_gpt":0.3536625064175569,"score_spread":0.32208851388487547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414572273","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027551644,0.9942008,0.00019474025,0.00085331476,0.00016018927,0.00030883093,0.000116090036,0.0000062957474,0.0014045287],"genre_scores_gemma":[0.01043457,0.9881435,0.00043035523,0.00028308554,0.000050252813,0.00036810897,0.000094611576,0.0000035714143,0.00019186245],"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","domain_scores_codex":[0.9920574,0.0027992816,0.002546281,0.0004292076,0.0017251507,0.000442728],"domain_scores_gemma":[0.9315666,0.057989515,0.0048803166,0.00042450224,0.0045727976,0.0005663418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012559537,0.001157494,0.0034918531,0.014407088,0.0016825492,0.005801011,0.0017347819,0.0031843826,0.0034409086],"category_scores_gemma":[0.05547677,0.0011728465,0.0038689978,0.014218108,0.0012829615,0.004352853,0.0025186543,0.0017016957,0.00043218982],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011772867,0.000065155415,0.0020593682,0.78578806,0.0015135593,0.0004163904,0.004704736,0.00015010482,0.00021166538,0.0015867603,0.004439147,0.19894731],"study_design_scores_gemma":[0.000023597731,0.00008020883,0.0032773004,0.9374789,0.0061860294,0.00040085564,0.004771303,0.00006217838,0.00016393105,0.00040102276,0.047122825,0.00003182373],"about_ca_topic_score_codex":0.014133631,"about_ca_topic_score_gemma":0.035559714,"teacher_disagreement_score":0.014407088,"about_ca_system_score_codex":0.005064684,"about_ca_system_score_gemma":0.022427762,"threshold_uncertainty_score":0.066421926},"labels":[],"label_agreement":null},{"id":"W4414713242","doi":"10.3389/frsc.2025.1645488","title":"Assessing the impact of Mobility-as-a-Service (MaaS) on sustainable urban travel behaviors: a systematic literature review","year":2025,"lang":"en","type":"article","venue":"Frontiers in Sustainable Cities","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Sustainability; Disadvantaged; Systematic review; Work (physics); Public transport; Subsidy; Corporate governance; Transition management (governance); Sustainable transport; Service (business)","score_opus":0.006768200271925931,"score_gpt":0.27707034642975453,"score_spread":0.2703021461578286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414713242","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013394621,0.9968959,0.00033111923,0.00028917723,0.000080210455,0.00020300571,0.00045174742,0.000009434436,0.00039988876],"genre_scores_gemma":[0.010803194,0.9874035,0.00085926283,0.0002825818,0.000043022817,0.00028494617,0.00025327445,0.0000069788016,0.000063227926],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.99109626,0.002841911,0.0032122126,0.00077535864,0.0018276917,0.00024656465],"domain_scores_gemma":[0.9463063,0.04118039,0.0060885316,0.0006790285,0.005233071,0.0005126891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012816797,0.0015560514,0.0053027347,0.016626576,0.0007409976,0.0034585013,0.0018679376,0.0019026932,0.0041059125],"category_scores_gemma":[0.051975884,0.0011438603,0.0072657866,0.016227944,0.0010561901,0.0030868058,0.0023274801,0.0014366105,0.0004438004],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009269845,0.000035093748,0.0017699393,0.8742598,0.0042328057,0.000091753485,0.00041751435,0.00023809711,0.00016798989,0.00071066606,0.001632453,0.11635105],"study_design_scores_gemma":[0.000049400256,0.00016122696,0.0053386227,0.940906,0.024097705,0.000240315,0.00062743446,0.0001332435,0.00019073841,0.0004837332,0.027726663,0.00004487935],"about_ca_topic_score_codex":0.014678764,"about_ca_topic_score_gemma":0.038288254,"teacher_disagreement_score":0.016626576,"about_ca_system_score_codex":0.0036826248,"about_ca_system_score_gemma":0.022897175,"threshold_uncertainty_score":0.06778252},"labels":[],"label_agreement":null},{"id":"W4414729380","doi":"10.1007/978-3-031-95111-4_7","title":"MAMC: A Multi-agent Autonomous Mobility Control System","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina; Western University","funders":"","keywords":"Task (project management); Mobile robot; Bidding; Robot; Control (management); Software; Path (computing); Controller (irrigation)","score_opus":0.008199018208102248,"score_gpt":0.20046154915453768,"score_spread":0.19226253094643542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414729380","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012587551,0.0004815105,0.9697328,0.00037185496,0.0003849886,0.00012547021,0.0003213162,0.006407641,0.009586818],"genre_scores_gemma":[0.5979829,0.00050169195,0.37775633,0.00047471974,0.000172296,0.00060722965,0.0007818927,0.0002106572,0.021512266],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998647,0.00002550672,0.0000075604876,0.00003669992,0.0000473448,0.000018290266],"domain_scores_gemma":[0.9998957,0.000020252673,0.000011138986,0.000013133549,0.000045418226,0.000014467502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002649164,0.0004860068,0.0007114321,0.00024018054,0.00048204308,0.00058905216,0.0011829112,0.0008312743,0.0037827217],"category_scores_gemma":[0.00039871864,0.00023315297,0.00029465609,0.00029339828,0.00029557306,0.0004173542,0.0009361486,0.00089211174,0.0013223535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048636625,0.00015384826,0.00072847464,0.00048580812,0.00012741752,0.00030580786,0.00017052704,0.51188725,0.06557968,0.031220563,0.0297242,0.35912997],"study_design_scores_gemma":[0.000041925698,0.0000934224,0.0002121422,0.000011367457,0.000017195773,0.00005153173,0.000010231039,0.9810635,0.003938271,0.0019618412,0.012581554,0.000017085695],"about_ca_topic_score_codex":0.0051523834,"about_ca_topic_score_gemma":0.004503873,"teacher_disagreement_score":0.0051523834,"about_ca_system_score_codex":0.0003213189,"about_ca_system_score_gemma":0.0008921981,"threshold_uncertainty_score":0.012654483},"labels":[],"label_agreement":null},{"id":"W4414807097","doi":"10.1016/b978-0-443-22392-1.00013-4","title":"Barriers to shared use of vehicles","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Neurotrauma Foundation","funders":"","keywords":"Variety (cybernetics); Automation; Car sharing; Sharing economy; Service (business); Private sector","score_opus":0.01803669237165155,"score_gpt":0.22594773982310717,"score_spread":0.2079110474514556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414807097","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034756277,0.0051898924,0.0058865887,0.008756922,0.0002995555,0.000029387349,0.00010123153,0.000053795102,0.9449263],"genre_scores_gemma":[0.48446015,0.008576986,0.0020343678,0.0007603331,0.00013394513,0.00009424307,0.00021828306,0.00012264203,0.50359905],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9982309,0.0005192449,0.000064878965,0.00014705386,0.00061344187,0.00042451292],"domain_scores_gemma":[0.99813396,0.0010315209,0.00020955098,0.00014078304,0.00023135068,0.0002529283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008619107,0.00040933737,0.00028679008,0.0007025402,0.0022436322,0.0073029366,0.0011018883,0.001726072,0.06453571],"category_scores_gemma":[0.0033085318,0.00030961592,0.0002966874,0.0014935397,0.0019791496,0.0049909335,0.005239013,0.0021619033,0.0067129945],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034347493,0.00007181853,0.0031181276,0.00025983618,0.0000140379325,0.00041043165,0.02187418,0.0010969285,0.0006686252,0.772085,0.05939018,0.14097653],"study_design_scores_gemma":[0.0000045263514,0.00003420495,0.0050315894,0.0011051412,0.000011298295,0.00061671494,0.050902378,0.0009294798,0.00046943247,0.0957352,0.8451377,0.000022292148],"about_ca_topic_score_codex":0.0123951435,"about_ca_topic_score_gemma":0.019027071,"teacher_disagreement_score":0.06453571,"about_ca_system_score_codex":0.0025868078,"about_ca_system_score_gemma":0.0032773989,"threshold_uncertainty_score":0.21589345},"labels":[],"label_agreement":null},{"id":"W4414807195","doi":"10.1016/b978-0-443-22392-1.00015-8","title":"A challenging transition: two competing markets","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Neurotrauma Foundation","funders":"","keywords":"Competition (biology); Service (business); Balance (ability); Psychological intervention; Public policy; Key (lock); Service provider; Control (management)","score_opus":0.01059810270183171,"score_gpt":0.22227075602598867,"score_spread":0.21167265332415697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414807195","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015344618,0.005721222,0.0127680255,0.03715832,0.0011670876,0.0000495403,0.000088377485,0.00006823456,0.9276345],"genre_scores_gemma":[0.55341196,0.011452723,0.008262478,0.0075188754,0.0013909821,0.00017947257,0.0001231082,0.00020537424,0.417455],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993724,0.0002064849,0.000011030665,0.00009089691,0.0001493986,0.00016973018],"domain_scores_gemma":[0.9992052,0.00040675426,0.000048460992,0.000048488546,0.00006377433,0.00022744261],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010983109,0.000535573,0.0006245569,0.00050348,0.0027778852,0.0133015895,0.001423397,0.0064876885,0.039810725],"category_scores_gemma":[0.0027605165,0.0003367492,0.00056857755,0.000775636,0.005346617,0.013025841,0.0034873327,0.005769665,0.0032998335],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018920282,0.00001986023,0.00003678045,0.000019957612,0.0000021115586,0.00007578492,0.0002480429,0.000501513,0.000074996984,0.9780548,0.014757858,0.006189391],"study_design_scores_gemma":[0.000022560373,0.000018787387,0.0001245613,0.000112791546,0.0000037938994,0.00011943511,0.0015404321,0.0028755863,0.00006911675,0.8851896,0.109904945,0.00001839288],"about_ca_topic_score_codex":0.002930345,"about_ca_topic_score_gemma":0.004040604,"teacher_disagreement_score":0.039810725,"about_ca_system_score_codex":0.0031417066,"about_ca_system_score_gemma":0.0028078891,"threshold_uncertainty_score":0.13318014},"labels":[],"label_agreement":null},{"id":"W4414807341","doi":"10.1016/b978-0-443-22392-1.00006-7","title":"The broad context of change","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Neurotrauma Foundation","funders":"","keywords":"Transformative learning; Monetization; Context (archaeology); Dual (grammatical number); Automation; Key (lock); Perspective (graphical); Consumer behaviour","score_opus":0.02944935508074372,"score_gpt":0.2393252736673678,"score_spread":0.20987591858662408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414807341","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014451272,0.04771501,0.0014064834,0.015142175,0.0011124342,0.000013595037,0.00004234585,0.000028522643,0.93309426],"genre_scores_gemma":[0.25637978,0.08113631,0.0029503086,0.008343942,0.0029747924,0.0001833753,0.00015928202,0.00014362784,0.6477286],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991665,0.00039241835,0.000021058262,0.000116461306,0.0001866804,0.00011696129],"domain_scores_gemma":[0.9995103,0.0002864613,0.000026163349,0.000060009133,0.00004644489,0.00007050147],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008961965,0.00074581464,0.0005593802,0.0011707792,0.0027635137,0.010063131,0.00077072124,0.0031616224,0.02745316],"category_scores_gemma":[0.0015898395,0.00031137426,0.00025788246,0.0023976637,0.014421335,0.007927217,0.0038466018,0.0040871515,0.0036751304],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000047034864,0.000008150125,0.00006047479,0.000050209863,0.000001944419,0.000043074215,0.0024427795,0.00007665055,0.000058540885,0.95987976,0.021459037,0.015914747],"study_design_scores_gemma":[0.0000038307485,0.0000064448595,0.00024314657,0.00027492942,0.0000021296573,0.000059192284,0.0029922319,0.00008032971,0.00003147305,0.39131027,0.6049911,0.0000049875975],"about_ca_topic_score_codex":0.005816903,"about_ca_topic_score_gemma":0.010112612,"teacher_disagreement_score":0.02745316,"about_ca_system_score_codex":0.0044514257,"about_ca_system_score_gemma":0.0032288881,"threshold_uncertainty_score":0.09183997},"labels":[],"label_agreement":null},{"id":"W4414807369","doi":"10.1016/b978-0-443-22392-1.00003-1","title":"Automated driving and transit-oriented development","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Neurotrauma Foundation","funders":"","keywords":"Software deployment; Automation; Transit-oriented development; Transit (satellite); Walkability; Advanced driver assistance systems; Key (lock); Emerging technologies","score_opus":0.007473082370210751,"score_gpt":0.211676803566419,"score_spread":0.20420372119620825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414807369","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023470817,0.009573951,0.021986326,0.00066296116,0.00042479573,0.000028851911,0.00011574327,0.00030622198,0.9645542],"genre_scores_gemma":[0.023186943,0.013639191,0.009960158,0.0001711291,0.00013701206,0.00003990561,0.00025279183,0.00013764673,0.9524752],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999907,0.00001243618,0.0000036324545,0.00001791102,0.00004785067,0.000011268225],"domain_scores_gemma":[0.9999057,0.00004183064,0.000005377272,0.000012580971,0.00002712865,0.0000073809133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011137629,0.0005789232,0.00015279063,0.0006538062,0.00037189884,0.0018473503,0.00040838245,0.0005820825,0.04765411],"category_scores_gemma":[0.00026503843,0.00022570045,0.00018040123,0.0010267205,0.00047609163,0.0011947652,0.0005173743,0.0006361051,0.0107573],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013671698,0.0000494665,0.00029513665,0.00023759663,0.0000059434938,0.00011368688,0.00042712365,0.0036896695,0.0017717737,0.26391667,0.12396494,0.6055142],"study_design_scores_gemma":[0.0000014247103,0.0000139635,0.000400235,0.00010812144,0.0000028263416,0.00010820231,0.00011792332,0.0018309116,0.00046512057,0.03186311,0.9650846,0.0000035648256],"about_ca_topic_score_codex":0.0034719014,"about_ca_topic_score_gemma":0.0059408303,"teacher_disagreement_score":0.04765411,"about_ca_system_score_codex":0.000780279,"about_ca_system_score_gemma":0.0006846625,"threshold_uncertainty_score":0.15941894},"labels":[],"label_agreement":null},{"id":"W4414807376","doi":"10.1016/b978-0-443-22392-1.00017-1","title":"Microtransit rising","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Neurotrauma Foundation","funders":"","keywords":"TRIPS architecture; Public transport; Bridging (networking); Service (business); Public service; Urban planning; Transit (satellite); Transit system","score_opus":0.010094294239260029,"score_gpt":0.2160129555748455,"score_spread":0.20591866133558548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414807376","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008039913,0.003204428,0.0012745835,0.0013488205,0.0013772047,0.000015136947,0.00012546667,0.00021925665,0.9916311],"genre_scores_gemma":[0.0060946383,0.0024668812,0.0005382011,0.0003389202,0.00018691692,0.000016430353,0.000105586616,0.00013066427,0.99012166],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99980897,0.0000177632,0.0000049901364,0.000039259972,0.00008542794,0.000043581254],"domain_scores_gemma":[0.9998938,0.000020015366,0.0000056740337,0.000026385966,0.000029187777,0.000024833316],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00015508202,0.0006478821,0.0002632027,0.0011301688,0.0016846907,0.0036475773,0.0006642387,0.0012563709,0.30245116],"category_scores_gemma":[0.0004730199,0.00035021766,0.00043007307,0.0017862278,0.00063994573,0.0030724853,0.0023192302,0.0021053625,0.090021014],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033287735,0.000028385586,0.00015234984,0.00017661515,0.000003317097,0.00014276362,0.00046643862,0.00028256915,0.0009405422,0.15943897,0.5297304,0.30860436],"study_design_scores_gemma":[0.000001215183,0.0000056482354,0.00015534308,0.000053468182,0.0000012788291,0.000058301008,0.00011672924,0.00007955545,0.00014179737,0.004679474,0.99470514,0.0000021115436],"about_ca_topic_score_codex":0.0041741333,"about_ca_topic_score_gemma":0.014656857,"teacher_disagreement_score":0.30245116,"about_ca_system_score_codex":0.0015734634,"about_ca_system_score_gemma":0.0011921842,"threshold_uncertainty_score":0.9949688},"labels":[],"label_agreement":null},{"id":"W4414818525","doi":"10.46298/cst.13086","title":"Promoting urban carpooling: a social cost approach based on the Lyon case study","year":2025,"lang":"en","type":"article","venue":"Les Cahiers scientifiques du transport","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Carpool; Externality; TRIPS architecture; Incentive; Public transport; Social cost; Revenue; Modal","score_opus":0.019967145999377503,"score_gpt":0.24262105609948842,"score_spread":0.22265391010011093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414818525","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94688684,0.00033436136,0.014402171,0.0005460362,0.000019125053,0.00018774586,0.00048883347,0.0000485033,0.037086256],"genre_scores_gemma":[0.99524987,0.00022248412,0.0026433473,0.000014836058,0.00000563764,0.000066175875,0.000076026896,0.000006679245,0.0017148715],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99887913,0.00074842514,0.000022941635,0.000053737884,0.00009277692,0.00020296892],"domain_scores_gemma":[0.9987563,0.0008352551,0.00011950502,0.000065607055,0.00014388152,0.000079433754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001045369,0.0007243497,0.0005262786,0.001807647,0.0006930332,0.0018874902,0.00089771516,0.0010214127,0.00439432],"category_scores_gemma":[0.0017332819,0.0002110464,0.0010657669,0.0018383329,0.00084930146,0.0010050716,0.0009918134,0.00058772945,0.00014390952],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024860623,0.00033672756,0.012660318,0.00016701031,0.0001044519,0.0008966232,0.00035275874,0.93969846,0.0007067694,0.035432868,0.00086823263,0.008527238],"study_design_scores_gemma":[0.00014588288,0.0007227021,0.01884307,0.00010138739,0.0001775297,0.0002599064,0.0050795325,0.9527882,0.001576924,0.0134353945,0.006746109,0.00012340638],"about_ca_topic_score_codex":0.043449346,"about_ca_topic_score_gemma":0.039068542,"teacher_disagreement_score":0.043449346,"about_ca_system_score_codex":0.004719966,"about_ca_system_score_gemma":0.0011260218,"threshold_uncertainty_score":0.08639288},"labels":[],"label_agreement":null},{"id":"W4414861741","doi":"10.1080/23249935.2025.2566439","title":"Extraboard transit operator scheduling considering driver absenteeism","year":2025,"lang":"en","type":"article","venue":"Transportmetrica A Transport Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scheduling (production processes); Operator (biology); Transit system; Public transport; Transit (satellite); Job shop scheduling","score_opus":0.011533341403783318,"score_gpt":0.24437141901931259,"score_spread":0.23283807761552927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414861741","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.65406215,0.00023222525,0.33659437,0.0007176683,0.00007708197,0.00017189236,0.00046608452,0.0001935901,0.0074849296],"genre_scores_gemma":[0.99016577,0.00006212309,0.008009889,0.000020436222,0.000013891363,0.00003612635,0.00010699771,0.000016422484,0.0015681979],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99920744,0.00031258824,0.000023298127,0.00015970667,0.000085685606,0.00021129406],"domain_scores_gemma":[0.9979856,0.0011798784,0.0003056632,0.000065896784,0.00019368365,0.00026928628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014171622,0.0007427329,0.00085742836,0.00038996967,0.00037219762,0.0012450158,0.0009452686,0.0010706716,0.00285407],"category_scores_gemma":[0.0035882862,0.00052401837,0.00063399004,0.0004568166,0.00053684996,0.00085476896,0.0008041407,0.0012285355,0.00016413725],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007834447,0.000042761167,0.00096301676,0.000019226201,0.000011641623,0.00006759862,0.000031580155,0.99408495,0.00031046683,0.0015172184,0.00016945465,0.0027038136],"study_design_scores_gemma":[0.0000061603214,0.00003747621,0.00044262645,0.0000022165148,0.0000049651385,0.000005919365,0.000028175766,0.99855214,0.00007959662,0.0007370149,0.000100542624,0.0000031863008],"about_ca_topic_score_codex":0.018609675,"about_ca_topic_score_gemma":0.014138608,"teacher_disagreement_score":0.018609675,"about_ca_system_score_codex":0.0012808058,"about_ca_system_score_gemma":0.0021833023,"threshold_uncertainty_score":0.037002683},"labels":[],"label_agreement":null},{"id":"W4414863333","doi":"10.1007/978-3-032-02983-6_20","title":"Digital Cross-Border Payment Technologies in Fragile, Conflict, and Vulnerable Settings","year":2025,"lang":"en","type":"book-chapter","venue":"Financial innovation and technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Sanctions; Resilience (materials science); Humanitarian aid; Civil society; Investment (military); Humanitarian crisis; Government (linguistics); Payment; Financial crisis","score_opus":0.007054031777005519,"score_gpt":0.26582122893728777,"score_spread":0.25876719716028224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414863333","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2880034,0.036839373,0.1337564,0.07002318,0.004612455,0.00074930384,0.001854292,0.0048991535,0.45926246],"genre_scores_gemma":[0.8839974,0.021643853,0.042915393,0.0056672404,0.001336209,0.0004473489,0.000918876,0.00029843725,0.04277525],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99841416,0.00069665874,0.00013805825,0.00017090584,0.00034099366,0.00023918384],"domain_scores_gemma":[0.9952317,0.0024050302,0.0004507458,0.0007222329,0.00060293457,0.0005873283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031689976,0.00038929348,0.00034284146,0.0016949318,0.001493938,0.0068102498,0.0012843166,0.002534652,0.020828433],"category_scores_gemma":[0.009526129,0.00023279266,0.00033203905,0.0015741347,0.0016423209,0.01246834,0.006907164,0.0016769152,0.0045724665],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043577584,0.00031780897,0.0106628835,0.0010294344,0.000043763393,0.0026696085,0.0069548883,0.0021597017,0.0028020726,0.2312653,0.09162622,0.6500325],"study_design_scores_gemma":[0.000097185846,0.00047279263,0.00953848,0.0027552554,0.00006671312,0.0064697247,0.014745327,0.009309902,0.0042305426,0.18803796,0.76414216,0.00013403744],"about_ca_topic_score_codex":0.00064273237,"about_ca_topic_score_gemma":0.0006671679,"teacher_disagreement_score":0.020828433,"about_ca_system_score_codex":0.001018792,"about_ca_system_score_gemma":0.0007901377,"threshold_uncertainty_score":0.06967801},"labels":[],"label_agreement":null},{"id":"W4414889635","doi":"10.1093/pch/pxaf068","title":"Showing up for no-shows: Why transportation equity matters","year":2025,"lang":"en","type":"article","venue":"Paediatrics & Child Health","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Alberta","funders":"Canada Research Chairs","keywords":"Equity (law); Dilemma; Health care; Disease; Health equity","score_opus":0.019566156070586913,"score_gpt":0.2894146753276924,"score_spread":0.26984851925710546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414889635","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.092112325,0.010024266,0.006376374,0.79636306,0.001982718,0.00006149169,0.00031410236,0.000077146025,0.09268845],"genre_scores_gemma":[0.94562423,0.007323863,0.0015878476,0.036011595,0.0008967784,0.000050161118,0.00011099486,0.00007686872,0.008317644],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9959794,0.0019578384,0.00012411024,0.00030253432,0.00078689505,0.000849152],"domain_scores_gemma":[0.99257654,0.0038100684,0.000815155,0.00023849553,0.0012777005,0.001282008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005320842,0.00021234852,0.00025179968,0.0006440869,0.00319282,0.0059467177,0.0010891986,0.0026838037,0.013985335],"category_scores_gemma":[0.018843515,0.00016920928,0.00037219195,0.00081215805,0.00775491,0.009293969,0.004237032,0.0038616979,0.00104428],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011077543,0.00014928343,0.04585544,0.0006436427,0.00006705746,0.00081607455,0.015681662,0.0015265616,0.00057482335,0.5510004,0.16818145,0.21539275],"study_design_scores_gemma":[0.00004769769,0.00025687562,0.04974064,0.0032381408,0.000072812945,0.0011424079,0.08433156,0.003023737,0.0012760073,0.38453856,0.47219035,0.0001411711],"about_ca_topic_score_codex":0.026453337,"about_ca_topic_score_gemma":0.02599279,"teacher_disagreement_score":0.026453337,"about_ca_system_score_codex":0.0062638386,"about_ca_system_score_gemma":0.0049103866,"threshold_uncertainty_score":0.052598715},"labels":[],"label_agreement":null},{"id":"W4414978578","doi":"10.1145/3763122","title":"Place Capability Graphs: A General-Purpose Model of Rust’s Ownership and Borrowing Guarantees","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Programming Languages","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rust (programming language); Aliasing; Function (biology); Type (biology); Capability approach; Measure (data warehouse)","score_opus":0.01296934673141616,"score_gpt":0.2482667241712301,"score_spread":0.23529737743981394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414978578","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0151788825,0.00011503957,0.9651176,0.00048520544,0.000049277296,0.00011516294,0.0008186331,0.003512784,0.014607387],"genre_scores_gemma":[0.45825273,0.0005823582,0.5177893,0.00043756995,0.00009933265,0.00061321066,0.0014979078,0.0026519403,0.018075649],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988262,0.00025738857,0.00006983351,0.00025866297,0.0004100413,0.00017785328],"domain_scores_gemma":[0.9979221,0.00070199656,0.00020222194,0.00081700424,0.000263027,0.000093689065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011894612,0.00089554524,0.00048159118,0.0014427684,0.00081807154,0.0026118648,0.0027645403,0.0016284923,0.0070454977],"category_scores_gemma":[0.0045600794,0.0008419429,0.0017569052,0.0011370752,0.0035775495,0.006139369,0.0021025513,0.0022466541,0.0014674048],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057565598,0.000022920363,0.00046971865,0.00008215938,0.000012602096,0.00020591966,0.0003442346,0.09715415,0.0014680235,0.8869682,0.0021456112,0.011068798],"study_design_scores_gemma":[0.00004173498,0.000043573516,0.00020757661,0.00007378711,0.000040074945,0.00021922695,0.000090043686,0.35929582,0.0048615336,0.5849295,0.05015111,0.00004605174],"about_ca_topic_score_codex":0.0076896846,"about_ca_topic_score_gemma":0.007394581,"teacher_disagreement_score":0.0076896846,"about_ca_system_score_codex":0.0014808155,"about_ca_system_score_gemma":0.0024679077,"threshold_uncertainty_score":0.023569584},"labels":[],"label_agreement":null},{"id":"W4414995447","doi":"10.1080/23249935.2025.2561893","title":"Examining the adoption potential of a new travel chain integrating electric vehicle sharing and rail transit","year":2025,"lang":"en","type":"article","venue":"Transportmetrica A Transport Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Electric vehicle; Public transport; Rail transit; Chain (unit); Transit (satellite)","score_opus":0.01806081216608966,"score_gpt":0.2322008488208468,"score_spread":0.21414003665475714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414995447","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981146,0.000026191328,0.00054572977,0.000052453015,0.0000018670595,0.000036676927,0.0000845906,0.000004150465,0.0011338013],"genre_scores_gemma":[0.9984003,0.000055621134,0.0009018989,0.000013216558,0.0000023046578,0.000038721533,0.00012951839,0.0000021194726,0.00045628572],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998939,0.0004961225,0.00006273165,0.00017669071,0.00016380759,0.00016162226],"domain_scores_gemma":[0.99370724,0.0032699958,0.0012761361,0.00035965856,0.0009428974,0.00044406523],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019563446,0.00030688284,0.00014273424,0.0010348611,0.00040241465,0.0015924287,0.00035095413,0.00051959325,0.0042062644],"category_scores_gemma":[0.008087424,0.00018431315,0.0005058219,0.0011472311,0.00035317117,0.0023126737,0.00088164734,0.0006836652,0.00048060063],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005854963,0.001700501,0.9319316,0.00017137246,0.00015832079,0.00019765373,0.0033949194,0.0065654544,0.002241938,0.0042304425,0.00042526392,0.048397005],"study_design_scores_gemma":[0.00009329367,0.005706698,0.8497833,0.00018215252,0.00043865698,0.00029480425,0.028240945,0.101976804,0.0031770403,0.0034334953,0.006576458,0.00009634209],"about_ca_topic_score_codex":0.010395121,"about_ca_topic_score_gemma":0.016375206,"teacher_disagreement_score":0.010395121,"about_ca_system_score_codex":0.0013066629,"about_ca_system_score_gemma":0.0011444751,"threshold_uncertainty_score":0.020669222},"labels":[],"label_agreement":null},{"id":"W4415009853","doi":"10.1080/03155986.2025.2561934","title":"Demand allocation policies for the charging station location and sizing problem","year":2025,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Group for Research in Decision Analysis; HEC Montréal","funders":"China Scholarship Council","keywords":"Sizing; Key (lock); Production (economics); Resource allocation; Demand forecasting","score_opus":0.03915981760008821,"score_gpt":0.33718066403670655,"score_spread":0.29802084643661836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415009853","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38863924,0.00064657576,0.5983868,0.0014221934,0.00009551009,0.0003454592,0.0007806593,0.00036065868,0.009322864],"genre_scores_gemma":[0.91531765,0.00030931938,0.08111006,0.00011115997,0.00003497877,0.0002191795,0.0004085858,0.00008818251,0.0024008206],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867105,0.0006898943,0.000055114197,0.00022058949,0.00015012558,0.00021325509],"domain_scores_gemma":[0.9950098,0.003808475,0.0005145466,0.00021728863,0.00020606875,0.00024386935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003323946,0.0012931679,0.0017891556,0.0009710889,0.00063282956,0.0015451096,0.001731364,0.0018789092,0.0038278424],"category_scores_gemma":[0.008865713,0.00089195836,0.0011664717,0.0013734604,0.0012350625,0.0029957755,0.0012622217,0.0018210531,0.0002587188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000064062995,0.000056667912,0.0003544154,0.000039266495,0.000014424962,0.000021060898,0.000030366129,0.98682845,0.00031074072,0.008230827,0.0003720658,0.0036778145],"study_design_scores_gemma":[0.000023509516,0.000040920462,0.00012469229,0.0000061754977,0.000005669366,0.000015224798,0.000023703466,0.9938712,0.00017517763,0.0054267244,0.00028142025,0.0000055669634],"about_ca_topic_score_codex":0.0059189447,"about_ca_topic_score_gemma":0.0044867336,"teacher_disagreement_score":0.0059189447,"about_ca_system_score_codex":0.0030000857,"about_ca_system_score_gemma":0.001499722,"threshold_uncertainty_score":0.021767199},"labels":[],"label_agreement":null},{"id":"W4415256869","doi":"10.1145/3757584","title":"Double Incomes, Single Calendar: Reimagining Shared Scheduling for Modern Families","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Negotiation; Onboarding; Thematic analysis; Participatory design; Scheduling (production processes); Intervention (counseling); Citizen journalism; Confidentiality","score_opus":0.04947683211250595,"score_gpt":0.31279791157281256,"score_spread":0.2633210794603066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415256869","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80400753,0.00046955398,0.16786677,0.0034992048,0.00021545509,0.00057071325,0.0002528895,0.001222519,0.021895371],"genre_scores_gemma":[0.88967043,0.00023896754,0.10632137,0.00017443168,0.00003141988,0.0003261412,0.00012871307,0.0001330826,0.0029755395],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99580884,0.0031805488,0.00012497936,0.0003038147,0.00027461196,0.00030721867],"domain_scores_gemma":[0.99303,0.003476794,0.00077414606,0.0014959531,0.00036037655,0.0008627465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0062379683,0.0005109354,0.00028857563,0.00063334027,0.002852655,0.002734365,0.0017595624,0.0006760951,0.0040283203],"category_scores_gemma":[0.015403682,0.00035485765,0.0003655886,0.0007037568,0.0018218177,0.0040783803,0.005267856,0.0007222552,0.00051824097],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067542476,0.00067764166,0.043058988,0.0006811488,0.000065915934,0.0012598983,0.14803731,0.0062419083,0.01040033,0.023260806,0.011999137,0.7536414],"study_design_scores_gemma":[0.0003850699,0.0033033788,0.03704263,0.001195727,0.00027991465,0.0025052354,0.31676167,0.029422268,0.025302915,0.081098825,0.50231045,0.00039192583],"about_ca_topic_score_codex":0.0025389462,"about_ca_topic_score_gemma":0.00499934,"teacher_disagreement_score":0.0062379683,"about_ca_system_score_codex":0.001359876,"about_ca_system_score_gemma":0.0028454305,"threshold_uncertainty_score":0.03298992},"labels":[],"label_agreement":null},{"id":"W4415260229","doi":"10.1287/ijoc.2024.0838","title":"Gamifying the Vehicle Routing Problem with Stochastic Requests","year":2025,"lang":"en","type":"article","venue":"INFORMS journal on computing","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Vehicle routing problem; Software; Reinforcement learning; Pascal (unit); Field (mathematics); Routing (electronic design automation); Stochastic programming; Optimization problem","score_opus":0.008995944244134841,"score_gpt":0.23758226565679505,"score_spread":0.22858632141266022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415260229","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29501823,0.0008755618,0.63559437,0.0061503057,0.00041895325,0.00034425643,0.00075400044,0.000707331,0.06013703],"genre_scores_gemma":[0.8458728,0.00053320365,0.13080795,0.00065788015,0.00008785397,0.00039070236,0.00042858545,0.00020032929,0.021020731],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993507,0.00033572153,0.00002640717,0.000092956965,0.00008116299,0.00011299044],"domain_scores_gemma":[0.99620014,0.0031294373,0.00018028033,0.000099160854,0.00014632846,0.0002446552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001550122,0.0011547667,0.0007615911,0.00039196762,0.0005548732,0.0013510558,0.0011344737,0.0018995209,0.008438642],"category_scores_gemma":[0.0072764605,0.000476642,0.00079493603,0.0003062866,0.0011811812,0.00202303,0.0018478542,0.0020500654,0.0004778065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022721596,0.0001329845,0.0017544191,0.00012748699,0.00004508469,0.00017893637,0.0001449194,0.91238946,0.00066235894,0.06344297,0.004315749,0.016578386],"study_design_scores_gemma":[0.000031688465,0.000039946117,0.0001705183,0.000018544737,0.000008929749,0.00002055903,0.000054937653,0.97294724,0.00018710775,0.02503362,0.001477786,0.000009021932],"about_ca_topic_score_codex":0.009681685,"about_ca_topic_score_gemma":0.013255464,"teacher_disagreement_score":0.009681685,"about_ca_system_score_codex":0.0013715468,"about_ca_system_score_gemma":0.0016768472,"threshold_uncertainty_score":0.028230071},"labels":[],"label_agreement":null},{"id":"W4415314677","doi":"10.1016/j.omega.2025.103445","title":"Fleet size planning in crowdsourced delivery: Balancing service level and driver utilization","year":2025,"lang":"en","type":"article","venue":"Omega","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Markov decision process; Fleet management; Sizing; Service (business); Function (biology); Service level; Process (computing); Matching (statistics)","score_opus":0.02703332678432519,"score_gpt":0.25610211119521065,"score_spread":0.22906878441088546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415314677","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.466285,0.000499084,0.51325786,0.0011119578,0.00020527215,0.00051537156,0.0005046602,0.000782734,0.016838085],"genre_scores_gemma":[0.97576547,0.0000673602,0.022013329,0.000051644,0.00002290607,0.00008253601,0.00011206873,0.000066434,0.00181824],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910647,0.00033479292,0.000031071773,0.00020252993,0.00014653886,0.00017861991],"domain_scores_gemma":[0.9968304,0.0021330728,0.0001932754,0.0001679145,0.0003557097,0.00031973244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002455136,0.000744441,0.00095051894,0.0010530414,0.0008060699,0.0016201949,0.00179834,0.0010305758,0.0035548478],"category_scores_gemma":[0.006820566,0.0007018336,0.0006078244,0.0010304084,0.0005477601,0.0021667266,0.0014312201,0.00077563967,0.0004721572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004227553,0.00026865426,0.0047330884,0.000108527405,0.00007691893,0.00009961913,0.00030852738,0.91660625,0.002412133,0.004556618,0.0019017812,0.06850509],"study_design_scores_gemma":[0.000031489584,0.00014051693,0.0024486592,0.000017603294,0.000035130106,0.000023802724,0.00040442197,0.9903627,0.00085613027,0.004810556,0.0008487965,0.000020159943],"about_ca_topic_score_codex":0.02201706,"about_ca_topic_score_gemma":0.025145482,"teacher_disagreement_score":0.02201706,"about_ca_system_score_codex":0.0023701706,"about_ca_system_score_gemma":0.0027341542,"threshold_uncertainty_score":0.043777823},"labels":[],"label_agreement":null},{"id":"W4415350142","doi":"10.33178/smj.2025.1.24","title":"Amusement park rides and cardiac devices: heart dropper or device stopper?","year":2025,"lang":"en","type":"article","venue":"UCC Student Medical Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Amusement; Theme park; Health care; Field (mathematics); Government (linguistics)","score_opus":0.012042225360147835,"score_gpt":0.3077583154269803,"score_spread":0.29571609006683247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415350142","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96994555,0.0054904106,0.00053351984,0.009989211,0.00037873033,0.00009943959,0.00052361545,0.000059731585,0.0129797375],"genre_scores_gemma":[0.9839717,0.0044981604,0.0011243096,0.0035838017,0.00031985104,0.000066623565,0.00037854188,0.000015859743,0.006041054],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99934715,0.0001911436,0.00008041566,0.00007999969,0.00014881822,0.00015250914],"domain_scores_gemma":[0.9984428,0.00021634773,0.00071306806,0.00003622906,0.00026065973,0.0003309156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057833537,0.00026170083,0.0003042096,0.00043543894,0.0010108906,0.00066669116,0.00055715605,0.0009683966,0.012887619],"category_scores_gemma":[0.0033186183,0.00018687769,0.0002769959,0.00043462534,0.00042733684,0.00087433186,0.0006109521,0.0006189629,0.0018384999],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021229066,0.0003359788,0.9165756,0.0005431143,0.00009787855,0.0014738733,0.0017351017,0.000048534606,0.00061097654,0.0001127778,0.014822399,0.063431546],"study_design_scores_gemma":[0.00003389151,0.00081535487,0.9361996,0.0012254457,0.000113731745,0.0067491108,0.023600828,0.00028386377,0.0003766567,0.00017875152,0.030385684,0.000036980342],"about_ca_topic_score_codex":0.012773491,"about_ca_topic_score_gemma":0.02910612,"teacher_disagreement_score":0.012887619,"about_ca_system_score_codex":0.00053694,"about_ca_system_score_gemma":0.00048248377,"threshold_uncertainty_score":0.04311341},"labels":[],"label_agreement":null},{"id":"W4415357299","doi":"10.2139/ssrn.5624450","title":"The Effect of eHMI Design on Cyclists’ Crossing behaviour When Interacting with Automated Vehicles in a Shared Space: A Virtual Reality Study","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Perception; Virtual reality; Time perception; Level crossing; Basis (linear algebra)","score_opus":0.016572703443301064,"score_gpt":0.3041771120656475,"score_spread":0.28760440862234643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415357299","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985769,0.00001721465,0.00074533396,0.000014345034,0.000005593956,0.000012449272,0.000023485492,0.000014043824,0.0005905917],"genre_scores_gemma":[0.9987852,0.000013994713,0.0007242427,0.0000091459515,0.0000031938173,0.000023720891,0.000029490457,0.000006482507,0.00040456504],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991345,0.0004114107,0.000046124373,0.00013410464,0.00011332855,0.0001606134],"domain_scores_gemma":[0.99345934,0.004440682,0.00066142174,0.00044099978,0.00041785586,0.00057966285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088125764,0.00049906294,0.00033131495,0.00036176504,0.00045737982,0.0012700326,0.00055286003,0.0010502638,0.0040943567],"category_scores_gemma":[0.00959119,0.00031231195,0.0003559347,0.00025186402,0.00046178015,0.0008242583,0.00092190126,0.0005775727,0.00041930383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.04025495,0.021576896,0.42536888,0.0020300983,0.0013973395,0.0019952212,0.037315026,0.054641183,0.26981702,0.0025608107,0.0016991841,0.14134334],"study_design_scores_gemma":[0.00071489956,0.03221708,0.8597511,0.00015501543,0.0013749562,0.00079035474,0.02599522,0.046609297,0.026013447,0.0015480351,0.0045800414,0.00025050587],"about_ca_topic_score_codex":0.0018153596,"about_ca_topic_score_gemma":0.0019083105,"teacher_disagreement_score":0.0040943567,"about_ca_system_score_codex":0.00032991925,"about_ca_system_score_gemma":0.00028906384,"threshold_uncertainty_score":0.013697028},"labels":[],"label_agreement":null},{"id":"W4415371181","doi":"10.3390/systems13100921","title":"Charging Decision Optimization Strategy for Shared Autonomous Electric Vehicles Considering Multi-Objective Conflicts: An Integrated Solution Process Combining Multi-Agent Simulation Model and Genetic Algorithm","year":2025,"lang":"en","type":"article","venue":"Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute on Governance","funders":"Specific Research Project of Guangxi for Research Bases and Talents; Natural Science Foundation of Ningbo; Natural Science Foundation of Zhejiang Province; Government of Jiangsu Province; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Battery (electricity); Genetic algorithm; Process (computing); State of charge; Optimization problem; Electric vehicle; Power (physics); Operator (biology); Demand response","score_opus":0.040889952296136504,"score_gpt":0.30124927453606143,"score_spread":0.2603593222399249,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415371181","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21010898,0.00029084194,0.78072923,0.00033254147,0.000047180154,0.0001433802,0.000054069205,0.000245842,0.008047934],"genre_scores_gemma":[0.9534243,0.0001398192,0.044515293,0.000048420734,0.000009323071,0.00016939531,0.00005401842,0.000023937793,0.001615577],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966204,0.00012607922,0.000015061262,0.000052154104,0.00006688346,0.00007785671],"domain_scores_gemma":[0.9993605,0.0003764117,0.00008463805,0.000022378716,0.00010670486,0.000049379156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009678326,0.0010481073,0.0012886267,0.00077558495,0.0007212369,0.0013829923,0.0010983616,0.0013393111,0.0011834444],"category_scores_gemma":[0.0015932423,0.00068389555,0.0010870228,0.0006826489,0.00072136754,0.0009856664,0.0011270521,0.00081843877,0.00010230346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000967875,0.000010502917,0.00019047795,0.0000057067546,0.000010262592,0.000020942516,0.000014369729,0.9970415,0.00014664436,0.000907398,0.000042005136,0.0016005784],"study_design_scores_gemma":[0.0000039695456,0.0000070657584,0.000026900936,8.4959356e-7,0.000003016029,0.0000016539072,0.0000073309047,0.99952555,0.00003784519,0.00034566462,0.00003879484,0.0000014187109],"about_ca_topic_score_codex":0.019394761,"about_ca_topic_score_gemma":0.009993708,"teacher_disagreement_score":0.019394761,"about_ca_system_score_codex":0.0013073874,"about_ca_system_score_gemma":0.002458703,"threshold_uncertainty_score":0.03856373},"labels":[],"label_agreement":null},{"id":"W4415402430","doi":"10.3390/vehicles7040121","title":"A