{"meta":{"query_hash":"905478ddba01","filters":{"venue":"Travel Behaviour and Society"},"cohort_total":59,"direct_labels_cover":0,"predictions_cover":59,"exported":59,"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/905478ddba01","api":"https://metacan.xera.ac/api/v1/cohort?venue=Travel+Behaviour+and+Society"},"results":[{"id":"W1516964172","doi":"10.1016/j.tbs.2018.12.002","title":"Transport sufficiency: Introduction &amp; case study","year":2018,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":19,"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":"TRIPS architecture; Sustainability; Key (lock); Environmental economics; Variable (mathematics); Transport engineering; Private transport; Personal mobility; Duration (music); Business; Consumption (sociology); Public transport; Quality (philosophy); Energy consumption; Sustainable transport; Travel behavior; Computer science; Economics; Engineering; Computer security; Mathematics; Ecology","score_opus":0.03575759102164059,"score_gpt":0.3313853791645449,"score_spread":0.2956277881429043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1516964172","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91682345,0.003993814,0.0067987,0.0042909505,0.00015741543,0.00075504015,0.0016265564,0.000047746908,0.065506384],"genre_scores_gemma":[0.97845113,0.0036447854,0.0042377254,0.0003613827,0.000107044696,0.00028524353,0.00033895188,0.000025214278,0.012548574],"study_design_codex":"case_report","study_design_gemma":"qualitative","domain_scores_codex":[0.99923825,0.000342496,0.000043540716,0.00005936284,0.00009424242,0.0002220783],"domain_scores_gemma":[0.9990625,0.0005479542,0.00012933931,0.000049814178,0.0000826653,0.00012778494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078681484,0.0006692593,0.00040695892,0.0022301143,0.00278387,0.0018516277,0.0014002315,0.003642969,0.007857986],"category_scores_gemma":[0.0028716568,0.00038348694,0.0006732011,0.0027267572,0.0019309858,0.0013863768,0.0021535668,0.001505183,0.0006696635],"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":[0.0011625532,0.007736272,0.18460399,0.0030816377,0.00015267561,0.5293642,0.05022216,0.011799563,0.0035033377,0.07010776,0.033341795,0.10492408],"study_design_scores_gemma":[0.00017735682,0.0019495395,0.10260926,0.0020109836,0.00021360526,0.5224424,0.18829207,0.010039893,0.0057200133,0.021833995,0.1445141,0.00019676531],"about_ca_topic_score_codex":0.013184799,"about_ca_topic_score_gemma":0.01848051,"teacher_disagreement_score":0.013184799,"about_ca_system_score_codex":0.0018238273,"about_ca_system_score_gemma":0.0009922065,"threshold_uncertainty_score":0.026287556},"labels":[],"label_agreement":null},{"id":"W1964250536","doi":"10.1016/j.tbs.2015.03.003","title":"Children’s travel and incidental community connections","year":2015,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":32,"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":"Criminology; Forensic engineering; Psychology; Transport engineering; Computer security; Medical emergency; Engineering; Medicine; Computer science","score_opus":0.04951170756259962,"score_gpt":0.3137116411536785,"score_spread":0.26419993359107885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964250536","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9904428,0.00034112736,0.000048516304,0.0002646803,0.000011405617,0.000006664115,0.0002777643,0.0000038976123,0.008603207],"genre_scores_gemma":[0.9985954,0.00021238126,0.000037349455,0.000011521344,0.000006183503,0.000006760671,0.00013040019,0.0000032585954,0.00099671],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99843067,0.00038430165,0.0001418263,0.00015980762,0.00027028285,0.0006130283],"domain_scores_gemma":[0.99394774,0.001533382,0.0022644268,0.00033211778,0.0005644823,0.0013578237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080614234,0.0003035748,0.0003364745,0.0014075595,0.0012162883,0.002134105,0.0007652397,0.000841991,0.010208877],"category_scores_gemma":[0.008662401,0.0002886824,0.00086046883,0.0025852742,0.001240774,0.0020297763,0.002405028,0.0013033492,0.00048159075],"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":[0.000091850896,0.00016651952,0.9851149,0.000060812938,0.000064667474,0.0005045295,0.0058195842,0.0001766578,0.000081447826,0.001509273,0.00048436585,0.0059254104],"study_design_scores_gemma":[0.0000033032898,0.000064212894,0.9848547,0.000054178337,0.000038921284,0.00042620255,0.01236618,0.00010512645,0.00006650057,0.00029327243,0.0017175275,0.000009952133],"about_ca_topic_score_codex":0.0730603,"about_ca_topic_score_gemma":0.10572507,"teacher_disagreement_score":0.0730603,"about_ca_system_score_codex":0.0013705989,"about_ca_system_score_gemma":0.001750716,"threshold_uncertainty_score":0.14527011},"labels":[],"label_agreement":null},{"id":"W2283511115","doi":"10.1016/j.tbs.2016.01.001","title":"Space–time