Systematic Review of Sustainable Ground-Based Last-Mile Delivery of Parcels: Insights from Operations Research","year":2025,"lang":"en","type":"review","venue":"Vehicles","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École Nationale d'Administration Publique; Université du Québec à Montréal; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University","keywords":"Sustainability; Supply chain; Urban sustainability; Supply chain management; Systematic review; Sustainable transport","score_opus":0.04315415483972633,"score_gpt":0.3270911475486812,"score_spread":0.28393699270895484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415402430","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008581921,0.99607927,0.00058453326,0.00062986324,0.00014910355,0.00030701768,0.0007445844,0.000011294834,0.0006360341],"genre_scores_gemma":[0.009013812,0.9877378,0.0015425675,0.0005484996,0.000059909537,0.0005500989,0.0004478967,0.000010958598,0.00008852722],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.97467923,0.00912905,0.009811855,0.0015976848,0.0042000017,0.0005821906],"domain_scores_gemma":[0.8867828,0.08783163,0.012903898,0.0019571797,0.009738442,0.00078601803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019541422,0.0018885668,0.0073228655,0.021996826,0.00097466307,0.0048431223,0.002977707,0.0024098689,0.005319411],"category_scores_gemma":[0.113957025,0.0014280126,0.009640547,0.02495321,0.0016097218,0.004203188,0.0024698996,0.0020248494,0.00056878675],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010506701,0.000022978167,0.00061386713,0.91648614,0.0038698083,0.00008898233,0.0003120961,0.0003008523,0.00012984639,0.0011081209,0.0027735154,0.07418868],"study_design_scores_gemma":[0.00006530524,0.00013157619,0.0019491551,0.947623,0.01562126,0.00013381235,0.00048078637,0.0001084395,0.00014284613,0.00085185905,0.032858644,0.00003332915],"about_ca_topic_score_codex":0.017218247,"about_ca_topic_score_gemma":0.04741398,"teacher_disagreement_score":0.021996826,"about_ca_system_score_codex":0.006435861,"about_ca_system_score_gemma":0.03614996,"threshold_uncertainty_score":0.10334617},"labels":[],"label_agreement":null},{"id":"W4415427665","doi":"10.3233/faia251421","title":"Learning an Efficient Optimizer via Hybrid-Policy Sub-Trajectory Balance","year":2025,"lang":"en","type":"book-chapter","venue":"Frontiers in artificial intelligence and applications","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Key Research and Development Program of China; China Scholarship Council; National Natural Science Foundation of China; Danmarks Grundforskningsfond","keywords":"Flexibility (engineering); Inefficiency; Inference; Artificial neural network; Limiting; Domain (mathematical analysis); Optimization problem","score_opus":0.014530502695010964,"score_gpt":0.24809377048204773,"score_spread":0.23356326778703676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415427665","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011232505,0.00022860154,0.9848905,0.00018068113,0.000033341403,0.000042349508,0.00003837163,0.0009081914,0.0024454677],"genre_scores_gemma":[0.60701686,0.00040762176,0.38118273,0.0004841196,0.000106836014,0.00034595167,0.00035510756,0.00071564305,0.009385101],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99956554,0.000108261585,0.000024772426,0.00014265772,0.00009819892,0.00006052849],"domain_scores_gemma":[0.99914765,0.00051267183,0.00007087341,0.00011651277,0.00010404332,0.00004818769],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012130066,0.001248717,0.0010957886,0.00041944633,0.00038564316,0.0012277939,0.0015289051,0.0013544158,0.0036603787],"category_scores_gemma":[0.0035025566,0.0007658511,0.0006051683,0.0005236985,0.00093274924,0.001906857,0.0017240766,0.0021522974,0.0010653061],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000083645675,0.00007223482,0.0005484448,0.00006645172,0.000046251625,0.00006995745,0.00007530807,0.85525805,0.0035022707,0.018870682,0.0022082645,0.11919829],"study_design_scores_gemma":[0.000005475766,0.000012008175,0.000029394609,0.0000032460791,0.000003074352,0.000006627143,0.000003144876,0.99483573,0.0005124076,0.0043138685,0.00027257725,0.0000024038989],"about_ca_topic_score_codex":0.0037356103,"about_ca_topic_score_gemma":0.00374025,"teacher_disagreement_score":0.0037356103,"about_ca_system_score_codex":0.0010401187,"about_ca_system_score_gemma":0.0012148346,"threshold_uncertainty_score":0.012245178},"labels":[],"label_agreement":null},{"id":"W4415470364","doi":"10.22215/rcgl/241112","title":"Understanding the State of Accessible Taxi Vehicles and Shared Mobility Services in Atlantic Canada: A pilot project","year":2022,"lang":"","type":"report","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Transport Canada","keywords":"Taxis; Workaround; Limiting; Key (lock); Public transport; State (computer science); Disadvantage; Focus group","score_opus":0.10747391820540216,"score_gpt":0.2821786111892066,"score_spread":0.17470469298380448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415470364","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9814952,0.00028332626,0.000494396,0.0030424441,0.000023997123,0.00043714972,0.00039366126,0.000017352691,0.013812421],"genre_scores_gemma":[0.990877,0.00073126564,0.0018137062,0.0005416387,0.000005073625,0.00030896656,0.0002835799,0.000012130818,0.005426663],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9947254,0.00083758385,0.00013033001,0.00035682507,0.0017730553,0.0021768329],"domain_scores_gemma":[0.9878078,0.0021757816,0.0005540082,0.00038323127,0.006576507,0.002502657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0066340296,0.00041533203,0.00055122154,0.0018013648,0.019712806,0.0061958637,0.0026066839,0.00082123134,0.0035801902],"category_scores_gemma":[0.010837954,0.00055652444,0.0004917622,0.0038664092,0.005093435,0.0026529205,0.0047710706,0.0026158616,0.00018656433],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021314752,0.0010721621,0.2221919,0.00037780902,0.000049055634,0.0009570276,0.64724374,0.00056482217,0.0016149973,0.012053625,0.008355407,0.105306335],"study_design_scores_gemma":[0.000020070036,0.00015195011,0.11717861,0.00021740001,0.000043624168,0.0000715174,0.85391635,0.0008903622,0.00053447235,0.0005259001,0.026396634,0.00005315928],"about_ca_topic_score_codex":0.9972692,"about_ca_topic_score_gemma":0.9989403,"teacher_disagreement_score":0.17034292,"about_ca_system_score_codex":0.17034292,"about_ca_system_score_gemma":0.36156583,"threshold_uncertainty_score":0.9622846},"labels":[],"label_agreement":null},{"id":"W4415555217","doi":"10.1007/978-3-031-95115-2_8","title":"Conceptual Framework for Equitable Integration of Emerging Mobility Services and Public Transit","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Conceptual framework; Equity (law); Disadvantage; Public transport; Stakeholder; Population; Digital divide","score_opus":0.015189102886758125,"score_gpt":0.23637931572976423,"score_spread":0.2211902128430061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415555217","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01805586,0.0012051372,0.39626193,0.020296736,0.00037741763,0.00037635895,0.00025783232,0.00013723511,0.56303144],"genre_scores_gemma":[0.7724928,0.0016782103,0.1748384,0.0017171531,0.00035598906,0.0009457908,0.00028218745,0.00012187278,0.04756746],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977291,0.0009144911,0.000104417595,0.00031857583,0.00050769706,0.0004256804],"domain_scores_gemma":[0.9983804,0.00055150886,0.00019651072,0.00017482726,0.00039917996,0.00029751658],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004347236,0.0007066261,0.0004431059,0.0030635477,0.00387351,0.010737456,0.0032267913,0.0042144074,0.016380753],"category_scores_gemma":[0.0050415974,0.000535862,0.0009117828,0.0036463179,0.01044869,0.012360705,0.0061446317,0.0044530067,0.0012965112],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.424328e-7,0.000004064256,0.000027054903,0.0000023015425,5.435794e-7,0.00001054421,0.00009003451,0.0002297317,0.000011440318,0.99888366,0.00019424026,0.0005458048],"study_design_scores_gemma":[0.000009342782,0.00001422801,0.00022835351,0.00010652005,0.000009674718,0.000100886355,0.0014495652,0.004449999,0.000095435884,0.94969773,0.043828588,0.00000966029],"about_ca_topic_score_codex":0.01301241,"about_ca_topic_score_gemma":0.012742951,"teacher_disagreement_score":0.016380753,"about_ca_system_score_codex":0.0083916355,"about_ca_system_score_gemma":0.0099724345,"threshold_uncertainty_score":0.060885847},"labels":[],"label_agreement":null},{"id":"W4415555247","doi":"10.1007/978-3-031-95115-2_2","title":"Evaluation of Community Transit Systems with Different Levels of Flexibility","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Flexibility (engineering); Transit (satellite); Service (business); Public transport; Work (physics); Service level; Transit system; Range (aeronautics)","score_opus":0.04185783384626354,"score_gpt":0.25520277628306665,"score_spread":0.2133449424368031,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415555247","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9866448,0.00021132953,0.006301056,0.00015194056,0.000037502625,0.00033041224,0.00046388843,0.00017449584,0.0056845257],"genre_scores_gemma":[0.9967673,0.000044118195,0.0020518992,0.000007917822,0.0000068622044,0.00007820723,0.00023160328,0.000017432196,0.00079461397],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99604577,0.002313713,0.000121998724,0.00035535172,0.00062681,0.0005364072],"domain_scores_gemma":[0.98643386,0.0082401,0.00060318434,0.00071975926,0.0030173545,0.0009857133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005149852,0.0013956366,0.000993396,0.001956555,0.00084636325,0.0017776933,0.001686005,0.0015303567,0.007239944],"category_scores_gemma":[0.011460572,0.00033806515,0.00068789115,0.0017739303,0.0009752617,0.0019675724,0.0009899366,0.00084584847,0.00042391891],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.01468686,0.0030537832,0.00961236,0.0007195683,0.0003237384,0.0002028347,0.00025451023,0.8975065,0.0102247,0.0048922338,0.0022845317,0.056238465],"study_design_scores_gemma":[0.0010633175,0.010187769,0.009191204,0.000056576053,0.00031333766,0.00006822136,0.0007115127,0.9659304,0.00867487,0.0021929375,0.0015401951,0.00006958223],"about_ca_topic_score_codex":0.01792238,"about_ca_topic_score_gemma":0.0109743895,"teacher_disagreement_score":0.01792238,"about_ca_system_score_codex":0.0051303618,"about_ca_system_score_gemma":0.0021373436,"threshold_uncertainty_score":0.037223577},"labels":[],"label_agreement":null},{"id":"W4415586803","doi":"10.21083/crrf.v36i1.8099","title":"Closing the Gap: How 2+1 Roads can Save Time, Lives, and Money","year":2025,"lang":"","type":"article","venue":"Proceedings of the Canadian Rural Revitalization Foundation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"SAFER; Work (physics); Closing (real estate); Rural area; Highway system; Traffic flow (computer networking)","score_opus":0.008839333302618718,"score_gpt":0.21155222603732843,"score_spread":0.20271289273470972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415586803","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024547642,0.022137566,0.008772529,0.4904328,0.010310849,0.00015632421,0.000990187,0.0008424816,0.44180968],"genre_scores_gemma":[0.4137797,0.05264578,0.028384335,0.09787468,0.0021884819,0.0002934639,0.0016559757,0.00094254734,0.4022351],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99760395,0.00054568,0.00004401489,0.00018253447,0.000740199,0.0008836632],"domain_scores_gemma":[0.9981304,0.00031846578,0.00007210383,0.0001142531,0.00067705277,0.00068774074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033714878,0.0007561507,0.00040118778,0.0006280665,0.0072087264,0.0072753406,0.0016143381,0.004390798,0.036215402],"category_scores_gemma":[0.0050879386,0.00025325533,0.00065437757,0.0010412997,0.0041030184,0.008574769,0.0046808473,0.0028395066,0.006955748],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008848657,0.00009603093,0.0021014006,0.0005145975,0.000024936657,0.00040326713,0.005488108,0.0007710175,0.00060613826,0.16939998,0.62047553,0.20003055],"study_design_scores_gemma":[0.000009022672,0.000047103236,0.0015950862,0.00032460532,0.000011816635,0.00009414985,0.0053171385,0.0002046813,0.00016070492,0.014453813,0.9777581,0.00002374289],"about_ca_topic_score_codex":0.31469998,"about_ca_topic_score_gemma":0.5606946,"teacher_disagreement_score":0.6853,"about_ca_system_score_codex":0.010243205,"about_ca_system_score_gemma":0.028518293,"threshold_uncertainty_score":0.6257365},"labels":[],"label_agreement":null},{"id":"W4415587018","doi":"10.21083/crrf.v33i1.7891","title":"Protocol for Developing a Shuttle Service in Rural Communities | Protocole de Développement D’un service de Navette Dans les Communautés Rurales","year":2025,"lang":"","type":"article","venue":"Proceedings of the Canadian Rural Revitalization Foundation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Service (business); Rural area; Protocol (science); Service provider; Rural health","score_opus":0.04484141793827928,"score_gpt":0.3278482332086194,"score_spread":0.2830068152703401,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415587018","genre_codex":"methods","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"protocol","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01959057,0.00050066866,0.64008695,0.0176736,0.004076551,0.044257343,0.023022205,0.016321767,0.23447031],"genre_scores_gemma":[0.23745452,0.0014892924,0.3155987,0.016683597,0.0016836366,0.0865349,0.060119353,0.0051834635,0.27525255],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.98758763,0.0048849834,0.0019333046,0.00077407627,0.0031952565,0.0016246213],"domain_scores_gemma":[0.9645832,0.014516166,0.0020558126,0.0048317453,0.012024912,0.0019880745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01995084,0.0010947984,0.0011351007,0.0018245452,0.004837667,0.0051014083,0.0017114688,0.004552426,0.05224521],"category_scores_gemma":[0.028789975,0.0012100177,0.0009931765,0.001141931,0.0026004717,0.0049832035,0.008424812,0.0048512854,0.026807398],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021378233,0.00046838413,0.004000636,0.0013789306,0.00012457701,0.001864864,0.006059338,0.004189333,0.035006844,0.24312657,0.61314607,0.088496685],"study_design_scores_gemma":[0.00078189373,0.0003702835,0.0032336225,0.00058592827,0.000048848182,0.00051174517,0.002444862,0.018282793,0.011965352,0.01993113,0.9415609,0.0002825756],"about_ca_topic_score_codex":0.026129154,"about_ca_topic_score_gemma":0.015205498,"teacher_disagreement_score":0.05224521,"about_ca_system_score_codex":0.0047537875,"about_ca_system_score_gemma":0.013430446,"threshold_uncertainty_score":0.17477763},"labels":[],"label_agreement":null},{"id":"W4415916977","doi":"10.1080/14649357.2025.2574656","title":"Innovating for Uncertain Futures: How Transportation Planners in Toronto Adapt Planning and Institutional Processes in Anticipation of Automated Vehicles","year":2025,"lang":"en","type":"article","venue":"Planning Theory & Practice","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Technische Universität Wien Bibliothek; Technische Universität Wien; Daimler und Benz Stiftung","keywords":"Anticipation (artificial intelligence); Transportation planning; Urban planning; Strategic planning","score_opus":0.021398712614349037,"score_gpt":0.32939555874790105,"score_spread":0.307996846133552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415916977","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87711596,0.001105308,0.009462016,0.020643985,0.000082114835,0.00020534066,0.00012115689,0.000114978895,0.09114919],"genre_scores_gemma":[0.99424934,0.00042054435,0.0019031387,0.00017179249,0.000005188223,0.000030020416,0.00003777064,0.000016635771,0.003165525],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9953186,0.002997769,0.00007809706,0.0003349047,0.00033348642,0.0009371375],"domain_scores_gemma":[0.99462897,0.0025207738,0.00076410477,0.0002673679,0.0004393776,0.0013794936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005576746,0.00048053465,0.00022743898,0.00088285026,0.011784999,0.0101537295,0.00214339,0.0023283206,0.004322853],"category_scores_gemma":[0.012196798,0.00043126466,0.00039430978,0.0020377832,0.015950602,0.0045805275,0.007964139,0.0020800123,0.00035254884],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010938072,0.000078156045,0.026027493,0.00017277479,0.000043940603,0.0016170904,0.84660274,0.010330692,0.0006878174,0.072549485,0.0070077004,0.034772795],"study_design_scores_gemma":[0.000025027211,0.0000795307,0.017831853,0.0001772896,0.000035632973,0.0001266064,0.89935344,0.004385554,0.00030031867,0.01489937,0.062725246,0.000060082522],"about_ca_topic_score_codex":0.63780326,"about_ca_topic_score_gemma":0.84040815,"teacher_disagreement_score":0.36219674,"about_ca_system_score_codex":0.055277564,"about_ca_system_score_gemma":0.051298067,"threshold_uncertainty_score":0.7286596},"labels":[],"label_agreement":null},{"id":"W4416377562","doi":"10.1111/caje.70023","title":"VancUber: The long‐run effect of ride‐hailing on public transportation, congestion, and traffic fatalities","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Counterfactual thinking; Control (management); Construct (python library); Public transport; Estimation; Difference in differences","score_opus":0.04526016507272331,"score_gpt":0.17601466458103537,"score_spread":0.13075449950831206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416377562","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3495019,0.61563337,0.004737842,0.005165044,0.0018188846,0.00037954096,0.013584001,0.00011300185,0.009066353],"genre_scores_gemma":[0.9453131,0.047277946,0.0014101034,0.00079940615,0.0003480042,0.00034203433,0.0021071108,0.000024330953,0.002378066],"study_design_codex":"meta_analysis","study_design_gemma":"observational","domain_scores_codex":[0.9930743,0.004287624,0.00065335643,0.0007495163,0.00092102616,0.0003142066],"domain_scores_gemma":[0.9763333,0.01767546,0.0023796526,0.0010084652,0.0021332898,0.00046984994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012629568,0.0008979021,0.0022128841,0.0024444028,0.00044451022,0.0021129942,0.0010342282,0.0014900877,0.0036991197],"category_scores_gemma":[0.02537502,0.00047891313,0.012263775,0.0029030198,0.000794869,0.0006499779,0.0009958423,0.0026730772,0.00029353707],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.01369037,0.0006416655,0.26172152,0.04753735,0.5726842,0.00031681123,0.0005875363,0.009092601,0.00075099757,0.0037175056,0.008014824,0.08124455],"study_design_scores_gemma":[0.0021037762,0.0027415294,0.33732727,0.013799068,0.6118466,0.00022897629,0.00067605113,0.005943738,0.00182554,0.0033299322,0.020006869,0.00017062825],"about_ca_topic_score_codex":0.115105994,"about_ca_topic_score_gemma":0.09996496,"teacher_disagreement_score":0.884894,"about_ca_system_score_codex":0.0026556347,"about_ca_system_score_gemma":0.002412548,"threshold_uncertainty_score":0.228872},"labels":[],"label_agreement":null},{"id":"W4416926221","doi":"10.36939/cjur/vol30no--/art342","title":"Are big city urban planners preparing for autonomous vehicles?","year":2021,"lang":"","type":"article","venue":"Canadian journal of urban research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Urban planning; Politics; Public transport; Private sector; Public engagement","score_opus":0.11067636171616092,"score_gpt":0.32819805019536263,"score_spread":0.21752168847920172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416926221","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5978265,0.0043801153,0.004304467,0.18553288,0.0011689015,0.00031443805,0.0010215419,0.0002487628,0.20520237],"genre_scores_gemma":[0.9728473,0.0026472823,0.0014365817,0.005566026,0.00008250369,0.00006799078,0.00047613966,0.00007112643,0.016805146],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.99716103,0.0006529828,0.00004676853,0.00026979708,0.0005407819,0.0013287575],"domain_scores_gemma":[0.99147815,0.0011332438,0.0007708354,0.00034903383,0.0016284096,0.0046402197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036756457,0.00034715346,0.00029387197,0.0011471857,0.012218487,0.00811368,0.0015153664,0.0014364949,0.013284072],"category_scores_gemma":[0.010395607,0.0005787974,0.00026081555,0.0025849494,0.007294945,0.006300569,0.0035549542,0.0032262478,0.0015077199],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011977458,0.00015569256,0.117393866,0.00038488954,0.00004494527,0.0010339498,0.34132716,0.0011866378,0.0005459291,0.10611913,0.3003437,0.13134432],"study_design_scores_gemma":[0.000012372347,0.000023877954,0.029983798,0.00026203916,0.000018567745,0.00014696948,0.614865,0.00040830794,0.00015278137,0.009945359,0.34409967,0.00008120072],"about_ca_topic_score_codex":0.6855221,"about_ca_topic_score_gemma":0.78328085,"teacher_disagreement_score":0.6855221,"about_ca_system_score_codex":0.021784453,"about_ca_system_score_gemma":0.051616598,"threshold_uncertainty_score":0.6326599},"labels":[],"label_agreement":null},{"id":"W4416926333","doi":"10.36939/cjur/vol30no--/art356","title":"Just rides: Ride-hailing, the capabilities approach and the just city","year":2022,"lang":"","type":"article","venue":"Canadian journal of urban research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Solidarity; Flexibility (engineering); Empowerment; Economic Justice; Local government; Government (linguistics)","score_opus":0.10110877087408199,"score_gpt":0.30707321021192346,"score_spread":0.20596443933784148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416926333","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46118975,0.0049018967,0.005737099,0.05086557,0.000272268,0.000051505547,0.0001215174,0.00003961617,0.4768208],"genre_scores_gemma":[0.9903335,0.0006582205,0.00023137651,0.00037272667,0.000011715359,0.0000073186957,0.000014483239,0.000007093604,0.008363556],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986034,0.0006087297,0.000022311022,0.000079049074,0.00015102133,0.0005354819],"domain_scores_gemma":[0.99902713,0.00027601648,0.00011797982,0.000057349927,0.00014770294,0.00037377345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009916773,0.00029065393,0.00016164318,0.0011015382,0.010013433,0.0085240565,0.0006672645,0.0013696222,0.005975967],"category_scores_gemma":[0.0016442068,0.00015055276,0.00019575084,0.0011740145,0.025875406,0.0066610486,0.0062653464,0.0017165533,0.0003382223],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023482206,0.000024836047,0.0070782234,0.00011690803,0.000010729244,0.0008472053,0.27926412,0.00038595806,0.00020253059,0.68865526,0.008619254,0.014771465],"study_design_scores_gemma":[0.000007063394,0.00003224479,0.008205943,0.0002127387,0.000014479702,0.00038428803,0.72055703,0.0003744503,0.00022630308,0.06733785,0.2026124,0.000035301884],"about_ca_topic_score_codex":0.20863761,"about_ca_topic_score_gemma":0.43222302,"teacher_disagreement_score":0.20863761,"about_ca_system_score_codex":0.015497672,"about_ca_system_score_gemma":0.008866522,"threshold_uncertainty_score":0.41484636},"labels":[],"label_agreement":null},{"id":"W4416926336","doi":"10.36939/cjur/vol32no1/art401","title":"Une analyse médiatique de l’accueil des nouvelles mobilités à Montréal : De Communauto aux Trottinettes","year":2023,"lang":"","type":"article","venue":"Canadian journal of urban research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Context (archaeology); Gender relations; Social innovation","score_opus":0.08680612788532718,"score_gpt":0.3454864750576509,"score_spread":0.2586803471723237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416926336","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7156961,0.006384129,0.0031109606,0.012703491,0.0002034134,0.00018679706,0.0031286888,0.00009104439,0.25849542],"genre_scores_gemma":[0.9588084,0.002776794,0.00089992105,0.00041182237,0.000055248867,0.00011243028,0.00047835053,0.00006972864,0.036387373],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.99831176,0.00039681984,0.00004580622,0.00024688756,0.00059268984,0.00040603956],"domain_scores_gemma":[0.9942545,0.0025361767,0.0006838114,0.00021576897,0.001836977,0.00047276128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001844479,0.0004301405,0.00028472065,0.003638831,0.0061040097,0.0082221925,0.0010843647,0.00088338624,0.01463815],"category_scores_gemma":[0.007739796,0.00031285227,0.00033161166,0.009212952,0.0064487224,0.0036103912,0.0027431378,0.0012248509,0.00054748607],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022884665,0.000056288805,0.06840896,0.0011841255,0.00012490946,0.001586898,0.58644086,0.002170455,0.0032820776,0.2146863,0.021298677,0.10053163],"study_design_scores_gemma":[0.000020387897,0.000062798965,0.2591427,0.0011679815,0.00012455843,0.000177506,0.34667677,0.0010509302,0.0017581536,0.0036911203,0.3859874,0.00013968734],"about_ca_topic_score_codex":0.9025142,"about_ca_topic_score_gemma":0.9313873,"teacher_disagreement_score":0.09748578,"about_ca_system_score_codex":0.054905917,"about_ca_system_score_gemma":0.03555746,"threshold_uncertainty_score":0.39837223},"labels":[],"label_agreement":null},{"id":"W4417273534","doi":"10.2139/ssrn.5869303","title":"Running on Empty? Reference Dependence and V-Shaped Decisions in Shared E-Bike User Choice","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Benchmark (surveying); Context (archaeology); Choice set; Bridging (networking); Salient; Decision theory; Prospect theory; Expected utility hypothesis; Core (optical fiber)","score_opus":0.02612710951245922,"score_gpt":0.2928364304353822,"score_spread":0.266709320922923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417273534","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94563705,0.00029262257,0.03023403,0.0016117673,0.00002286166,0.00003218515,0.000173308,0.000060556555,0.021935634],"genre_scores_gemma":[0.99701357,0.000043235963,0.000788549,0.000056517063,0.0000073532015,0.00000848881,0.000028969785,0.000013276521,0.0020401517],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99750865,0.0013300822,0.00008492105,0.00040457313,0.00018589121,0.0004859709],"domain_scores_gemma":[0.9611741,0.030749368,0.0024999843,0.0020344383,0.0011893087,0.0023527078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052557616,0.0003077686,0.0014399814,0.0007235194,0.00095423695,0.004046484,0.0016021598,0.0031760142,0.018057378],"category_scores_gemma":[0.0400088,0.00087902014,0.0008327371,0.0012287602,0.0020828706,0.0046048877,0.0020096018,0.0029340896,0.0012671279],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0056469915,0.0012281502,0.098022036,0.00027981453,0.0004422439,0.0015476446,0.0056132027,0.055880487,0.0045317938,0.75583124,0.0036047648,0.06737157],"study_design_scores_gemma":[0.00024047286,0.00045083457,0.039449997,0.000060810395,0.00013229079,0.0002700753,0.0043159192,0.15320516,0.0008920602,0.7994262,0.0014460771,0.00011013357],"about_ca_topic_score_codex":0.007447562,"about_ca_topic_score_gemma":0.006246659,"teacher_disagreement_score":0.018057378,"about_ca_system_score_codex":0.00123619,"about_ca_system_score_gemma":0.0009082201,"threshold_uncertainty_score":0.060407937},"labels":[],"label_agreement":null},{"id":"W4417339329","doi":"10.1109/gcaiot68269.2025.11275553","title":"Agentic AI for Personalized Trip Planning","year":2025,"lang":"","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"King Fahd University of Petroleum and Minerals","keywords":"Personalization; Stability (learning theory); Similarity (geometry); Compromise; Automated planning and scheduling","score_opus":0.026814856525462064,"score_gpt":0.3197264130262176,"score_spread":0.29291155650075557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417339329","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022743462,0.0004112088,0.95826054,0.0005395378,0.00008887868,0.00014519283,0.00021969927,0.0040276223,0.013563831],"genre_scores_gemma":[0.53284055,0.0005687201,0.4593231,0.00028675003,0.000043812415,0.00021045086,0.0006295132,0.0002747172,0.005822378],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995454,0.00017904944,0.00003098101,0.00007526493,0.00013882341,0.000030434907],"domain_scores_gemma":[0.9991297,0.00046613094,0.000054780212,0.00017839528,0.00012266144,0.00004830917],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086512044,0.00052538374,0.00027485585,0.0003870711,0.00043431306,0.0011203383,0.0010695114,0.0006860871,0.0044036927],"category_scores_gemma":[0.0024790766,0.00031614563,0.00067397335,0.0003869265,0.0005951832,0.0011977153,0.0010786523,0.0012465067,0.00089816435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000229639,0.00022129166,0.0028718528,0.0004925774,0.00019046958,0.00035424312,0.00068277627,0.68127584,0.019291075,0.072433025,0.011167839,0.21078926],"study_design_scores_gemma":[0.000016924389,0.000054928973,0.00023177185,0.000023125574,0.00003402658,0.00006197123,0.00008592431,0.9595475,0.0026159517,0.02453982,0.012775122,0.000013070087],"about_ca_topic_score_codex":0.0065147514,"about_ca_topic_score_gemma":0.008907329,"teacher_disagreement_score":0.0065147514,"about_ca_system_score_codex":0.0008099619,"about_ca_system_score_gemma":0.0011121337,"threshold_uncertainty_score":0.014731765},"labels":[],"label_agreement":null},{"id":"W50973252","doi":"","title":"Typology of Carsharing Members","year":2011,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Typology; Geography; General partnership; Order (exchange); Business; Transport engineering; Marketing; Engineering; Finance","score_opus":0.017154057696744232,"score_gpt":0.21745075850538506,"score_spread":0.20029670080864082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W50973252","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9806025,0.0004496631,0.004591025,0.00021438063,0.000026333519,0.00021615603,0.0012843006,0.00008825644,0.012527326],"genre_scores_gemma":[0.9914704,0.00033997046,0.0029353553,0.0000254685,0.000012654198,0.00014798496,0.0015121339,0.000028429295,0.0035276858],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975804,0.00047579003,0.0002426957,0.0003556054,0.0010143741,0.0003310219],"domain_scores_gemma":[0.9928276,0.0021247456,0.0014570748,0.0006172414,0.002110828,0.00086249167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012633487,0.00040617175,0.0003309983,0.0071302876,0.0015075929,0.0023237716,0.0013848837,0.00056303793,0.0042352118],"category_scores_gemma":[0.0068152673,0.00022987639,0.0003682386,0.007269575,0.0010572376,0.0019156474,0.0015367811,0.00033599834,0.0009078122],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021421214,0.00014931515,0.8817254,0.00029797686,0.00008721953,0.0010839351,0.033574566,0.0019226783,0.0036013005,0.006087459,0.0046459488,0.06660997],"study_design_scores_gemma":[0.000014224112,0.00022041194,0.7723557,0.00031413013,0.00005800973,0.0025223498,0.14213549,0.012768333,0.0026219322,0.003926694,0.06293686,0.00012583546],"about_ca_topic_score_codex":0.019842723,"about_ca_topic_score_gemma":0.018974464,"teacher_disagreement_score":0.98015726,"about_ca_system_score_codex":0.0016283758,"about_ca_system_score_gemma":0.0011135553,"threshold_uncertainty_score":0.03945446},"labels":[],"label_agreement":null},{"id":"W52101158","doi":"10.1609/socs.v2i1.18197","title":"Repeated-Task Canadian Traveler Problem","year":2021,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Combinatorial Search","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Heuristics; Disjoint sets; Computer science; Task (project management); Mathematical optimization; Fraction (chemistry); Path (computing); Tree traversal; Graph; Mathematics; Algorithm; Theoretical computer science; Combinatorics","score_opus":0.01008616326361533,"score_gpt":0.21989138575806066,"score_spread":0.20980522249444533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W52101158","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20850097,0.001844168,0.5445978,0.008518543,0.00083579635,0.0025789551,0.017328627,0.0043212282,0.21147391],"genre_scores_gemma":[0.7038541,0.0010406132,0.20628496,0.0009994007,0.00013850754,0.00066571176,0.010042117,0.0006789718,0.0762957],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982546,0.0002906656,0.00004816703,0.0004237195,0.00032656858,0.0006562499],"domain_scores_gemma":[0.9984755,0.00051861483,0.000102852304,0.00014518712,0.00032965577,0.0004282073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012048779,0.0017848307,0.0017031676,0.0010195859,0.0035362744,0.0025183798,0.0044093262,0.0032638886,0.030393226],"category_scores_gemma":[0.0039468464,0.0006591414,0.0012629571,0.0029606025,0.001739679,0.0031192373,0.0019557367,0.0021758056,0.0019770062],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000887533,0.00046310044,0.0026151382,0.00075105316,0.00021597093,0.0009157395,0.00060339976,0.5437116,0.0019719081,0.2008304,0.12677684,0.120257296],"study_design_scores_gemma":[0.00027454674,0.00017067425,0.0018424087,0.000067476685,0.00012501917,0.0005164421,0.00088797655,0.82466686,0.001992116,0.08753926,0.08176744,0.00014982397],"about_ca_topic_score_codex":0.53425974,"about_ca_topic_score_gemma":0.5538508,"teacher_disagreement_score":0.46574026,"about_ca_system_score_codex":0.009818973,"about_ca_system_score_gemma":0.020492125,"threshold_uncertainty_score":0.9369662},"labels":[],"label_agreement":null},{"id":"W52155069","doi":"10.1007/978-3-642-56423-9_15","title":"Adaptive Memory Programming for a Class of Demand Responsive Transit Systems","year":2001,"lang":"en","type":"book-chapter","venue":"Lecture notes in economics and mathematical systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Schedule; Mathematical optimization; Heuristic; Set (abstract data type); Public transport; Class (philosophy); Service (business); Order (exchange); Operations research; Distributed computing; Engineering; Transport engineering; Artificial intelligence; Mathematics; Economics","score_opus":0.01805864478256067,"score_gpt":0.2153114538528881,"score_spread":0.19725280907032744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W52155069","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03972138,0.00095009245,0.94170874,0.0012107621,0.00012405399,0.00007833589,0.0002240273,0.00021184966,0.01577065],"genre_scores_gemma":[0.8846626,0.0017868865,0.06530753,0.00043215553,0.00036001526,0.00038559444,0.00031856552,0.00014138753,0.046605192],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999564,0.00013569172,0.000016329697,0.00010956076,0.00006815412,0.00010623693],"domain_scores_gemma":[0.9983388,0.0012207108,0.00013837447,0.00006467803,0.00014090262,0.00009639461],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011362745,0.0012985491,0.0014316522,0.0005002257,0.0004986925,0.0018392254,0.0018890711,0.001995908,0.0061735543],"category_scores_gemma":[0.004457583,0.00056401175,0.0010089773,0.0008075258,0.0011731873,0.0015858231,0.0012688248,0.0025993155,0.0003730011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013055948,0.00008546767,0.0003491352,0.00018059045,0.00007233245,0.00015919626,0.00013064007,0.59046847,0.0014439061,0.3758373,0.005633286,0.02550922],"study_design_scores_gemma":[0.000019051351,0.000026065476,0.000056501467,0.000007795146,0.000010097101,0.000017075436,0.000015589421,0.91534275,0.00010492823,0.08384926,0.00054331904,0.0000075791877],"about_ca_topic_score_codex":0.003596349,"about_ca_topic_score_gemma":0.0024559093,"teacher_disagreement_score":0.0061735543,"about_ca_system_score_codex":0.0011009228,"about_ca_system_score_gemma":0.0010037988,"threshold_uncertainty_score":0.020652592},"labels":[],"label_agreement":null},{"id":"W560587873","doi":"","title":"Acheson Industrial Area Transit Feasibility Study: A Case for Vanpools","year":2013,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Service (business); Transport engineering; Subsidy; Business; Transit (satellite); Public transport; Work (physics); Finance; Engineering; Economics; Marketing","score_opus":0.11742289013247034,"score_gpt":0.28110914168682594,"score_spread":0.1636862515543556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W560587873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87870085,0.00026845193,0.002889052,0.005516346,0.000057523914,0.001066591,0.00030482752,0.000038112874,0.111158274],"genre_scores_gemma":[0.9692384,0.00039149768,0.0039498517,0.0010188434,0.000031081014,0.00052499754,0.0002640964,0.0000318815,0.024549361],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99571276,0.0018087048,0.000110677516,0.00037421088,0.00060455746,0.0013892461],"domain_scores_gemma":[0.9918276,0.0045539904,0.00044594772,0.00037481292,0.0017043744,0.0010932861],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00508183,0.0003895814,0.00030384323,0.0014844764,0.0051729307,0.004091962,0.0020039883,0.0025494047,0.01491682],"category_scores_gemma":[0.009902261,0.0006429502,0.0008299272,0.0014994199,0.0016351101,0.0027468605,0.0027048357,0.0025413167,0.0006763067],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027134262,0.0059907823,0.21436147,0.0017496449,0.0002187588,0.13362004,0.065995015,0.031129858,0.008936083,0.35320586,0.049350545,0.13272847],"study_design_scores_gemma":[0.00082547934,0.006400152,0.120472156,0.0015278695,0.00025605748,0.015574578,0.41165358,0.042562462,0.004253377,0.024595164,0.37151134,0.00036791185],"about_ca_topic_score_codex":0.12131896,"about_ca_topic_score_gemma":0.24008864,"teacher_disagreement_score":0.12131896,"about_ca_system_score_codex":0.0068693585,"about_ca_system_score_gemma":0.010640441,"threshold_uncertainty_score":0.2412256},"labels":[],"label_agreement":null},{"id":"W562354095","doi":"","title":"SMART MODERN TIMES","year":2004,"lang":"en","type":"article","venue":"EUROTRANSPORT","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Smart card; Public transport; Business; Climate change; Telecommunications; Commerce; Engineering; Computer security; Computer science; Transport engineering","score_opus":0.010626679477363867,"score_gpt":0.2053032478882095,"score_spread":0.19467656841084563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W562354095","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009456487,0.024878388,0.0036649143,0.10038378,0.016790459,0.000049128572,0.0012290404,0.00047148182,0.84307635],"genre_scores_gemma":[0.14311491,0.028246876,0.0043420023,0.038151566,0.006257766,0.000112561014,0.0014979587,0.00033134085,0.77794504],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99936014,0.0001258881,0.000030479685,0.00010705424,0.0002195379,0.00015682321],"domain_scores_gemma":[0.99939215,0.000084193365,0.000072984156,0.00009773421,0.00011665704,0.00023625024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083236815,0.00054672704,0.0002448091,0.00069268956,0.003159297,0.008418131,0.00043159735,0.0022472527,0.067459136],"category_scores_gemma":[0.0026316978,0.00015903014,0.00026640345,0.0014173419,0.0018777989,0.0072916793,0.0033571238,0.003358088,0.018048894],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044822635,0.000018718922,0.00089733506,0.00012388373,0.000010583859,0.00015706857,0.0030491778,0.00011265261,0.00046138922,0.30122057,0.600558,0.09334586],"study_design_scores_gemma":[0.0000010659949,0.0000051510774,0.00042439025,0.000029084653,0.0000013307741,0.00004776403,0.00053393695,0.000019602505,0.000037387592,0.006168303,0.99272835,0.00000361189],"about_ca_topic_score_codex":0.002566121,"about_ca_topic_score_gemma":0.005988326,"teacher_disagreement_score":0.067459136,"about_ca_system_score_codex":0.0017055195,"about_ca_system_score_gemma":0.0017186285,"threshold_uncertainty_score":0.22567332},"labels":[],"label_agreement":null},{"id":"W562736115","doi":"","title":"Entry Controls in Taxi Regulation: Lessons from North American Experience","year":2007,"lang":"en","type":"article","venue":"Transportation Research Board 86th Annual MeetingTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Control (management); Barriers to entry; Business; Quality (philosophy); Service (business); Industrial organization; Economics; Marketing; Transport engineering; Engineering; Market structure","score_opus":0.050758564204109145,"score_gpt":0.3773184383694673,"score_spread":0.3265598741653582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W562736115","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85045326,0.0034029041,0.0023207008,0.04322371,0.00015201067,0.000068921,0.00010789703,0.000029200553,0.1002415],"genre_scores_gemma":[0.98787934,0.0020302378,0.00049034395,0.002810715,0.00003861697,0.000037332637,0.000044045053,0.000020496102,0.0066488897],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.9943288,0.0026500463,0.00016884992,0.00036804655,0.0012354085,0.0012489891],"domain_scores_gemma":[0.98969346,0.0060193464,0.00060588575,0.0004533709,0.0021706473,0.0010573756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0065245638,0.00013902652,0.00030426847,0.0005868294,0.0066207224,0.004259978,0.0011115919,0.001544366,0.0023885746],"category_scores_gemma":[0.011159263,0.00026034625,0.00027856746,0.0021210932,0.005410904,0.0020774277,0.0019166562,0.0037748073,0.0001648976],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020745657,0.001539835,0.24636964,0.00024942725,0.00006831605,0.0018658546,0.3434964,0.0053075217,0.00065538206,0.16347758,0.050669067,0.18609358],"study_design_scores_gemma":[0.00009733353,0.0004006569,0.22285858,0.00065771077,0.00006911617,0.00065239385,0.39490587,0.003034317,0.0012436222,0.016099077,0.35978487,0.00019644786],"about_ca_topic_score_codex":0.6388906,"about_ca_topic_score_gemma":0.78266346,"teacher_disagreement_score":0.36110938,"about_ca_system_score_codex":0.019012757,"about_ca_system_score_gemma":0.018212983,"threshold_uncertainty_score":0.726472},"labels":[],"label_agreement":null},{"id":"W565555005","doi":"","title":"Dark clouds over Ontario Northland : will 2012 be the final year for ONR passengers?","year":2012,"lang":"en","type":"article","venue":"Passenger train journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Aeronautics; Engineering","score_opus":0.03384397389460867,"score_gpt":0.2518678431196587,"score_spread":0.21802386922505004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W565555005","genre_codex":"empirical","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4040095,0.0047913566,0.000565144,0.3727329,0.009165793,0.00014917042,0.017557539,0.00028006258,0.1907486],"genre_scores_gemma":[0.7274727,0.0027510722,0.0005425902,0.023812793,0.000880715,0.00008355369,0.0051119654,0.0001815454,0.23916295],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990828,0.000028250055,0.000012561975,0.000046544497,0.00022265171,0.0006072484],"domain_scores_gemma":[0.9976267,0.000041897685,0.0001597679,0.000029707586,0.0005960899,0.0015459104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061808864,0.00028932688,0.0002536328,0.00034324452,0.008495616,0.0050032414,0.000777562,0.0032271163,0.029440634],"category_scores_gemma":[0.00179755,0.00027505663,0.00033234246,0.00073778105,0.0011941424,0.0018360295,0.0018192086,0.0030532195,0.002874315],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037897166,0.00009154302,0.10562588,0.00021520708,0.000044358934,0.0013388713,0.010743974,0.00022745969,0.0013762158,0.0065266406,0.8497166,0.023714228],"study_design_scores_gemma":[0.000022321688,0.00004801227,0.29198518,0.00022873786,0.000024304043,0.00016305897,0.049156126,0.00021382736,0.0002609248,0.00066787924,0.65717256,0.00005709123],"about_ca_topic_score_codex":0.94994587,"about_ca_topic_score_gemma":0.99252206,"teacher_disagreement_score":0.050054133,"about_ca_system_score_codex":0.024951015,"about_ca_system_score_gemma":0.042825215,"threshold_uncertainty_score":0.18103307},"labels":[],"label_agreement":null},{"id":"W569481912","doi":"","title":"Modeling Commuting Mode Choice with Explicit Consideration of Carpools in the Choice Formation: A Case Study in Alberta","year":2011,"lang":"en","type":"article","venue":"Transportation Research Board 90th Annual MeetingTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Carpool; Mode choice; Context (archaeology); Transport engineering; Set (abstract data type); Computer science; Mode (computer interface); Operations research; Choice set; Engineering; Econometrics; Economics; Public transport; Geography","score_opus":0.1351558440441011,"score_gpt":0.3823510677656856,"score_spread":0.2471952237215845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W569481912","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99401265,0.0000577943,0.0028274956,0.00014426842,0.0000036037961,0.000043293236,0.00009531486,0.000010698407,0.0028049124],"genre_scores_gemma":[0.9911951,0.00010738222,0.004420063,0.000024473808,0.0000030738702,0.000038410537,0.00017838531,0.000006589266,0.0040265187],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9993999,0.000312022,0.000014779209,0.00007213318,0.00005518062,0.00014598412],"domain_scores_gemma":[0.9980355,0.0014952887,0.00008005585,0.00006774951,0.00017652755,0.00014479122],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013643217,0.00044060106,0.00036209193,0.0004896433,0.0012608729,0.0017643119,0.0014789855,0.0010285106,0.0029526479],"category_scores_gemma":[0.0026963109,0.00033050985,0.0007104872,0.0011964662,0.00075261947,0.00068125036,0.0010108497,0.000994117,0.00015308885],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008854764,0.0025160452,0.2408985,0.00012796176,0.00018028007,0.0022861545,0.0041681607,0.6826575,0.0019569925,0.027346859,0.001963693,0.035012323],"study_design_scores_gemma":[0.000075333184,0.00024444034,0.04940331,0.000025600042,0.0000874734,0.000058764286,0.008016503,0.93555397,0.0004992236,0.0033417519,0.0026369174,0.00005680311],"about_ca_topic_score_codex":0.77612114,"about_ca_topic_score_gemma":0.8459438,"teacher_disagreement_score":0.22387886,"about_ca_system_score_codex":0.008837977,"about_ca_system_score_gemma":0.0058759414,"threshold_uncertainty_score":0.45039463},"labels":[],"label_agreement":null},{"id":"W576380228","doi":"","title":"Assessing Greenhouse Gas Emission Impacts from Carsharing in North America: Theoretical and Methodological Design","year":2008,"lang":"en","type":"article","venue":"15th World Congress on Intelligent Transport Systems and ITS America's 2008 Annual MeetingITS AmericaERTICOITS JapanTransCore","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; Truck; Transport engineering; Business; Plan (archaeology); Environmental economics; Geography; Engineering; Economics","score_opus":0.05377779086786014,"score_gpt":0.28829019100724357,"score_spread":0.23451240013938343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W576380228","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.334327,0.002003424,0.6104589,0.0017466852,0.000082788676,0.01815015,0.0014417266,0.00014757874,0.03164174],"genre_scores_gemma":[0.50107336,0.0016870132,0.4493633,0.000458628,0.00003525612,0.043447718,0.0007580089,0.000040727602,0.003136033],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98148364,0.014651631,0.00062504684,0.0014543803,0.0013253931,0.00045999032],"domain_scores_gemma":[0.98454976,0.010701815,0.0012631943,0.000711697,0.0025880407,0.00018541554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01963401,0.0010788311,0.00094851514,0.003174383,0.0025055134,0.002673826,0.001985731,0.0012479519,0.003236794],"category_scores_gemma":[0.024195306,0.0011266968,0.0017175612,0.004691046,0.0026351556,0.0016310402,0.0028828527,0.0012386516,0.00017787586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00086751656,0.002856073,0.14349358,0.0041121035,0.0015197948,0.00088493293,0.01169196,0.17454705,0.0050717304,0.36937732,0.0030108844,0.2825671],"study_design_scores_gemma":[0.0018579558,0.005970456,0.14295885,0.0017974545,0.0024801418,0.0006448403,0.06321738,0.36191696,0.014551667,0.30694175,0.09725612,0.00040652987],"about_ca_topic_score_codex":0.052246585,"about_ca_topic_score_gemma":0.059770398,"teacher_disagreement_score":0.052246585,"about_ca_system_score_codex":0.0100418925,"about_ca_system_score_gemma":0.010291492,"threshold_uncertainty_score":0.103884935},"labels":[],"label_agreement":null},{"id":"W578537992","doi":"","title":"2006 Paratransit Survey: Paratransit Providers Strive to Balance Costs & Demand","year":2006,"lang":"en","type":"article","venue":"Metrologia","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Paratransit; Quarter (Canadian coin); Baby boomers; Business; Public transport; Demographics; Private sector; Survey data collection; Service (business); Balance (ability); Demographic economics; Transport engineering; Marketing; Economics; Geography; Economic growth; Engineering; Demography; Statistics; Medicine; Mathematics","score_opus":0.009891807853657432,"score_gpt":0.2208295053853122,"score_spread":0.21093769753165478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W578537992","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5002072,0.00062679115,0.0011902724,0.0038359195,0.00016310254,0.0007813102,0.394955,0.00042745602,0.09781292],"genre_scores_gemma":[0.62473726,0.002297003,0.0037864102,0.002361444,0.00013619148,0.00092881033,0.27089846,0.00019007208,0.09466421],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99930286,0.00005398149,0.000041395044,0.00006705994,0.00041372806,0.00012107521],"domain_scores_gemma":[0.9946315,0.0002725876,0.0008634921,0.00010733115,0.0034681945,0.00065689825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005592443,0.00018504921,0.00016060064,0.0013560401,0.0007615279,0.0006635911,0.0005279668,0.000277391,0.014400685],"category_scores_gemma":[0.002573054,0.00019195936,0.0001831918,0.0041212062,0.00012894071,0.0004690062,0.00042574634,0.000620889,0.0050074444],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012390727,0.00018647841,0.49428794,0.00020856448,0.000017571578,0.000095990596,0.0008532159,0.0003650245,0.0005378777,0.00042151962,0.4614077,0.041494247],"study_design_scores_gemma":[0.000018051483,0.00008096528,0.8147395,0.000071614784,0.000010472755,0.00016893806,0.0017928225,0.00042424593,0.00031975852,0.000051365663,0.18230806,0.0000141885685],"about_ca_topic_score_codex":0.296431,"about_ca_topic_score_gemma":0.49274042,"teacher_disagreement_score":0.296431,"about_ca_system_score_codex":0.0034485448,"about_ca_system_score_gemma":0.0056376597,"threshold_uncertainty_score":0.58941114},"labels":[],"label_agreement":null},{"id":"W583641091","doi":"","title":"Where next for London's route master?","year":2006,"lang":"en","type":"article","venue":"BUSES","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Public transport; Service (business); Bridge (graph theory); Engineering; Level of service; Bus priority; Telecommunications; Business","score_opus":0.021479947598247572,"score_gpt":0.21794170841973753,"score_spread":0.19646176082148997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W583641091","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029368282,0.015777934,0.0014250231,0.11241923,0.020163037,0.00010704851,0.0011462593,0.0011071219,0.8449174],"genre_scores_gemma":[0.007808291,0.0040849745,0.0005967517,0.007702017,0.0005326872,0.000020641524,0.0003129303,0.0001945884,0.97874707],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99955016,0.000075799784,0.000029199822,0.00007010801,0.00013264091,0.00014206227],"domain_scores_gemma":[0.99940264,0.000031000876,0.00003852029,0.000036692054,0.00016902183,0.00032218613],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00033714995,0.00051624863,0.00033941228,0.00076807773,0.0023005984,0.0049920916,0.00063818647,0.00270887,0.3694027],"category_scores_gemma":[0.0011509696,0.0002814131,0.00035505882,0.0009667829,0.000753154,0.0045007337,0.0020529414,0.0015565598,0.14976923],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019968988,0.000007875635,0.00032857346,0.00012694205,0.0000021706674,0.00025765787,0.00043050348,0.000026446838,0.00018731624,0.005011855,0.9420839,0.051516794],"study_design_scores_gemma":[0.000001251536,0.000004014907,0.00016796715,0.000038224258,5.939698e-7,0.00005679917,0.00041759384,0.0000040229866,0.000017138758,0.00013167986,0.99915814,0.00000261121],"about_ca_topic_score_codex":0.021731874,"about_ca_topic_score_gemma":0.10418032,"teacher_disagreement_score":0.3694027,"about_ca_system_score_codex":0.002458047,"about_ca_system_score_gemma":0.0026417798,"threshold_uncertainty_score":0.8994705},"labels":[],"label_agreement":null},{"id":"W584762287","doi":"","title":"FAR North Transit: Dependable Mobility in Northernmost Minnesota","year":2013,"lang":"en","type":"article","venue":"Community Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Public transport; Transit (satellite); State (computer science); Service (business); Service provider; Asset (computer security); Business; Transport engineering; Geography; Engineering; Computer science; Marketing; Computer security","score_opus":0.01534782386700835,"score_gpt":0.20805184452515338,"score_spread":0.19270402065814501,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W584762287","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75231266,0.012072621,0.0019288904,0.055197574,0.0024142617,0.000058949307,0.0007130204,0.00010656866,0.17519552],"genre_scores_gemma":[0.8561781,0.011788626,0.0013014858,0.00298176,0.00032017942,0.000030502615,0.00030566333,0.000052502874,0.1270412],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998863,0.000025818628,0.000004578735,0.000021728985,0.00002274528,0.00003888979],"domain_scores_gemma":[0.99977845,0.000027953649,0.000031037267,0.000005665366,0.000043324573,0.00011355927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019666023,0.000108090375,0.000069707516,0.00019645349,0.002772704,0.0017595012,0.00035864103,0.00040137177,0.0038292645],"category_scores_gemma":[0.00037427523,0.00009309771,0.00007455729,0.00040016585,0.00070105615,0.0007857636,0.000904131,0.00057936093,0.00033087275],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017471604,0.00017439011,0.1903081,0.0010365108,0.00003312794,0.011284057,0.14526983,0.002208936,0.0082156,0.054286316,0.33633274,0.25067568],"study_design_scores_gemma":[0.0000022747586,0.000059914728,0.11118764,0.00028194484,0.000012349398,0.0016657194,0.07960827,0.0004293045,0.00051337574,0.0008459648,0.8053642,0.000029072513],"about_ca_topic_score_codex":0.4134342,"about_ca_topic_score_gemma":0.8509498,"teacher_disagreement_score":0.4134342,"about_ca_system_score_codex":0.004429162,"about_ca_system_score_gemma":0.0042959577,"threshold_uncertainty_score":0.8220555},"labels":[],"label_agreement":null},{"id":"W585816276","doi":"","title":"BC transit provides 50 million rides in British Columbia transit area","year":2009,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Geography; Public transport; Transport engineering; Engineering","score_opus":0.009243500374035115,"score_gpt":0.1943831518310366,"score_spread":0.18513965145700148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W585816276","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.65346885,0.0010707396,0.00084442034,0.0031713154,0.0003303389,0.00039619784,0.06599503,0.0005930676,0.27413005],"genre_scores_gemma":[0.53974414,0.00081504945,0.0007641121,0.0005218642,0.000034509605,0.00010104038,0.014678797,0.00013948785,0.443201],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995189,0.000037382495,0.000016124859,0.00007196641,0.00016355838,0.00019204956],"domain_scores_gemma":[0.9993437,0.000021635748,0.000029276904,0.00001690092,0.00043208792,0.0001564145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015059482,0.00043086975,0.0003591344,0.0014288512,0.0043427963,0.0017482276,0.0006756915,0.00076674606,0.048521698],"category_scores_gemma":[0.00079509284,0.0003203899,0.0002447475,0.002447919,0.00030146362,0.0003950538,0.0009593935,0.000802379,0.011017425],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029231317,0.0003574383,0.23815772,0.00025516184,0.00010161365,0.0015479212,0.0015153225,0.0038693235,0.0021489065,0.001946572,0.5871097,0.16269806],"study_design_scores_gemma":[0.00005043491,0.000091735834,0.62277985,0.00016478437,0.000101043566,0.0005897904,0.012424512,0.006041308,0.0012922429,0.0003842974,0.35601738,0.0000626277],"about_ca_topic_score_codex":0.96871847,"about_ca_topic_score_gemma":0.99165547,"teacher_disagreement_score":0.048521698,"about_ca_system_score_codex":0.011361205,"about_ca_system_score_gemma":0.016131124,"threshold_uncertainty_score":0.16232127},"labels":[],"label_agreement":null},{"id":"W587320459","doi":"","title":"Greyhound: Building a Better Breed of Bus Company","year":2006,"lang":"en","type":"article","venue":"Metrologia","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Demographics; Logo (programming language); Advertising; Spring (device); Business; Marketing; Computer science; Sociology; Engineering; Demography; Mechanical engineering","score_opus":0.0075379757315989756,"score_gpt":0.20336434591978564,"score_spread":0.19582637018818666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W587320459","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15604949,0.005367306,0.0132740345,0.047601767,0.0025678822,0.00039036735,0.0009589113,0.0058760885,0.7679142],"genre_scores_gemma":[0.16962127,0.0017535997,0.01969201,0.0036760983,0.00018667939,0.00004782473,0.0010107715,0.00080636,0.8032054],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99936575,0.000053148437,0.000008336386,0.00010956828,0.00025527918,0.00020793237],"domain_scores_gemma":[0.9987832,0.000036020607,0.000020710575,0.000067834415,0.0002409999,0.000851309],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072353834,0.0004831937,0.00017500011,0.0008869788,0.0034492367,0.0044168644,0.00077425985,0.0014160548,0.080353014],"category_scores_gemma":[0.00095789105,0.0003508429,0.00020628022,0.0005336458,0.0011714832,0.0052522053,0.0029745633,0.0011766825,0.013987302],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010941603,0.00039251678,0.0065090507,0.00013014817,0.000010248776,0.00071562966,0.003502106,0.00045166304,0.0063053905,0.048775617,0.67279345,0.26030475],"study_design_scores_gemma":[0.000010121583,0.00005933278,0.0027040718,0.000031472686,0.0000030327503,0.0001862508,0.0022680797,0.00039908444,0.00060761545,0.0012096599,0.9925055,0.000015607324],"about_ca_topic_score_codex":0.08587954,"about_ca_topic_score_gemma":0.2516967,"teacher_disagreement_score":0.08587954,"about_ca_system_score_codex":0.003946837,"about_ca_system_score_gemma":0.008755439,"threshold_uncertainty_score":0.26880765},"labels":[],"label_agreement":null},{"id":"W588658656","doi":"","title":"US Light Rail Booms","year":2006,"lang":"en","type":"article","venue":"International railway journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Light rail transit; Electrification; Transit (satellite); Transport engineering; Light rail; Rail transit; Track (disk drive); Public transport; Boom; Population; Engineering; Environmental science; Electricity; Environmental engineering; Electrical engineering","score_opus":0.0041783684881668524,"score_gpt":0.20282715255164302,"score_spread":0.19864878406347616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W588658656","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016903136,0.0015097752,0.0006226305,0.02494942,0.0033495156,0.00005610851,0.0067300913,0.0008642667,0.945015],"genre_scores_gemma":[0.07796392,0.0017093875,0.0006590518,0.010033472,0.0003400053,0.000063948915,0.005115704,0.00016230965,0.90395224],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.999603,0.000021628195,0.000011256615,0.00005370886,0.00017628202,0.00013428695],"domain_scores_gemma":[0.9996183,0.000023605424,0.00002033894,0.0000232589,0.00021684715,0.00009758828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028697142,0.0003526265,0.0001189496,0.00072484027,0.0019405282,0.002498064,0.0002921489,0.0013433114,0.11556653],"category_scores_gemma":[0.0010683587,0.00014366959,0.00024387121,0.001040535,0.0003346456,0.0012194621,0.001135065,0.0013395451,0.026869481],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039116836,0.00002681519,0.001924918,0.00003418723,0.00000314097,0.0000755463,0.00010939225,0.000059180355,0.00034749633,0.012855835,0.92805845,0.05646595],"study_design_scores_gemma":[0.000004998653,0.00001579235,0.0033253415,0.000022382972,0.0000029653822,0.00003599421,0.00014902563,0.000055885197,0.0001679897,0.00060093624,0.99561477,0.000003797139],"about_ca_topic_score_codex":0.08831962,"about_ca_topic_score_gemma":0.15522157,"teacher_disagreement_score":0.11556653,"about_ca_system_score_codex":0.0025489137,"about_ca_system_score_gemma":0.0035423436,"threshold_uncertainty_score":0.38660854},"labels":[],"label_agreement":null},{"id":"W588845992","doi":"10.82308/42283","title":"A peer-to-peer matching system for grocery home delivery","year":2014,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Toronto; McGill University","keywords":"Matching (statistics); Grocery shopping; Grocery store; Peer-to-peer; Incentive; Truck; Business; Computer science; Order (exchange); Food delivery; Service (business); Advertising; Marketing; Computer network; Engineering; Mathematics","score_opus":0.013503926228073976,"score_gpt":0.2145739446556687,"score_spread":0.20107001842759473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W588845992","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0399917,0.00044225398,0.94040847,0.00036549495,0.00026517708,0.00090623467,0.00021622368,0.0023771871,0.01502728],"genre_scores_gemma":[0.5644873,0.00058493944,0.41082698,0.0002451955,0.0002009542,0.0007901319,0.0006812854,0.00025852895,0.02192479],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983765,0.00048752682,0.00007974262,0.00039902044,0.00050728646,0.00014994264],"domain_scores_gemma":[0.99900514,0.00033223652,0.000095169664,0.00016744007,0.00029902672,0.00010096999],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001474699,0.0005708927,0.0010357236,0.0007136087,0.0013122489,0.0012551126,0.0029713223,0.0011792139,0.010725425],"category_scores_gemma":[0.0031393943,0.00034882952,0.000566249,0.0010491043,0.00042538732,0.0021664165,0.0018370479,0.0008940205,0.0029428897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081538054,0.0007867269,0.0018665253,0.0006263639,0.00015770433,0.0009003578,0.00051523093,0.30131003,0.02402384,0.046788283,0.026562247,0.59564734],"study_design_scores_gemma":[0.000117219824,0.000374827,0.00056408864,0.000019692383,0.00004514273,0.00042978433,0.00017500651,0.9434001,0.0063247,0.010360139,0.03813619,0.00005311308],"about_ca_topic_score_codex":0.0027925025,"about_ca_topic_score_gemma":0.002319217,"teacher_disagreement_score":0.010725425,"about_ca_system_score_codex":0.0008713155,"about_ca_system_score_gemma":0.0012535271,"threshold_uncertainty_score":0.03588015},"labels":[],"label_agreement":null},{"id":"W590871421","doi":"","title":"PAY TO PARK WITH YOUR MOBILE PHONE : NOW IN SEATTLE AND VANCOUVER","year":2002,"lang":"en","type":"article","venue":"Parking Today","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Phone; Mobile phone; Payment; Credit card; Business; Advertising; Telecommunications; Computer science; Internet privacy; Finance","score_opus":0.012595550813673377,"score_gpt":0.21206739616074083,"score_spread":0.19947184534706744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W590871421","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012015537,0.00077508437,0.00064459053,0.0072257663,0.0024995885,0.000094991636,0.00095043884,0.0011745321,0.97461945],"genre_scores_gemma":[0.013621171,0.00045441676,0.00023630857,0.0005272367,0.000087249835,0.00001879846,0.00031635334,0.0000915889,0.9846469],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997602,0.000014552964,0.000006705037,0.000031698506,0.00008785471,0.00009897412],"domain_scores_gemma":[0.9988716,0.000026520062,0.000020660345,0.000031963686,0.0003169458,0.0007321304],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00016407449,0.0005534738,0.0002940788,0.00061312993,0.0041033397,0.0026380622,0.0005249442,0.0013832854,0.5531755],"category_scores_gemma":[0.00079248997,0.00026301655,0.00022402257,0.00058259343,0.0003347611,0.0012837088,0.0011982579,0.0010454486,0.29032624],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004650634,0.00008759388,0.0025912551,0.000029202707,0.0000026732755,0.00019106224,0.00015623191,0.000018995335,0.00053678226,0.0006286642,0.90722257,0.0884884],"study_design_scores_gemma":[0.000013093918,0.000043710876,0.0053013107,0.000049660506,0.000007084715,0.00026051805,0.00095445296,0.00005672241,0.0003768029,0.00017181643,0.9927497,0.000015160873],"about_ca_topic_score_codex":0.044973906,"about_ca_topic_score_gemma":0.2058388,"teacher_disagreement_score":0.9550261,"about_ca_system_score_codex":0.000672949,"about_ca_system_score_gemma":0.0015496284,"threshold_uncertainty_score":0.6373409},"labels":[],"label_agreement":null},{"id":"W591061401","doi":"","title":"CARPOOLING ON THE WEB : CANADIAN COMMUTERS CAN NOW ENJOY FREE RIDE- MATCHING","year":2003,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Set (abstract data type); Advertising; Transport engineering; Business; Geography; Computer science; Engineering; Medicine","score_opus":0.011489351374538988,"score_gpt":0.18835730139446347,"score_spread":0.17686795001992447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W591061401","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10099896,0.0015968656,0.0021472112,0.017685931,0.00054012117,0.00015181706,0.008907798,0.0030476146,0.8649237],"genre_scores_gemma":[0.41212344,0.003331277,0.0062711863,0.003081612,0.00029376766,0.000114775314,0.0128277745,0.0005924504,0.5613637],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.999569,0.00002157534,0.000008843497,0.00002623685,0.00016821692,0.00020606279],"domain_scores_gemma":[0.99891317,0.00006965016,0.000026978896,0.00007317269,0.00044153872,0.00047541896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005276881,0.0002195038,0.0001978632,0.0008318919,0.003774264,0.0033068531,0.0006011314,0.000773915,0.06800133],"category_scores_gemma":[0.0016227152,0.00014706011,0.0002079053,0.0023609337,0.0005747421,0.002124759,0.0013816252,0.0007499087,0.011032686],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017920838,0.00016526904,0.010193346,0.0001154576,0.00001007007,0.00025421384,0.0026262472,0.00018214094,0.00094242167,0.0067376634,0.74526286,0.23333114],"study_design_scores_gemma":[0.000038818198,0.000026110316,0.030643994,0.000049148737,0.000016327424,0.00007636693,0.0043904856,0.0005211645,0.0005174797,0.00091746345,0.9627576,0.000045142984],"about_ca_topic_score_codex":0.9195475,"about_ca_topic_score_gemma":0.97692776,"teacher_disagreement_score":0.0804525,"about_ca_system_score_codex":0.005479597,"about_ca_system_score_gemma":0.012156505,"threshold_uncertainty_score":0.22748709},"labels":[],"label_agreement":null},{"id":"W591429882","doi":"","title":"Tapestry of Inclusion","year":2004,"lang":"en","type":"article","venue":"10th International Conference on Mobility and Transport for Elderly and Disabled PeopleJapan Society of Civil EngineersTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Agency (philosophy); Inclusion (mineral); Administration (probate law); Business; Public administration; Public relations; Political science; Sociology; Law","score_opus":0.044046633047208024,"score_gpt":0.316164154535907,"score_spread":0.272117521488699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W591429882","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0064700195,0.0057776473,0.004570783,0.09041901,0.013069736,0.00014382956,0.0003512884,0.00021813034,0.87897956],"genre_scores_gemma":[0.27971718,0.008762318,0.004825873,0.025351707,0.0067548254,0.00059092086,0.0006393236,0.0005577006,0.6728001],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.97215784,0.009960607,0.0018124654,0.0022929425,0.010452672,0.0033234602],"domain_scores_gemma":[0.9440926,0.01497516,0.002397454,0.011234408,0.01931871,0.007981772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013896843,0.00057422655,0.0013048751,0.0048978003,0.023900706,0.022825353,0.0032805938,0.0041569467,0.06175044],"category_scores_gemma":[0.07690851,0.0005265506,0.0005503907,0.005738727,0.02360304,0.017610444,0.032370638,0.010441395,0.015602984],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006890759,0.000027533151,0.0005338375,0.00025428657,0.000006901528,0.00032374496,0.038774204,0.00005478546,0.00017962296,0.6253762,0.23217857,0.102221325],"study_design_scores_gemma":[0.0000045939596,0.000013376816,0.00024558546,0.00036993762,0.0000022489664,0.00016170852,0.008929005,0.00003304879,0.000059177066,0.023555715,0.9666148,0.000010773204],"about_ca_topic_score_codex":0.024007505,"about_ca_topic_score_gemma":0.032822594,"teacher_disagreement_score":0.06175044,"about_ca_system_score_codex":0.009897185,"about_ca_system_score_gemma":0.019897409,"threshold_uncertainty_score":0.20657581},"labels":[],"label_agreement":null},{"id":"W594665962","doi":"","title":"Finding a New Path: Mediation","year":2004,"lang":"en","type":"article","venue":"10th International Conference on Mobility and Transport for Elderly and Disabled PeopleJapan Society of Civil EngineersTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Mediation; Agency (philosophy); Process (computing); Dispute resolution; Process management; Business; Resolution (logic); Public relations; Computer science; Law and economics; Risk analysis (engineering); Operations research; Political science; Economics; Engineering; Sociology; Law; Artificial intelligence","score_opus":0.05857618294903662,"score_gpt":0.3207275617685618,"score_spread":0.2621513788195252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W594665962","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0218381,0.0023908915,0.64853203,0.06743564,0.0020600967,0.001208692,0.00010957066,0.00044846238,0.2559766],"genre_scores_gemma":[0.6882607,0.0013247876,0.23902798,0.0068290452,0.0005072813,0.0016529,0.000117112904,0.0002127161,0.06206744],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.96410686,0.020401733,0.0012214974,0.004754446,0.0060008387,0.0035146081],"domain_scores_gemma":[0.9712172,0.01646066,0.0026446318,0.004322547,0.003772998,0.0015819748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.031756017,0.001114709,0.0011233066,0.0033136006,0.011185102,0.014641975,0.0066101304,0.011501696,0.034019046],"category_scores_gemma":[0.055356838,0.00069736753,0.0021156368,0.0023499697,0.016114542,0.028441284,0.017911967,0.008008762,0.00401902],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027193608,0.00003541179,0.00020689672,0.00009524435,0.000021084694,0.00015232143,0.002975583,0.00032342877,0.00019375168,0.9765862,0.002790538,0.016592385],"study_design_scores_gemma":[0.00009180334,0.000121643214,0.00015939411,0.0004142009,0.00005227221,0.00043742015,0.0075511206,0.0029774425,0.0007060357,0.8126923,0.1747215,0.000074858704],"about_ca_topic_score_codex":0.0032126936,"about_ca_topic_score_gemma":0.0035192375,"teacher_disagreement_score":0.034019046,"about_ca_system_score_codex":0.0045061633,"about_ca_system_score_gemma":0.014215495,"threshold_uncertainty_score":0.16794384},"labels":[],"label_agreement":null},{"id":"W598927296","doi":"","title":"Google News, Google Maps, Google... Bus?","year":2007,"lang":"en","type":"article","venue":"Metrologia","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Mile; Work (physics); Quarter (Canadian coin); Service (business); Peninsula; Business; Bay; Transport engineering; Advertising; Aeronautics; Computer science; Geography; Engineering; Marketing; Archaeology","score_opus":0.010639633847614295,"score_gpt":0.22416135308047053,"score_spread":0.21352171923285623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W598927296","genre_codex":"other","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003037992,0.0085169,0.003742377,0.015535632,0.0041089216,0.00021291479,0.0563483,0.042779397,0.8657176],"genre_scores_gemma":[0.03619027,0.015116264,0.007567433,0.008893171,0.0046177735,0.0002533017,0.07736778,0.016638162,0.83335584],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.999546,0.000055441476,0.00002428456,0.000050055536,0.00022122536,0.000102953636],"domain_scores_gemma":[0.99884135,0.0002232052,0.00009283837,0.00018209523,0.00035157095,0.0003088465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041683094,0.0012755875,0.00060752645,0.003725802,0.0018572022,0.007687742,0.001064412,0.0025018752,0.28970212],"category_scores_gemma":[0.0034920254,0.0004757752,0.0005220449,0.0065008467,0.0007330166,0.009974826,0.0031369599,0.0014206262,0.35020626],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027766584,0.000006523636,0.00019580149,0.00017165925,0.000003801851,0.000106274354,0.00012505542,0.000028260709,0.0000800331,0.0018458401,0.96143025,0.035978757],"study_design_scores_gemma":[0.000005428792,0.0000047254766,0.00047639117,0.000050115912,0.0000034050715,0.00010636557,0.00033253306,0.000070145645,0.000105259605,0.0008610515,0.9979705,0.000014165436],"about_ca_topic_score_codex":0.017346388,"about_ca_topic_score_gemma":0.026861796,"teacher_disagreement_score":0.28970212,"about_ca_system_score_codex":0.00089176884,"about_ca_system_score_gemma":0.00090636365,"threshold_uncertainty_score":0.9691501},"labels":[],"label_agreement":null},{"id":"W600591597","doi":"","title":"McLean Group's Blackcomb Av serves real estate, movie and TV activities","year":2011,"lang":"en","type":"article","venue":"Professional pilot","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Real estate; Group (periodic table); Advertising; Aeronautics; Business; Engineering; Telecommunications; Computer science; Finance; Physics","score_opus":0.038266713457970655,"score_gpt":0.24936003665344023,"score_spread":0.21109332319546958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W600591597","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.095099635,0.000540481,0.0029815426,0.002404773,0.00025962765,0.00024383972,0.0014365889,0.0026545867,0.8943789],"genre_scores_gemma":[0.14941934,0.00022821319,0.0034449012,0.0005185709,0.000035225054,0.000044765806,0.00074236706,0.00022124687,0.84534544],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994665,0.00003903272,0.000007986619,0.00010215416,0.00024110958,0.0001432344],"domain_scores_gemma":[0.9991092,0.000045307257,0.000024594845,0.000034539742,0.00033197054,0.00045435663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033692422,0.0007098277,0.00021781342,0.0010867319,0.0043014786,0.0017505626,0.0005458242,0.0005778587,0.18429822],"category_scores_gemma":[0.0005846343,0.0002873309,0.00017068307,0.0006880829,0.00051163154,0.0006575781,0.0016002915,0.0005284439,0.033594213],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004848561,0.00045748355,0.027366986,0.0001351473,0.000014937124,0.00077106286,0.0034738488,0.00028354616,0.011983936,0.004453745,0.52695805,0.42361647],"study_design_scores_gemma":[0.000050882834,0.00039805443,0.033566162,0.000083354666,0.000015106,0.0008390142,0.0060846335,0.0011993808,0.0034971898,0.00045435014,0.9537823,0.00002949077],"about_ca_topic_score_codex":0.23610881,"about_ca_topic_score_gemma":0.6561177,"teacher_disagreement_score":0.23610881,"about_ca_system_score_codex":0.0022250505,"about_ca_system_score_gemma":0.003626281,"threshold_uncertainty_score":0.616539},"labels":[],"label_agreement":null},{"id":"W603436407","doi":"","title":"Suburb-to-Suburb Service Creates Robust Challenge for Pace","year":2007,"lang":"en","type":"article","venue":"Metrologia","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Paratransit; Pace; Transport engineering; Service (business); Public transport; Business; Transit (satellite); Population; Geography; Engineering; Marketing; Environmental health","score_opus":0.03283615417290568,"score_gpt":0.2565968607469985,"score_spread":0.2237607065740928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W603436407","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3039977,0.0006284958,0.017771771,0.08708204,0.0034831811,0.0003994414,0.0024486424,0.0013733308,0.58281547],"genre_scores_gemma":[0.77306,0.0008009392,0.012063078,0.010668186,0.0012572875,0.00022909159,0.0020132635,0.00047372642,0.19943435],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9975867,0.00040313194,0.00007230122,0.00022830126,0.0008984763,0.00081104256],"domain_scores_gemma":[0.99524695,0.00062158925,0.0002464044,0.00033851896,0.0012350631,0.0023114935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018741203,0.00025136166,0.00031554757,0.0007693582,0.0033772562,0.0045704897,0.0010680971,0.0016123026,0.03866881],"category_scores_gemma":[0.003727394,0.00022604759,0.0006614005,0.0014266302,0.0010790902,0.0027105864,0.0042251647,0.002136275,0.008081115],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039371412,0.0009387589,0.08495968,0.00031195383,0.000040087893,0.004256324,0.00725995,0.0031045845,0.004233177,0.15068357,0.47763044,0.26618785],"study_design_scores_gemma":[0.00003582973,0.00029024947,0.02640077,0.000048296268,0.000010300634,0.0015230931,0.009673182,0.0024069215,0.00054760434,0.0077492325,0.9512809,0.00003361458],"about_ca_topic_score_codex":0.005807034,"about_ca_topic_score_gemma":0.01757829,"teacher_disagreement_score":0.03866881,"about_ca_system_score_codex":0.0022214646,"about_ca_system_score_gemma":0.006245975,"threshold_uncertainty_score":0.12936008},"labels":[],"label_agreement":null},{"id":"W614149161","doi":"","title":"Access to Travel Web Site","year":2004,"lang":"en","type":"article","venue":"10th International Conference on Mobility and Transport for Elderly and Disabled PeopleJapan Society of Civil EngineersTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"General partnership; Government (linguistics); Web site; Population; Business; World Wide Web; Public relations; The Internet; Computer science; Political science","score_opus":0.06381398503095242,"score_gpt":0.3389870245633099,"score_spread":0.2751730395323575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W614149161","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0068865367,0.0014462896,0.0056853606,0.0026322156,0.0007352374,0.0009520765,0.06575599,0.016108176,0.8997981],"genre_scores_gemma":[0.05475966,0.0032453716,0.0148085505,0.0028370174,0.0004630091,0.0006787087,0.10278858,0.0044088187,0.81601024],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995055,0.00004393407,0.000020944059,0.000038306716,0.00027754295,0.00011378072],"domain_scores_gemma":[0.9970702,0.0002310889,0.00005648277,0.00020668263,0.0017047961,0.0007307751],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006159085,0.0004269565,0.00038214435,0.0020736814,0.0025367842,0.003183835,0.000870241,0.0008061347,0.33604488],"category_scores_gemma":[0.0031430614,0.00015753342,0.00031433452,0.0028762426,0.0002759955,0.0016056211,0.001697239,0.00097133784,0.15151861],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004550773,0.00008642078,0.0012361859,0.00017404833,0.0000044187495,0.00012247276,0.0002578818,0.000098172946,0.0004682024,0.0017028172,0.87827957,0.11752427],"study_design_scores_gemma":[0.000009745756,0.000020392567,0.0031978823,0.00007421166,0.000004328218,0.000097465134,0.00030813637,0.00019869505,0.00020028018,0.0004765908,0.99539065,0.000021664278],"about_ca_topic_score_codex":0.18010549,"about_ca_topic_score_gemma":0.31772858,"teacher_disagreement_score":0.33604488,"about_ca_system_score_codex":0.0024691115,"about_ca_system_score_gemma":0.006351648,"threshold_uncertainty_score":0.9470514},"labels":[],"label_agreement":null},{"id":"W614789457","doi":"10.1016/j.trc.2015.07.016","title":"Agent based model for dynamic ridesharing","year":2015,"lang":"en","type":"article","venue":"Transportation Research Part C Emerging Technologies","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Integer programming; Dynamic programming; Scale (ratio); Mathematical optimization; Integer (computer science); Operations research; Binary number; Transport engineering; Engineering; Algorithm","score_opus":0.17547997931849435,"score_gpt":0.3873340437948765,"score_spread":0.21185406447638216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W614789457","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.044171527,0.0007920783,0.9076778,0.0014075007,0.00028063796,0.00017866782,0.0014604983,0.0008050975,0.043226097],"genre_scores_gemma":[0.8952825,0.0007735933,0.041555617,0.00019279798,0.00008513954,0.00040329166,0.0007724108,0.00011851326,0.06081612],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995222,0.00013690513,0.00002673894,0.00012599512,0.00009472765,0.00009346711],"domain_scores_gemma":[0.99948907,0.00023687328,0.00006121114,0.00003530696,0.00011778878,0.000059643742],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005527957,0.000906339,0.0021082156,0.00071874727,0.0010168009,0.0026078187,0.0029091616,0.0031003424,0.014803436],"category_scores_gemma":[0.0015930361,0.0007624857,0.00093357085,0.0009824352,0.0010144119,0.0018202541,0.0019030727,0.0017766444,0.0020370928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040097242,0.000026586173,0.0001331826,0.000036882495,0.00001872659,0.000088166205,0.00003249193,0.9773846,0.00028003857,0.017590605,0.0009976872,0.0033709249],"study_design_scores_gemma":[0.0000095917785,0.000009844408,0.000031805,0.0000030015874,0.0000054705547,0.000007912988,0.000007325468,0.9960524,0.000034240602,0.0032456554,0.0005885598,0.000004114022],"about_ca_topic_score_codex":0.028231744,"about_ca_topic_score_gemma":0.015246008,"teacher_disagreement_score":0.028231744,"about_ca_system_score_codex":0.0015038219,"about_ca_system_score_gemma":0.0014680526,"threshold_uncertainty_score":0.05613482},"labels":[],"label_agreement":null},{"id":"W618331843","doi":"","title":"Ontario officials confirm development of training requirements for new drivers","year":2014,"lang":"en","type":"article","venue":"Transport topics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Training (meteorology); Aeronautics; Transport engineering; Engineering; Truck; Business; Engineering management; Forensic engineering; Operations management; Automotive engineering; Geography; Meteorology","score_opus":0.0693511461624124,"score_gpt":0.2602500608421421,"score_spread":0.1908989146797297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W618331843","genre_codex":"other","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3396946,0.0009817106,0.0046933563,0.12640405,0.0022225203,0.0018640701,0.0052305222,0.0009636412,0.5179455],"genre_scores_gemma":[0.47089615,0.001384886,0.0058986587,0.02652472,0.0004121742,0.0010388087,0.0030446243,0.00018174059,0.4906183],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9919253,0.00056831865,0.0004122428,0.0003158479,0.004525247,0.0022530437],"domain_scores_gemma":[0.9460632,0.008772621,0.0021763083,0.0011904868,0.034930516,0.0068668756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005421657,0.00035364318,0.00030788098,0.0016676711,0.009932746,0.0026580999,0.0014970081,0.0032882625,0.024764383],"category_scores_gemma":[0.023673275,0.0005988905,0.00052687165,0.0013596015,0.0011531014,0.0010286954,0.0013493045,0.0031706835,0.0036387448],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026720905,0.00042624635,0.15450394,0.00071286433,0.000026074398,0.00078070414,0.020834872,0.0009034855,0.008118631,0.009877363,0.73266107,0.070887536],"study_design_scores_gemma":[0.000046384346,0.00019043841,0.3675952,0.0002414497,0.000031041556,0.00011552151,0.0148344645,0.00066572026,0.002932462,0.00037159093,0.6129208,0.000054912045],"about_ca_topic_score_codex":0.863088,"about_ca_topic_score_gemma":0.96130633,"teacher_disagreement_score":0.13691199,"about_ca_system_score_codex":0.021481242,"about_ca_system_score_gemma":0.08836293,"threshold_uncertainty_score":0.27543652},"labels":[],"label_agreement":null},{"id":"W620218817","doi":"","title":"Time to Phase Out Toll Booths","year":2005,"lang":"en","type":"article","venue":"RCC's public works financing","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Toll; Transponder (aeronautics); Toll road; Electronic toll collection; Standardization; Transport engineering; Interoperability; Business; Telecommunications; Engineering; Computer science; World Wide Web","score_opus":0.012601084704316512,"score_gpt":0.2393385633315075,"score_spread":0.22673747862719099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W620218817","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25739992,0.0009469069,0.054223526,0.004856752,0.0023709931,0.0019542347,0.0011628304,0.0037065854,0.6733783],"genre_scores_gemma":[0.63889116,0.00046970634,0.022801306,0.001134953,0.0003870208,0.00043224852,0.0009621099,0.00039304464,0.33452842],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99890757,0.00014130272,0.000046809142,0.00007965108,0.0003863913,0.000438236],"domain_scores_gemma":[0.99861765,0.00031047076,0.00011607,0.00018266802,0.00036514743,0.00040799697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007635255,0.00035849834,0.0001928642,0.00069063564,0.001662799,0.0018052026,0.00088117574,0.00082293747,0.1516898],"category_scores_gemma":[0.0035050223,0.00032155393,0.00031003446,0.00026625974,0.00038970954,0.0019295113,0.001342505,0.001153986,0.021165797],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046768365,0.0012417677,0.0098609235,0.0002259213,0.000012786624,0.0006046963,0.0012466398,0.0023931658,0.0054534213,0.04083529,0.13501497,0.80264264],"study_design_scores_gemma":[0.00016794684,0.0015333609,0.021631226,0.00028206952,0.00002262664,0.00093971274,0.0048511806,0.0035484622,0.007161039,0.015808716,0.9439682,0.000085506144],"about_ca_topic_score_codex":0.0020555074,"about_ca_topic_score_gemma":0.004153182,"teacher_disagreement_score":0.1516898,"about_ca_system_score_codex":0.0007201864,"about_ca_system_score_gemma":0.0016608665,"threshold_uncertainty_score":0.50745296},"labels":[],"label_agreement":null},{"id":"W624581603","doi":"","title":"DRIVER