mismatch between transit service and observed travel patterns in the Wasatch Front, Utah: A social equity perspective","year":2016,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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":"University of Toronto; The Scarborough Hospital","funders":"National Institute for Transportation and Communities; Portland State University; U.S. Department of Transportation","keywords":"Public transport; TRIPS architecture; Destinations; Travel behavior; Transport engineering; Equity (law); Transit (satellite); Descriptive statistics; Geography; Business; Supply and demand; Demographic economics; Economics; Engineering; Tourism; Statistics; Mathematics","score_opus":0.07057255134156942,"score_gpt":0.3242956110056941,"score_spread":0.2537230596641247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2283511115","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990056,0.000042832253,0.00008231454,0.00023084956,0.0000026102039,0.0000021012056,0.00007455778,0.0000012178928,0.0005579313],"genre_scores_gemma":[0.99982375,0.0000123100845,0.000026177546,0.000012394689,0.0000030100746,0.0000014832412,0.000034199114,6.9812444e-7,0.00008597829],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99916184,0.00024658698,0.000035277295,0.00016339553,0.0000998291,0.00029313436],"domain_scores_gemma":[0.9985568,0.00057474634,0.0003639581,0.000077852405,0.00021094494,0.00021570406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013205041,0.00014088201,0.00025307963,0.001140908,0.0013168876,0.0016880505,0.0010205309,0.00076050754,0.0014768456],"category_scores_gemma":[0.0047787363,0.00021926282,0.00034319283,0.0019583418,0.0016430425,0.0015410058,0.0020246762,0.00071062736,0.00006957271],"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":[0.00009521644,0.00007490056,0.9897462,0.000009421009,0.000057022935,0.0001018464,0.0040934496,0.0012894799,0.00022586822,0.0013525566,0.00023327152,0.0027207662],"study_design_scores_gemma":[0.00000209975,0.00002818973,0.989224,0.0000054985103,0.0000136527005,0.000027464906,0.0077990377,0.001972011,0.00006335724,0.00056862115,0.00029003757,0.000005891024],"about_ca_topic_score_codex":0.4315845,"about_ca_topic_score_gemma":0.50621426,"teacher_disagreement_score":0.4315845,"about_ca_system_score_codex":0.0035238068,"about_ca_system_score_gemma":0.0019284711,"threshold_uncertainty_score":0.8581448},"labels":[],"label_agreement":null},{"id":"W2328756156","doi":"10.1016/j.tbs.2016.03.001","title":"Recommending transit: Disentangling users’ willingness to recommend transit and their intended continued use","year":2016,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":45,"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; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transit (satellite); Transport engineering; Public transport; Business; Engineering","score_opus":0.0435022414740638,"score_gpt":0.29378225571990874,"score_spread":0.25028001424584495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2328756156","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998517,0.000050103965,0.0001628869,0.00008472055,0.0000038766575,0.000008569832,0.00013685017,0.000003582974,0.0010323379],"genre_scores_gemma":[0.9994809,0.000025810104,0.00010865019,0.000016314207,0.000004180882,0.0000064905066,0.000105362626,0.00000223836,0.00025013802],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99861646,0.00062580704,0.00018681302,0.0001583698,0.00026613314,0.00014638726],"domain_scores_gemma":[0.97712976,0.0149421925,0.003932059,0.0014040566,0.0012316088,0.0013603704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002343731,0.0002851575,0.0003453638,0.00087768404,0.00056890905,0.0017078285,0.0006210669,0.0011946532,0.005002712],"category_scores_gemma":[0.018687882,0.00029061656,0.0011709365,0.0012941117,0.00061264425,0.0023406278,0.00078014814,0.0011954323,0.00055820745],"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":[0.00032941884,0.00015467018,0.9934842,0.00003052851,0.0002535185,0.000043029326,0.001364281,0.00014101899,0.00025650565,0.00012961058,0.00008044788,0.003732808],"study_design_scores_gemma":[0.0000067394935,0.00014286277,0.9955414,0.000011454812,0.00015274103,0.00007701204,0.0019442979,0.0016410139,0.00011824633,0.0001542442,0.00019878123,0.0000112123535],"about_ca_topic_score_codex":0.018740566,"about_ca_topic_score_gemma":0.026453812,"teacher_disagreement_score":0.018740566,"about_ca_system_score_codex":0.00041105188,"about_ca_system_score_gemma":0.00052119343,"threshold_uncertainty_score":0.037262976},"labels":[],"label_agreement":null},{"id":"W2465082530","doi":"10.1016/j.tbs.2016.06.003","title":"Driving