TRAINING AND RISK","year":2001,"lang":"en","type":"article","venue":"INTERNATIONAL CONFERENCE ON TRAFFIC AND TRANSPORT PSYCHOLOGY - ICTTP 2000, HELD 4-7 SEPTEMBER 2000, BERNE, SWITZERLAND - KEYNOTES, SYMPOSIA, THEMATIC SESSIONS, WORKSHOPS, POSTERS, LIST OF PARTICIPANTS AND WORD VIEWER - CD ROM","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Training (meteorology); Applied psychology; Human factors and ergonomics; Accident (philosophy); Suicide prevention; Engineering; Poison control; Psychology; Transport engineering; Environmental health; Geography; Medicine","score_opus":0.048672840441643876,"score_gpt":0.31188557022807945,"score_spread":0.26321272978643556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W624581603","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6913153,0.027025884,0.0030375705,0.05749955,0.0009878462,0.00006106435,0.0003287794,0.00006121203,0.21968283],"genre_scores_gemma":[0.98620033,0.00398527,0.00022165308,0.00077498815,0.0002284964,0.000010116125,0.000046779165,0.000007665574,0.008524715],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989371,0.0004559063,0.000043408992,0.000100531804,0.0002516844,0.00021126973],"domain_scores_gemma":[0.9965203,0.0014508598,0.00063287694,0.0001107396,0.0004789303,0.0008063596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088366284,0.00020386212,0.00020348051,0.0008673882,0.0010394932,0.0019851376,0.00029952437,0.0014015303,0.010031938],"category_scores_gemma":[0.007750188,0.00010915349,0.00019704388,0.00046679,0.0010516244,0.00088114047,0.0011608746,0.0010503182,0.00079646613],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004195947,0.001159785,0.57549185,0.00036832507,0.00017281892,0.0012476858,0.01019957,0.0012147746,0.00059294124,0.09263152,0.021934478,0.2945667],"study_design_scores_gemma":[0.0000491557,0.0007692347,0.6952769,0.0007870674,0.00017915004,0.005353365,0.020142993,0.0022778667,0.00059957016,0.08000306,0.19441332,0.00014831142],"about_ca_topic_score_codex":0.0038289553,"about_ca_topic_score_gemma":0.002719891,"teacher_disagreement_score":0.010031938,"about_ca_system_score_codex":0.00077441,"about_ca_system_score_gemma":0.00066210085,"threshold_uncertainty_score":0.033560157},"labels":[],"label_agreement":null},{"id":"W627131654","doi":"","title":"How Captive Is the Captive Market Anyway? Reexamination of the Impact of Auto Availability","year":2013,"lang":"en","type":"article","venue":"Transportation Research Board 92nd Annual MeetingTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Mode choice; Occupancy; Marketing; Market research; Business; Travel behavior; Economics; Transport engineering; Public transport; Geography; Microeconomics; Engineering","score_opus":0.040582043190851506,"score_gpt":0.3332139123936083,"score_spread":0.2926318692027568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W627131654","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80461913,0.0015297502,0.00959066,0.010131447,0.0001580508,0.00010546381,0.00051496644,0.000057840894,0.17329265],"genre_scores_gemma":[0.99745077,0.00020147403,0.00034123656,0.00022891696,0.00004772548,0.000007778379,0.00004272531,0.000010575276,0.0016688557],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9975871,0.0009900299,0.00005233094,0.00038788674,0.0005923663,0.00039033813],"domain_scores_gemma":[0.9868709,0.007177645,0.0023340257,0.0009104507,0.0018091337,0.0008977744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029600637,0.0003041049,0.00046990212,0.00083077815,0.0014535036,0.0058710687,0.0018219512,0.001083406,0.010613293],"category_scores_gemma":[0.016980413,0.00020706668,0.0004897243,0.0009395941,0.0042427797,0.006453139,0.002427869,0.0018338024,0.00048300214],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012607243,0.00075802946,0.24118337,0.0006180107,0.0005366803,0.0026203983,0.011755849,0.02458066,0.003704814,0.55785733,0.01041519,0.14470896],"study_design_scores_gemma":[0.00008414786,0.0012478333,0.56195235,0.0006121397,0.0005221393,0.0009335445,0.052112054,0.05671959,0.0033757337,0.21688268,0.10538005,0.00017769105],"about_ca_topic_score_codex":0.034760743,"about_ca_topic_score_gemma":0.035349507,"teacher_disagreement_score":0.034760743,"about_ca_system_score_codex":0.0032975806,"about_ca_system_score_gemma":0.0021519116,"threshold_uncertainty_score":0.06911683},"labels":[],"label_agreement":null},{"id":"W628475814","doi":"","title":"Digital dialogue : Canada expands text messaging between cockpits and control rooms","year":2014,"lang":"en","type":"article","venue":"Aviation week & space technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Control (management); Business; Computer science; Aeronautics; Engineering","score_opus":0.0034269954591037866,"score_gpt":0.17326928727889826,"score_spread":0.16984229181979446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W628475814","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23822217,0.0010254428,0.012343795,0.028878218,0.0012864025,0.00049442914,0.0034765066,0.0035794252,0.71069354],"genre_scores_gemma":[0.7934305,0.00056275976,0.0118839955,0.0056221928,0.00019264744,0.00019819564,0.0021389069,0.0005620024,0.18540889],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99736744,0.00039643198,0.00005415537,0.00045662822,0.0009550007,0.0007704385],"domain_scores_gemma":[0.992007,0.002059963,0.00016551187,0.00042092495,0.0033718937,0.001974619],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020882217,0.0004296643,0.00023915408,0.0012947688,0.0060757883,0.007379466,0.0017752335,0.0021141758,0.04050413],"category_scores_gemma":[0.009026393,0.00024162894,0.00029105134,0.0019638957,0.0020083294,0.0032212806,0.0036541633,0.0016774277,0.004615262],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016783184,0.00074219174,0.014137505,0.0005522012,0.000028753015,0.00064656447,0.03481751,0.003917861,0.01461052,0.08357927,0.34227487,0.50301445],"study_design_scores_gemma":[0.00022373167,0.0001780887,0.016070787,0.00019412949,0.000050552193,0.000109068045,0.020875137,0.0047333967,0.0039113513,0.0030970164,0.9504427,0.0001140433],"about_ca_topic_score_codex":0.95623237,"about_ca_topic_score_gemma":0.9610096,"teacher_disagreement_score":0.04376763,"about_ca_system_score_codex":0.03161497,"about_ca_system_score_gemma":0.06133756,"threshold_uncertainty_score":0.22938377},"labels":[],"label_agreement":null},{"id":"W631764179","doi":"","title":"Dynamic Real-Time Ridesharing: A Literature Review and Early Findings from a Market Demand Study of a Dynamic Transportation Trading Platform for the University of Calgary's Main Campus","year":2014,"lang":"en","type":"review","venue":"Transportation Research Board 93rd Annual MeetingTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Seekers; Order (exchange); Travel behavior; Marketing; Dynamic pricing; Business; Advertising; Public relations; Transport engineering; Engineering; Political science; Finance","score_opus":0.028958252946851375,"score_gpt":0.3319198860746831,"score_spread":0.3029616331278317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W631764179","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010110586,0.9975585,0.00010044209,0.0002613529,0.00005544861,0.00002104417,0.000033027944,0.000002749903,0.0009563111],"genre_scores_gemma":[0.006134203,0.99324894,0.00024949946,0.00012364775,0.000034274075,0.000022485678,0.00004097042,0.0000016510196,0.00014430557],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998505,0.00036149778,0.00032773108,0.00023549482,0.00048627402,0.0000841013],"domain_scores_gemma":[0.98858505,0.008494728,0.0009544332,0.00012178288,0.0016757281,0.00016832793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032494275,0.0007453646,0.0018777122,0.0065255747,0.00060038303,0.0023273716,0.0013044731,0.001621763,0.0027922199],"category_scores_gemma":[0.0073345974,0.0006422434,0.0009805593,0.012246159,0.0008869281,0.002339981,0.00069593015,0.0011345424,0.00054104946],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015176383,0.00020668145,0.0018021215,0.26357764,0.00034993925,0.0005960071,0.0015824096,0.00044078712,0.0010347101,0.0032499186,0.010113909,0.71689403],"study_design_scores_gemma":[0.00006379079,0.00077754457,0.027504135,0.27697647,0.002642919,0.003064232,0.007186707,0.0004620835,0.0014816852,0.0015356977,0.67815906,0.00014574561],"about_ca_topic_score_codex":0.0095251575,"about_ca_topic_score_gemma":0.021569906,"teacher_disagreement_score":0.0095251575,"about_ca_system_score_codex":0.0017780876,"about_ca_system_score_gemma":0.006776362,"threshold_uncertainty_score":0.018939435},"labels":[],"label_agreement":null},{"id":"W633022394","doi":"","title":"SHARED-USE VEHICLE SERVICES: A SURVEY OF NORTH AMERICAN MARKET DEVELOPMENTS","year":2002,"lang":"en","type":"article","venue":"9th World Congress on Intelligent Transport SystemsITS America, ITS Japan, ERTICO (Intelligent Transport Systems and Services-Europe)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Investment (military); Business; Service (business); Marketing; Finance; Political science","score_opus":0.02925400569460212,"score_gpt":0.22392821152870598,"score_spread":0.19467420583410386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W633022394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9929005,0.0005778337,0.00005694367,0.00062293746,0.0000067830483,0.00001416413,0.0010965544,0.0000069608705,0.004717466],"genre_scores_gemma":[0.99234855,0.0018470234,0.00016694637,0.00040328404,0.0000183033,0.000041969815,0.0014825122,0.0000074755335,0.0036840672],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994236,0.00009421263,0.00004770536,0.00007343266,0.00023803778,0.00012310856],"domain_scores_gemma":[0.99748355,0.00037370203,0.0010906742,0.00007018794,0.0005129793,0.00046897618],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005383029,0.00013834085,0.00014006493,0.0020723685,0.0007026892,0.00088725146,0.00034788283,0.0003850038,0.0037274803],"category_scores_gemma":[0.0011997547,0.00015944785,0.00012665307,0.003653542,0.00031385513,0.0015073997,0.000750732,0.00046601865,0.0005534501],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035904708,0.00017039615,0.94948995,0.00007897834,0.000014890399,0.00034714598,0.009279182,0.000060555143,0.00062817946,0.0005289648,0.009596364,0.029769529],"study_design_scores_gemma":[0.0000015058182,0.000047024027,0.97054446,0.000029346342,0.000004066908,0.0002555459,0.013684018,0.00014025695,0.00012900351,0.000026050719,0.015132236,0.0000064286946],"about_ca_topic_score_codex":0.033272598,"about_ca_topic_score_gemma":0.07360495,"teacher_disagreement_score":0.033272598,"about_ca_system_score_codex":0.00095212547,"about_ca_system_score_gemma":0.00091597374,"threshold_uncertainty_score":0.06615788},"labels":[],"label_agreement":null},{"id":"W633744967","doi":"","title":"When, Where and How Taxis Are Used in Montreal","year":2014,"lang":"en","type":"article","venue":"Transportation Research Board 93rd Annual MeetingTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Taxis; Global Positioning System; Public transport; Descriptive statistics; Geography; Transport engineering; Business; Computer science; Statistics; Telecommunications; Mathematics; Engineering","score_opus":0.03964250107746879,"score_gpt":0.3194872898995598,"score_spread":0.279844788822091,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W633744967","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9766649,0.00055737136,0.00022279243,0.0007195824,0.000011788236,0.00004394111,0.008404921,0.000050006707,0.01332468],"genre_scores_gemma":[0.9908043,0.00045208895,0.00027232838,0.00005878808,0.000005202817,0.000015253507,0.002285385,0.000014142183,0.006092463],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99973065,0.000029233572,0.0000091946295,0.00006937608,0.00006656212,0.0000949627],"domain_scores_gemma":[0.9995515,0.000047005284,0.00012735427,0.00002237768,0.00014346204,0.00010828236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020573987,0.00018885921,0.00013661012,0.00096982403,0.0011810885,0.0016612863,0.00051899237,0.00025700498,0.0043661655],"category_scores_gemma":[0.0010385746,0.00014840186,0.00023884371,0.0023627507,0.00058159395,0.0006403795,0.0006104881,0.00036412184,0.00038160008],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013433842,0.00004559916,0.9203918,0.00017894042,0.00013975742,0.00069447677,0.008985466,0.0023076674,0.002630456,0.003276438,0.0178681,0.04334692],"study_design_scores_gemma":[0.0000024699418,0.00001659091,0.9794153,0.000034312114,0.000017657074,0.000062358326,0.0068995226,0.00084229844,0.00025800164,0.00005979604,0.012359696,0.000031948937],"about_ca_topic_score_codex":0.96501166,"about_ca_topic_score_gemma":0.98545897,"teacher_disagreement_score":0.034988344,"about_ca_system_score_codex":0.011432385,"about_ca_system_score_gemma":0.004591346,"threshold_uncertainty_score":0.08294809},"labels":[],"label_agreement":null},{"id":"W637802204","doi":"","title":"SILENCE IS GOLDEN","year":2002,"lang":"en","type":"article","venue":"Commercial motor","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Legislation; Mobile phone; Government (linguistics); Computer security; Phone; Law enforcement; Enforcement; Service (business); Advertising; Internet privacy; Business; Engineering; Telecommunications; Computer science; Political science; Law; Marketing","score_opus":0.02958704407384566,"score_gpt":0.2215865127752411,"score_spread":0.19199946870139545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W637802204","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0073527507,0.02167186,0.004685812,0.3558015,0.052529167,0.00008779686,0.0003712761,0.0005082706,0.5569916],"genre_scores_gemma":[0.18427132,0.011979751,0.0015858919,0.2503385,0.016160859,0.00026543107,0.0004924643,0.0011325496,0.5337731],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9893674,0.0042083287,0.00038311805,0.0013712491,0.0029669811,0.0017030158],"domain_scores_gemma":[0.9864028,0.005036459,0.00085473683,0.0021071078,0.0028741346,0.00272484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008313541,0.00087920617,0.0011420214,0.0012942695,0.012318632,0.013398225,0.0019355817,0.0058415057,0.050293464],"category_scores_gemma":[0.03269719,0.0004696274,0.00079507736,0.0009419242,0.025126968,0.013829348,0.014052213,0.013308169,0.02709941],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011232342,0.00003954597,0.0006681202,0.00026192426,0.00002528141,0.00057225727,0.05043633,0.00006654371,0.0007813829,0.28071943,0.587625,0.07869183],"study_design_scores_gemma":[0.000003779678,0.000010387273,0.00017469797,0.00017834689,0.0000034137918,0.000105787825,0.006178888,0.000012813316,0.00008124512,0.011009913,0.98223037,0.000010321517],"about_ca_topic_score_codex":0.008259887,"about_ca_topic_score_gemma":0.0096399,"teacher_disagreement_score":0.050293464,"about_ca_system_score_codex":0.0050157025,"about_ca_system_score_gemma":0.0057066837,"threshold_uncertainty_score":0.16824841},"labels":[],"label_agreement":null},{"id":"W639699967","doi":"","title":"Examination of the Impact of a Hands-Free Regulation on In-Vehicle Calling Volume","year":2011,"lang":"en","type":"article","venue":"Transportation Research Board 90th Annual MeetingTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Phone; Hands free; Volume (thermodynamics); Set (abstract data type); Computer science; Business; Telecommunications","score_opus":0.07131854415130938,"score_gpt":0.34369262912784243,"score_spread":0.27237408497653304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W639699967","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99053603,0.000096037795,0.00015372255,0.00030271048,0.00001964862,0.000018974968,0.0009734842,0.000013788835,0.007885695],"genre_scores_gemma":[0.9962469,0.000069918315,0.00008381832,0.00010041733,0.000025720776,0.00001725881,0.0008923389,0.000006749816,0.0025569536],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99674594,0.0005937024,0.00014391351,0.00026909876,0.001698868,0.00054843037],"domain_scores_gemma":[0.979455,0.008402813,0.0059253606,0.0007719387,0.004574172,0.00087075226],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014911466,0.0001317389,0.0002832348,0.00068475906,0.0006632709,0.0016664943,0.0007525911,0.0004991652,0.0023778907],"category_scores_gemma":[0.011993894,0.00018012467,0.00039712337,0.0012368956,0.00058029545,0.00048696506,0.00039291446,0.0008222668,0.00039686184],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043377036,0.00032812034,0.9752935,0.000054688287,0.00012697486,0.00021423156,0.0019595877,0.0014566412,0.0026330713,0.0006089576,0.0016715013,0.015218925],"study_design_scores_gemma":[0.0000019559127,0.00006237026,0.99849784,0.0000024312167,0.00000814259,0.000010038745,0.0003045381,0.00020110606,0.0002043568,0.000011495963,0.00069167075,0.000004034951],"about_ca_topic_score_codex":0.38670716,"about_ca_topic_score_gemma":0.50513524,"teacher_disagreement_score":0.38670716,"about_ca_system_score_codex":0.0052095037,"about_ca_system_score_gemma":0.0031203495,"threshold_uncertainty_score":0.76891255},"labels":[],"label_agreement":null},{"id":"W643480618","doi":"","title":"User Evaluation of Accessible Services","year":2001,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Helpfulness; Agency (philosophy); Transport engineering; Publicity; Business; Schedule; CLARITY; Aircrew; Engineering; Marketing; Aeronautics; Computer science; Psychology","score_opus":0.030279196634082534,"score_gpt":0.2967324445559142,"score_spread":0.26645324792183167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W643480618","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9127294,0.0007219074,0.002480478,0.0006263068,0.000103534025,0.0018735954,0.0027277232,0.0003861042,0.07835099],"genre_scores_gemma":[0.98457783,0.00046127767,0.0037010803,0.00019624092,0.000038540697,0.0011082622,0.001247027,0.00010644472,0.008563398],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9645169,0.021176854,0.0023105259,0.0007450489,0.009844199,0.0014065169],"domain_scores_gemma":[0.93208784,0.035647333,0.0030952697,0.0031642148,0.022120642,0.003884751],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019488813,0.00048295423,0.0008020102,0.0043073827,0.0014978788,0.003289657,0.0008031165,0.00083313265,0.018385973],"category_scores_gemma":[0.08015151,0.0002028405,0.001103301,0.0033091826,0.0007753448,0.0018389646,0.0026053267,0.0006233066,0.0023615328],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0044055097,0.0028109278,0.35326308,0.0016873627,0.00022267294,0.000631474,0.061355017,0.0012312818,0.00144981,0.0024355673,0.01870225,0.5518049],"study_design_scores_gemma":[0.0004773253,0.010621471,0.74537796,0.0014289604,0.00050033233,0.0008453276,0.11103097,0.0069086105,0.0037413938,0.0015462632,0.11714362,0.00037778108],"about_ca_topic_score_codex":0.01662186,"about_ca_topic_score_gemma":0.015878813,"teacher_disagreement_score":0.019488813,"about_ca_system_score_codex":0.0034423494,"about_ca_system_score_gemma":0.0026875406,"threshold_uncertainty_score":0.103067935},"labels":[],"label_agreement":null},{"id":"W646291490","doi":"","title":"Some Aspects of Travel by Older People","year":2001,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Demography; Quarter (Canadian coin); Foot (prosody); Older people; Geography; Gerontology; Medicine; Sociology; Transport engineering; Engineering","score_opus":0.007487775885330201,"score_gpt":0.21031441192411415,"score_spread":0.20282663603878395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W646291490","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20007114,0.31167498,0.0018267194,0.15631464,0.0046772887,0.0002372467,0.010224217,0.00010447111,0.3148694],"genre_scores_gemma":[0.62440866,0.31306535,0.001185052,0.0140923625,0.0059100986,0.0001839172,0.00434745,0.000044410364,0.036762763],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9996257,0.00014887986,0.00004387081,0.000027514487,0.00008818199,0.00006592053],"domain_scores_gemma":[0.99954295,0.00010563972,0.000094541356,0.00002387714,0.00012563333,0.00010746296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039185272,0.00017350343,0.000101924095,0.0011675335,0.0010138564,0.0013764754,0.00027674486,0.0007490584,0.0062996317],"category_scores_gemma":[0.0018143541,0.00009791567,0.00022498026,0.0034373198,0.00051117607,0.001847857,0.00064915355,0.00071961974,0.0009323175],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014484269,0.00015273567,0.1674123,0.0023098704,0.00007347414,0.0008716071,0.03130533,0.0011860387,0.0006357253,0.040545747,0.30457598,0.4507863],"study_design_scores_gemma":[0.000005181695,0.00012945395,0.31174043,0.0008098917,0.000016156355,0.0005857369,0.013356073,0.0001565724,0.00006439447,0.003920216,0.6691926,0.000023256413],"about_ca_topic_score_codex":0.037283305,"about_ca_topic_score_gemma":0.043241613,"teacher_disagreement_score":0.037283305,"about_ca_system_score_codex":0.0010961854,"about_ca_system_score_gemma":0.00057032006,"threshold_uncertainty_score":0.07413256},"labels":[],"label_agreement":null},{"id":"W650493706","doi":"","title":"LONDON IS BURNING! ...AND OTHER NON-EVENTS IN THE AFTERMATH OF CONGESTION CHARGING","year":2003,"lang":"en","type":"article","venue":"TDM Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Champion; Traffic congestion; Congestion pricing; Singapore Area Licensing Scheme; Revenue; Road pricing; Transport engineering; Plan (archaeology); Demand management; Business; Finance; Engineering; Economics; History","score_opus":0.01739963361732018,"score_gpt":0.26047736139341926,"score_spread":0.2430777277760991,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W650493706","genre_codex":"other","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04237879,0.3194658,0.0022199468,0.052759625,0.0039420333,0.00010438075,0.0005911537,0.00034271606,0.57819563],"genre_scores_gemma":[0.24182056,0.25799006,0.0016270186,0.015865324,0.00090273446,0.00006194479,0.00062548305,0.00009885268,0.481008],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999353,0.00013346839,0.000026105077,0.00005667183,0.00031692014,0.00011392588],"domain_scores_gemma":[0.9996369,0.00007252785,0.00006723972,0.000021247395,0.00015096957,0.000051106817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005924659,0.00023660682,0.00023453038,0.00052698643,0.0012438536,0.0034256447,0.0006155581,0.0014013948,0.011976272],"category_scores_gemma":[0.00097306893,0.00012721335,0.00024751283,0.0016722463,0.00071705057,0.0013315381,0.0006616599,0.00065971835,0.0032010498],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020957708,0.000058310008,0.0036724126,0.0039590043,0.00006279115,0.002259894,0.0044742324,0.0007538679,0.0024690202,0.06914562,0.28287923,0.6300561],"study_design_scores_gemma":[0.0000035880917,0.000030470837,0.001785859,0.0002301847,0.00000960311,0.00019951416,0.0010286263,0.00002219174,0.00036379113,0.0005913986,0.99572855,0.000006129706],"about_ca_topic_score_codex":0.05563658,"about_ca_topic_score_gemma":0.14817642,"teacher_disagreement_score":0.05563658,"about_ca_system_score_codex":0.0044747265,"about_ca_system_score_gemma":0.0033332885,"threshold_uncertainty_score":0.110625505},"labels":[],"label_agreement":null},{"id":"W651870069","doi":"","title":"AUTOMATED PEOPLE MOVERS READY FOR URBAN USE","year":2001,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Service (business); Renting; Transit (satellite); Public transport; Business; Engineering; Civil engineering; Marketing","score_opus":0.027529779297010094,"score_gpt":0.2566602294094397,"score_spread":0.22913045011242963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W651870069","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23646647,0.0019527889,0.22752416,0.0029701022,0.0013709959,0.0018404825,0.0043397336,0.044666186,0.4788691],"genre_scores_gemma":[0.4188577,0.0011440946,0.1277416,0.00038278574,0.00024287165,0.00057388714,0.005310454,0.0016483024,0.44409838],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995358,0.00009684893,0.000013182757,0.000101834805,0.00017722421,0.00007515935],"domain_scores_gemma":[0.9994703,0.00008692081,0.000026967773,0.00015990628,0.00018926803,0.000066702094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005715469,0.0006872696,0.00034387223,0.00079416606,0.0010193678,0.0013445235,0.00085240946,0.00056809,0.063504964],"category_scores_gemma":[0.00126667,0.000356865,0.0004042132,0.0005833719,0.00033729526,0.001294172,0.0014667106,0.00040433998,0.021365464],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051060965,0.00030685103,0.0063115763,0.00018985104,0.000030004154,0.00050452276,0.0018725925,0.0029667523,0.01114896,0.008947137,0.15933086,0.80788034],"study_design_scores_gemma":[0.00016503058,0.00046525247,0.011296739,0.00009541796,0.000075774784,0.00040853213,0.0019613656,0.012094046,0.011320087,0.00351788,0.9585403,0.000059559694],"about_ca_topic_score_codex":0.007405544,"about_ca_topic_score_gemma":0.015333451,"teacher_disagreement_score":0.063504964,"about_ca_system_score_codex":0.00046470467,"about_ca_system_score_gemma":0.00058221706,"threshold_uncertainty_score":0.21244526},"labels":[],"label_agreement":null},{"id":"W652674096","doi":"","title":"Information to Go","year":2001,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Signage; Computer security; Internet privacy; SAFER; Agency (philosophy); Computer science; Braille; Public transport; Business; Transport engineering; Engineering; Advertising","score_opus":0.007292555062009084,"score_gpt":0.20760238797654829,"score_spread":0.20030983291453922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W652674096","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00041746566,0.0010289163,0.00068434427,0.008173036,0.004315642,0.0002665049,0.010143579,0.0025198932,0.9724506],"genre_scores_gemma":[0.003319165,0.0014598867,0.00080678595,0.007930684,0.0010568866,0.00020827117,0.007940847,0.0009568379,0.9763207],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99892634,0.00017559025,0.000067858375,0.00019998472,0.00040912753,0.00022101232],"domain_scores_gemma":[0.9967398,0.0004609044,0.00012376442,0.0004338431,0.0011708403,0.001070837],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008961188,0.0009938726,0.00088252773,0.0022867597,0.0023842223,0.007632842,0.0016935251,0.004197904,0.9050368],"category_scores_gemma":[0.007206925,0.00031250736,0.00084763806,0.0017080982,0.00075624004,0.006227988,0.005145776,0.0023204852,0.8021538],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027411525,0.000024399853,0.00017328467,0.00017875379,0.0000022244697,0.00006130408,0.00006173342,0.000015822961,0.00006512016,0.0023952704,0.93229026,0.06470441],"study_design_scores_gemma":[0.0000070613796,0.0000077764935,0.0001960968,0.00008285487,0.0000014299403,0.0000431436,0.00009504396,0.0000109136545,0.00002403468,0.0007868574,0.9987404,0.000004484417],"about_ca_topic_score_codex":0.0045360606,"about_ca_topic_score_gemma":0.0071904478,"teacher_disagreement_score":0.9050368,"about_ca_system_score_codex":0.0015030046,"about_ca_system_score_gemma":0.003040008,"threshold_uncertainty_score":0.1354534},"labels":[],"label_agreement":null},{"id":"W653572276","doi":"","title":"Hybrid approach : Canadian firm bets that hybrid air vehicles will find a niche serving remote locations","year":2011,"lang":"en","type":"article","venue":"Aviation week & space technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Niche; Air travel; Business; Aviation; Aeronautics; Meteorology; Transport engineering; Environmental science; Industrial organization; Aerospace engineering; Engineering; Geography; Ecology; Biology","score_opus":0.020945488779227854,"score_gpt":0.2016538760422356,"score_spread":0.18070838726300775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W653572276","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23013154,0.0006491685,0.005722037,0.022858923,0.00048844464,0.00047756842,0.0026221916,0.0003163374,0.73673373],"genre_scores_gemma":[0.9337616,0.0002680293,0.002129174,0.0060844747,0.000079472535,0.000082946615,0.0005266796,0.000036367554,0.057031255],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99679846,0.00023934236,0.000036676523,0.00032168452,0.0015569263,0.0010470029],"domain_scores_gemma":[0.9963007,0.0007186829,0.0003388441,0.00026924085,0.001265455,0.0011070005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017937192,0.0005393562,0.0003824016,0.0016124854,0.0075138593,0.0071032727,0.0019310106,0.0039067175,0.036061957],"category_scores_gemma":[0.0073118433,0.00034529882,0.00078182115,0.0023446232,0.0025237435,0.0019646783,0.0019595677,0.0040202667,0.002372079],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024882208,0.0009099515,0.17788482,0.00037167358,0.00062517566,0.0015937557,0.003381915,0.016835514,0.006298153,0.21477173,0.34549087,0.22934826],"study_design_scores_gemma":[0.0009220414,0.0010449114,0.3238373,0.00032362624,0.00079234503,0.0010213039,0.0321524,0.037382588,0.004774867,0.08402752,0.5130909,0.00063021365],"about_ca_topic_score_codex":0.89664286,"about_ca_topic_score_gemma":0.97009504,"teacher_disagreement_score":0.103357136,"about_ca_system_score_codex":0.031239223,"about_ca_system_score_gemma":0.036479566,"threshold_uncertainty_score":0.22665751},"labels":[],"label_agreement":null},{"id":"W657369435","doi":"","title":"Uncommon- Use Kiosks","year":2006,"lang":"en","type":"article","venue":"Airports international","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Interactive kiosk; Air travel; Service (business); Transport engineering; Advertising; Space (punctuation); Business; Aeronautics; Engineering; Aviation; Marketing; Computer science; World Wide Web","score_opus":0.00715510768948819,"score_gpt":0.18929927228618915,"score_spread":0.18214416459670096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W657369435","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79072905,0.00059830653,0.015820952,0.001116189,0.00041043237,0.0005089892,0.0016176677,0.004059123,0.18513936],"genre_scores_gemma":[0.94127005,0.0003262537,0.0046479073,0.00052075664,0.00009328535,0.00020026817,0.001998046,0.00048271765,0.05046081],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99355006,0.0008825475,0.00067154574,0.0007607255,0.002880378,0.0012547597],"domain_scores_gemma":[0.97645515,0.0036155207,0.004927463,0.0046642944,0.007259699,0.0030779073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002279299,0.00056011893,0.0004158292,0.0020555838,0.0019215058,0.0028341154,0.0018134784,0.00075782783,0.02432736],"category_scores_gemma":[0.020125624,0.00032712895,0.0004802663,0.0019340079,0.0012110036,0.0039668945,0.0037635916,0.0011119192,0.010681914],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081177475,0.001216324,0.43348202,0.00075230916,0.00015752384,0.002303041,0.008676244,0.0019026843,0.007676294,0.026158294,0.062151443,0.454712],"study_design_scores_gemma":[0.0000932803,0.0014756215,0.43423787,0.0007245936,0.00018822374,0.010123716,0.022121478,0.009622468,0.011316972,0.008826229,0.5009973,0.00027226497],"about_ca_topic_score_codex":0.0087643,"about_ca_topic_score_gemma":0.012659179,"teacher_disagreement_score":0.02432736,"about_ca_system_score_codex":0.0012739756,"about_ca_system_score_gemma":0.0019167044,"threshold_uncertainty_score":0.08138317},"labels":[],"label_agreement":null},{"id":"W659319501","doi":"","title":"Budd cars across the Canadian shield","year":2006,"lang":"en","type":"article","venue":"Railfan and Railroad","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Shield; Forensic engineering; Engineering; Aeronautics; Mining engineering; Archaeology; Geology; History; Paleontology","score_opus":0.006890771046759747,"score_gpt":0.2132710294388541,"score_spread":0.20638025839209434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W659319501","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46561736,0.0051396075,0.0014788008,0.045918956,0.00088446884,0.00015380299,0.0031931985,0.00020677161,0.47740698],"genre_scores_gemma":[0.7046497,0.0019645009,0.00109557,0.0036752564,0.00004992488,0.000030381607,0.00064684515,0.00007543604,0.28781235],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981865,0.00007169276,0.000016739152,0.00018582887,0.0006003271,0.0009388153],"domain_scores_gemma":[0.9978751,0.000072374554,0.00004791903,0.00005197803,0.0011261995,0.000826506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006798102,0.0003065913,0.00028651298,0.0017254985,0.01903751,0.004405309,0.0011222055,0.001363378,0.026744211],"category_scores_gemma":[0.0017885852,0.00033994546,0.00041360914,0.0024415755,0.0022649588,0.0009888532,0.0025211112,0.002520055,0.0015014955],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057672214,0.00024961794,0.15168291,0.00040129942,0.000117542804,0.002922283,0.029852211,0.002578367,0.003711404,0.201681,0.31066483,0.2955618],"study_design_scores_gemma":[0.00001890301,0.000054727207,0.18764547,0.00021697236,0.000041894513,0.00023180507,0.033081576,0.0006656434,0.0006274802,0.0018478144,0.775499,0.00006869936],"about_ca_topic_score_codex":0.9949169,"about_ca_topic_score_gemma":0.9992131,"teacher_disagreement_score":0.087788455,"about_ca_system_score_codex":0.087788455,"about_ca_system_score_gemma":0.1258274,"threshold_uncertainty_score":0.6369528},"labels":[],"label_agreement":null},{"id":"W6888886252","doi":"10.24406/h-418945","title":"Exploring \"automobility engagement”: A predictor of shared, automated, and electric mobility interest?","year":2022,"lang":"en","type":"article","venue":"Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"SFU Community Trust Endowment Fund; Social Sciences and Humanities Research Council of Canada; Simon Fraser University; Pacific Institute for Climate Solutions","keywords":"Work (physics); Measure (data warehouse); Electric shock; Noise (video); Identification (biology)","score_opus":0.06864981845141802,"score_gpt":0.253651943496068,"score_spread":0.18500212504465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6888886252","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99712676,0.000099366924,0.00032812785,0.00035095573,0.000011513564,0.000007751818,0.0002699865,0.0000065811796,0.0017989355],"genre_scores_gemma":[0.9990783,0.000058279926,0.00016993204,0.000036635814,0.000011925403,0.000011794081,0.00028352204,0.0000033173715,0.00034629903],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99911135,0.00040663304,0.000051668067,0.0001624541,0.00009379088,0.00017412448],"domain_scores_gemma":[0.9931952,0.0029511524,0.001618236,0.00051753386,0.00044548218,0.001272312],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013831734,0.000269033,0.0003519538,0.000638528,0.0006468626,0.0020436388,0.00065866945,0.0016518019,0.0068296352],"category_scores_gemma":[0.011888835,0.00025533658,0.00055717304,0.00082289043,0.0005556867,0.0015630963,0.0015285689,0.0010919669,0.0010450702],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016161635,0.00014052671,0.994034,0.00002334416,0.0001312773,0.0000491762,0.0008493519,0.00027580073,0.00018444356,0.00028547976,0.0003495297,0.0035154535],"study_design_scores_gemma":[0.000008471812,0.000103663915,0.9930568,0.000026146905,0.00006721971,0.00011089487,0.0029805554,0.0019003024,0.00012469507,0.0007844382,0.0008226728,0.000014073272],"about_ca_topic_score_codex":0.008191609,"about_ca_topic_score_gemma":0.013871284,"teacher_disagreement_score":0.008191609,"about_ca_system_score_codex":0.00026119905,"about_ca_system_score_gemma":0.0004788059,"threshold_uncertainty_score":0.022847474},"labels":[],"label_agreement":null},{"id":"W6889142258","doi":"10.25384/sage.22273237","title":"sj-docx-1-trr-10.1177_03611981231155434 – Supplemental material for How Has Anticipated Post-Pandemic Ride-Sourcing Use Changed During the COVID-19 Pandemic? Evidence from a Two-Cycle Survey of the Greater Toronto Area","year":2023,"lang":"en","type":"article","venue":"Sage Journals Data","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Survey data collection; Data collection; Work (physics); Survey research","score_opus":0.2557572127194363,"score_gpt":0.3574601875512952,"score_spread":0.10170297483185892,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6889142258","genre_codex":"dataset","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00028623274,0.00002029509,0.00007907907,0.00040184896,0.00014778327,0.000094874806,0.9896215,0.0003881516,0.008960218],"genre_scores_gemma":[0.0051016295,0.00017568498,0.00088215154,0.0007550668,0.00020013347,0.0008782411,0.9290073,0.0008510536,0.06214877],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99810576,0.00015622626,0.00030962846,0.00019022792,0.00092772173,0.0003104013],"domain_scores_gemma":[0.96273315,0.011728672,0.002537648,0.0029020288,0.0178059,0.0022925453],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0017906858,0.00089540106,0.0008605165,0.004394466,0.0016895417,0.0038916771,0.002354702,0.0019355254,0.83475864],"category_scores_gemma":[0.034448884,0.0013611957,0.00088445167,0.00925595,0.0005116686,0.0026174246,0.0022449412,0.0014897309,0.4881903],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003299861,0.00002223291,0.0009870473,0.00025746014,0.000006851345,0.000009005562,0.0000474303,0.000042803145,0.000034298144,0.00016404915,0.99593997,0.0024558867],"study_design_scores_gemma":[0.0006914301,0.000089904104,0.042212978,0.0011564841,0.00004275149,0.000042640164,0.0014811101,0.00027316407,0.00035905134,0.0009035257,0.95266986,0.0000770347],"about_ca_topic_score_codex":0.23405756,"about_ca_topic_score_gemma":0.36873582,"teacher_disagreement_score":0.83475864,"about_ca_system_score_codex":0.0036151044,"about_ca_system_score_gemma":0.007520657,"threshold_uncertainty_score":0.46539038},"labels":[],"label_agreement":null},{"id":"W6891742446","doi":"10.48550/arxiv.1802.06180","title":"Virtual Immersive Reality for Stated Preference Travel Behaviour Experiments: A Case Study of Autonomous Vehicles on Urban Roads","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Preference; Virtual reality; Pedestrian; Preference elicitation; Virtual world; Virtual machine","score_opus":0.14098270849730102,"score_gpt":0.2425126895268069,"score_spread":0.10152998102950589,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6891742446","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.993547,0.000025429375,0.0041354615,0.00005486196,0.000008465952,0.00017470946,0.0004618772,0.000050063692,0.001542096],"genre_scores_gemma":[0.98783475,0.0000560614,0.010198175,0.00003827828,0.0000072018424,0.00020609927,0.00047965904,0.000019509169,0.0011602314],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99877566,0.0008158134,0.000037095826,0.00012111744,0.00014267584,0.00010756558],"domain_scores_gemma":[0.9967584,0.0021937382,0.00020045401,0.00031802466,0.00029663576,0.000232781],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000988579,0.0005420106,0.00035359833,0.00034746522,0.00047845754,0.0005979967,0.0007809191,0.0010663834,0.0033497184],"category_scores_gemma":[0.003970876,0.00022495708,0.00045771126,0.0005064971,0.0005406672,0.000615804,0.00068492093,0.00074725674,0.0004387579],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009354354,0.041388754,0.19615774,0.003603947,0.0009821011,0.010442153,0.041345652,0.32917312,0.16716129,0.016890341,0.016555358,0.16694525],"study_design_scores_gemma":[0.0014128264,0.035124883,0.28674266,0.0002667341,0.0004648493,0.0035364311,0.03701512,0.48143306,0.10530907,0.013962441,0.033922512,0.00080945157],"about_ca_topic_score_codex":0.007507205,"about_ca_topic_score_gemma":0.01432624,"teacher_disagreement_score":0.007507205,"about_ca_system_score_codex":0.00046305472,"about_ca_system_score_gemma":0.00038272253,"threshold_uncertainty_score":0.01492703},"labels":[],"label_agreement":null},{"id":"W6892672565","doi":"10.5281/zenodo.11617424","title":"Rethinking Cars for Sustainable Mobility – Shared-Autonomous Vehicles and Circularity","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Process (computing); Circular economy; Sustainability; State (computer science); Face (sociological concept); Power (physics); Focus (optics); Business model; Sustainable transport","score_opus":0.027081771451227397,"score_gpt":0.2353025030542527,"score_spread":0.20822073160302532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6892672565","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10571247,0.17166229,0.19837289,0.0916148,0.004313114,0.00033745504,0.0006275092,0.0007109794,0.42664853],"genre_scores_gemma":[0.8291267,0.08823268,0.03597613,0.007464898,0.001138742,0.00021758933,0.0004928895,0.00023277813,0.037117667],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980696,0.0005839823,0.00008243253,0.0003105088,0.00066197664,0.0002914366],"domain_scores_gemma":[0.998254,0.0007778106,0.00015068914,0.00022111268,0.00047823827,0.00011816779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001523348,0.00046972837,0.00027319606,0.0014032872,0.0022034245,0.007430447,0.0012054214,0.003012173,0.0039204583],"category_scores_gemma":[0.0027382618,0.00030494048,0.0005515274,0.0015797985,0.0051677534,0.014761408,0.004461049,0.002592572,0.001137288],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000193696,0.000026763973,0.0012458493,0.0006391085,0.000017997532,0.00029862,0.0034097668,0.0024708456,0.0010523484,0.90349025,0.008279347,0.07904977],"study_design_scores_gemma":[0.000004201392,0.00006241132,0.0015350595,0.0011428179,0.000020268679,0.0006223623,0.0081336135,0.0055327606,0.0015725044,0.24299888,0.73831284,0.000062198014],"about_ca_topic_score_codex":0.0067786444,"about_ca_topic_score_gemma":0.0072633177,"teacher_disagreement_score":0.007430447,"about_ca_system_score_codex":0.002640917,"about_ca_system_score_gemma":0.002576255,"threshold_uncertainty_score":0.019161284},"labels":[],"label_agreement":null},{"id":"W6893720134","doi":"10.5281/zenodo.4808265","title":"DOWNLOAD ALBUM: Drake - Care Package (Zip Mp3)","year":2021,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Download; Club; Photography; Ledger","score_opus":0.019782624483414186,"score_gpt":0.22333499239903273,"score_spread":0.20355236791561854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6893720134","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00090731436,0.0004961193,0.01577686,0.0011260363,0.0015695201,0.0007204443,0.11333713,0.25868747,0.607379],"genre_scores_gemma":[0.004571853,0.0003744387,0.0067417133,0.0008723297,0.0004449683,0.0006494383,0.081858166,0.12224662,0.78224045],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995554,0.0000335133,0.000020459363,0.00008263103,0.0002235425,0.00008434286],"domain_scores_gemma":[0.99747926,0.000305313,0.00008030516,0.00049786037,0.0012227227,0.00041454195],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00057815126,0.0020400875,0.0011948296,0.0018480881,0.0012076492,0.0040360414,0.0024754028,0.0014901239,0.89735764],"category_scores_gemma":[0.005659997,0.0013154328,0.0008730245,0.001688973,0.00033466093,0.0044658016,0.0041633155,0.0015699831,0.86409664],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038436698,0.0000074607437,0.00003808546,0.000066138025,0.0000018080674,0.000015055873,0.000016094948,0.000031886204,0.000181472,0.00026210988,0.9830829,0.01625853],"study_design_scores_gemma":[0.00004153643,0.000018815224,0.00044725684,0.00005760348,0.0000052795763,0.000054436026,0.00002667723,0.0002093198,0.00075065036,0.00078316295,0.99758255,0.000022668628],"about_ca_topic_score_codex":0.0054037087,"about_ca_topic_score_gemma":0.0066080675,"teacher_disagreement_score":0.10264236,"about_ca_system_score_codex":0.0010315714,"about_ca_system_score_gemma":0.0006757134,"threshold_uncertainty_score":0.14640689},"labels":[],"label_agreement":null},{"id":"W6903249447","doi":"10.7922/g2zc811p","title":"Innovative Mobility: Carsharing Outlook","year":2018,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Key (lock); Operator (biology); Car sharing; Technology transfer","score_opus":0.01460150917011194,"score_gpt":0.21611608055810327,"score_spread":0.20151457138799134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6903249447","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034992537,0.01472431,0.017708803,0.00828722,0.004230426,0.00019105029,0.008032812,0.021029647,0.92229646],"genre_scores_gemma":[0.032478243,0.023813358,0.011162252,0.0014994447,0.0020019393,0.0001861838,0.021216461,0.0026381873,0.905004],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996871,0.000020849087,0.000008949661,0.000054172877,0.00015007136,0.00007891268],"domain_scores_gemma":[0.9991178,0.00008495906,0.000026709979,0.000081839156,0.00036867915,0.0003201176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010103423,0.0013091424,0.00030448032,0.0013445613,0.000827624,0.0029771577,0.0010098919,0.001586481,0.25249904],"category_scores_gemma":[0.0011772537,0.00027951295,0.00043440744,0.0015729272,0.00036129667,0.004285859,0.0018918035,0.0017199247,0.13053901],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006208423,0.00006930483,0.00024869575,0.00014226274,0.000005559086,0.000048304326,0.000040790685,0.00071958173,0.0010176038,0.0132933045,0.76191646,0.22243612],"study_design_scores_gemma":[0.000009679999,0.000027598613,0.00018334521,0.000053836553,0.0000032041908,0.000033829205,0.00003153123,0.0007015295,0.00037173767,0.0015455015,0.9970305,0.00000764625],"about_ca_topic_score_codex":0.004701957,"about_ca_topic_score_gemma":0.0057072844,"teacher_disagreement_score":0.25249904,"about_ca_system_score_codex":0.0009404195,"about_ca_system_score_gemma":0.0012793367,"threshold_uncertainty_score":0.8446934},"labels":[],"label_agreement":null},{"id":"W6910638101","doi":"10.48550/arxiv.2404.12317","title":"Synthetic Participatory Planning of Shard Automated Electric Mobility Systems","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Workflow; Plan (archaeology); Interpretability; Citizen journalism; Participatory planning; Parameterized complexity; Individual mobility","score_opus":0.08684613444242906,"score_gpt":0.21275554550177436,"score_spread":0.1259094110593453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6910638101","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21328396,0.000071455805,0.76731855,0.00062013656,0.000032889566,0.0002713418,0.00027138475,0.000350818,0.017779466],"genre_scores_gemma":[0.83208406,0.000041686864,0.16469619,0.00004153464,0.000005433651,0.000290184,0.0001963527,0.000055179582,0.0025893052],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974214,0.0018566378,0.000053747757,0.00028510517,0.0002479362,0.0001352456],"domain_scores_gemma":[0.9952362,0.0036617648,0.00021041838,0.0005213202,0.00019471692,0.00017561039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031592848,0.00056513667,0.00036182764,0.0004369798,0.000980415,0.0014332333,0.0011028406,0.0010907826,0.0032413509],"category_scores_gemma":[0.0062357816,0.00037314088,0.0008377239,0.0004577082,0.0019392642,0.0011932838,0.0031946267,0.00070621073,0.00019741095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008878095,0.00005734201,0.0010785122,0.000069618276,0.0000275008,0.0003582724,0.0017390517,0.930784,0.002089939,0.050957896,0.0004148675,0.012334293],"study_design_scores_gemma":[0.000025839556,0.00005889635,0.0001638258,0.000015984766,0.000009179069,0.000027531652,0.00083130033,0.9557954,0.00137183,0.037710562,0.0039762147,0.000013387678],"about_ca_topic_score_codex":0.0054442533,"about_ca_topic_score_gemma":0.00924268,"teacher_disagreement_score":0.0054442533,"about_ca_system_score_codex":0.0016235048,"about_ca_system_score_gemma":0.0016917491,"threshold_uncertainty_score":0.016708076},"labels":[],"label_agreement":null},{"id":"W6923426685","doi":"10.14288/1.0377753","title":"Convenience, savings, or lifestyle? Distinct motivations and travel patterns of one-way and two-way carsharing members in Vancouver, Canada","year":2019,"lang":"en","type":"article","venue":"Open Collections","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Relevance (law); Travel behavior; Mode choice; Point (geometry); Air travel; Taxis; Car ownership","score_opus":0.011692659541933235,"score_gpt":0.21784458924557468,"score_spread":0.20615192970364143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6923426685","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99625564,0.00016784201,0.00003386848,0.00041715917,0.000010633657,0.000018041774,0.00034928494,0.0000026087546,0.002744886],"genre_scores_gemma":[0.9945235,0.00028237462,0.00008744272,0.000121899786,0.000003761214,0.000012190751,0.00028572115,0.000007307607,0.004675698],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992324,0.00008004881,0.000029558325,0.00009130255,0.00014826425,0.00041843095],"domain_scores_gemma":[0.9976521,0.00017257535,0.0002553857,0.000042616397,0.0006600963,0.0012173504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005085902,0.00019776815,0.0004412807,0.0010438503,0.0063819075,0.0031108442,0.0011121734,0.0006726118,0.005526279],"category_scores_gemma":[0.001505593,0.00042364703,0.00046727457,0.0027172603,0.0015884534,0.0007188143,0.0013519085,0.001583614,0.00051803846],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013329422,0.00020906089,0.94095814,0.00003861065,0.00004448757,0.00026279915,0.04075405,0.00006796443,0.00036743892,0.0007069013,0.0032063522,0.013250836],"study_design_scores_gemma":[0.0000069829152,0.00003032465,0.8183427,0.000077274046,0.000015502208,0.00007596546,0.17747235,0.00020136862,0.000069500726,0.000077534925,0.003596354,0.000034197954],"about_ca_topic_score_codex":0.98791647,"about_ca_topic_score_gemma":0.9974867,"teacher_disagreement_score":0.0136504145,"about_ca_system_score_codex":0.0136504145,"about_ca_system_score_gemma":0.018688345,"threshold_uncertainty_score":0.099041164},"labels":[],"label_agreement":null},{"id":"W6928060252","doi":"10.34989/san-2024-24","title":"How do Canadians perceive access to cash?","year":2024,"lang":"en","type":"article","venue":"Bank of Canada Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Cash; Perception; Financial institution; Institution; Measure (data warehouse)","score_opus":0.049388762195506385,"score_gpt":0.3327639532439045,"score_spread":0.28337519104839815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6928060252","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96694404,0.000907037,0.00043306392,0.003685028,0.000053914697,0.000034210898,0.0014539993,0.000015298661,0.026473386],"genre_scores_gemma":[0.99636793,0.0005423379,0.00017136736,0.00036364896,0.00000763762,0.000008813058,0.00046454734,0.0000056895956,0.0020680563],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986438,0.0001348248,0.000041314284,0.00011145031,0.00062448985,0.00044403147],"domain_scores_gemma":[0.99607134,0.00030145512,0.0005366983,0.000082090686,0.0019957698,0.0010126301],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010855849,0.00026017576,0.0003159576,0.001531318,0.004292857,0.0031498652,0.0006654746,0.0006267339,0.0059696613],"category_scores_gemma":[0.005818401,0.00018494092,0.00038062822,0.002659516,0.0023501853,0.0010615188,0.0010256247,0.0009380909,0.00044972723],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022979492,0.0001164533,0.86490595,0.00019671004,0.0001011403,0.0004112779,0.065869436,0.00037462727,0.0007189387,0.0051654847,0.015611942,0.046298172],"study_design_scores_gemma":[0.000019058394,0.00007211946,0.8616865,0.00015801373,0.000041169355,0.00015226685,0.11286009,0.00040230702,0.00016435326,0.0007152394,0.023618564,0.0001103242],"about_ca_topic_score_codex":0.9878511,"about_ca_topic_score_gemma":0.9897054,"teacher_disagreement_score":0.014296059,"about_ca_system_score_codex":0.014296059,"about_ca_system_score_gemma":0.0144303255,"threshold_uncertainty_score":0.10372561},"labels":[],"label_agreement":null},{"id":"W6931667308","doi":"10.5683/sp3/iutdkl","title":"Employers &amp; Newcomer Workforce Integration - Research Report","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Workforce; Workforce development; Work (physics); Workforce planning; Qualitative research","score_opus":0.10897876186821161,"score_gpt":0.37123662420236997,"score_spread":0.2622578623341584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931667308","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004553455,0.000025372477,0.000019582674,0.00008152967,0.0000331029,0.0000075477415,0.99939156,0.00009182448,0.0003040706],"genre_scores_gemma":[0.00014048356,0.000024912919,0.00010051691,0.000051815987,0.000012654738,0.00006933157,0.9984738,0.000040556457,0.0010858988],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99692875,0.00035698456,0.00035673968,0.0006650061,0.0010934374,0.00059903396],"domain_scores_gemma":[0.9882995,0.0021989914,0.0010959634,0.0018188792,0.0043352894,0.0022514018],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034730001,0.004055684,0.0024583007,0.0070881275,0.0014033347,0.004859806,0.004561017,0.004400909,0.11515787],"category_scores_gemma":[0.016883083,0.0015106443,0.002555098,0.01018714,0.00060953264,0.0023166232,0.004065191,0.0035793995,0.20815805],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025283127,0.000011843151,0.0004193445,0.00016651541,0.00001277079,0.0000053380345,0.0000067477663,0.00007127853,0.000015896248,0.00007094169,0.99844545,0.0007486101],"study_design_scores_gemma":[0.001072885,0.000064535496,0.0146396505,0.0007657282,0.0001053184,0.000054915443,0.00024412113,0.0006751018,0.00032356466,0.0011009537,0.9808709,0.00008244138],"about_ca_topic_score_codex":0.099181935,"about_ca_topic_score_gemma":0.1555781,"teacher_disagreement_score":0.11515787,"about_ca_system_score_codex":0.0029710226,"about_ca_system_score_gemma":0.007338486,"threshold_uncertainty_score":0.38524145},"labels":[],"label_agreement":null},{"id":"W6939305385","doi":"10.6084/m9.figshare.16935785.v1","title":"Additional file 1 of Differential impacts of ridesharing on alcohol-related crashes by socioeconomic municipalities: rate of technology adoption matters","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Socioeconomic status; Differential (mechanical device); Table (database); Economic impact analysis; Crash","score_opus":0.013721061623928756,"score_gpt":0.21822329133495624,"score_spread":0.2045022297110275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6939305385","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00027414423,0.000008707924,0.00007205191,0.00006211459,0.000009628292,0.000056840174,0.99868816,0.000043407203,0.0007849545],"genre_scores_gemma":[0.015712421,0.00011539711,0.0014423039,0.00035336343,0.000083626604,0.0022338135,0.9664715,0.00026173133,0.013325785],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.999196,0.00014980778,0.00013938792,0.00016846362,0.00019862002,0.00014785376],"domain_scores_gemma":[0.9836447,0.010039018,0.001664461,0.0008191822,0.0034316233,0.00040098376],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0012610946,0.00087628973,0.0009047428,0.002235863,0.00090415723,0.0009935693,0.0015959555,0.00095656596,0.7901136],"category_scores_gemma":[0.026259838,0.00044446552,0.00096581894,0.004686798,0.00015893554,0.0018394197,0.0010245923,0.00089953427,0.106774785],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015790333,0.000068298395,0.0054588253,0.0009792486,0.000039445687,0.000030016883,0.000059151665,0.00034765512,0.000025454792,0.00056556176,0.98800206,0.004266392],"study_design_scores_gemma":[0.0055897413,0.00055539614,0.20627071,0.006077573,0.00043287224,0.00048207192,0.0023181986,0.004707021,0.00077237946,0.009000962,0.7635916,0.00020145524],"about_ca_topic_score_codex":0.041004896,"about_ca_topic_score_gemma":0.047648787,"teacher_disagreement_score":0.7901136,"about_ca_system_score_codex":0.0011340259,"about_ca_system_score_gemma":0.0020662525,"threshold_uncertainty_score":0.29937738},"labels":[],"label_agreement":null},{"id":"W6949273643","doi":"10.5281/zenodo.14232090","title":"Vehicle Allocation Modeling: Optimizing the Logistics Behind a Free-Flow Carsharing in Milan, Italy","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Resource (disambiguation); Resource allocation; Individual mobility; Value (mathematics); Complement (music); Key (lock); Resource efficiency; Sustainable transport; Demand forecasting","score_opus":0.04440412171598436,"score_gpt":0.2388737394966213,"score_spread":0.19446961778063693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6949273643","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8897198,0.00072832004,0.06289941,0.0011150845,0.00009140113,0.00020382847,0.0011983641,0.00026471057,0.043779004],"genre_scores_gemma":[0.985504,0.00019669074,0.005668547,0.000048615617,0.00001267653,0.000084043364,0.00037943752,0.00003945552,0.008066558],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999803,0.00006276961,0.0000048792313,0.00003942967,0.00001550615,0.00007449181],"domain_scores_gemma":[0.99969673,0.0001647817,0.00003943936,0.000013358223,0.000036861966,0.000048843296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040287044,0.0009689517,0.0006134868,0.0006859769,0.0005537368,0.0016284008,0.0009084481,0.001360895,0.0035310593],"category_scores_gemma":[0.0010385598,0.0005663964,0.000792958,0.0006282476,0.0006500915,0.000732584,0.00085716695,0.00056655216,0.0004016824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039735198,0.000017098992,0.0011043225,0.000013647777,0.000009150869,0.000072990595,0.000023498718,0.99622774,0.00013285194,0.0010166225,0.00032080017,0.001021573],"study_design_scores_gemma":[0.0000097522825,0.000020307465,0.000779965,0.0000054888724,0.000008272078,0.000009021245,0.0000546464,0.99802077,0.000069247784,0.00050920044,0.0005083657,0.0000050283097],"about_ca_topic_score_codex":0.07842532,"about_ca_topic_score_gemma":0.052556686,"teacher_disagreement_score":0.07842532,"about_ca_system_score_codex":0.0025730773,"about_ca_system_score_gemma":0.0021125115,"threshold_uncertainty_score":0.15593767},"labels":[],"label_agreement":null},{"id":"W6958198459","doi":"10.6084/m9.figshare.16935785","title":"Additional file 1 of Differential impacts of ridesharing on alcohol-related crashes by socioeconomic municipalities: rate of technology adoption matters","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Socioeconomic status; Differential (mechanical device); Table (database); Economic impact analysis; Crash","score_opus":0.013721061623928756,"score_gpt":0.21822329133495624,"score_spread":0.2045022297110275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958198459","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00027414423,0.000008707924,0.00007205191,0.00006211459,0.000009628292,0.000056840174,0.99868816,0.000043407203,0.0007849545],"genre_scores_gemma":[0.015712421,0.00011539711,0.0014423039,0.00035336343,0.000083626604,0.0022338135,0.9664715,0.00026173133,0.013325785],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.999196,0.00014980778,0.00013938792,0.00016846362,0.00019862002,0.00014785376],"domain_scores_gemma":[0.9836447,0.010039018,0.001664461,0.0008191822,0.0034316233,0.00040098376],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0012610946,0.00087628973,0.0009047428,0.002235863,0.00090415723,0.0009935693,0.0015959555,0.00095656596,0.7901136],"category_scores_gemma":[0.026259838,0.00044446552,0.00096581894,0.004686798,0.00015893554,0.0018394197,0.0010245923,0.00089953427,0.106774785],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015790333,0.000068298395,0.0054588253,0.0009792486,0.000039445687,0.000030016883,0.000059151665,0.00034765512,0.000025454792,0.00056556176,0.98800206,0.004266392],"study_design_scores_gemma":[0.0055897413,0.00055539614,0.20627071,0.006077573,0.00043287224,0.00048207192,0.0023181986,0.004707021,0.00077237946,0.009000962,0.7635916,0.00020145524],"about_ca_topic_score_codex":0.041004896,"about_ca_topic_score_gemma":0.047648787,"teacher_disagreement_score":0.7901136,"about_ca_system_score_codex":0.0011340259,"about_ca_system_score_gemma":0.0020662525,"threshold_uncertainty_score":0.29937738},"labels":[],"label_agreement":null},{"id":"W6964256148","doi":"10.25904/1912/4813","title":"Energy Conservation Education Intervention for People with End-Stage Kidney Disease Receiving Haemodialysis (EVEREST)","year":2023,"lang":"en","type":"other","venue":"Griffith Research Online (Griffith University, Queensland, Australia)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quality of life (healthcare); Intervention (counseling); Psychological intervention; Kidney disease; Patient education; Dialysis; Cluster randomised controlled trial; Randomized controlled trial","score_opus":0.06425700167847068,"score_gpt":0.33397867648097773,"score_spread":0.2697216748025071,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6964256148","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941565,0.0009935227,0.00018747809,0.00060552557,0.000074173244,0.002700389,0.00011102721,0.000009531442,0.0011617938],"genre_scores_gemma":[0.97814196,0.0028656924,0.005177914,0.000953191,0.000075372154,0.011293232,0.00015497667,0.0000019663455,0.0013358404],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99959034,0.0002202069,0.000042893218,0.000044158,0.000045868386,0.00005649758],"domain_scores_gemma":[0.99929345,0.00035567733,0.000143235,0.00002100838,0.000039545524,0.00014714569],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014416031,0.00018275323,0.00062117726,0.0002544425,0.0005900734,0.0004453449,0.00044296947,0.0006707339,0.0028547281],"category_scores_gemma":[0.0021801414,0.00018232297,0.00071989646,0.00020675556,0.00026409578,0.0003567543,0.0010530314,0.000922051,0.00013115956],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.06900526,0.11446904,0.036608595,0.028062925,0.000998558,0.0004951872,0.012949251,0.0010336913,0.008129857,0.002330846,0.005067533,0.7208492],"study_design_scores_gemma":[0.13558315,0.49142435,0.3231097,0.007441034,0.003012373,0.0005242229,0.009494007,0.0019174287,0.0053734146,0.0014896445,0.02052295,0.00010773854],"about_ca_topic_score_codex":0.001175883,"about_ca_topic_score_gemma":0.002250472,"teacher_disagreement_score":0.0028547281,"about_ca_system_score_codex":0.00045716204,"about_ca_system_score_gemma":0.0023130223,"threshold_uncertainty_score":0.009550035},"labels":[],"label_agreement":null},{"id":"W6967945427","doi":"10.5281/zenodo.14232091","title":"Vehicle Allocation Modeling: Optimizing the Logistics Behind a Free-Flow Carsharing in Milan, Italy","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Resource (disambiguation); Resource allocation; Individual mobility; Value (mathematics); Complement (music); Key (lock); Resource efficiency; Sustainable transport; Demand forecasting","score_opus":0.04440412171598436,"score_gpt":0.2388737394966213,"score_spread":0.19446961778063693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6967945427","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8897198,0.00072832004,0.06289941,0.0011150845,0.00009140113,0.00020382847,0.0011983641,0.00026471057,0.043779004],"genre_scores_gemma":[0.985504,0.00019669074,0.005668547,0.000048615617,0.00001267653,0.000084043364,0.00037943752,0.00003945552,0.008066558],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999803,0.00006276961,0.0000048792313,0.00003942967,0.00001550615,0.00007449181],"domain_scores_gemma":[0.99969673,0.0001647817,0.00003943936,0.000013358223,0.000036861966,0.000048843296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040287044,0.0009689517,0.0006134868,0.0006859769,0.0005537368,0.0016284008,0.0009084481,0.001360895,0.0035310593],"category_scores_gemma":[0.0010385598,0.0005663964,0.000792958,0.0006282476,0.0006500915,0.000732584,0.00085716695,0.00056655216,0.0004016824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039735198,0.000017098992,0.0011043225,0.000013647777,0.000009150869,0.000072990595,0.000023498718,0.99622774,0.00013285194,0.0010166225,0.00032080017,0.001021573],"study_design_scores_gemma":[0.0000097522825,0.000020307465,0.000779965,0.0000054888724,0.000008272078,0.000009021245,0.0000546464,0.99802077,0.000069247784,0.00050920044,0.0005083657,0.0000050283097],"about_ca_topic_score_codex":0.07842532,"about_ca_topic_score_gemma":0.052556686,"teacher_disagreement_score":0.07842532,"about_ca_system_score_codex":0.0025730773,"about_ca_system_score_gemma":0.0021125115,"threshold_uncertainty_score":0.15593767},"labels":[],"label_agreement":null},{"id":"W6968189930","doi":"10.5281/zenodo.16740064","title":"Elite GTA Towing","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Towing; Elite; Service (business); Downtown; Port (circuit theory); Swift","score_opus":0.01975783845286184,"score_gpt":0.2331441999081922,"score_spread":0.21338636145533038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6968189930","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13562854,0.002112366,0.024743306,0.0046953578,0.0019333187,0.0003099183,0.0020634884,0.003674635,0.8248391],"genre_scores_gemma":[0.14778888,0.0015545206,0.0134573355,0.00071116386,0.00019915689,0.000066785586,0.0019895928,0.001221743,0.83301073],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99910575,0.00004745975,0.000024645475,0.00012464962,0.00046734005,0.00023011214],"domain_scores_gemma":[0.99869674,0.00005225328,0.000031059677,0.000096421085,0.0004752339,0.00064832874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001237355,0.0007671568,0.0002963965,0.00072615116,0.0029183656,0.0019634098,0.000866028,0.00077003957,0.1661617],"category_scores_gemma":[0.0011266866,0.0002976172,0.0004056892,0.0013946116,0.00089444255,0.0015576391,0.0030346627,0.0013277169,0.0481222],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038474536,0.00069045776,0.009019638,0.00042768958,0.000031801454,0.0015463447,0.005832976,0.0009610446,0.013997727,0.00434907,0.46276084,0.49999768],"study_design_scores_gemma":[0.0000313087,0.00036683993,0.01230611,0.000104409024,0.000017027149,0.0016358788,0.0038154742,0.00067866006,0.002793098,0.0010207413,0.9771817,0.00004883222],"about_ca_topic_score_codex":0.043343104,"about_ca_topic_score_gemma":0.14122182,"teacher_disagreement_score":0.1661617,"about_ca_system_score_codex":0.002022114,"about_ca_system_score_gemma":0.003183113,"threshold_uncertainty_score":0.55586624},"labels":[],"label_agreement":null},{"id":"W6977064043","doi":"10.6084/m9.figshare.19311479","title":"Additional file 5 of LIBERATE: a study protocol for midodrine for the early liberation from vasopressor support in the intensive care unit (LIBERATE): protocol for a randomized controlled trial","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Health Services; University of Calgary; University of Alberta","funders":"","keywords":"Midodrine; Randomized controlled trial; Protocol (science); Intensive care unit; Product (mathematics); Patient care","score_opus":0.05235502668504984,"score_gpt":0.321787585357884,"score_spread":0.26943255867283417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6977064043","genre_codex":"dataset","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"protocol","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024689012,0.0010487172,0.004333129,0.0021360815,0.0009724506,0.14598328,0.8225051,0.0015477198,0.019004656],"genre_scores_gemma":[0.025296422,0.0011335071,0.017356666,0.0034684238,0.00057819416,0.8301082,0.07833792,0.00060672115,0.0431139],"study_design_codex":"not_applicable","study_design_gemma":"randomized_trial","domain_scores_codex":[0.9975829,0.0011924066,0.00043226342,0.00027644774,0.0002762722,0.00023973345],"domain_scores_gemma":[0.97286576,0.019838132,0.002775929,0.0012941675,0.0024678442,0.0007580906],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007050938,0.0016303477,0.0027951912,0.0012297713,0.0009898442,0.0018027176,0.0014117098,0.0020350756,0.8218895],"category_scores_gemma":[0.04349232,0.0012687704,0.001430318,0.0018568947,0.0006603291,0.0015835643,0.0007234177,0.0021621007,0.071213074],"study_design_candidate":"randomized_trial","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.037217613,0.0011177621,0.0004803945,0.040274773,0.00045320427,0.00008191929,0.00027248444,0.00081667566,0.0002956313,0.005394827,0.8800568,0.03353803],"study_design_scores_gemma":[0.52970076,0.005099866,0.0074589504,0.020538617,0.0010595953,0.00025407065,0.00027824639,0.00305621,0.0009986077,0.025344152,0.4059902,0.00022068218],"about_ca_topic_score_codex":0.0025775358,"about_ca_topic_score_gemma":0.0045331526,"teacher_disagreement_score":0.8218895,"about_ca_system_score_codex":0.0020295987,"about_ca_system_score_gemma":0.0037628335,"threshold_uncertainty_score":0.25405294},"labels":[],"label_agreement":null},{"id":"W6978013434","doi":"10.7922/g28w3bnj","title":"Local Governments Adopted Strategies to Improve Shared Micromobility Infrastructure","year":2024,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Agency (philosophy); General partnership; Sustainability; Pandemic; Work (physics); Data collection","score_opus":0.00635203930635428,"score_gpt":0.20305734599331524,"score_spread":0.19670530668696096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6978013434","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42043373,0.002851326,0.080760054,0.09827338,0.0011807444,0.005295099,0.0010453411,0.0043737846,0.3857865],"genre_scores_gemma":[0.9254938,0.0008830991,0.025437076,0.008484838,0.00015399796,0.001095762,0.00054603367,0.00012976464,0.03777567],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99543375,0.0014894434,0.00014963478,0.0004651471,0.0009050099,0.0015568883],"domain_scores_gemma":[0.9926501,0.0011409777,0.00080934056,0.001297591,0.0026880095,0.0014138644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0060978425,0.00074787333,0.00043496583,0.002815984,0.0057713087,0.0051613194,0.0037163836,0.0028990225,0.01400931],"category_scores_gemma":[0.013577539,0.0005064206,0.0008040875,0.0037882833,0.0034330166,0.006311194,0.014205415,0.0029571184,0.0015604768],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014448345,0.0012795104,0.04952242,0.0017733292,0.00019807543,0.0018831877,0.033617612,0.018850116,0.004350609,0.2749141,0.15531285,0.45815378],"study_design_scores_gemma":[0.00012401,0.0005888745,0.03521552,0.00063860416,0.00012012058,0.00030544173,0.04257281,0.005749513,0.0020858436,0.032465253,0.8800356,0.00009837242],"about_ca_topic_score_codex":0.045367952,"about_ca_topic_score_gemma":0.07797291,"teacher_disagreement_score":0.045367952,"about_ca_system_score_codex":0.010032553,"about_ca_system_score_gemma":0.03300145,"threshold_uncertainty_score":0.090207756},"labels":[],"label_agreement":null},{"id":"W6980135128","doi":"","title":"Automobility realism: How the auto-dominated present constrains our imagined futures","year":2020,"lang":"en","type":"dissertation","venue":"Open MIND","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Vision; Futures contract; Futures studies; Sociotechnical system; Conceptual framework; Hierarchy; Nexus (standard); Corporate governance; Vulnerability (computing)","score_opus":0.030022560317106824,"score_gpt":0.30080242408268976,"score_spread":0.27077986376558294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6980135128","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14715663,0.0042382786,0.029195301,0.060753725,0.00072831794,0.00005905303,0.00009017754,0.000114515715,0.757664],"genre_scores_gemma":[0.98753184,0.0007951099,0.0013375161,0.0015100907,0.000105654566,0.000037489302,0.000024193534,0.000047364392,0.008610854],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99306256,0.005251832,0.00008628558,0.00056858186,0.0005491753,0.00048150148],"domain_scores_gemma":[0.99617934,0.002332802,0.0002772979,0.0005376857,0.00028490173,0.0003880291],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059591904,0.0006542335,0.00039245852,0.0015010294,0.010908063,0.016033081,0.0015894006,0.0039172117,0.0076674414],"category_scores_gemma":[0.007188331,0.00055622007,0.0006461636,0.00090576615,0.07210248,0.017159948,0.009286135,0.0057982425,0.00086788094],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015178623,0.000010566618,0.00035721954,0.00003224292,0.0000042997403,0.00013043323,0.061477363,0.00038574619,0.00011203041,0.9333929,0.0019347069,0.0021473202],"study_design_scores_gemma":[0.000027241547,0.00003988755,0.0006555366,0.0003037318,0.000014821471,0.0003472549,0.09119588,0.0015489663,0.0002446174,0.63888085,0.2666875,0.000053576732],"about_ca_topic_score_codex":0.009205864,"about_ca_topic_score_gemma":0.007696688,"teacher_disagreement_score":0.016033081,"about_ca_system_score_codex":0.0076616323,"about_ca_system_score_gemma":0.0033859373,"threshold_uncertainty_score":0.05558926},"labels":[],"label_agreement":null},{"id":"W6987872822","doi":"","title":"UNDERSTANDING BEHAVIORAL INTENTION AND ADOPTION OF AUTOMATED VEHICLES IN CANADIAN CENSUS METROPOLITAN AREAS","year":2023,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Strong","keywords":"Metropolitan area; Context (archaeology); Sustainability; Data collection; Travel behavior; Theory of planned behavior; Census; Focus group","score_opus":0.04234657095898646,"score_gpt":0.24162840085254655,"score_spread":0.19928182989356008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6987872822","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932674,0.0001629717,0.0001608147,0.00040987536,0.000008535947,0.000053523603,0.0008881786,0.000006606072,0.0050421325],"genre_scores_gemma":[0.99783224,0.00031194818,0.00025708068,0.00006311165,0.0000020953437,0.00002972765,0.0006128853,0.0000029690577,0.00088782376],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99891484,0.00009632485,0.000058861202,0.00013741537,0.00048013037,0.0003125262],"domain_scores_gemma":[0.996259,0.00044754648,0.00064688624,0.0001422691,0.0018359065,0.00066839514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001611372,0.00034150417,0.00032557733,0.001991812,0.0033692117,0.0020695254,0.0013480387,0.00044744255,0.002575772],"category_scores_gemma":[0.0063083298,0.000313722,0.00068889064,0.003913468,0.0012219499,0.00086900097,0.0012194267,0.00084076874,0.00021424351],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030462741,0.00009800034,0.97816133,0.00003813534,0.000034449156,0.000039549937,0.009841918,0.0002781066,0.00012931431,0.0008007484,0.0011815388,0.009366341],"study_design_scores_gemma":[0.00000365496,0.000026649666,0.97850776,0.000055698674,0.000017933335,0.000012256583,0.018505143,0.0008685088,0.0000613552,0.00008041364,0.0018419854,0.000018631168],"about_ca_topic_score_codex":0.9963898,"about_ca_topic_score_gemma":0.99750715,"teacher_disagreement_score":0.028426426,"about_ca_system_score_codex":0.028426426,"about_ca_system_score_gemma":0.0362692,"threshold_uncertainty_score":0.20624912},"labels":[],"label_agreement":null},{"id":"W6987931736","doi":"","title":"Using the Social Identity Approach to Understand Pro-Social and Anti-Social Moral Behaviour Toward Teammates in Competitive Youth Soccer.","year":2023,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cape Breton University; Nipissing University","funders":"","keywords":"Social identity theory; Identity (music); Association (psychology); Identification (biology); Social cognitive theory; Affect (linguistics); Test (biology); Competition (biology); Social identity approach","score_opus":0.158266942694912,"score_gpt":0.3329841697835464,"score_spread":0.17471722708863438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6987931736","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9715153,0.0030501715,0.008350861,0.002219388,0.00013951259,0.00013032509,0.00009363128,0.000009805079,0.0144911],"genre_scores_gemma":[0.9941837,0.0012641284,0.0031769439,0.0002843231,0.000025354399,0.00011137768,0.000050798364,0.0000036072502,0.0008996903],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988236,0.00064004696,0.00005263901,0.00013865993,0.00020871316,0.00013630492],"domain_scores_gemma":[0.9984958,0.00046298298,0.00052885694,0.00007003914,0.00016926446,0.00027305956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024695988,0.00045120955,0.00038449472,0.0021412678,0.0014869296,0.0021542544,0.0005370316,0.0007354257,0.0013460463],"category_scores_gemma":[0.003170922,0.0001986299,0.0006050928,0.0010254175,0.0024655717,0.0021793293,0.002412506,0.0014780978,0.00014758494],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052791936,0.00060823414,0.75674355,0.00039143773,0.00014855762,0.0005470436,0.10065155,0.0005646918,0.0018184693,0.02444711,0.0012474895,0.11277897],"study_design_scores_gemma":[0.0000087181,0.00021776593,0.8754883,0.00035997474,0.000060216425,0.00057020655,0.09598119,0.001784803,0.00039521052,0.017339114,0.0077644144,0.000030099729],"about_ca_topic_score_codex":0.0119347535,"about_ca_topic_score_gemma":0.029684618,"teacher_disagreement_score":0.0119347535,"about_ca_system_score_codex":0.0017348495,"about_ca_system_score_gemma":0.0020761094,"threshold_uncertainty_score":0.023730576},"labels":[],"label_agreement":null},{"id":"W6993051822","doi":"","title":"News | Taxelco launches Téo, a reinvented taxi service for Montreal","year":2015,"lang":"en","type":"other","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Service (business); Government (linguistics); Postal service; Service provider; Work (physics)","score_opus":0.024946251453174407,"score_gpt":0.23486748482009193,"score_spread":0.2099212333669175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6993051822","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020469949,0.0034033814,0.0004501725,0.091062054,0.018549722,0.00023037512,0.012295393,0.0019383914,0.87002355],"genre_scores_gemma":[0.0025710384,0.00049138063,0.00007250595,0.004983523,0.0005920888,0.000017664657,0.0015830005,0.00011453158,0.98957425],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992508,0.000023553466,0.000010394066,0.000053884505,0.0004318144,0.00022947557],"domain_scores_gemma":[0.9989785,0.000051634204,0.000025904099,0.000033893102,0.00050780224,0.0004022379],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066126435,0.00090071786,0.00039403132,0.0009107691,0.0039217765,0.0056799767,0.0010036081,0.004397874,0.25850266],"category_scores_gemma":[0.0017548249,0.00040872052,0.0006552188,0.00087889534,0.00088708836,0.0014791173,0.00122454,0.0045374045,0.079330094],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000067725555,0.0000061357787,0.00008455993,0.00000844489,8.828997e-7,0.000022640623,0.000008978701,0.000011955724,0.000034626162,0.00052015757,0.99625033,0.003044439],"study_design_scores_gemma":[0.000007906688,0.0000057394805,0.0011766537,0.000013164354,0.0000014929113,0.000008418222,0.000051575684,0.000041507334,0.000044561708,0.000085423424,0.99855834,0.0000052747405],"about_ca_topic_score_codex":0.60334474,"about_ca_topic_score_gemma":0.8549775,"teacher_disagreement_score":0.39665526,"about_ca_system_score_codex":0.007496029,"about_ca_system_score_gemma":0.015801081,"threshold_uncertainty_score":0.86477757},"labels":[],"label_agreement":null},{"id":"W6997167906","doi":"","title":"Urban Rapid Rail Transit System Intermodality: &#13;\\nIdentifying Themes In Urban Public Transit within Canada and the United States","year":2023,"lang":"en","type":"dissertation","venue":"Spectrum Research Repository (Concordia University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"U.S. Department of Transportation","keywords":"Public transport; Index (typography); Rail transit; Service (business); Transit (satellite); Transit system; Public service; Level of service; Transportation infrastructure","score_opus":0.023769966058706883,"score_gpt":0.23472553861833936,"score_spread":0.2109555725596325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6997167906","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95635676,0.0006575234,0.0009227849,0.00069295126,0.000025417166,0.000090383306,0.005346558,0.00005970298,0.03584792],"genre_scores_gemma":[0.99265,0.00041534327,0.0006580242,0.000054498123,0.0000065571517,0.00003264365,0.002021377,0.000022990444,0.00413856],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9993807,0.000040833245,0.000023025088,0.000079003985,0.00023488546,0.000241522],"domain_scores_gemma":[0.99860865,0.0000691448,0.0002251002,0.0000398408,0.0008400065,0.00021727613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040339577,0.0001538215,0.0001503479,0.0047414876,0.0027263165,0.002236327,0.0005265446,0.00018780172,0.0025366382],"category_scores_gemma":[0.0016069096,0.00010131517,0.00021791935,0.010395807,0.001419368,0.00077296677,0.0018776782,0.00034861205,0.00017951138],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008397756,0.000031193074,0.85081327,0.00020542067,0.00003097847,0.00035818332,0.044871427,0.0009091525,0.0016538231,0.013900348,0.0105268,0.07661541],"study_design_scores_gemma":[0.0000012572976,0.00000965257,0.9266235,0.00007265905,0.000013164541,0.000094365576,0.04481433,0.00061571354,0.00020283989,0.00041559615,0.027123544,0.0000132878495],"about_ca_topic_score_codex":0.9558593,"about_ca_topic_score_gemma":0.97864026,"teacher_disagreement_score":0.044140697,"about_ca_system_score_codex":0.015300821,"about_ca_system_score_gemma":0.016850451,"threshold_uncertainty_score":0.11101574},"labels":[],"label_agreement":null},{"id":"W6998602294","doi":"","title":"Analyzing the Competitiveness of Transit-Integrated Ridesourcing Systems","year":2022,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Transit (satellite); Public transport; Typology; Dispose pattern","score_opus":0.007422494887539621,"score_gpt":0.18479716993096407,"score_spread":0.17737467504342444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6998602294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9905849,0.00006848792,0.00062530086,0.000041598654,0.000003522779,0.000059389728,0.00039682913,0.000010589054,0.008209283],"genre_scores_gemma":[0.99784696,0.00005967787,0.0006260283,0.000004767721,0.0000023186983,0.000018976432,0.0005318363,0.000006471324,0.0009029107],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99794406,0.00039757276,0.00016827292,0.00028311458,0.00085311505,0.00035399993],"domain_scores_gemma":[0.9938222,0.001193537,0.0010592097,0.00028630413,0.003043206,0.000595497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015616079,0.00028856078,0.0002908821,0.00422189,0.0009269464,0.0032577622,0.0008064585,0.00041048368,0.0045236344],"category_scores_gemma":[0.008660952,0.00015522372,0.00037927282,0.0062939,0.001132159,0.0022698056,0.0017180502,0.00023523113,0.0005176485],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033309447,0.00019066955,0.94369215,0.00018732596,0.00016821876,0.0006153328,0.005996035,0.007949238,0.0022471969,0.005310412,0.0011165367,0.032193694],"study_design_scores_gemma":[0.000021301323,0.0004715429,0.9232434,0.000055459688,0.00008823791,0.00022165435,0.050037082,0.017296592,0.0013252744,0.0007804376,0.0064295726,0.000029403565],"about_ca_topic_score_codex":0.09836157,"about_ca_topic_score_gemma":0.134716,"teacher_disagreement_score":0.09836157,"about_ca_system_score_codex":0.0045650518,"about_ca_system_score_gemma":0.0016071384,"threshold_uncertainty_score":0.19557804},"labels":[],"label_agreement":null},{"id":"W6998607409","doi":"","title":"Anàlisi de l’eficiència del servei de taxi a Barcelona. Propostes de millora","year":2010,"lang":"ca","type":"dissertation","venue":"UPCommons institutional repository (Universitat Politècnica de Catalunya)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tourism; Quarter (Canadian coin); Electrocution","score_opus":0.006589740966763382,"score_gpt":0.22184849121416575,"score_spread":0.21525875024740238,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6998607409","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94877183,0.0020118977,0.005030426,0.0020874012,0.00006798345,0.000045750265,0.0071446225,0.0002403465,0.034599684],"genre_scores_gemma":[0.97837824,0.00042536212,0.0015768989,0.00005533548,0.000007976745,0.000023321705,0.0027661768,0.00004182083,0.016725],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99956125,0.000103636805,0.00001908793,0.0001243031,0.00012025761,0.00007145966],"domain_scores_gemma":[0.9985669,0.0005281551,0.00021093318,0.000098995806,0.0004912297,0.0001037207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088286796,0.0003739881,0.00038179694,0.0017591413,0.00044585927,0.001896846,0.0007000007,0.0005727928,0.007916783],"category_scores_gemma":[0.0037641118,0.00036072708,0.00050676975,0.0025692717,0.00036444984,0.00054803555,0.0006962403,0.00067782315,0.0017487961],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012113926,0.00019694315,0.7354879,0.0006447566,0.0004741039,0.00071237836,0.0042477413,0.09514116,0.003571031,0.012869168,0.02915382,0.11628956],"study_design_scores_gemma":[0.000043016666,0.00021623631,0.8934138,0.0001267527,0.00015807383,0.00018941327,0.006520114,0.059871767,0.0017197045,0.0025470739,0.03513309,0.000060932427],"about_ca_topic_score_codex":0.30406302,"about_ca_topic_score_gemma":0.3398607,"teacher_disagreement_score":0.30406302,"about_ca_system_score_codex":0.0044864165,"about_ca_system_score_gemma":0.0011896454,"threshold_uncertainty_score":0.60458636},"labels":[],"label_agreement":null},{"id":"W6999182963","doi":"","title":"CARSHARINGâS IMPACT ON HOUSEHOLD VEHICLE HOLDINGS: RESULTS FROM A NORTH AMERICAN SHARED-USE VEHICLE SURVEY","year":2010,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"San José State University; Arizona State University; California Department of Transportation; University of California, Davis; U.S. Department of Transportation","keywords":"Metropolitan area; Vehicle miles of travel; Sample (material); Survey data collection; Gallon (US); Distribution (mathematics); Aggregate (composite)","score_opus":0.023024256458277385,"score_gpt":0.22011108138090027,"score_spread":0.1970868249226229,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6999182963","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997962,0.000036026606,0.000055765522,0.000034383545,0.0000020207465,0.000013457216,0.0013261439,0.0000033441418,0.00056688936],"genre_scores_gemma":[0.9956938,0.00015590299,0.00014620207,0.000052243577,0.0000045588367,0.000041436364,0.0026696953,0.000003885797,0.0012322906],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99952066,0.0001512105,0.00003280752,0.00007990621,0.00014526663,0.00007025279],"domain_scores_gemma":[0.99845576,0.00030957078,0.00038643574,0.00011307791,0.00055253785,0.00018265026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007266828,0.00019607006,0.00018341081,0.0007610995,0.00046170465,0.00048350624,0.00032530772,0.0002856274,0.001537781],"category_scores_gemma":[0.00096271874,0.00025621348,0.00035962398,0.001517247,0.00022926,0.00050958013,0.000602165,0.00039437704,0.00045281713],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031009975,0.000113395705,0.995023,0.000016008682,0.00003890038,0.00002945116,0.0007131832,0.0000809197,0.00017692415,0.000016495303,0.0005930692,0.003167541],"study_design_scores_gemma":[0.0000011004256,0.00003444775,0.99806494,0.000003964668,0.000009647497,0.00001748441,0.0013646358,0.00010827496,0.000059121423,0.0000055347055,0.00032828777,0.0000025603238],"about_ca_topic_score_codex":0.11111266,"about_ca_topic_score_gemma":0.25201234,"teacher_disagreement_score":0.11111266,"about_ca_system_score_codex":0.0006199001,"about_ca_system_score_gemma":0.00052440015,"threshold_uncertainty_score":0.22093183},"labels":[],"label_agreement":null},{"id":"W7008908401","doi":"","title":"Curbing Enthusiasm: Examining Canadian Cities’ Proactive Responses to Evolving Curbside Pressures","year":2024,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Amenity; Flexibility (engineering); Pace; Corporate governance; Public transport; Government (linguistics); Public policy; Diversity (politics)","score_opus":0.014725443243776311,"score_gpt":0.20859890930766606,"score_spread":0.19387346606388975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7008908401","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94094694,0.0007487011,0.00043467502,0.007190956,0.000096010204,0.00023730799,0.0013345019,0.000053424632,0.048957597],"genre_scores_gemma":[0.987541,0.00083574647,0.0005091952,0.0011783296,0.000016858841,0.00011447396,0.00063490105,0.00003643674,0.009133139],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.9939389,0.00068495626,0.00016591171,0.0004380293,0.0022069893,0.002565319],"domain_scores_gemma":[0.984057,0.0014812048,0.0016162604,0.00041799905,0.009183902,0.0032436084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049483473,0.000594385,0.0006110144,0.0053636143,0.021338068,0.009150182,0.0040311296,0.0018859135,0.005898798],"category_scores_gemma":[0.013656958,0.00060901116,0.0006360957,0.011436869,0.0064809727,0.0030188404,0.006135219,0.0025957169,0.0006182209],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027220015,0.00025349617,0.30957285,0.0005353796,0.00006390143,0.0006384545,0.58549184,0.00046799867,0.0010851087,0.010674791,0.038041364,0.05290264],"study_design_scores_gemma":[0.000011133862,0.000051076167,0.23563993,0.00016182032,0.000020890171,0.00003411816,0.72262883,0.0003744891,0.00014391169,0.00035976034,0.04047713,0.00009692026],"about_ca_topic_score_codex":0.9923822,"about_ca_topic_score_gemma":0.99668294,"teacher_disagreement_score":0.16733225,"about_ca_system_score_codex":0.16733225,"about_ca_system_score_gemma":0.17977478,"threshold_uncertainty_score":0.96577656},"labels":[],"label_agreement":null},{"id":"W7008932393","doi":"","title":"Designing and Implementing effective autonomous vehicle regulation in Toronto, Ontario","year":2018,"lang":"en","type":"dissertation","venue":"DSpace@MIT (Massachusetts Institute of Technology)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Context (archaeology); Data collection; Process (computing); Control (management)","score_opus":0.006714935285772397,"score_gpt":0.24130989318363316,"score_spread":0.23459495789786078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7008932393","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7097959,0.0027167029,0.06807742,0.0067571052,0.00014480992,0.0010926132,0.001247412,0.0008759381,0.2092921],"genre_scores_gemma":[0.9397929,0.0011101564,0.016612628,0.00020583102,0.000010247361,0.0001931624,0.0005049521,0.0000847099,0.04148547],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99847645,0.00027580882,0.00004682639,0.00019913394,0.0005645026,0.00043723092],"domain_scores_gemma":[0.99862874,0.00024865996,0.00009100302,0.00010017571,0.00064980827,0.00028174798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013319503,0.00038748368,0.00028781316,0.00028871212,0.005628416,0.0022853035,0.0010349399,0.0007306659,0.0045050853],"category_scores_gemma":[0.0027428963,0.00043176528,0.00031153372,0.00076363387,0.0029528937,0.00072740024,0.0014257501,0.0006119641,0.00050644425],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017292982,0.00060805824,0.10612238,0.0015555056,0.00022701202,0.002420336,0.072769195,0.19206697,0.04423607,0.13700858,0.07292378,0.3683329],"study_design_scores_gemma":[0.00043209107,0.0010345002,0.16506633,0.0005336137,0.00031744572,0.00023995378,0.06782824,0.17871104,0.027469119,0.013009541,0.5450506,0.00030754338],"about_ca_topic_score_codex":0.98076415,"about_ca_topic_score_gemma":0.99460006,"teacher_disagreement_score":0.051410332,"about_ca_system_score_codex":0.051410332,"about_ca_system_score_gemma":0.10184128,"threshold_uncertainty_score":0.3730098},"labels":[],"label_agreement":null},{"id":"W7010243861","doi":"","title":"Horizontal Collusions Organized by Uber: Time for a Change in Canada","year":2020,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Competition (biology); Section (typography); Competition law; Market competition","score_opus":0.012123711879084882,"score_gpt":0.21078506245518625,"score_spread":0.19866135057610138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7010243861","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7689033,0.00095119973,0.0024303023,0.0564327,0.00032904497,0.00012463152,0.00030869112,0.000093633214,0.17042652],"genre_scores_gemma":[0.9709265,0.00033526408,0.0005923621,0.003234835,0.000022109458,0.000014390466,0.00006951535,0.000027468419,0.0247776],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9934088,0.00034452358,0.00008345179,0.00058848556,0.001909594,0.003665183],"domain_scores_gemma":[0.99412537,0.00061552133,0.00052461907,0.00030767365,0.0019236006,0.0025030933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023671563,0.00022153358,0.000366378,0.0010958543,0.026468663,0.009823898,0.0024499085,0.0030524663,0.0087841805],"category_scores_gemma":[0.0069908043,0.0003860084,0.00047516535,0.0022239075,0.009890926,0.0030390038,0.005284328,0.004868803,0.00033756418],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001494358,0.00020862541,0.087461926,0.000108591885,0.000061190745,0.004600544,0.08479477,0.0018071365,0.0017553276,0.6751196,0.061581258,0.0823516],"study_design_scores_gemma":[0.000059439528,0.000099798744,0.15064722,0.00028646697,0.000073206895,0.0005357727,0.23342746,0.004862434,0.0015382172,0.031148717,0.5770833,0.00023796034],"about_ca_topic_score_codex":0.98438835,"about_ca_topic_score_gemma":0.993258,"teacher_disagreement_score":0.09275948,"about_ca_system_score_codex":0.09275948,"about_ca_system_score_gemma":0.1397516,"threshold_uncertainty_score":0.6730203},"labels":[],"label_agreement":null},{"id":"W7011041324","doi":"","title":"LET’s SuPpOrT 1-888-527-34o1 apple computer customer care number icloud customer service contact number icloud help number icloud","year":2016,"lang":"en","type":"other","venue":"OSF Preprints (OSF Preprints)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Customer advocacy; Customer Service Assurance; Phone; Customer retention; Service (business); Customer to customer; Customer intelligence","score_opus":0.009522924824337243,"score_gpt":0.2503416155370153,"score_spread":0.24081869071267803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7011041324","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00034116697,0.00027341605,0.00048006795,0.0017868014,0.0017232398,0.00018843132,0.0013988751,0.0030163492,0.9907917],"genre_scores_gemma":[0.00068258273,0.00013169012,0.0001235914,0.00034449273,0.00016466009,0.000057517827,0.00046037373,0.0005002636,0.99753475],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99913055,0.00007703427,0.000029864714,0.00014156506,0.00042150493,0.00019948039],"domain_scores_gemma":[0.99634105,0.00029836895,0.00010461916,0.00028555185,0.0016129967,0.0013574066],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007394348,0.0013314139,0.0011294817,0.0015082497,0.002774725,0.0051079174,0.0012577076,0.0023549474,0.94364536],"category_scores_gemma":[0.0053659957,0.0007267805,0.00049267145,0.001169048,0.00036675506,0.002578578,0.002589633,0.0018182539,0.937476],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020101841,0.000019512678,0.00005519812,0.000023221697,6.3619706e-7,0.00001609238,0.000020774763,0.000006865224,0.00015002831,0.00020484763,0.98714024,0.012342476],"study_design_scores_gemma":[0.000012511948,0.000020611331,0.00032504834,0.000043812073,0.0000025360412,0.000026239639,0.00008910862,0.000040854404,0.000102274265,0.000056286615,0.999275,0.0000056426757],"about_ca_topic_score_codex":0.00780549,"about_ca_topic_score_gemma":0.0127936555,"teacher_disagreement_score":0.056354642,"about_ca_system_score_codex":0.0009908964,"about_ca_system_score_gemma":0.0016312918,"threshold_uncertainty_score":0.080383},"labels":[],"label_agreement":null},{"id":"W7018896446","doi":"","title":"eHi Car Services Announces First Quarter 2017 Results","year":2017,"lang":"en","type":"other","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Work (physics)","score_opus":0.012197563979827656,"score_gpt":0.23402173238947116,"score_spread":0.2218241684096435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7018896446","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027564482,0.0006943943,0.0012560085,0.026254797,0.012973811,0.0003950795,0.03591234,0.0025307643,0.9172263],"genre_scores_gemma":[0.005276924,0.00033041628,0.00033230495,0.0034167215,0.001330108,0.00015736911,0.016107045,0.00065535295,0.9723937],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9921788,0.00035834828,0.00013675218,0.00027197818,0.0055219186,0.0015322061],"domain_scores_gemma":[0.9873509,0.0011049944,0.00025949025,0.0006721717,0.0074683535,0.0031440635],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006369597,0.0012762734,0.00081328175,0.0035465523,0.004501789,0.014168756,0.0021543733,0.005809625,0.37726203],"category_scores_gemma":[0.0121137425,0.00057610555,0.0016416846,0.0020805132,0.0012078529,0.0040519703,0.0042586955,0.005890946,0.29925698],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045197925,0.00004472591,0.00024916584,0.000018546678,0.0000020767402,0.0000125587685,0.000012461061,0.000037112484,0.000029274654,0.0022248037,0.99246407,0.0048599974],"study_design_scores_gemma":[0.000037995516,0.000032609623,0.0023711522,0.00005599886,0.0000073017295,0.0000136142635,0.00019896287,0.00024668558,0.00033161064,0.001469185,0.9952193,0.000015558984],"about_ca_topic_score_codex":0.05542449,"about_ca_topic_score_gemma":0.11927651,"teacher_disagreement_score":0.37726203,"about_ca_system_score_codex":0.006360556,"about_ca_system_score_gemma":0.016483504,"threshold_uncertainty_score":0.8882601},"labels":[],"label_agreement":null},{"id":"W7019022321","doi":"","title":"Exploring the impact of gender in travel behaviour: A case study of suburban commuters in Montreal","year":2007,"lang":"en","type":"article","venue":"Infoscience (Ecole Polytechnique Fédérale de Lausanne)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Public transport; Travel behavior; Preference; Affect (linguistics); Work (physics); Mode choice; Travel survey; Travel time","score_opus":0.05924279312666106,"score_gpt":0.3023998349344875,"score_spread":0.24315704180782646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7019022321","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990651,0.000030492809,0.00008589133,0.00008717108,0.0000011944851,0.00004145907,0.00011792919,0.0000025926329,0.0005682666],"genre_scores_gemma":[0.9977233,0.00010972264,0.000348509,0.000057396242,0.0000029913556,0.00003212779,0.00011921633,0.0000039038227,0.0016027524],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994005,0.00023815216,0.000012671099,0.000069286936,0.000062656385,0.00021673334],"domain_scores_gemma":[0.9991308,0.00031192251,0.00014994007,0.000044350276,0.00015537077,0.00020763862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007789443,0.00054995104,0.00035802906,0.00095816393,0.0034845632,0.00086861517,0.0011228557,0.0008962114,0.0028351357],"category_scores_gemma":[0.0018458632,0.00028206714,0.0004288142,0.001894878,0.0009913046,0.000591449,0.0008529786,0.00058574846,0.00027784388],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027050794,0.0009011159,0.88861716,0.00010236808,0.00009016969,0.009619843,0.07482217,0.0015189308,0.0020919277,0.0010867837,0.0014895946,0.01938947],"study_design_scores_gemma":[0.000034645484,0.00049785525,0.8505117,0.000029559025,0.00005380422,0.0007302055,0.14010274,0.0034151203,0.00046222308,0.00015592942,0.00394229,0.00006393457],"about_ca_topic_score_codex":0.91401476,"about_ca_topic_score_gemma":0.9692593,"teacher_disagreement_score":0.08598524,"about_ca_system_score_codex":0.0094952425,"about_ca_system_score_gemma":0.0041018045,"threshold_uncertainty_score":0.17298323},"labels":[],"label_agreement":null},{"id":"W7019067802","doi":"","title":"Examining Connected and Automated Vehicle (CAV) Policy in Ontario: A Modified Multiple Streams Framework Analysis","year":2021,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Scope (computer science); Domain (mathematical analysis); Plan (archaeology); Confluence; STREAMS; Policy analysis","score_opus":0.07953442088789112,"score_gpt":0.29229685219886614,"score_spread":0.21276243131097503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7019067802","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74299157,0.0048476695,0.062740356,0.01629574,0.00015796564,0.001824965,0.011867864,0.00013316498,0.15914072],"genre_scores_gemma":[0.975726,0.0018403977,0.014211472,0.000222591,0.000026151387,0.00041682195,0.0009949754,0.00002784515,0.00653378],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.99748933,0.0009809514,0.000093187475,0.00030180713,0.00057373464,0.0005609424],"domain_scores_gemma":[0.99599165,0.0018409446,0.00049527426,0.00014867654,0.0011791713,0.0003443786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033349206,0.0005491915,0.00062206184,0.005185195,0.0037174642,0.0037445736,0.0012515641,0.00077978615,0.005476692],"category_scores_gemma":[0.008134659,0.0004290794,0.0011210717,0.008279354,0.0029031967,0.0021948363,0.0029603015,0.0010391541,0.00020095913],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018921932,0.00018383113,0.2796061,0.0011769787,0.0004324451,0.0012856218,0.037824713,0.0538249,0.0006809116,0.5354054,0.015473802,0.07391597],"study_design_scores_gemma":[0.00017948105,0.00022194783,0.28286725,0.0020470275,0.0009818561,0.00021094737,0.1138342,0.19899906,0.0010404257,0.2128773,0.1864718,0.00026866756],"about_ca_topic_score_codex":0.9570527,"about_ca_topic_score_gemma":0.9645921,"teacher_disagreement_score":0.075754285,"about_ca_system_score_codex":0.075754285,"about_ca_system_score_gemma":0.08049677,"threshold_uncertainty_score":0.5496384},"labels":[],"label_agreement":null},{"id":"W7019954549","doi":"","title":"Innovative Mobility: Carsharing Outlook Carsharing Market Overview, Analysis, And Trends.","year":2020,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Service (business); Operator (biology); Car sharing; Postal service; Work (physics)","score_opus":0.0194726572439504,"score_gpt":0.21986981381657897,"score_spread":0.20039715657262858,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7019954549","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.121286765,0.118968084,0.004636265,0.01885876,0.002715668,0.00038723496,0.30067256,0.0055946456,0.42688006],"genre_scores_gemma":[0.26301283,0.10437898,0.0056008496,0.0032242178,0.001966884,0.00029705578,0.30971316,0.0008300674,0.31097594],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.999637,0.000011831619,0.000016228081,0.00005564066,0.00019640091,0.000082937004],"domain_scores_gemma":[0.9981406,0.00013806018,0.00025791954,0.000028169365,0.0011125631,0.00032272676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058137614,0.00069256383,0.00018773996,0.0050324164,0.0004029098,0.0023353393,0.0005266916,0.00069467246,0.032328114],"category_scores_gemma":[0.0011397636,0.00021585039,0.0002968303,0.009620555,0.00015778613,0.0038468062,0.00070576766,0.0010513428,0.015327837],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000114352995,0.0001409078,0.018916095,0.0005424137,0.000015519432,0.000086102926,0.00016066841,0.00045259998,0.0005685216,0.004567662,0.7390385,0.23539671],"study_design_scores_gemma":[0.0000128585225,0.00009448951,0.07618111,0.00035759973,0.000029399758,0.00021414364,0.0008017103,0.0012746125,0.0006850371,0.0006660533,0.91964954,0.00003342564],"about_ca_topic_score_codex":0.022501297,"about_ca_topic_score_gemma":0.035844695,"teacher_disagreement_score":0.032328114,"about_ca_system_score_codex":0.0014222277,"about_ca_system_score_gemma":0.0013827559,"threshold_uncertainty_score":0.10814828},"labels":[],"label_agreement":null},{"id":"W7022585777","doi":"","title":"The Uber Effect","year":2016,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Unemployment; Falling (accident); Population; Unemployment rate; Control (management); Term (time); Variable (mathematics)","score_opus":0.04402631206432242,"score_gpt":0.27767941491871345,"score_spread":0.23365310285439103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7022585777","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5339942,0.00977689,0.038230494,0.01580434,0.0011358206,0.0006214247,0.0062276665,0.00082640507,0.3933827],"genre_scores_gemma":[0.93970746,0.0021426848,0.0014708217,0.0023915814,0.00041234656,0.00013514,0.0008117739,0.00006525166,0.052863043],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9957963,0.0011315265,0.00021528959,0.0011598474,0.00087060337,0.0008264227],"domain_scores_gemma":[0.98421925,0.0073177684,0.005129445,0.0013148576,0.0011424487,0.0008762575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035156957,0.0006994012,0.0012563266,0.0015253766,0.001298272,0.00208914,0.0008430977,0.0017604397,0.05365288],"category_scores_gemma":[0.01340892,0.00037282068,0.0013037297,0.0017102154,0.0017407906,0.0026295723,0.0024514275,0.0022668377,0.0045438595],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008301475,0.00081219926,0.57875466,0.0004073198,0.0010634388,0.0009083015,0.0015951293,0.0073896274,0.00079817604,0.19744489,0.035857696,0.17413844],"study_design_scores_gemma":[0.0003469066,0.0013695785,0.7042535,0.00050583686,0.0012447407,0.0007570495,0.0033171093,0.013859377,0.0023098693,0.10743082,0.16444217,0.00016306825],"about_ca_topic_score_codex":0.016738981,"about_ca_topic_score_gemma":0.013825102,"teacher_disagreement_score":0.05365288,"about_ca_system_score_codex":0.0013189611,"about_ca_system_score_gemma":0.0013524011,"threshold_uncertainty_score":0.17948675},"labels":[],"label_agreement":null},{"id":"W7023677851","doi":"","title":"Optimization of semi-flexible transit operation for low demand scenarios","year":2024,"lang":"en","type":"dissertation","venue":"Mspace (University of Manitoba)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Paratransit; Headway; Transit (satellite); Service (business); Adaptability; Public transport; Operator (biology); Operating cost; Transshipment (information security)","score_opus":0.009683972904375508,"score_gpt":0.2013953238903034,"score_spread":0.1917113509859279,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7023677851","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7188156,0.00033190558,0.2582981,0.00048412534,0.000047358622,0.00029592888,0.0006774374,0.00026717104,0.020782232],"genre_scores_gemma":[0.9875919,0.00007278913,0.010741012,0.000017805094,0.0000030130575,0.000060252245,0.000092320406,0.000019776695,0.0014011558],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965024,0.00014161356,0.000011440705,0.000047774553,0.00004907167,0.00009984019],"domain_scores_gemma":[0.99929106,0.00040915378,0.00010322859,0.000030526626,0.000082439336,0.00008350375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086897536,0.0008818423,0.0006124171,0.000606499,0.00042707965,0.001249785,0.00068541366,0.0008039419,0.0025825398],"category_scores_gemma":[0.001774159,0.0005315933,0.0006445079,0.0006376402,0.0005903035,0.0007561712,0.0006780767,0.000850725,0.00020795527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044969904,0.000021537591,0.00035414842,0.000021177066,0.000010326106,0.000040220024,0.00001543822,0.99553126,0.0006083114,0.00088674464,0.00013378881,0.0023321572],"study_design_scores_gemma":[0.000008894316,0.00008632148,0.0004020753,0.0000051338448,0.000007661818,0.000009361136,0.00006817711,0.99820244,0.00024292858,0.0007530555,0.00021035789,0.0000035973835],"about_ca_topic_score_codex":0.010176471,"about_ca_topic_score_gemma":0.009055679,"teacher_disagreement_score":0.010176471,"about_ca_system_score_codex":0.001303872,"about_ca_system_score_gemma":0.0014541293,"threshold_uncertainty_score":0.020234466},"labels":[],"label_agreement":null},{"id":"W7025287780","doi":"","title":"What about free-floating carsharing? A look at the Montréal case","year":2014,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Popularity; Public transport; Service (business); Relation (database); Car ownership; Central business district; Level of service","score_opus":0.007910651706228707,"score_gpt":0.2112769929984021,"score_spread":0.2033663412921734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7025287780","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7845068,0.0025437877,0.00068678206,0.030060096,0.00011266511,0.00016548843,0.0010877125,0.000033632365,0.18080305],"genre_scores_gemma":[0.9858634,0.00082499586,0.00024175394,0.0013524422,0.000049146496,0.00003142665,0.00017476834,0.000011417855,0.011450777],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99758685,0.00048344894,0.00002199944,0.000110173896,0.00032823224,0.001469309],"domain_scores_gemma":[0.99754494,0.0003185222,0.00020567222,0.000060821465,0.00045427,0.001415735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094230974,0.00039700375,0.00027039612,0.0012409284,0.008762112,0.0034626368,0.002047775,0.0018082295,0.011655258],"category_scores_gemma":[0.0029041409,0.000208854,0.00054243155,0.002891721,0.0029837906,0.001407006,0.0017075259,0.001752728,0.000332192],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000360106,0.0012103495,0.44794282,0.00043642157,0.0001824911,0.042249147,0.043514438,0.006704493,0.0019122598,0.2838605,0.09288196,0.07874509],"study_design_scores_gemma":[0.00014575692,0.00030021826,0.48642373,0.00069768296,0.00014467546,0.0047507454,0.21539643,0.00918752,0.0007401674,0.010047421,0.27186364,0.00030190105],"about_ca_topic_score_codex":0.97914815,"about_ca_topic_score_gemma":0.9877073,"teacher_disagreement_score":0.04792075,"about_ca_system_score_codex":0.04792075,"about_ca_system_score_gemma":0.015549069,"threshold_uncertainty_score":0.347691},"labels":[],"label_agreement":null},{"id":"W7028687936","doi":"","title":"Fußgängerwartezeitmodelle und ihre Anwendbarkeit an freien Abschnitten bei innerstädtischem Verkehr","year":2007,"lang":"de","type":"article","venue":"reposiTUm (TU Wien)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Power (physics); Quarter (Canadian coin); Period (music)","score_opus":0.015584279100771616,"score_gpt":0.2657504094731078,"score_spread":0.2501661303723362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7028687936","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7177172,0.0016847639,0.24267349,0.00087856426,0.0001767672,0.00019342356,0.0011759395,0.0017042293,0.033795662],"genre_scores_gemma":[0.9690915,0.0005271288,0.02417925,0.000035451787,0.0000070179985,0.00012348015,0.00039569155,0.00012352077,0.00551691],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991949,0.00031739657,0.00003831859,0.0001269903,0.00019886755,0.00012338077],"domain_scores_gemma":[0.99804926,0.0012840496,0.00015045062,0.00018755085,0.000276467,0.00005215823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016638229,0.0009319746,0.00063884247,0.001121442,0.0007172344,0.0040545287,0.0010184854,0.0016400238,0.0064964998],"category_scores_gemma":[0.005871406,0.000669302,0.0008523851,0.0010222236,0.0006811844,0.0028391895,0.0009955629,0.0012775017,0.0009091252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034615438,0.00028427647,0.003116198,0.00016893238,0.00007644327,0.000061311875,0.00041374844,0.9172617,0.004418349,0.016949896,0.00096369593,0.05593926],"study_design_scores_gemma":[0.00003179271,0.00020725875,0.001769114,0.00007377603,0.00009599807,0.000025038365,0.0003869224,0.97098565,0.00724152,0.013940483,0.005191156,0.000051337825],"about_ca_topic_score_codex":0.024250556,"about_ca_topic_score_gemma":0.019317957,"teacher_disagreement_score":0.024250556,"about_ca_system_score_codex":0.0017842453,"about_ca_system_score_gemma":0.0015010686,"threshold_uncertainty_score":0.048218846},"labels":[],"label_agreement":null},{"id":"W7029889243","doi":"","title":"Le rôle de la présence attentive dans la prévention du trouble de stress post-traumatique chez les pompiers","year":2023,"lang":"fr","type":"other","venue":"Archipelago (University of Quebec in Montreal)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Population; Context (archaeology); Poison control","score_opus":0.00495197153479148,"score_gpt":0.19404147075204525,"score_spread":0.18908949921725376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7029889243","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98250765,0.004414993,0.00071166287,0.003175639,0.00013541791,0.000059656682,0.00034022992,0.000015434644,0.008639257],"genre_scores_gemma":[0.9925046,0.0030307109,0.0009198843,0.0007358377,0.00007507057,0.0000636413,0.00015203467,0.000008494421,0.002509851],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99933666,0.00020977747,0.000028299683,0.00012611717,0.0001425443,0.00015648427],"domain_scores_gemma":[0.99708635,0.00072236365,0.0012142234,0.00012038285,0.00036827984,0.00048850075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011570635,0.00067913864,0.00045143822,0.0007155283,0.0019472028,0.0018656888,0.0007235373,0.0010708148,0.009960695],"category_scores_gemma":[0.008027304,0.0004050234,0.00037730613,0.0005187515,0.0014397749,0.0010506235,0.0014162422,0.0016831133,0.0009223783],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043510096,0.00044344863,0.9081305,0.0007739784,0.00024216555,0.0020211982,0.030119197,0.00009325412,0.002018924,0.0015031878,0.002399538,0.05181944],"study_design_scores_gemma":[0.000019816222,0.00043362126,0.95970845,0.00093162066,0.00015946786,0.0013496509,0.028572712,0.00014954912,0.0004005254,0.0014040355,0.006826623,0.00004396111],"about_ca_topic_score_codex":0.0148505205,"about_ca_topic_score_gemma":0.029882638,"teacher_disagreement_score":0.0148505205,"about_ca_system_score_codex":0.0009551002,"about_ca_system_score_gemma":0.0018361562,"threshold_uncertainty_score":0.033321798},"labels":[],"label_agreement":null},{"id":"W7033721160","doi":"","title":"Ryan : Génie de l'animation","year":2005,"lang":"fr","type":"other","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Context (archaeology); Natural (archaeology)","score_opus":0.007940256811474462,"score_gpt":0.2224510210679846,"score_spread":0.21451076425651014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7033721160","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004234294,0.0014855742,0.0035160421,0.0049974085,0.007992648,0.0001292519,0.004128571,0.005116997,0.97221],"genre_scores_gemma":[0.0036889021,0.00088331365,0.002777072,0.00087025017,0.0009393648,0.000106408545,0.0018235128,0.002761556,0.98614955],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99940264,0.00010340417,0.00002152785,0.00006941142,0.00034599926,0.000057022375],"domain_scores_gemma":[0.9988863,0.00021615277,0.000038256774,0.00013037775,0.0005870578,0.00014187628],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007398391,0.00078629615,0.0005280139,0.0013075667,0.0016687815,0.003034322,0.0006732085,0.0012263246,0.6334331],"category_scores_gemma":[0.0037518048,0.00040177145,0.00040600705,0.000775234,0.00042798257,0.001498839,0.001598977,0.0021200972,0.32629073],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022696759,0.000004929295,0.000021140842,0.000039238257,8.281253e-7,0.00002957103,0.0000891779,0.000030757074,0.0001858643,0.0019333954,0.97571635,0.021926032],"study_design_scores_gemma":[0.0000028661445,0.000002199902,0.00008316572,0.000025749292,5.723745e-7,0.000026514368,0.00004294834,0.00004132555,0.00007025599,0.0001615511,0.99954045,0.000002477184],"about_ca_topic_score_codex":0.010848556,"about_ca_topic_score_gemma":0.01868716,"teacher_disagreement_score":0.6334331,"about_ca_system_score_codex":0.00088519446,"about_ca_system_score_gemma":0.0012021072,"threshold_uncertainty_score":0.52286315},"labels":[],"label_agreement":null},{"id":"W7034459872","doi":"","title":"Unjust Enrichment for Cohabiting Couples: Reassessing the Common Intention Constructive Trust","year":2022,"lang":"en","type":"other","venue":"Durham e-Theses (Durham University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Unjust enrichment; Constructive trust; Cohabitation; Doctrine; Common law; Context (archaeology); Legislature; Tort; Scholarship; Constructive","score_opus":0.01302063892422642,"score_gpt":0.214342072045214,"score_spread":0.20132143312098758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7034459872","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5781465,0.00859868,0.02545651,0.11846425,0.0014040747,0.00018845654,0.000015989759,0.000035886493,0.2676896],"genre_scores_gemma":[0.9888475,0.001090874,0.0013953636,0.0030263793,0.00007643078,0.000035667585,0.0000035135497,0.000009878834,0.005514419],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98754287,0.008403224,0.0003300998,0.00048361544,0.0015161524,0.0017240001],"domain_scores_gemma":[0.989351,0.0063260174,0.00088919204,0.00090521394,0.0012404098,0.0012882364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015951365,0.00026525938,0.0005300046,0.0008717074,0.013782421,0.010011802,0.0018399679,0.0044537634,0.002118271],"category_scores_gemma":[0.018243864,0.0003254349,0.00050815166,0.0006056161,0.048110843,0.008806192,0.015346408,0.007272056,0.0003131408],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032414417,0.000036796508,0.0022201983,0.00008286283,0.0000059421504,0.0013307146,0.22410756,0.00015348892,0.00025287998,0.75186825,0.0017013275,0.018207557],"study_design_scores_gemma":[0.00003136602,0.0002954685,0.0047000083,0.0013276861,0.000041740375,0.0019231893,0.4642155,0.001585406,0.0011403689,0.33921853,0.18541327,0.000107381355],"about_ca_topic_score_codex":0.029242203,"about_ca_topic_score_gemma":0.039840672,"teacher_disagreement_score":0.029242203,"about_ca_system_score_codex":0.008981706,"about_ca_system_score_gemma":0.013573407,"threshold_uncertainty_score":0.084359884},"labels":[],"label_agreement":null},{"id":"W7042297535","doi":"","title":"Opposing trends in the prevalence of health professional-diagnosed asthma by sex: A Canadian National Population Health Survey study","year":2008,"lang":"en","type":"article","venue":"PubMed Central","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Asthma; Population; Rural population; Rural area; Prevalence; Epidemiology; National Health Interview Survey; Age groups; Public health","score_opus":0.04329401730680616,"score_gpt":0.2894469418541596,"score_spread":0.24615292454735344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7042297535","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9689659,0.0066106305,0.0002720467,0.0020871547,0.0000836045,0.00014018755,0.015266063,0.0000319038,0.006542453],"genre_scores_gemma":[0.9920705,0.0018629405,0.00033686685,0.00041037178,0.000013253274,0.00004586615,0.004456772,0.000011237722,0.0007922051],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99651873,0.0003271621,0.00019724877,0.00063568534,0.0016015235,0.00071970007],"domain_scores_gemma":[0.9958121,0.00023752394,0.0005351564,0.00015795579,0.0025282532,0.00072898983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026073323,0.00043125518,0.00077023264,0.0028691934,0.0022380648,0.0014048831,0.0023947456,0.0009925389,0.0019682625],"category_scores_gemma":[0.004561461,0.0006972851,0.0013784341,0.0083753,0.0008353557,0.000552157,0.001087304,0.0010715746,0.00020131354],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009593611,0.00002452022,0.993558,0.00007045306,0.00014690038,0.00005254279,0.00067530555,0.000045394307,0.00009329998,0.0000995655,0.0015818187,0.0035563065],"study_design_scores_gemma":[0.000007932677,0.000011081862,0.99885845,0.000023502513,0.000033751145,0.000028718596,0.00043863655,0.00008656846,0.000010362396,0.000015138328,0.000477054,0.000008802404],"about_ca_topic_score_codex":0.9895704,"about_ca_topic_score_gemma":0.9930194,"teacher_disagreement_score":0.016838077,"about_ca_system_score_codex":0.016838077,"about_ca_system_score_gemma":0.026273571,"threshold_uncertainty_score":0.122169375},"labels":[],"label_agreement":null},{"id":"W7043603299","doi":"","title":"Taxelco Launches Teo, a Reinvented Taxi Service for Montreal","year":2015,"lang":"en","type":"other","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Service (business); Government (linguistics); Postal service; Service provider","score_opus":0.022689784736329696,"score_gpt":0.22993049142561095,"score_spread":0.20724070668928124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7043603299","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009670578,0.0010142424,0.0017423899,0.012064176,0.0016376036,0.00042967824,0.008984374,0.00198006,0.9624769],"genre_scores_gemma":[0.010754866,0.00028109166,0.00047894169,0.0006279338,0.000072288974,0.000025969559,0.0017008109,0.00018364782,0.98587453],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989423,0.000032213127,0.000009811312,0.000091342234,0.00057108555,0.00035325775],"domain_scores_gemma":[0.99851924,0.000052750845,0.000033907836,0.00005712093,0.00071733794,0.0006196999],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007241612,0.0008652239,0.0002632569,0.0015926145,0.0047087925,0.0052204947,0.0011342182,0.0021430424,0.22102343],"category_scores_gemma":[0.0018495172,0.00039730457,0.00051139266,0.001285322,0.0009511332,0.0014168627,0.0016467426,0.0026869515,0.032196183],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000588032,0.00010385575,0.002547783,0.000060206577,0.000008534411,0.00017617481,0.00017288513,0.00026721283,0.00086664816,0.020492224,0.9221659,0.05307987],"study_design_scores_gemma":[0.000014322616,0.000024344987,0.0041366452,0.00002199493,0.0000039965316,0.00003679178,0.0001742833,0.00039509087,0.00031514207,0.00037251506,0.9944922,0.000012688977],"about_ca_topic_score_codex":0.85317546,"about_ca_topic_score_gemma":0.9459791,"teacher_disagreement_score":0.22102343,"about_ca_system_score_codex":0.017296763,"about_ca_system_score_gemma":0.04440488,"threshold_uncertainty_score":0.73939705},"labels":[],"label_agreement":null},{"id":"W7043780266","doi":"","title":"Towards the reduction of greenhouse gas emissions : models and algorithms for ridesharing and carbon capture and storage","year":2023,"lang":"fr","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Resources Canada; Université de Montréal; Natural Sciences and Engineering Research Council of Canada; Government of Canada; Polytechnique Montréal","keywords":"Greenhouse gas; Environmental policy; Moving horizon estimation","score_opus":0.014430904667915374,"score_gpt":0.19614913458361272,"score_spread":0.18171822991569733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7043780266","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020381736,0.0015219465,0.966234,0.000828594,0.00010919311,0.0000625029,0.00017473323,0.0006304405,0.010056839],"genre_scores_gemma":[0.67314607,0.0032677806,0.29796067,0.00032858725,0.00019131445,0.00047400026,0.00046441532,0.0004096954,0.023757426],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997209,0.00010384521,0.0000137298675,0.00005703988,0.000056471883,0.00004803212],"domain_scores_gemma":[0.99918455,0.00057854335,0.000063325315,0.00003572548,0.00010245478,0.00003533345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087661296,0.0011740855,0.0014652475,0.00054697256,0.0006599111,0.0019036768,0.0015940525,0.0020900855,0.0037804833],"category_scores_gemma":[0.0024919608,0.000756377,0.0015830601,0.0009073349,0.00109398,0.0015912462,0.001401868,0.0019584936,0.000784909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012025953,0.000008114307,0.00007500941,0.000018441879,0.00000732599,0.0000062947192,0.00001267331,0.99132526,0.00008111588,0.0042159148,0.00024101345,0.0039968276],"study_design_scores_gemma":[0.0000029759992,0.000004089136,0.00001837918,0.0000031312154,0.0000019423533,0.0000014657205,0.000003814763,0.99745804,0.00003880293,0.0021949161,0.0002707209,0.0000017832928],"about_ca_topic_score_codex":0.030187272,"about_ca_topic_score_gemma":0.015889442,"teacher_disagreement_score":0.030187272,"about_ca_system_score_codex":0.0015092893,"about_ca_system_score_gemma":0.001869987,"threshold_uncertainty_score":0.06002313},"labels":[],"label_agreement":null},{"id":"W7070878583","doi":"","title":"Power and Workplace Well-Being: A Comparison of Rank Group Differences in the Canadian Armed Forces","year":2016,"lang":"en","type":"other","venue":"OSF Preprints (OSF Preprints)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Power (physics); Rank (graph theory); Group (periodic table); Work (physics); Order (exchange)","score_opus":0.010367777294344998,"score_gpt":0.24260652040731565,"score_spread":0.23223874311297066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7070878583","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9944646,0.0005520699,0.000042859574,0.00031842044,0.000024741146,0.00002185878,0.0012098228,0.0000040939876,0.0033615134],"genre_scores_gemma":[0.9975648,0.00027037392,0.00004460619,0.00003770527,0.000007644112,0.000012859452,0.00083913165,0.0000032173566,0.0012197534],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99832135,0.00012814761,0.000060704228,0.0001422301,0.00051852246,0.0008290281],"domain_scores_gemma":[0.99716586,0.000223543,0.00035418718,0.00010846327,0.0012654951,0.0008823465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012590351,0.000462302,0.0006471916,0.0027923244,0.0036167144,0.0018542655,0.0015575798,0.00075507566,0.0053389263],"category_scores_gemma":[0.004969672,0.00029788347,0.0009127285,0.005561791,0.0012141938,0.00063160335,0.0014489499,0.0009464338,0.0004812713],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030434944,0.00017614296,0.97317433,0.00004646065,0.00019922489,0.000065843036,0.0063215983,0.00017557475,0.00022119208,0.00061796355,0.0028065678,0.015890785],"study_design_scores_gemma":[0.0000062709405,0.000031635747,0.99520457,0.000013590479,0.000013097099,0.000005525115,0.004032958,0.00006701466,0.000016440923,0.00004534478,0.0005531305,0.0000104362925],"about_ca_topic_score_codex":0.9847735,"about_ca_topic_score_gemma":0.99162334,"teacher_disagreement_score":0.9853157,"about_ca_system_score_codex":0.01468429,"about_ca_system_score_gemma":0.018380044,"threshold_uncertainty_score":0.10654247},"labels":[],"label_agreement":null},{"id":"W7084125854","doi":"10.64628/aap.se9y5jnvc","title":"Se réunir en marchant pour améliorer la créativité et les relations de travail","year":2021,"lang":"fr","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Context (archaeology); Industrial relations; Relation (database); Labor relations; Order (exchange)","score_opus":0.018610115095837487,"score_gpt":0.26867672374241813,"score_spread":0.25006660864658065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7084125854","genre_codex":"empirical","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43230927,0.0032126752,0.09007049,0.03610923,0.0035364244,0.00038507418,0.00033360498,0.0027294862,0.43131372],"genre_scores_gemma":[0.6136684,0.0010893196,0.0274644,0.0016741164,0.00027916525,0.000112757465,0.00029874008,0.0006066811,0.3548064],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978248,0.0005932108,0.00006740732,0.00037498193,0.00066339213,0.00047623232],"domain_scores_gemma":[0.99643385,0.00048513673,0.00043801538,0.0006464053,0.0011094685,0.0008871534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027724272,0.0010752128,0.00050572236,0.0011131545,0.0048618633,0.008483563,0.0014191341,0.0026759773,0.033325087],"category_scores_gemma":[0.0050661117,0.00025683866,0.0008363262,0.0010030761,0.0020293081,0.0056642494,0.003550182,0.003275689,0.012750272],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045503295,0.0016744054,0.027581096,0.00058293366,0.00015306588,0.003250227,0.06274189,0.0038907595,0.03888066,0.15037154,0.06709609,0.6433223],"study_design_scores_gemma":[0.000050206443,0.0005587398,0.021993993,0.00049482094,0.00014722477,0.001660116,0.0698587,0.0045018117,0.01652868,0.04792359,0.8361676,0.00011456717],"about_ca_topic_score_codex":0.014143693,"about_ca_topic_score_gemma":0.020402912,"teacher_disagreement_score":0.033325087,"about_ca_system_score_codex":0.0028121502,"about_ca_system_score_gemma":0.0064401003,"threshold_uncertainty_score":0.111483514},"labels":[],"label_agreement":null},{"id":"W7084386191","doi":"10.5281/zenodo.17247618","title":"napari: a multi-dimensional image viewer for Python","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Innovation Cluster (Canada)","funders":"","keywords":"Python (programming language); Scripting language; Bridging (networking); Byte; Software versioning; Development environment; Source code","score_opus":0.025313975387403844,"score_gpt":0.2500467951101505,"score_spread":0.22473281972274664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7084386191","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007567793,0.000602969,0.1644965,0.0005340568,0.000581355,0.0002412472,0.07035963,0.7338802,0.028547252],"genre_scores_gemma":[0.013655024,0.001003614,0.17611063,0.0017883192,0.00026217278,0.0013424046,0.19802065,0.55075663,0.057060644],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990938,0.0001307843,0.000083800594,0.00017466977,0.0003779612,0.00013897866],"domain_scores_gemma":[0.9986953,0.0002577176,0.000087854416,0.00028828369,0.00048959826,0.00018133683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016327673,0.001984535,0.0011459778,0.001696421,0.0008788372,0.0034896152,0.0048153633,0.0014995992,0.2671661],"category_scores_gemma":[0.0043737525,0.002068086,0.0019259509,0.0010972876,0.0005806922,0.005569093,0.0044937846,0.0043679858,0.25555727],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010678736,0.000017135828,0.00015682884,0.0003420428,0.000031664695,0.00005072058,0.000097343815,0.00033241377,0.0020797353,0.002258471,0.9706425,0.023884512],"study_design_scores_gemma":[0.00012336303,0.000028671482,0.0011900302,0.00020251871,0.000025295834,0.0003388957,0.000065023254,0.006414869,0.007157157,0.0097227115,0.9745633,0.00016817322],"about_ca_topic_score_codex":0.003611719,"about_ca_topic_score_gemma":0.005392393,"teacher_disagreement_score":0.2671661,"about_ca_system_score_codex":0.0007825602,"about_ca_system_score_gemma":0.0017266325,"threshold_uncertainty_score":0.89375967},"labels":[],"label_agreement":null},{"id":"W7085625776","doi":"10.1016/j.rtbm.2025.101527","title":"Origin-destination demand prediction for shared mobility service using fully convolutional neural network","year":2025,"lang":"en","type":"article","venue":"Research in Transportation Business & Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Chiang Mai University","keywords":"Convolutional neural network; Baseline (sea); Graph; Individual mobility; Predictive modelling; Demand patterns; Service (business); Demand forecasting; Data modeling","score_opus":0.07705506648530622,"score_gpt":0.3513306759918735,"score_spread":0.27427560950656726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7085625776","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8482784,0.0008615627,0.13594443,0.00094826735,0.0003439336,0.000043293097,0.0067478474,0.0021133246,0.0047189873],"genre_scores_gemma":[0.987525,0.00009695812,0.00508687,0.0000520662,0.000053558797,0.000016687813,0.004153293,0.000023065446,0.002992495],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998567,0.000009174511,0.0000065452386,0.000051052823,0.000021484375,0.000055038305],"domain_scores_gemma":[0.9998048,0.00006190558,0.000022804128,0.000024629058,0.000061364226,0.000024587029],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022147383,0.00082240475,0.00060893863,0.00065998343,0.0002785717,0.00042383728,0.0010973195,0.0007837247,0.0027793043],"category_scores_gemma":[0.0006889304,0.00039109009,0.0006562324,0.0007975431,0.00018935815,0.00074202084,0.0005656923,0.00094989524,0.0010873128],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007507294,0.00050383515,0.03625476,0.00008122458,0.00018398449,0.00031225296,0.000052724456,0.7954479,0.0036108005,0.0015320693,0.013916311,0.14735352],"study_design_scores_gemma":[0.0000019869615,0.0000052651826,0.00077352376,0.0000010758969,0.0000043359223,0.000005293922,0.000004381326,0.99877864,0.00014570414,0.00019775493,0.00008002932,0.000001946725],"about_ca_topic_score_codex":0.06351282,"about_ca_topic_score_gemma":0.06782906,"teacher_disagreement_score":0.06351282,"about_ca_system_score_codex":0.0010129836,"about_ca_system_score_gemma":0.00085589784,"threshold_uncertainty_score":0.12628621},"labels":[],"label_agreement":null},{"id":"W7094354384","doi":"","title":"Summer 2004 Book Notes, Notes &amp; News","year":2004,"lang":"","type":"article","venue":"Insecta mundi","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Web site; Circumpolar star; Period (music)","score_opus":0.03834798008130215,"score_gpt":0.26930839775981996,"score_spread":0.23096041767851783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7094354384","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019541847,0.007880706,0.0002967137,0.009151531,0.020418465,0.00004581468,0.0012864636,0.0005466599,0.9601784],"genre_scores_gemma":[0.00034217275,0.0020632802,0.00010339716,0.0012122763,0.0013852388,0.00001083705,0.00038189424,0.000080320315,0.9944207],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99961394,0.000024267136,0.0000128868505,0.000040474803,0.00026567237,0.000042889038],"domain_scores_gemma":[0.99902034,0.00014653573,0.000045918885,0.00008310587,0.00048696224,0.00021710881],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00033767073,0.00077620975,0.0004961057,0.0013399196,0.0018005976,0.0055052782,0.0008986793,0.0016770925,0.44625393],"category_scores_gemma":[0.0018190892,0.00043511117,0.00029445082,0.0022318126,0.00048657603,0.0026475212,0.00093779655,0.0022184711,0.44958362],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000032819444,0.000004920659,0.000010829956,0.0000153058,2.0517886e-7,0.000007428046,0.0000085807915,0.0000075190896,0.000018869003,0.00041375868,0.9868745,0.012634834],"study_design_scores_gemma":[6.513505e-7,0.0000012341415,0.000059619968,0.000021009708,2.0968132e-7,0.000007090841,0.0000145773065,0.0000040325826,0.000009151384,0.00007497707,0.99980646,0.0000010588243],"about_ca_topic_score_codex":0.0130527625,"about_ca_topic_score_gemma":0.042191323,"teacher_disagreement_score":0.5537461,"about_ca_system_score_codex":0.0014879332,"about_ca_system_score_gemma":0.0016055531,"threshold_uncertainty_score":0.78985155},"labels":[],"label_agreement":null},{"id":"W7095855605","doi":"","title":"ABSTRACT UNIVERSITY OF LUND CAR SHARING NETWORKS ROLE OF CAR SHARING IN TRANSPORTATION","year":2005,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Equity (law); Sustainable transport; Sustainable development; Car ownership; Greenhouse gas; Car sharing; Sharing economy; Personal mobility","score_opus":0.00785665859912933,"score_gpt":0.1917290631334535,"score_spread":0.18387240453432419,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7095855605","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017960496,0.032000873,0.0032609345,0.01949157,0.006459598,0.00009487961,0.0026222432,0.0006437314,0.9174657],"genre_scores_gemma":[0.063596666,0.014310816,0.0019925442,0.0005029142,0.0005858725,0.000055587254,0.00082269026,0.00018336248,0.9179495],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99891007,0.00015633008,0.000072412186,0.00027805404,0.00036988265,0.00021326197],"domain_scores_gemma":[0.9988508,0.0002406453,0.00009359738,0.000061487415,0.0003527363,0.00040074228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053530966,0.00095909473,0.00076679897,0.001363561,0.0024811507,0.007397364,0.00067975355,0.0019809306,0.24656521],"category_scores_gemma":[0.0016764898,0.0003537686,0.00050665066,0.001082161,0.0010143366,0.0021378126,0.0033075318,0.0013288694,0.08968604],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006072251,0.00026312703,0.0027203471,0.0019452332,0.000032462394,0.0014706542,0.0016392319,0.003447686,0.0034647698,0.13404629,0.44742993,0.40293306],"study_design_scores_gemma":[0.000009431104,0.000048726368,0.0010404297,0.000564989,0.0000074675936,0.00021546477,0.00042811094,0.0002982857,0.0011348951,0.0049292776,0.9913059,0.0000169412],"about_ca_topic_score_codex":0.007317425,"about_ca_topic_score_gemma":0.0085670585,"teacher_disagreement_score":0.24656521,"about_ca_system_score_codex":0.0046144337,"about_ca_system_score_gemma":0.0042191204,"threshold_uncertainty_score":0.8248428},"labels":[],"label_agreement":null},{"id":"W7096457011","doi":"","title":"Carsharing in North America: Market growth, current developments and future potential. Transportation Research Record No","year":2006,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Popularity; Car ownership; Public transport; Car sharing; Mainstreaming","score_opus":0.01397787585646798,"score_gpt":0.24786161228714218,"score_spread":0.2338837364306742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7096457011","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.299393,0.26800695,0.0009084451,0.07320485,0.0016814804,0.000095844734,0.014198322,0.00042035486,0.34209067],"genre_scores_gemma":[0.7077285,0.17815222,0.0021209205,0.0022136688,0.0009852488,0.00007551907,0.015070412,0.000060646158,0.093592905],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99941385,0.00007299214,0.000035217745,0.00009078719,0.0002753959,0.000111678455],"domain_scores_gemma":[0.99605054,0.0010120742,0.00057914143,0.000103563165,0.0018022412,0.00045254728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011071411,0.00019566517,0.00020313488,0.0019660888,0.0008207228,0.0030397116,0.00068439636,0.0007855016,0.02593835],"category_scores_gemma":[0.0019302388,0.0001184909,0.00019101432,0.007729392,0.0006199406,0.0031009377,0.00048218397,0.0006378219,0.003042006],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016620371,0.00034165088,0.11834018,0.0012527881,0.000027920934,0.00023275915,0.0020604893,0.0003403309,0.0009970592,0.0072503807,0.19994417,0.6690461],"study_design_scores_gemma":[0.000013677304,0.00021286892,0.40753382,0.00082249753,0.000044385524,0.0003624481,0.016340392,0.0005803714,0.0008966101,0.0010514688,0.5721117,0.000029681267],"about_ca_topic_score_codex":0.095351174,"about_ca_topic_score_gemma":0.22034582,"teacher_disagreement_score":0.095351174,"about_ca_system_score_codex":0.002862247,"about_ca_system_score_gemma":0.0040837233,"threshold_uncertainty_score":0.1895923},"labels":[],"label_agreement":null},{"id":"W7096597179","doi":"","title":"Impacts of Express Bus Service on Passenger Demand Impacts of Express Bus Service on Passenger Demand","year":2014,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Metropolitan area; Service (business); Transit (satellite); Destinations; Public transport; Price elasticity of demand; Passenger transport; Key (lock)","score_opus":0.012403635632305754,"score_gpt":0.23478257339259676,"score_spread":0.222378937760291,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7096597179","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99242145,0.000058863083,0.00020535206,0.00020259857,0.000004117133,0.000012523761,0.0010523751,0.000009609703,0.0060331468],"genre_scores_gemma":[0.9980782,0.000045278208,0.00006215342,0.000013773141,0.0000022753106,0.0000037674217,0.00043831771,0.0000040272707,0.0013521973],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99900025,0.00021252735,0.000035560843,0.00006083943,0.00029653247,0.0003942051],"domain_scores_gemma":[0.99799794,0.00071449496,0.0002786694,0.0000787967,0.00064722664,0.0002828956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038051122,0.00024434694,0.00028803412,0.00041833462,0.00044942705,0.0013334639,0.00035642317,0.0003358454,0.0057591433],"category_scores_gemma":[0.0031622744,0.00015957667,0.00046318886,0.001231908,0.0005602847,0.00059269724,0.0007345711,0.0005404655,0.00027877896],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00077856693,0.0003151409,0.80554724,0.00012398307,0.00021114483,0.0011245277,0.0013126376,0.1603426,0.0052983793,0.0049627703,0.0030601753,0.016922904],"study_design_scores_gemma":[0.000011685866,0.00012513557,0.95284605,0.000014176775,0.00005488164,0.0000741567,0.0030405219,0.03949247,0.0010124214,0.00045704073,0.0028425502,0.000028917284],"about_ca_topic_score_codex":0.6045738,"about_ca_topic_score_gemma":0.66140825,"teacher_disagreement_score":0.6045738,"about_ca_system_score_codex":0.006439005,"about_ca_system_score_gemma":0.0027064017,"threshold_uncertainty_score":0.79550993},"labels":[],"label_agreement":null},{"id":"W7096760347","doi":"","title":"SIMON HALL É AUTOMATED HIGHWAY SYSTEMS: PLATOONS OF VEHICLES VIEWED AS A","year":2008,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Automation; Pilotage; Term (time)","score_opus":0.017515633384898643,"score_gpt":0.2258271086924445,"score_spread":0.20831147530754585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7096760347","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.055178735,0.043769557,0.5887884,0.042215403,0.010767027,0.0001268241,0.0016964502,0.0014571821,0.25600043],"genre_scores_gemma":[0.80248773,0.030282741,0.06686044,0.0012032867,0.0027618627,0.000085954554,0.0011273344,0.00025836666,0.09493239],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99962616,0.00010178264,0.000014737679,0.000103406484,0.00010986641,0.000043952114],"domain_scores_gemma":[0.9992574,0.00035626674,0.000072744595,0.000091802336,0.00012756875,0.00009422167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038725475,0.00097034994,0.0005157322,0.00093040464,0.00096684496,0.002649281,0.0007321087,0.0016980433,0.016941283],"category_scores_gemma":[0.0030671924,0.0004899608,0.00048272888,0.0012803954,0.0016593349,0.0039380942,0.0012482122,0.0013602704,0.0026721912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016356798,0.000034980945,0.0022134187,0.00023035785,0.000052941843,0.0003093183,0.00033109047,0.07618088,0.00091878494,0.76175374,0.092333354,0.065477625],"study_design_scores_gemma":[0.00006002223,0.0000628997,0.0016225196,0.00016628382,0.000050332863,0.00024019887,0.00045367327,0.19606926,0.001402377,0.6122552,0.18754809,0.00006909954],"about_ca_topic_score_codex":0.014437454,"about_ca_topic_score_gemma":0.008703634,"teacher_disagreement_score":0.016941283,"about_ca_system_score_codex":0.001194672,"about_ca_system_score_gemma":0.0011457163,"threshold_uncertainty_score":0.056674242},"labels":[],"label_agreement":null},{"id":"W7099391782","doi":"","title":"SUMMARY","year":2015,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Investment (military); Sustainability; Public transport; Fleet management; Service (business); Capital expenditure; Strategic planning; Software deployment; Public sector; Public policy","score_opus":0.02861677044666166,"score_gpt":0.22999376881938988,"score_spread":0.2013769983727282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7099391782","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0028198576,0.0041997386,0.0033041663,0.020388024,0.016593894,0.00046354107,0.008748208,0.001242164,0.9422404],"genre_scores_gemma":[0.011741077,0.0031669873,0.0016905603,0.006148107,0.0018045208,0.000193973,0.006537312,0.00026323754,0.9684543],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988078,0.00012873518,0.00008837812,0.00021730723,0.00055078417,0.00020697116],"domain_scores_gemma":[0.99773765,0.00017627906,0.00007961608,0.00021396064,0.0012616414,0.00053098175],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0010111743,0.00067748246,0.0005206252,0.0013375583,0.002009491,0.00416592,0.0014353115,0.002055393,0.50752884],"category_scores_gemma":[0.0037058739,0.00026419654,0.00057622197,0.001236823,0.0004326832,0.0022651237,0.00247058,0.0015609672,0.32569262],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007148102,0.00005087016,0.0007118195,0.00018746193,0.0000050453705,0.00015044313,0.00015725578,0.000081842416,0.0002824545,0.009058837,0.85096335,0.13827913],"study_design_scores_gemma":[0.000004914195,0.00001812564,0.00054200663,0.00007808513,0.0000020334678,0.000089649526,0.000117017604,0.000024265175,0.000092160975,0.0009102952,0.9981177,0.0000038370463],"about_ca_topic_score_codex":0.0047157435,"about_ca_topic_score_gemma":0.0060127676,"teacher_disagreement_score":0.49247116,"about_ca_system_score_codex":0.0018298442,"about_ca_system_score_gemma":0.003940427,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W7104280815","doi":"10.71781/578","title":"Inégalités sociales dans la diffusion d'une innovation en transport actif : le cas des vélos en libre-service à Montréal","year":2014,"lang":"fr","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Agrégation; Tissue remodeling","score_opus":0.008939539010309442,"score_gpt":0.1925687546014349,"score_spread":0.18362921559112547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7104280815","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98290664,0.0011119859,0.00054492016,0.0039988332,0.000024832292,0.000054128956,0.00048971863,0.000012144747,0.0108568035],"genre_scores_gemma":[0.99733186,0.0003445059,0.00015501177,0.00008841558,0.000008581313,0.000022414051,0.000084458195,0.000004385272,0.001960383],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.996467,0.0010691715,0.00008916916,0.00049028336,0.00073747267,0.00114687],"domain_scores_gemma":[0.9865802,0.0042110737,0.0034509192,0.00053585996,0.0024839109,0.0027381293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038756449,0.0003595066,0.00043756585,0.0020933591,0.004234564,0.0050302343,0.0015808443,0.0010585968,0.0104350075],"category_scores_gemma":[0.014880352,0.00044849556,0.000669524,0.0031525344,0.004133161,0.0019205677,0.0036617978,0.001525039,0.00032557797],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011203016,0.00009683398,0.9325624,0.00009762567,0.00013492504,0.00042548118,0.035069626,0.0007655809,0.00028665745,0.010557706,0.0015780565,0.018313074],"study_design_scores_gemma":[0.000012003388,0.0000724768,0.9488779,0.00015554091,0.0000926615,0.0000719755,0.03998164,0.001210848,0.00012551885,0.00083538156,0.008508723,0.000055374578],"about_ca_topic_score_codex":0.92707545,"about_ca_topic_score_gemma":0.9276774,"teacher_disagreement_score":0.072924554,"about_ca_system_score_codex":0.03059377,"about_ca_system_score_gemma":0.027715798,"threshold_uncertainty_score":0.22197437},"labels":[],"label_agreement":null},{"id":"W7106245700","doi":"10.5281/zenodo.17665207","title":"Deliverable D2.2 Mapping the existing planning and governance practices and business frameworks","year":2025,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"European Commission","keywords":"Corporate governance; Deliverable; Population; Zoning; Urban planning; Odds; Regional planning","score_opus":0.05891826657027076,"score_gpt":0.2750333330404204,"score_spread":0.2161150664701496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7106245700","genre_codex":"dataset","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036312966,0.00069617707,0.05282464,0.003200799,0.00071004266,0.00094156695,0.4999042,0.01642478,0.42166656],"genre_scores_gemma":[0.051633358,0.0021975955,0.10154929,0.0013981828,0.00028802393,0.0035030192,0.55470294,0.013482067,0.2712455],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99858594,0.00021910437,0.00006210005,0.00023535517,0.0007130533,0.00018437966],"domain_scores_gemma":[0.9971265,0.00094927486,0.00013514864,0.00062113,0.00093226775,0.00023570185],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016966825,0.00087874715,0.0005842839,0.0029903445,0.0009905858,0.0052869306,0.0014725204,0.0014496855,0.3535536],"category_scores_gemma":[0.0074594216,0.0005385358,0.0010767089,0.0059051597,0.00047359237,0.004066297,0.005045704,0.0014270792,0.17895451],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010887968,0.000053705397,0.0013124438,0.0016149401,0.000023029777,0.00019559149,0.0018220115,0.0038467965,0.001341817,0.027689513,0.8209318,0.14105944],"study_design_scores_gemma":[0.000019535033,0.000013992022,0.0014231986,0.00030836777,0.0000067030883,0.000057358262,0.0010853915,0.0010638785,0.00052343565,0.008036691,0.98743373,0.000027559061],"about_ca_topic_score_codex":0.03410554,"about_ca_topic_score_gemma":0.033094775,"teacher_disagreement_score":0.3535536,"about_ca_system_score_codex":0.0022346624,"about_ca_system_score_gemma":0.0041259234,"threshold_uncertainty_score":0.92207736},"labels":[],"label_agreement":null},{"id":"W7106343354","doi":"10.5281/zenodo.17665208","title":"Deliverable D2.2 Mapping the existing planning and governance practices and business frameworks","year":2025,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"European Commission","keywords":"Corporate governance; Deliverable; Population; Zoning; Urban planning; Odds; Regional planning","score_opus":0.05891826657027076,"score_gpt":0.2750333330404204,"score_spread":0.2161150664701496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7106343354","genre_codex":"dataset","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036312966,0.00069617707,0.05282464,0.003200799,0.00071004266,0.00094156695,0.4999042,0.01642478,0.42166656],"genre_scores_gemma":[0.051633358,0.0021975955,0.10154929,0.0013981828,0.00028802393,0.0035030192,0.55470294,0.013482067,0.2712455],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99858594,0.00021910437,0.00006210005,0.00023535517,0.0007130533,0.00018437966],"domain_scores_gemma":[0.9971265,0.00094927486,0.00013514864,0.00062113,0.00093226775,0.00023570185],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016966825,0.00087874715,0.0005842839,0.0029903445,0.0009905858,0.0052869306,0.0014725204,0.0014496855,0.3535536],"category_scores_gemma":[0.0074594216,0.0005385358,0.0010767089,0.0059051597,0.00047359237,0.004066297,0.005045704,0.0014270792,0.17895451],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010887968,0.000053705397,0.0013124438,0.0016149401,0.000023029777,0.00019559149,0.0018220115,0.0038467965,0.001341817,0.027689513,0.8209318,0.14105944],"study_design_scores_gemma":[0.000019535033,0.000013992022,0.0014231986,0.00030836777,0.0000067030883,0.000057358262,0.0010853915,0.0010638785,0.00052343565,0.008036691,0.98743373,0.000027559061],"about_ca_topic_score_codex":0.03410554,"about_ca_topic_score_gemma":0.033094775,"teacher_disagreement_score":0.3535536,"about_ca_system_score_codex":0.0022346624,"about_ca_system_score_gemma":0.0041259234,"threshold_uncertainty_score":0.92207736},"labels":[],"label_agreement":null},{"id":"W7110140408","doi":"10.1080/0144929x.2025.2596887","title":"Has the sharing economy changed our lives? Unveiling the effects of car-sharing on urban public transportation use","year":2025,"lang":"en","type":"article","venue":"Behaviour and Information Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact","funders":"","keywords":"Public transport; Sharing economy; Public policy; Government (linguistics)","score_opus":0.014580142062019921,"score_gpt":0.21798408991159102,"score_spread":0.2034039478495711,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7110140408","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99318624,0.0007688611,0.00048067042,0.0018539443,0.00002187069,0.0000074043455,0.00018512347,0.0000030068486,0.0034928108],"genre_scores_gemma":[0.9994097,0.00022647178,0.000086103224,0.00007246623,0.0000065155077,0.0000023003706,0.000027596041,0.0000018600815,0.00016700223],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988336,0.00062873884,0.000041860814,0.00015068304,0.00012388597,0.0002212071],"domain_scores_gemma":[0.99732625,0.00092558376,0.00097245985,0.00019876745,0.00031080766,0.00026624417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014271676,0.00021535558,0.0002467033,0.0006139524,0.00056297064,0.0016585925,0.0004708951,0.00046781873,0.0035172196],"category_scores_gemma":[0.0035521514,0.00017465389,0.00047588695,0.00085790193,0.0016310913,0.002331677,0.0016127902,0.00094093755,0.00017799495],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021435365,0.00023475043,0.916044,0.00021368379,0.0002891467,0.00040829336,0.012924882,0.002036582,0.00100612,0.0129421,0.0014791806,0.052206893],"study_design_scores_gemma":[0.0000036887802,0.0001707754,0.9454701,0.00020036605,0.00015287478,0.00011369511,0.039065238,0.0024844299,0.00062872324,0.0037882437,0.007886193,0.00003562812],"about_ca_topic_score_codex":0.015434137,"about_ca_topic_score_gemma":0.029610131,"teacher_disagreement_score":0.015434137,"about_ca_system_score_codex":0.0013922421,"about_ca_system_score_gemma":0.0009819481,"threshold_uncertainty_score":0.030688643},"labels":[],"label_agreement":null},{"id":"W7111837357","doi":"","title":"AI and Cloud Infrastructure is the Railway of the Future — Why Isn't Canada Building It?","year":2025,"lang":"","type":"article","venue":"eYLS (Yale Law School)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cloud computing; Key (lock); Work (physics); Government (linguistics)","score_opus":0.0039839379600873255,"score_gpt":0.21455184214180453,"score_spread":0.2105679041817172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7111837357","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0066345264,0.003114649,0.0010191161,0.787345,0.0015514774,0.000022173923,0.00019733438,0.0000778604,0.20003784],"genre_scores_gemma":[0.37387374,0.010166073,0.0024803942,0.39020112,0.0013679722,0.000073443654,0.00022152318,0.0002601602,0.22135554],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9923332,0.0008919919,0.00012186758,0.00071593525,0.0033719554,0.0025650968],"domain_scores_gemma":[0.98726255,0.0020776228,0.00039566358,0.0003702677,0.0063864663,0.0035073648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00459486,0.00039585942,0.00036227668,0.0011511791,0.02176585,0.019919552,0.0014073008,0.008667075,0.02407632],"category_scores_gemma":[0.012746646,0.00031023374,0.00048590766,0.0027460651,0.018692197,0.012316282,0.0031615412,0.01677317,0.0026097554],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026132957,0.00003055042,0.0023917079,0.000053924417,0.000015066477,0.0001470511,0.0023864391,0.00026323923,0.00018552976,0.6153608,0.3588481,0.020291377],"study_design_scores_gemma":[0.000014866143,0.000018960523,0.002806866,0.00024438882,0.000021919795,0.000062637046,0.009078342,0.00046810618,0.00024409717,0.059205394,0.9277574,0.00007699084],"about_ca_topic_score_codex":0.9494418,"about_ca_topic_score_gemma":0.9514431,"teacher_disagreement_score":0.05599318,"about_ca_system_score_codex":0.05599318,"about_ca_system_score_gemma":0.13130838,"threshold_uncertainty_score":0.4062609},"labels":[],"label_agreement":null},{"id":"W7112980103","doi":"","title":"Frontier Technologies in Non-Core Automotive Regions: Autonomous Vehicle R&amp;D in Canada","year":2020,"lang":"en","type":"article","venue":"Project Muse (Johns Hopkins University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Automotive industry; Frontier; Automation; Work (physics); Automotive engine","score_opus":0.020394093780008032,"score_gpt":0.19873934177283797,"score_spread":0.17834524799282994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7112980103","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7045617,0.01795124,0.0041172267,0.017243287,0.00041430118,0.00028843337,0.005198556,0.00038542278,0.2498398],"genre_scores_gemma":[0.91913915,0.006834253,0.0031905996,0.00086025597,0.000020482004,0.000030645722,0.0009747456,0.000039438964,0.06891052],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99895006,0.000042761872,0.000013960855,0.00009265263,0.0003297539,0.0005709234],"domain_scores_gemma":[0.9980704,0.000106800006,0.00006430507,0.0000313913,0.0009990715,0.0007280527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007557069,0.0004035281,0.00023177282,0.0018601639,0.0036182662,0.0033445037,0.0007801663,0.0007055989,0.0065342826],"category_scores_gemma":[0.0010431688,0.00019836759,0.00036270262,0.0029921092,0.0011605876,0.0010167161,0.0012188433,0.0008049652,0.00067164225],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015331069,0.0005019015,0.231801,0.0010062605,0.00018397238,0.0026781664,0.006186507,0.009585885,0.01572541,0.14307047,0.08528097,0.50244635],"study_design_scores_gemma":[0.00012881975,0.00038162043,0.53987527,0.00043870075,0.00012021357,0.00041172816,0.012647757,0.0057598352,0.0064551095,0.0051399902,0.428543,0.00009804858],"about_ca_topic_score_codex":0.9923819,"about_ca_topic_score_gemma":0.9966822,"teacher_disagreement_score":0.937391,"about_ca_system_score_codex":0.062609024,"about_ca_system_score_gemma":0.20949827,"threshold_uncertainty_score":0.45426238},"labels":[],"label_agreement":null},{"id":"W7115812490","doi":"","title":"Vervoersprognose TESO. Prognose tot 2050 van aantallen passagiers en voertuigen.","year":2025,"lang":"","type":"book","venue":"Breda University of Applied Sciences Portal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact","funders":"","keywords":"Work (physics); Term (time); Yield (engineering); Context (archaeology); Investment (military)","score_opus":0.00995117528883833,"score_gpt":0.20382652983548918,"score_spread":0.19387535454665086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7115812490","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008712993,0.1734579,0.008367377,0.06795661,0.02055237,0.00010282895,0.105560355,0.0018163618,0.6134732],"genre_scores_gemma":[0.053556785,0.091036394,0.0060960343,0.00523884,0.0030483368,0.00018795158,0.038920153,0.00097246806,0.80094314],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984586,0.00002476418,0.00000984236,0.000021116275,0.00007591337,0.000022452492],"domain_scores_gemma":[0.99964356,0.00013645767,0.000042900985,0.000012709547,0.000099378616,0.00006495951],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052360195,0.0005669316,0.00028311062,0.00077739824,0.00027978385,0.002294295,0.00034867987,0.0007014026,0.060689896],"category_scores_gemma":[0.0015726343,0.00025805563,0.0003426338,0.0012787629,0.00023802396,0.0010537163,0.00046044608,0.0012644605,0.021082627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005595677,0.000015744348,0.0006187217,0.00025864478,0.0000100207635,0.000054524597,0.00006562699,0.0010150379,0.00014293111,0.007971993,0.87261295,0.117177844],"study_design_scores_gemma":[0.000014566384,0.00002679628,0.0020966951,0.00052556756,0.00001467128,0.0001889174,0.00014564669,0.0005335229,0.00015391574,0.0053071696,0.9909801,0.000012509306],"about_ca_topic_score_codex":0.025453933,"about_ca_topic_score_gemma":0.031866543,"teacher_disagreement_score":0.060689896,"about_ca_system_score_codex":0.00093127874,"about_ca_system_score_gemma":0.0023751603,"threshold_uncertainty_score":0.2030279},"labels":[],"label_agreement":null},{"id":"W7115901740","doi":"10.2139/ssrn.5936894","title":"Embedding or not: Strategic and operational considerations of ride-hailing and third-party platforms","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Stylized fact; Embedding; Robustness (evolution); Scalability; Revenue; Scale (ratio)","score_opus":0.027807328550189317,"score_gpt":0.28693172111492643,"score_spread":0.2591243925647371,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7115901740","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46822587,0.0015120915,0.07942883,0.013749852,0.0002691722,0.00021198073,0.00021641488,0.00012682962,0.4362591],"genre_scores_gemma":[0.9926725,0.00016313433,0.0022398992,0.00009126525,0.000032322212,0.000023967017,0.00001978721,0.000015025721,0.0047420748],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970047,0.0011584271,0.000093981114,0.00027264658,0.00059602683,0.00087419484],"domain_scores_gemma":[0.9921599,0.0042829267,0.00077412237,0.0008511587,0.0012470839,0.00068473443],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033836018,0.0005198422,0.00048227038,0.00085204205,0.0022642077,0.0112091275,0.0016812595,0.0043108035,0.018384429],"category_scores_gemma":[0.014738394,0.00038338624,0.00051451847,0.0010090504,0.00410844,0.015058123,0.0039964537,0.0025187558,0.0013158157],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004917597,0.00014406261,0.006391947,0.00012504826,0.000026879283,0.0007212668,0.0015421172,0.015067521,0.0025524688,0.92948914,0.0027853998,0.04066252],"study_design_scores_gemma":[0.00006193561,0.00077009463,0.011492705,0.0002774287,0.00012665252,0.0010171485,0.03210692,0.093433954,0.008116219,0.8116221,0.040815648,0.00015925952],"about_ca_topic_score_codex":0.004502306,"about_ca_topic_score_gemma":0.005660703,"teacher_disagreement_score":0.018384429,"about_ca_system_score_codex":0.0019341314,"about_ca_system_score_gemma":0.0022519405,"threshold_uncertainty_score":0.06150204},"labels":[],"label_agreement":null},{"id":"W7116844556","doi":"10.1109/isc266238.2025.11293296","title":"An Agent-Based Approach to Emission-Aware Modal Assignment Strategies in Urban Mobility","year":2025,"lang":"","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Public transport; Incentive; Population; Modal; Work (physics); Mode choice; Mode (computer interface); Travel time; Multimodal transport","score_opus":0.017634624426426253,"score_gpt":0.2764499798778874,"score_spread":0.2588153554514611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116844556","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018291397,0.00016953617,0.9756856,0.00039055303,0.00003995142,0.00004650686,0.00003054092,0.00013624992,0.0052096313],"genre_scores_gemma":[0.8851482,0.00024925196,0.109707676,0.000107354586,0.000056722565,0.00016733124,0.000042257074,0.000032918222,0.004488352],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995584,0.00023734604,0.0000140490765,0.00007048159,0.000069579124,0.00005016909],"domain_scores_gemma":[0.9996039,0.00019433546,0.000069641384,0.000032918197,0.000055320677,0.000043992568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007410164,0.0006056986,0.0006760764,0.00037360055,0.00057933695,0.0009648808,0.0012816003,0.0009183318,0.0017664286],"category_scores_gemma":[0.0016577202,0.00037309108,0.00054221234,0.00038224345,0.0008082815,0.0009222514,0.0009335121,0.0008489997,0.00021838403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016791104,0.000017414817,0.00017862645,0.000011889983,0.000020280204,0.000023576296,0.00003104,0.9774165,0.00032880416,0.017195433,0.00019450409,0.004565192],"study_design_scores_gemma":[0.0000057325365,0.000013476556,0.00003151359,0.0000021828419,0.000004359196,0.000005591919,0.0000062058734,0.9945966,0.000075598036,0.004813615,0.00044255832,0.0000026041967],"about_ca_topic_score_codex":0.006397586,"about_ca_topic_score_gemma":0.005532923,"teacher_disagreement_score":0.006397586,"about_ca_system_score_codex":0.00092979765,"about_ca_system_score_gemma":0.0012587839,"threshold_uncertainty_score":0.0127206445},"labels":[],"label_agreement":null},{"id":"W7117235014","doi":"10.2139/ssrn.5964392","title":"Hybrid Predictive Rebalancing Control of Perceived Usability in Shared E-Scooter Systems","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Usability; Service (business); Control (management); Relocation; Quality (philosophy); Process (computing); Markov decision process; Quality of service","score_opus":0.0066617159749800215,"score_gpt":0.22993628922518597,"score_spread":0.22327457325020594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117235014","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9280405,0.00016168001,0.06879004,0.000097913144,0.00004145089,0.00004603672,0.000032002492,0.00037512867,0.002415251],"genre_scores_gemma":[0.9990404,0.0000065542245,0.000754287,0.0000053120366,0.0000019829859,0.0000073033752,0.000005133942,0.000004362559,0.00017451776],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995258,0.00010279567,0.000025479065,0.00011075585,0.00013040013,0.00010483262],"domain_scores_gemma":[0.9976993,0.0012741268,0.00021978213,0.00019771255,0.00049841066,0.000110644694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065030035,0.00050331926,0.0004825817,0.00037925006,0.00032052127,0.0012200745,0.00061602297,0.00036269394,0.0015810536],"category_scores_gemma":[0.0033332712,0.00023587298,0.0002125766,0.00027005374,0.0003236089,0.00079457177,0.00083603297,0.0004866133,0.00023148525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005191359,0.002864036,0.023835385,0.0005297651,0.00027825596,0.0003655154,0.0016737485,0.40764612,0.2398294,0.0028381362,0.0014678526,0.31348044],"study_design_scores_gemma":[0.00009231471,0.0009529747,0.018503834,0.000022328062,0.0000810312,0.00003934199,0.00033269273,0.96061,0.017880514,0.0010633433,0.00038239927,0.000039296247],"about_ca_topic_score_codex":0.0051073483,"about_ca_topic_score_gemma":0.0047012228,"teacher_disagreement_score":0.0051073483,"about_ca_system_score_codex":0.00042737715,"about_ca_system_score_gemma":0.00041922688,"threshold_uncertainty_score":0.010155201},"labels":[],"label_agreement":null},{"id":"W7117458346","doi":"10.3390/math14010116","title":"Hybrid Graph Convolutional-Recurrent Framework with Community Detection for Spatiotemporal Demand Prediction in Micromobility Systems","year":2025,"lang":"en","type":"article","venue":"Mathematics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; National Research Council of Thailand; Chiang Mai University","keywords":"Baseline (sea); Partition (number theory); Graph; Generalization; Convolutional neural network; Resource (disambiguation); Sustainability; Deep learning","score_opus":0.01389983425919901,"score_gpt":0.23828309023273972,"score_spread":0.2243832559735407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117458346","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3054289,0.0015149842,0.6829198,0.0012664204,0.00020536936,0.00006740223,0.0010505534,0.0029089036,0.0046376577],"genre_scores_gemma":[0.969842,0.0002253634,0.02652903,0.00014034215,0.000040372463,0.00003631916,0.0007995628,0.000054566717,0.0023323768],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998136,0.00003375859,0.000008798354,0.00006480163,0.000028376904,0.00005071434],"domain_scores_gemma":[0.99968266,0.00013773296,0.000044947028,0.000026327565,0.00007831451,0.000030074307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004225101,0.00088524463,0.00068701163,0.00071336894,0.00032187233,0.00053634593,0.0013926168,0.00075891044,0.0010503103],"category_scores_gemma":[0.0014034704,0.00040008003,0.0006932129,0.0006827983,0.00037306815,0.0010106807,0.00071801577,0.0010672346,0.0002918171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000106256295,0.00009289625,0.0042128875,0.000050726063,0.000076088516,0.000120302684,0.000044735334,0.93252116,0.001795976,0.0025534048,0.0021405602,0.056285042],"study_design_scores_gemma":[0.0000010541214,0.000004362966,0.00013289887,0.0000012501788,0.0000025208756,0.000003040023,0.0000025955276,0.9992005,0.00010569765,0.0004883009,0.000056647084,0.0000011805398],"about_ca_topic_score_codex":0.043567695,"about_ca_topic_score_gemma":0.052466903,"teacher_disagreement_score":0.043567695,"about_ca_system_score_codex":0.0010232964,"about_ca_system_score_gemma":0.000867735,"threshold_uncertainty_score":0.0866282},"labels":[],"label_agreement":null},{"id":"W7124834574","doi":"10.22215/etd/2024-16825","title":"Are Canada's Roadway Infrastructure and People Ready for Autonomous Vehicles?","year":2024,"lang":"","type":"dissertation","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Key (lock); Work (physics); Government (linguistics); Agency (philosophy); Process (computing)","score_opus":0.008425473223125153,"score_gpt":0.23632781346834528,"score_spread":0.22790234024522013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7124834574","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.092100285,0.017101478,0.0007114027,0.35003132,0.0018324838,0.00007883087,0.0043720333,0.00006999491,0.53370225],"genre_scores_gemma":[0.7116903,0.032571,0.001337984,0.026552005,0.0004049873,0.000055493078,0.0016964475,0.00006519703,0.22562659],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9980567,0.00009113809,0.000016358963,0.00014200363,0.0006525099,0.0010413238],"domain_scores_gemma":[0.99638474,0.0002645521,0.00014486129,0.00006344638,0.0020730274,0.001069276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001064593,0.0003709447,0.00028866148,0.0011271772,0.008715078,0.01040013,0.0009099078,0.0021327417,0.024979645],"category_scores_gemma":[0.003973634,0.0002073415,0.0004201054,0.0032482988,0.0041855895,0.0033732094,0.0012712308,0.0029290356,0.0018548063],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012983002,0.00010141873,0.04343594,0.00043710644,0.00006448657,0.0003556805,0.01628934,0.0009263061,0.00045176403,0.300531,0.5158922,0.12138489],"study_design_scores_gemma":[0.000022460203,0.00003133754,0.0849651,0.0010635955,0.0000865778,0.00007971685,0.08016569,0.0004379922,0.00048555766,0.018632265,0.81394565,0.0000839746],"about_ca_topic_score_codex":0.99559194,"about_ca_topic_score_gemma":0.99778914,"teacher_disagreement_score":0.076880656,"about_ca_system_score_codex":0.076880656,"about_ca_system_score_gemma":0.24554503,"threshold_uncertainty_score":0.5578108},"labels":[],"label_agreement":null},{"id":"W7125480211","doi":"10.1109/iceamst67459.2025.11335782","title":"Agile Voyager: Smart Travel Itinerary Planner","year":2025,"lang":"","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"","score_opus":0.00859462765296489,"score_gpt":0.2295467906097563,"score_spread":0.2209521629567914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7125480211","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048221122,0.00047090743,0.57408285,0.0025635238,0.0011488369,0.001114183,0.006179536,0.13260312,0.23361585],"genre_scores_gemma":[0.4066727,0.0006051671,0.44700393,0.00049767306,0.00012265725,0.0007334254,0.0073613515,0.005168889,0.13183436],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983203,0.000035545134,0.0000068862773,0.000035785775,0.000046933004,0.00004268883],"domain_scores_gemma":[0.99957913,0.000059285027,0.000019672703,0.00006284049,0.00008731929,0.00019172442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046548384,0.0006794747,0.00035090712,0.0005576156,0.00063835894,0.0014819348,0.0009734134,0.00062433165,0.053333595],"category_scores_gemma":[0.0011672943,0.0004959447,0.00026004136,0.00054198445,0.0002317624,0.0014684162,0.0019129779,0.0009765071,0.010000382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009884926,0.00038494938,0.0045151045,0.00021635753,0.000044788932,0.0004796864,0.000709267,0.06426042,0.010229573,0.027953403,0.43407235,0.4561456],"study_design_scores_gemma":[0.00028364558,0.00034124346,0.0021404016,0.00008936539,0.000050167888,0.00032534442,0.0014549413,0.33574316,0.0076950183,0.017711295,0.63406193,0.000103475024],"about_ca_topic_score_codex":0.0044467538,"about_ca_topic_score_gemma":0.009559079,"teacher_disagreement_score":0.053333595,"about_ca_system_score_codex":0.00049022684,"about_ca_system_score_gemma":0.0017242064,"threshold_uncertainty_score":0.17841864},"labels":[],"label_agreement":null},{"id":"W7125608318","doi":"10.1109/wsc68292.2025.11339081","title":"Evaluating Third-Party Impacts in Urban Air Mobility Community Integration: A Digital Twin Approach","year":2025,"lang":"","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Air pollution; Field (mathematics); Work (physics); Urban heat island; Climate change","score_opus":0.0511965754195363,"score_gpt":0.3282115016132352,"score_spread":0.2770149261936989,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7125608318","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94540215,0.00018554609,0.019152462,0.00023926847,0.00009601433,0.00067671074,0.0006833718,0.000059178106,0.033505265],"genre_scores_gemma":[0.9900383,0.00011098321,0.0068170135,0.000049095437,0.000015430542,0.0003492307,0.00033194222,0.00001985221,0.0022681754],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9929317,0.0038827676,0.00020868875,0.0005730199,0.0017550001,0.0006487657],"domain_scores_gemma":[0.9829186,0.009913289,0.0014283897,0.0022400292,0.0027796049,0.00072014617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00892555,0.00080519,0.0007388143,0.0025456352,0.0013139597,0.0047820006,0.0017719084,0.00145621,0.011311935],"category_scores_gemma":[0.030639483,0.00037112972,0.0013844314,0.0035165208,0.002154724,0.006330991,0.007357299,0.0016269619,0.000983529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0111709125,0.0118372,0.2464156,0.0013093479,0.002627262,0.00052326015,0.0031774295,0.24831079,0.005198756,0.14688037,0.0033943574,0.31915474],"study_design_scores_gemma":[0.0011926627,0.016707312,0.18351464,0.00047765308,0.004077928,0.00025730542,0.020207794,0.6370835,0.02090462,0.09591506,0.019418998,0.00024256656],"about_ca_topic_score_codex":0.013781832,"about_ca_topic_score_gemma":0.011780596,"teacher_disagreement_score":0.013781832,"about_ca_system_score_codex":0.004095605,"about_ca_system_score_gemma":0.0028479835,"threshold_uncertainty_score":0.047203362},"labels":[],"label_agreement":null},{"id":"W7128630310","doi":"10.1109/ictmod66732.2025.11372033","title":"Toward Inclusive and Ethical Adoption of Autonomous Vehicles in Smart Urban Environments","year":2025,"lang":"","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Corporate governance; Key (lock); Capability approach; Economic Justice; Smart city; Perception; Grounded theory; Sociotechnical system","score_opus":0.011084199065046709,"score_gpt":0.24551909805159278,"score_spread":0.23443489898654607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7128630310","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3837324,0.0005626312,0.43436474,0.04396377,0.00018984177,0.0006982933,0.00015371744,0.00031297348,0.13602163],"genre_scores_gemma":[0.96590525,0.00017621879,0.031087192,0.0007972092,0.00002114328,0.00019723318,0.000046455876,0.00004816336,0.0017210714],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.95898926,0.02999789,0.0010664177,0.002408019,0.0056163287,0.0019220926],"domain_scores_gemma":[0.9392314,0.030279025,0.008966926,0.011549453,0.007527965,0.002445222],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.036456462,0.0004979937,0.00041818133,0.0014775181,0.0053262226,0.014681393,0.001825977,0.0036692375,0.0022713772],"category_scores_gemma":[0.075395316,0.00053956395,0.00081241695,0.0013688814,0.019798487,0.011331572,0.011706899,0.0051798946,0.00044628006],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004803888,0.00023080863,0.023054605,0.00017396979,0.00004465183,0.00031721705,0.024996653,0.011060256,0.0015176686,0.8905836,0.0028551728,0.04511732],"study_design_scores_gemma":[0.000043641747,0.000111975445,0.0063918442,0.00030668566,0.00003598541,0.0001869178,0.021908836,0.035854127,0.002460361,0.8702689,0.062356267,0.000074486314],"about_ca_topic_score_codex":0.0052497694,"about_ca_topic_score_gemma":0.0075676055,"teacher_disagreement_score":0.036456462,"about_ca_system_score_codex":0.007917644,"about_ca_system_score_gemma":0.012940099,"threshold_uncertainty_score":0.19280255},"labels":[],"label_agreement":null},{"id":"W7132866892","doi":"","title":"Towards Effective Integration of On-Demand Transit into Transit Systems: Developing Guiding Principles for Planning and Exploring the Determinants of Ridership and Trip Cancellations","year":2025,"lang":"","type":"dissertation","venue":"TSpace","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Hudbay Minerals (Canada)","funders":"","keywords":"Transit (satellite); TRIPS architecture; Service (business); Popularity; Public transport; Level of service; Travel time; Transportation planning","score_opus":0.12857291465857618,"score_gpt":0.35750171221868626,"score_spread":0.2289287975601101,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132866892","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08739582,0.0007876781,0.8887389,0.0062352144,0.000060876187,0.0008984464,0.00042687496,0.00018207199,0.0152742015],"genre_scores_gemma":[0.57296234,0.0026187492,0.41837323,0.0002904954,0.000058771486,0.00085809577,0.0005320563,0.00011139634,0.004194861],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9969593,0.0015547678,0.00015088676,0.00036787524,0.00064958335,0.0003175184],"domain_scores_gemma":[0.9942438,0.0031576017,0.00073573756,0.000349663,0.0012552778,0.00025789085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005258829,0.0011482872,0.0014509085,0.0016118108,0.001113559,0.005310107,0.0023691559,0.0017518412,0.0014750214],"category_scores_gemma":[0.011743527,0.00197057,0.0016421347,0.0021829773,0.0022040715,0.005290274,0.003350272,0.0034663773,0.00033240835],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002002462,0.00039342657,0.028748244,0.00032636154,0.00011245115,0.00027155795,0.0018339594,0.623373,0.0008846604,0.28305733,0.0026903474,0.058288615],"study_design_scores_gemma":[0.0000098427245,0.00009252157,0.0058524366,0.00017433708,0.000033479515,0.000045504315,0.0015178574,0.84582233,0.00035885887,0.14085282,0.005205734,0.000034283235],"about_ca_topic_score_codex":0.052380018,"about_ca_topic_score_gemma":0.04449455,"teacher_disagreement_score":0.052380018,"about_ca_system_score_codex":0.0050643166,"about_ca_system_score_gemma":0.013989235,"threshold_uncertainty_score":0.104150295},"labels":[],"label_agreement":null},{"id":"W7132932668","doi":"","title":"An Examination of Under-studied Aspects of Ride-sourcing Adoption and Use in Large Metropolitan Areas","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Multinomial logistic regression; Estimation; Metropolitan area; Popularity; Logistic regression; Externality; Econometric model; Logit","score_opus":0.023330095255863985,"score_gpt":0.3138418910877304,"score_spread":0.2905117958318664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132932668","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966474,0.00041216222,0.00028198896,0.00040195097,0.0000032413548,0.00003120787,0.00027665877,0.0000051772995,0.0019402873],"genre_scores_gemma":[0.997656,0.00093187013,0.0004385834,0.000071500384,0.000007126141,0.000037017897,0.0002181218,0.0000052089545,0.00063448766],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974705,0.0010841888,0.0002111401,0.0002959793,0.0006417379,0.00029639818],"domain_scores_gemma":[0.97858673,0.009961869,0.005361767,0.0009912206,0.0041427193,0.00095571205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052509024,0.0002063296,0.0003913907,0.002003854,0.0009980187,0.002072769,0.0007954328,0.000509722,0.0017972036],"category_scores_gemma":[0.02085225,0.00029643718,0.00044904352,0.0053992816,0.0009776414,0.0020647007,0.0014193936,0.00073849823,0.00024112815],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041875464,0.00007007813,0.91890407,0.0003202836,0.00008295986,0.00015284082,0.047028173,0.00026991143,0.0004674409,0.0006793968,0.0005605783,0.031422444],"study_design_scores_gemma":[0.0000012982388,0.000044319127,0.9514039,0.000138378,0.000016571623,0.000044306198,0.04520797,0.00042160688,0.00009419063,0.00007762777,0.0025381136,0.000011769097],"about_ca_topic_score_codex":0.17102683,"about_ca_topic_score_gemma":0.3345564,"teacher_disagreement_score":0.17102683,"about_ca_system_score_codex":0.002769855,"about_ca_system_score_gemma":0.0033813496,"threshold_uncertainty_score":0.34006268},"labels":[],"label_agreement":null},{"id":"W7132947750","doi":"","title":"Luottotietosääntelyn muutoksien vaikutukset pankkien luottoriskien hallintaan","year":2023,"lang":"fi","type":"dissertation","venue":"Trepo - Institutional Repository of Tampere University","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Research methodology; Order (exchange); Quarter (Canadian coin)","score_opus":0.014539084073251845,"score_gpt":0.2158811842383108,"score_spread":0.20134210016505893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132947750","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19041412,0.018480845,0.019454919,0.010231777,0.0038609183,0.00038412158,0.0019048406,0.0016328383,0.7536357],"genre_scores_gemma":[0.22379258,0.0073326547,0.015860379,0.0016283044,0.00046332311,0.00023425286,0.0013555015,0.0008162824,0.7485167],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99895823,0.00013420162,0.00005530403,0.0002811344,0.0003706781,0.00020044917],"domain_scores_gemma":[0.9989705,0.0001966655,0.00011877431,0.00009457916,0.00035926065,0.00026024418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000992164,0.0008001823,0.00069867435,0.0009630517,0.0038722407,0.0061322884,0.0010673866,0.0014699986,0.08919464],"category_scores_gemma":[0.001574104,0.0005638419,0.00074551196,0.00085305184,0.0013703248,0.0033200951,0.0043990267,0.002833012,0.02754818],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021546355,0.0009079958,0.024302624,0.0034907712,0.00016479746,0.0043522925,0.027126191,0.0006761176,0.1933747,0.06515783,0.06972638,0.6085657],"study_design_scores_gemma":[0.000026505342,0.00023525684,0.010749479,0.00038022606,0.00006558834,0.0008707853,0.005758071,0.00024707333,0.021400267,0.0028926062,0.95730567,0.000068455345],"about_ca_topic_score_codex":0.006031052,"about_ca_topic_score_gemma":0.01997093,"teacher_disagreement_score":0.08919464,"about_ca_system_score_codex":0.002190732,"about_ca_system_score_gemma":0.0036718145,"threshold_uncertainty_score":0.2983858},"labels":[],"label_agreement":null},{"id":"W7133014639","doi":"","title":"The Adoption, Use, and Impacts of Ride-sourcing Services in the Metro Vancouver Area","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Hudbay Minerals (Canada)","funders":"","keywords":"Work (physics); Metropolitan area; Novelty; Public transport; Transportation planning; Mode choice; Journey to work","score_opus":0.0154689842558677,"score_gpt":0.28027606075270267,"score_spread":0.264807076496835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7133014639","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961808,0.000101452046,0.000023155144,0.00016953846,0.0000026208418,0.00002079269,0.000109938475,0.0000014989408,0.0033901972],"genre_scores_gemma":[0.9960765,0.00055639603,0.00010349103,0.000054330165,0.0000030762671,0.00002345906,0.00014290467,0.0000029242965,0.0030367677],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988599,0.00022768405,0.00004273188,0.00011552781,0.00038158172,0.0003725],"domain_scores_gemma":[0.99754494,0.00043887514,0.00034758184,0.000068796944,0.0009716222,0.00062810525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006708225,0.00019732965,0.0002885052,0.0007490327,0.0027356527,0.0028455618,0.0006390693,0.0003681984,0.0016954069],"category_scores_gemma":[0.0036908078,0.00021185001,0.00018392745,0.0024765276,0.0010705894,0.0005263163,0.0014570589,0.0008900453,0.00026752413],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014394902,0.00036385097,0.9090726,0.00013168826,0.000051902312,0.0005500381,0.039480492,0.00048512002,0.00091497944,0.00065744866,0.001827554,0.046320457],"study_design_scores_gemma":[0.0000051057596,0.00007827726,0.8968417,0.00009241189,0.000014676294,0.000066380235,0.099067785,0.00035227288,0.00012752609,0.00004445848,0.0032919524,0.000017517448],"about_ca_topic_score_codex":0.9516744,"about_ca_topic_score_gemma":0.981306,"teacher_disagreement_score":0.0483256,"about_ca_system_score_codex":0.01212524,"about_ca_system_score_gemma":0.013555581,"threshold_uncertainty_score":0.09722036},"labels":[],"label_agreement":null},{"id":"W7133032312","doi":"","title":"Essays in Technology and Market Power","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Counterfactual thinking; Production (economics); Population; Instrumental variable; Control (management); Power (physics); Population growth; Public transport","score_opus":0.006368363903511578,"score_gpt":0.28325003828604395,"score_spread":0.27688167438253236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7133032312","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006456237,0.1276886,0.0045330524,0.1593678,0.011239819,0.000025824282,0.00026023234,0.00008037778,0.690348],"genre_scores_gemma":[0.3341193,0.139008,0.002310124,0.02039034,0.03867632,0.00011750285,0.00042635418,0.00022337434,0.46472865],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993641,0.00022011969,0.000030070285,0.000099707715,0.00019616069,0.00008990428],"domain_scores_gemma":[0.997843,0.0015415531,0.00012698887,0.00012361296,0.00021982429,0.00014490723],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008592268,0.00071664643,0.0004625105,0.0014537147,0.0019164635,0.0049013826,0.00068821246,0.0020619603,0.023953399],"category_scores_gemma":[0.00414547,0.00022233049,0.0005327505,0.0020093867,0.004455631,0.0056199566,0.0011387309,0.0024786263,0.002766471],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001251403,0.000018943996,0.00022749246,0.00013589287,0.000007860238,0.00006269757,0.0010736344,0.0003387427,0.000087977416,0.81620115,0.16518909,0.016644046],"study_design_scores_gemma":[0.0000071438203,0.000012689907,0.00052250456,0.0003083753,0.000004310233,0.000055516004,0.00095080544,0.00031564428,0.00006006743,0.19650653,0.8012502,0.0000062369672],"about_ca_topic_score_codex":0.0018820855,"about_ca_topic_score_gemma":0.0016308506,"teacher_disagreement_score":0.023953399,"about_ca_system_score_codex":0.0034624888,"about_ca_system_score_gemma":0.0014977853,"threshold_uncertainty_score":0.08013213},"labels":[],"label_agreement":null},{"id":"W7133032648","doi":"","title":"Environmental and Energy Implications of Emerging Technologies and Trends in Road Transport","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Hudbay Minerals (Canada)","funders":"","keywords":"Electrification; Greenhouse gas; Electricity; Electric vehicle; Public transport; Kilometer; Limiting; Emerging technologies; Offset (computer science)","score_opus":0.00878369411486261,"score_gpt":0.2741005832207139,"score_spread":0.2653168891058513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7133032648","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.951525,0.0051768846,0.004276571,0.00356438,0.00012508393,0.000047317753,0.0024361645,0.000030508596,0.03281812],"genre_scores_gemma":[0.991284,0.005163422,0.0009002192,0.00012855967,0.000048496146,0.000008714969,0.00049662276,0.000008805321,0.001961147],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99947566,0.00009186882,0.000023732287,0.00006717114,0.00021441573,0.00012719157],"domain_scores_gemma":[0.9992143,0.00013198181,0.0002261847,0.000044880406,0.0003335033,0.000049051578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041382192,0.0002494165,0.000114168535,0.00080117997,0.000395637,0.0018825307,0.00035409676,0.00056738924,0.0021807484],"category_scores_gemma":[0.0010019762,0.00010908992,0.00037538187,0.002035029,0.0005786868,0.0016086893,0.000700842,0.000578854,0.00022411464],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025751247,0.00030054676,0.6671214,0.0009699696,0.00031914658,0.0025265361,0.0020567751,0.09748064,0.013794938,0.047347136,0.0057810023,0.16204442],"study_design_scores_gemma":[0.000008041336,0.00039627615,0.8758061,0.00034118036,0.00014371442,0.0007863532,0.014524141,0.027828531,0.006154054,0.009712292,0.06423011,0.00006931743],"about_ca_topic_score_codex":0.04662501,"about_ca_topic_score_gemma":0.12631285,"teacher_disagreement_score":0.04662501,"about_ca_system_score_codex":0.003283044,"about_ca_system_score_gemma":0.0009913179,"threshold_uncertainty_score":0.09270728},"labels":[],"label_agreement":null},{"id":"W7133051980","doi":"","title":"Autonomous Vehicles: How they can Transform Perceived Travel Times and Toronto’s Transportation Network in the Process","year":2023,"lang":"","type":"dissertation","venue":"TSpace","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Hudbay Minerals (Canada)","funders":"","keywords":"Process (computing); Perception; Preference; Travel time; Travel survey; Travel behavior","score_opus":0.013522732347490546,"score_gpt":0.2792253124896069,"score_spread":0.26570258014211634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7133051980","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9699784,0.00014180205,0.0005230597,0.0012438297,0.000016682738,0.00002745746,0.00012460777,0.000007771449,0.027936405],"genre_scores_gemma":[0.9965933,0.000103599836,0.00022232895,0.000029449318,0.00000216333,0.000007056609,0.00003591624,0.000004050747,0.0030021823],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941266,0.0002437674,0.00001567397,0.000057605062,0.00014177513,0.00012852905],"domain_scores_gemma":[0.9984761,0.00040152788,0.00026460044,0.00007221841,0.00037609652,0.0004094151],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008485738,0.000171142,0.00009013992,0.00050256326,0.0019270555,0.0038802002,0.0005209481,0.00036520092,0.004731433],"category_scores_gemma":[0.0035245938,0.00011979101,0.00017836805,0.00091548247,0.0017587192,0.0013690373,0.0015272908,0.00046682445,0.00025262038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028883314,0.00023802956,0.3564627,0.0002119689,0.00007237268,0.0006858727,0.51503885,0.0021644984,0.002462488,0.05491052,0.008476909,0.058987],"study_design_scores_gemma":[0.000025440315,0.00013131539,0.38585818,0.00013668189,0.000057831723,0.00008278586,0.5389914,0.003666943,0.0005904075,0.0034287632,0.06698414,0.000046071862],"about_ca_topic_score_codex":0.77505916,"about_ca_topic_score_gemma":0.8567192,"teacher_disagreement_score":0.22494084,"about_ca_system_score_codex":0.020471489,"about_ca_system_score_gemma":0.009266437,"threshold_uncertainty_score":0.4525311},"labels":[],"label_agreement":null},{"id":"W7133077275","doi":"","title":"Social, Platform, and Individual Choices in Ride-Sharing","year":2023,"lang":"","type":"dissertation","venue":"TSpace","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Social planner; Planner; Revenue; Revenue sharing; Preference; Externality; Social Welfare; Service (business)","score_opus":0.07031654317062752,"score_gpt":0.35855210567771845,"score_spread":0.2882355625070909,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7133077275","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89453983,0.0013289654,0.020370582,0.0017012745,0.000023722278,0.0001311343,0.00022315481,0.000024867632,0.08165659],"genre_scores_gemma":[0.99576545,0.0002383792,0.001060128,0.000035750076,0.0000071407067,0.0000217628,0.00001813245,0.0000054128727,0.002847855],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99869186,0.000783792,0.000031160933,0.00015260534,0.00011161395,0.00022888747],"domain_scores_gemma":[0.9961731,0.0024262806,0.0006691545,0.00019733894,0.00016474437,0.00036942877],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020959228,0.0002963346,0.0003283807,0.00041483916,0.0010831124,0.0025623974,0.0006629119,0.00116794,0.010304293],"category_scores_gemma":[0.0053268517,0.00018607153,0.0004457928,0.0005919743,0.0021928719,0.0023970741,0.0016028503,0.0009496784,0.0004008787],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008963605,0.0010232107,0.080518,0.00038219738,0.00037169852,0.00064385706,0.0060193115,0.17315781,0.0035112945,0.6506865,0.0041455,0.07864427],"study_design_scores_gemma":[0.00015479012,0.00081303896,0.109166674,0.00022598065,0.00024406725,0.00039302898,0.022599457,0.26013437,0.0024334455,0.5770014,0.026607953,0.00022578506],"about_ca_topic_score_codex":0.005804934,"about_ca_topic_score_gemma":0.00876887,"teacher_disagreement_score":0.010304293,"about_ca_system_score_codex":0.0018765508,"about_ca_system_score_gemma":0.00071119476,"threshold_uncertainty_score":0.034471333},"labels":[],"label_agreement":null},{"id":"W7133081882","doi":"","title":"Understanding Travel Behaviours and Overcoming Barriers: Case Studies of Achieving Equitable Public Transit for Disadvantaged Groups in Canada","year":2023,"lang":"","type":"dissertation","venue":"TSpace","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; University of Toronto","keywords":"Disadvantaged; Paratransit; Public transport; Social exclusion; Transit (satellite); Quality (philosophy); Empirical research; Inequality","score_opus":0.12184398621844912,"score_gpt":0.3508928241969719,"score_spread":0.22904883797852277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7133081882","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9878698,0.00077245943,0.00029141488,0.0017166511,0.00002029504,0.00022563552,0.00023538605,0.000008368407,0.008859987],"genre_scores_gemma":[0.9893329,0.002541922,0.0013464853,0.00043481993,0.0000077208815,0.00012016152,0.00019041482,0.000014603893,0.006011008],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.99787307,0.000560738,0.00007120439,0.00015525855,0.0004228906,0.0009167919],"domain_scores_gemma":[0.9974343,0.00087680755,0.00021497619,0.00009086236,0.00073622493,0.00064679945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017415299,0.0005200791,0.0006204968,0.0019087909,0.021258123,0.0038711391,0.0026155442,0.0017709513,0.0027520328],"category_scores_gemma":[0.0045779953,0.00043586403,0.00060299604,0.0056877,0.0039674807,0.0014037885,0.0032737164,0.0019836994,0.00018099806],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000098161036,0.00047456802,0.077815466,0.00052564795,0.0000423668,0.008697992,0.8701864,0.0011515421,0.00083872874,0.0073586665,0.0054562367,0.027354298],"study_design_scores_gemma":[0.000010637672,0.00007702224,0.046977855,0.0002741321,0.000028268661,0.0004600219,0.93001777,0.00065450696,0.00021788974,0.00030202366,0.020945258,0.000034673427],"about_ca_topic_score_codex":0.98991954,"about_ca_topic_score_gemma":0.99683446,"teacher_disagreement_score":0.079091914,"about_ca_system_score_codex":0.079091914,"about_ca_system_score_gemma":0.08046326,"threshold_uncertainty_score":0.5738547},"labels":[],"label_agreement":null},{"id":"W7134202470","doi":"10.1109/bigdata66926.2025.11402078","title":"Analyzing the Role of Autonomous Vehicles and Vehicle-As-A-Service in Enhancing Public Transport Efficiency in SãO Paulo","year":2025,"lang":"","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Public transport; Government (linguistics); Work (physics); Data collection","score_opus":0.007680666964949188,"score_gpt":0.22611810299287757,"score_spread":0.2184374360279284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7134202470","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9899345,0.00019684678,0.0016857282,0.0004431385,0.000007972416,0.000023332512,0.00011262661,0.0000122586525,0.0075834915],"genre_scores_gemma":[0.9985746,0.000110712404,0.00032713127,0.0000080700875,0.0000021664591,0.000004523771,0.000047356596,0.0000038301578,0.00092160533],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994881,0.00014531096,0.000015424896,0.00006381867,0.00011506306,0.00017220575],"domain_scores_gemma":[0.9985695,0.00074677274,0.00015338323,0.00004563803,0.0003934317,0.00009122832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008681179,0.00025050636,0.00019805726,0.0008453566,0.0005017964,0.0016219205,0.0004901318,0.0004299388,0.0015339069],"category_scores_gemma":[0.0030540933,0.0002034483,0.0004990413,0.0011572256,0.00064438564,0.00083830405,0.0007013839,0.000523462,0.000110561414],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028186262,0.00045067855,0.71853834,0.0004404973,0.0004819501,0.0019746267,0.008834399,0.082944356,0.0060549383,0.11580582,0.0025510653,0.06164139],"study_design_scores_gemma":[0.000020233281,0.00030013433,0.7872488,0.00021939563,0.00046034402,0.00022754283,0.035413753,0.14769489,0.0021143567,0.007477147,0.018780924,0.000042425723],"about_ca_topic_score_codex":0.3100295,"about_ca_topic_score_gemma":0.3958161,"teacher_disagreement_score":0.3100295,"about_ca_system_score_codex":0.0044332664,"about_ca_system_score_gemma":0.0039599543,"threshold_uncertainty_score":0.61644983},"labels":[],"label_agreement":null},{"id":"W7139201056","doi":"","title":"From Fixed Routes to Flexible Rides: Feasibility of On-Demand Transit Alternatives for Suburban Networks and A Case Study on Mississauga","year":2025,"lang":"","type":"dissertation","venue":"TSpace (University of Toronto)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Public transport; Software deployment; Service (business); Level of service; Quality (philosophy); Transit time; Operational costs; Service level","score_opus":0.035131812305072896,"score_gpt":0.30206115239311143,"score_spread":0.26692934008803854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7139201056","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9947872,0.000054740245,0.00096549833,0.00011293719,0.000005013013,0.000108929715,0.00007167362,0.000009901289,0.003884157],"genre_scores_gemma":[0.9968821,0.00007821631,0.0019186113,0.0000116277015,0.0000020197747,0.00004769172,0.00008122923,0.0000053407475,0.000973331],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9987312,0.0007197765,0.000025138654,0.00013012176,0.00013345864,0.00026033126],"domain_scores_gemma":[0.9981614,0.0010856249,0.00014529892,0.000101705635,0.00031740044,0.000188658],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015400024,0.0010067679,0.00046898477,0.00081848213,0.0014859077,0.0020575263,0.0014512449,0.0011352532,0.0030412683],"category_scores_gemma":[0.003469436,0.00039315876,0.00087868184,0.00082058867,0.00078831735,0.0013304487,0.0008689123,0.00065830303,0.00016118068],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002675775,0.0043231323,0.079259776,0.0007323804,0.00023203003,0.0072972374,0.003355465,0.8114088,0.009456756,0.020647954,0.0035675927,0.05704311],"study_design_scores_gemma":[0.00027950687,0.0048954342,0.025342537,0.00011915906,0.00014638208,0.00041235937,0.015069944,0.9422377,0.0031604196,0.0026717526,0.005593276,0.00007158969],"about_ca_topic_score_codex":0.15594691,"about_ca_topic_score_gemma":0.28217196,"teacher_disagreement_score":0.8440531,"about_ca_system_score_codex":0.006982636,"about_ca_system_score_gemma":0.0026740676,"threshold_uncertainty_score":0.31007838},"labels":[],"label_agreement":null},{"id":"W7144905912","doi":"","title":"Arc, a New Transit Fare Payment System in the Edmonton Metropolitan Region","year":2022,"lang":"ja","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Payment; Transit (satellite); Transit system; Rapid transit; Public transport","score_opus":0.022662957699005597,"score_gpt":0.24245433437016745,"score_spread":0.21979137667116186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7144905912","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64455426,0.0009729689,0.0097495895,0.010339717,0.0007211873,0.0016579019,0.0382508,0.007026117,0.28672746],"genre_scores_gemma":[0.49547344,0.0008836613,0.030582093,0.0014758798,0.00025095997,0.00064395973,0.03638315,0.00076282,0.433544],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986181,0.00024087942,0.000101532816,0.00025349588,0.0005936867,0.00019232168],"domain_scores_gemma":[0.9958091,0.00064056116,0.00029895085,0.0005356141,0.001995839,0.00071995816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002833792,0.00022410334,0.00023635227,0.0026640135,0.0017632053,0.0035314353,0.0013220413,0.0007702381,0.022162383],"category_scores_gemma":[0.0048593264,0.000396051,0.00028501562,0.0033801205,0.0005805068,0.0020046846,0.0012589517,0.00075006444,0.0040436564],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017445947,0.0011794873,0.13266815,0.0003910073,0.00011309942,0.001519582,0.003590416,0.012198006,0.006134481,0.054217633,0.42924395,0.35699955],"study_design_scores_gemma":[0.00036907618,0.00030904653,0.13931786,0.00012522802,0.000090185116,0.0003952611,0.003498513,0.014461208,0.0030650485,0.0018404573,0.83641803,0.00011015107],"about_ca_topic_score_codex":0.3544327,"about_ca_topic_score_gemma":0.3512767,"teacher_disagreement_score":0.6455673,"about_ca_system_score_codex":0.008915327,"about_ca_system_score_gemma":0.024194118,"threshold_uncertainty_score":0.70473933},"labels":[],"label_agreement":null},{"id":"W7161792323","doi":"10.82308/43395","title":"Regulation and case analysis of the ridesharing economy","year":2018,"lang":"en","type":"dissertation","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Taxis; Local Development; Western europe; Economic analysis","score_opus":0.008738377019556882,"score_gpt":0.22943560022706017,"score_spread":0.2206972232075033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7161792323","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35526645,0.002040388,0.06565486,0.0033696422,0.00008918885,0.00046425065,0.0005653183,0.000118888915,0.572431],"genre_scores_gemma":[0.9340416,0.001193947,0.014484464,0.0001972243,0.000021013197,0.00036490103,0.0001976438,0.000024178062,0.04947499],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99678624,0.001639361,0.00014295468,0.00032981945,0.0006852306,0.00041632392],"domain_scores_gemma":[0.99658304,0.002198372,0.000342653,0.00041925788,0.0003595427,0.00009717569],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025657974,0.00018045782,0.00053219555,0.0022107512,0.0028139225,0.004350234,0.0013042942,0.0024233516,0.014301743],"category_scores_gemma":[0.007602458,0.000291043,0.0008089141,0.0033565671,0.0030452614,0.002673596,0.002453455,0.0010992272,0.0007082151],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003378915,0.000062636864,0.0035747918,0.000059370275,0.000017629567,0.0007463733,0.0033477226,0.008722535,0.00027044123,0.9721895,0.0013602711,0.009614946],"study_design_scores_gemma":[0.00009287596,0.00018460078,0.019984104,0.0005470897,0.00011945498,0.0014684284,0.049500052,0.14577806,0.003746017,0.5248014,0.25362006,0.00015781839],"about_ca_topic_score_codex":0.04136861,"about_ca_topic_score_gemma":0.03577829,"teacher_disagreement_score":0.04136861,"about_ca_system_score_codex":0.005608486,"about_ca_system_score_gemma":0.0029536043,"threshold_uncertainty_score":0.0822556},"labels":[],"label_agreement":null},{"id":"W7162721908","doi":"","title":"Arc, a New Transit Fare Payment System in the Edmonton Metropolitan Region","year":2022,"lang":"ja","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Payment; Transit (satellite); Transit system; Rapid transit; Public transport","score_opus":0.022662957699005597,"score_gpt":0.24245433437016745,"score_spread":0.21979137667116186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7162721908","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64455426,0.0009729689,0.0097495895,0.010339717,0.0007211873,0.0016579019,0.0382508,0.007026117,0.28672746],"genre_scores_gemma":[0.49547344,0.0008836613,0.030582093,0.0014758798,0.00025095997,0.00064395973,0.03638315,0.00076282,0.433544],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986181,0.00024087942,0.000101532816,0.00025349588,0.0005936867,0.00019232168],"domain_scores_gemma":[0.9958091,0.00064056116,0.00029895085,0.0005356141,0.001995839,0.00071995816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002833792,0.00022410334,0.00023635227,0.0026640135,0.0017632053,0.0035314353,0.0013220413,0.0007702381,0.022162383],"category_scores_gemma":[0.0048593264,0.000396051,0.00028501562,0.0033801205,0.0005805068,0.0020046846,0.0012589517,0.00075006444,0.0040436564],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017445947,0.0011794873,0.13266815,0.0003910073,0.00011309942,0.001519582,0.003590416,0.012198006,0.006134481,0.054217633,0.42924395,0.35699955],"study_design_scores_gemma":[0.00036907618,0.00030904653,0.13931786,0.00012522802,0.000090185116,0.0003952611,0.003498513,0.014461208,0.0030650485,0.0018404573,0.83641803,0.00011015107],"about_ca_topic_score_codex":0.3544327,"about_ca_topic_score_gemma":0.3512767,"teacher_disagreement_score":0.6455673,"about_ca_system_score_codex":0.008915327,"about_ca_system_score_gemma":0.024194118,"threshold_uncertainty_score":0.70473933},"labels":[],"label_agreement":null},{"id":"W759996246","doi":"","title":"Charlottetown Transit System: A Private Motorcoach Company Runs Public Transportation in This Tourist Town","year":2008,"lang":"en","type":"article","venue":"Mass transit","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Paratransit; Public transport; Tourism; Transit (satellite); Transport engineering; General partnership; Service (business); Square (algebra); Agency (philosophy); Population; Business; Engineering; Marketing; Finance; Geography; Sociology; Archaeology","score_opus":0.01950365005978158,"score_gpt":0.1953418678821111,"score_spread":0.17583821782232953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W759996246","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49056336,0.0012796962,0.003677103,0.0024238592,0.0003300356,0.00045463548,0.0009290657,0.00094155193,0.49940068],"genre_scores_gemma":[0.42330188,0.0006071867,0.0028023396,0.00040723666,0.000038092807,0.00010922421,0.0006356238,0.00011242086,0.571986],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99987507,0.0000104317105,0.0000025204565,0.000028549011,0.000038736336,0.00004474396],"domain_scores_gemma":[0.99974114,0.000016373826,0.000015590525,0.000016290076,0.00008641622,0.00012414313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001025583,0.0002525787,0.00010022194,0.00039212703,0.0024922001,0.0014630334,0.00028752547,0.00039107556,0.056347866],"category_scores_gemma":[0.00021342878,0.00019765749,0.00008267845,0.00049324165,0.00053911057,0.0005821463,0.0009978242,0.0004950242,0.0069407085],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007128723,0.0007520074,0.06930945,0.00071908516,0.00003249789,0.0065686377,0.017121682,0.0012140113,0.031566676,0.014051392,0.37418216,0.4837695],"study_design_scores_gemma":[0.0000339,0.000290163,0.05956199,0.000078319325,0.000009731259,0.001986174,0.0070000817,0.00073884317,0.0026633306,0.00014733212,0.92746466,0.000025525933],"about_ca_topic_score_codex":0.114356406,"about_ca_topic_score_gemma":0.3315239,"teacher_disagreement_score":0.8856436,"about_ca_system_score_codex":0.0022317509,"about_ca_system_score_gemma":0.0041153785,"threshold_uncertainty_score":0.22738153},"labels":[],"label_agreement":null},{"id":"W79914725","doi":"","title":"British Columbia launches open source Evergreen ILS Project","year":2007,"lang":"en","type":"article","venue":"Smart Libraries Newsletter","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Open source; Computer science","score_opus":0.017229045462605976,"score_gpt":0.2213477654015893,"score_spread":0.2041187199389833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W79914725","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021317024,0.00030899103,0.007535146,0.008025208,0.0013177401,0.00032784915,0.010155809,0.020941535,0.9300708],"genre_scores_gemma":[0.02382843,0.0001760034,0.005957109,0.0008189268,0.000064742846,0.00007591168,0.0062103253,0.0016722077,0.9611964],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989672,0.000054944834,0.000014262897,0.000079341204,0.00065433746,0.0002299372],"domain_scores_gemma":[0.9960401,0.0002571388,0.00005096831,0.00029921162,0.00234751,0.001005009],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.001433528,0.00075212045,0.00033623303,0.0016857417,0.004459137,0.005736248,0.0008627772,0.0013301945,0.11620095],"category_scores_gemma":[0.0020860874,0.00039735646,0.00035232742,0.0013304567,0.00082635955,0.0013306868,0.0022358606,0.001909607,0.038336404],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001423076,0.00014000435,0.0024218273,0.00005201577,0.000007926743,0.00019373943,0.00033533564,0.00038783895,0.0024031778,0.0035836005,0.90403974,0.08629247],"study_design_scores_gemma":[0.000022803235,0.00002129086,0.002837293,0.00002508114,0.000008813744,0.000023603183,0.00053562364,0.000902619,0.0011840181,0.00045260836,0.99396825,0.000018137549],"about_ca_topic_score_codex":0.6372037,"about_ca_topic_score_gemma":0.82126325,"teacher_disagreement_score":0.9991372,"about_ca_system_score_codex":0.006197705,"about_ca_system_score_gemma":0.01429104,"threshold_uncertainty_score":0.7298658},"labels":[],"label_agreement":null},{"id":"W804619935","doi":"","title":"WI-FI BLAZING TRAIL FOR ONBOARD TECH CONVENIENCE","year":2005,"lang":"en","type":"article","venue":"Metrologia","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Train; Telecommunications; Transit (satellite); Service (business); The Internet; Position (finance); Business; Transport engineering; Track (disk drive); Wireless; Advertising; Computer science; Marketing; Public transport; Engineering; Finance; World Wide Web; Geography","score_opus":0.016526568764228106,"score_gpt":0.23753061084674837,"score_spread":0.22100404208252025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W804619935","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013789837,0.0032111655,0.020831898,0.015935881,0.0038644376,0.0001105079,0.0004639627,0.0017736235,0.94001853],"genre_scores_gemma":[0.05961386,0.0025290807,0.006566605,0.003527892,0.0005790305,0.00004509616,0.00028463703,0.00039436037,0.9264595],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99947697,0.00005682266,0.000018351757,0.000057596302,0.00027809088,0.00011219344],"domain_scores_gemma":[0.99937326,0.000093034614,0.000041105657,0.00014323537,0.00027713436,0.000072286755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004864202,0.0007021731,0.00018890423,0.0009015928,0.0026214486,0.0034604792,0.00038962185,0.00080544595,0.15031236],"category_scores_gemma":[0.0019570673,0.00020529542,0.00026266222,0.0009744109,0.0010435664,0.0027966523,0.0016468578,0.0015552449,0.07336417],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016944378,0.00008865659,0.0021989672,0.00012966851,0.000012377664,0.0003214362,0.0009847651,0.0002891985,0.0071796607,0.10635927,0.42495215,0.45731443],"study_design_scores_gemma":[0.0000052999035,0.000028667979,0.0010202521,0.000049383645,0.0000046665577,0.0001793703,0.00034092754,0.00014645726,0.000715531,0.0022437738,0.9952586,0.0000069918706],"about_ca_topic_score_codex":0.008108045,"about_ca_topic_score_gemma":0.013809462,"teacher_disagreement_score":0.15031236,"about_ca_system_score_codex":0.0009611552,"about_ca_system_score_gemma":0.0013836372,"threshold_uncertainty_score":0.5028449},"labels":[],"label_agreement":null},{"id":"W814093649","doi":"","title":"Residential On-Site Carsharing and Off -Street Parking Policy in the San Francisco Bay Area, Research Report 11-28","year":2012,"lang":"en","type":"article","venue":"San José State University ScholarWorks (San Jose State University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"San José State University; York University; California Department of Transportation; Research and Innovative Technology Administration; U.S. Department of Transportation","keywords":"Bay; Geography; Transport engineering; Vehicle miles of travel; Environmental planning; Archaeology; Engineering","score_opus":0.025723411367399352,"score_gpt":0.25296446218299645,"score_spread":0.2272410508155971,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W814093649","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98061717,0.00090533204,0.00018171182,0.0015169153,0.000013308749,0.00006505783,0.00046371698,0.0000166463,0.016220212],"genre_scores_gemma":[0.9870228,0.001039799,0.00057823077,0.00010819099,0.000010651063,0.00005332403,0.0005625489,0.000006065981,0.010618473],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99951255,0.00014975866,0.00001884537,0.00007671556,0.00008426536,0.00015785191],"domain_scores_gemma":[0.99821436,0.00047660616,0.00029521468,0.00007968968,0.0004966788,0.0004373924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008973436,0.00021741669,0.000149899,0.00051595893,0.0014453654,0.0015392987,0.00079554756,0.0005849648,0.0041874265],"category_scores_gemma":[0.0018026567,0.0002144659,0.0001608874,0.0009115105,0.0006807697,0.0009307226,0.0005932565,0.0005612519,0.00025883032],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029739158,0.0017554682,0.8589476,0.0006881983,0.00010796932,0.00096111395,0.030659286,0.0032587794,0.0024897656,0.014062421,0.019373938,0.06739811],"study_design_scores_gemma":[0.000046019693,0.00040070302,0.8969976,0.0002221958,0.0000888765,0.00011339456,0.0551008,0.0018171024,0.0010666375,0.0003978358,0.043719623,0.000029252764],"about_ca_topic_score_codex":0.48030162,"about_ca_topic_score_gemma":0.6801996,"teacher_disagreement_score":0.48030162,"about_ca_system_score_codex":0.0074936175,"about_ca_system_score_gemma":0.0073148897,"threshold_uncertainty_score":0.9550119},"labels":[],"label_agreement":null},{"id":"W834944855","doi":"","title":"Paccar's 1st-quarter profits, revenue soar as worldwide demand for trucks increases","year":2011,"lang":"en","type":"article","venue":"Transport topics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Truck; Soar; Quarter (Canadian coin); Revenue; Business; Finance; Agricultural economics; Commerce; Automotive engineering; Economics; Engineering; Computer science; Geography","score_opus":0.020597234069590332,"score_gpt":0.22766047978630247,"score_spread":0.20706324571671214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W834944855","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21370767,0.0015837227,0.0020574941,0.0552821,0.003487877,0.00007457978,0.0061038476,0.00222458,0.715478],"genre_scores_gemma":[0.52563184,0.0023281742,0.0014411941,0.005407574,0.00089369074,0.000042672713,0.0052285003,0.0005343093,0.4584921],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99952734,0.000021352109,0.000009038999,0.000050144477,0.00027990597,0.000112283546],"domain_scores_gemma":[0.99880695,0.00012027795,0.00011995996,0.00005966901,0.00058184756,0.00031135607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059986964,0.0003889452,0.00022583539,0.0010239844,0.0011720753,0.0058928085,0.0005118333,0.0014585026,0.044035953],"category_scores_gemma":[0.0030327532,0.0002451983,0.00045579855,0.0011369587,0.00048092622,0.0024119446,0.0010399355,0.0021615052,0.011522092],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030395007,0.00021384847,0.024873128,0.00013011275,0.000022597704,0.0004208427,0.00036107498,0.002024866,0.0034155569,0.030342598,0.7867422,0.15114923],"study_design_scores_gemma":[0.000024418136,0.00014881713,0.061007675,0.000057198635,0.00002044793,0.00053814275,0.0015363513,0.0041257865,0.0024301447,0.002552963,0.9275212,0.00003681723],"about_ca_topic_score_codex":0.017087568,"about_ca_topic_score_gemma":0.03130216,"teacher_disagreement_score":0.044035953,"about_ca_system_score_codex":0.0025665544,"about_ca_system_score_gemma":0.0029924735,"threshold_uncertainty_score":0.1473149},"labels":[],"label_agreement":null},{"id":"W854859345","doi":"","title":"Class 8 truck fleet growth rose in 3rd quarter, Polk data shows","year":2005,"lang":"en","type":"article","venue":"Transport topics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"POLK; Truck; Rose (mathematics); Quarter (Canadian coin); Engineering; Class (philosophy); Automotive engineering; Transport engineering; Geography; Computer science; Archaeology; Biology","score_opus":0.0266985615849157,"score_gpt":0.2499326114650751,"score_spread":0.22323404988015938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W854859345","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35052434,0.0011934141,0.0017199995,0.018389108,0.0024254965,0.00018772193,0.36775878,0.0021907208,0.25561047],"genre_scores_gemma":[0.3361783,0.0009832913,0.0004933372,0.0031315433,0.00033817845,0.00016098372,0.25450522,0.00042043155,0.4037886],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992262,0.000022898863,0.000032246782,0.00013359498,0.00030669538,0.00027823806],"domain_scores_gemma":[0.9980379,0.00023800852,0.00035562363,0.00011966884,0.0009572198,0.00029154238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042727817,0.00040604692,0.00046061666,0.0025858656,0.001007035,0.0031965615,0.0005289561,0.0013117316,0.027744647],"category_scores_gemma":[0.0019964154,0.00027513533,0.00056163315,0.00331207,0.00027761565,0.0013254377,0.00096795376,0.0021156298,0.013775994],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054757175,0.00010115815,0.15593244,0.00020076914,0.000030881223,0.00024392823,0.0005723991,0.00065254926,0.0010117865,0.0021310798,0.79713076,0.041444615],"study_design_scores_gemma":[0.000018921037,0.00008713552,0.5926281,0.000053207605,0.00002045456,0.00012195836,0.001859101,0.0006707249,0.001807104,0.00027047066,0.40244153,0.000021307138],"about_ca_topic_score_codex":0.10015596,"about_ca_topic_score_gemma":0.25494716,"teacher_disagreement_score":0.10015596,"about_ca_system_score_codex":0.0025966514,"about_ca_system_score_gemma":0.001851535,"threshold_uncertainty_score":0.19914597},"labels":[],"label_agreement":null}]}