over the life course: The automobility of Canada’s Millennial, Generation X, Baby Boomer and Greatest Generations","year":2016,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":74,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University","funders":"","keywords":"Baby boomers; TRIPS architecture; Generation x; License; Demographic economics; Descriptive statistics; Diversity (politics); Demographics; Demography; Life course approach; Geography; Advertising; Sociology; Psychology; Political science; Business; Economics; Engineering; Social psychology; Transport engineering","score_opus":0.023176544167888637,"score_gpt":0.27371513523927404,"score_spread":0.25053859107138543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2465082530","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96520776,0.0038984006,0.00011885805,0.016331501,0.00013505657,0.000033857326,0.0020139427,0.000012703947,0.012247941],"genre_scores_gemma":[0.9913874,0.002880697,0.00012363857,0.00066781,0.000022799448,0.000010619203,0.0006388912,0.000008860491,0.004259256],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99929774,0.00005465796,0.000017948432,0.00006921007,0.00013379502,0.00042657557],"domain_scores_gemma":[0.9990119,0.000027709242,0.000095737974,0.000019219568,0.00028032914,0.0005650284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040657152,0.00027278013,0.00033829905,0.001023684,0.0067119426,0.0038828366,0.0014193457,0.0010739992,0.0045920587],"category_scores_gemma":[0.0010988467,0.0002402481,0.00049462303,0.0040513757,0.0015217091,0.0016436388,0.0025504914,0.0020788398,0.00026984655],"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":[0.000121285346,0.00015635625,0.85906655,0.00011205118,0.00008867097,0.0006091672,0.047234103,0.00031976166,0.00033738906,0.009921577,0.021136176,0.060896926],"study_design_scores_gemma":[0.000005882082,0.000044478922,0.8336929,0.00026985226,0.000060698443,0.00021265654,0.13403736,0.00045540807,0.00010241246,0.00088540115,0.030177642,0.000055397424],"about_ca_topic_score_codex":0.99421483,"about_ca_topic_score_gemma":0.9980413,"teacher_disagreement_score":0.029598754,"about_ca_system_score_codex":0.029598754,"about_ca_system_score_gemma":0.06116852,"threshold_uncertainty_score":0.214755},"labels":[],"label_agreement":null},{"id":"W2606862732","doi":"10.1016/j.tbs.2017.04.005","title":"Transport and child well-being: An integrative review","year":2017,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":157,"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":"VINNOVA","keywords":"Psychology","score_opus":0.02254743391307575,"score_gpt":0.3277857970941735,"score_spread":0.30523836318109776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606862732","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":[0.00020770512,0.99938405,0.00002062518,0.00022210054,0.000058354784,0.0000022123443,0.000011114838,4.969334e-7,0.00009329738],"genre_scores_gemma":[0.0014010452,0.99830246,0.000059946793,0.00009917073,0.00009418326,0.000004933255,0.000010025378,3.9760306e-7,0.00002776744],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.9994505,0.00018080008,0.00012902604,0.00010695288,0.00009181921,0.000040797288],"domain_scores_gemma":[0.99557555,0.0035044288,0.0004561705,0.000049548704,0.00032567664,0.00008857144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020979373,0.0010932639,0.0029302964,0.0036925247,0.00043560416,0.0029186697,0.0012998241,0.0019871604,0.0030620934],"category_scores_gemma":[0.0050534946,0.0005651144,0.0012149562,0.006346735,0.0011199424,0.0026559376,0.0017284466,0.0015148513,0.00028440513],"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":[0.00039770154,0.00027165396,0.0049587996,0.23134021,0.002419822,0.00034296344,0.0013618706,0.00045905373,0.0004253754,0.0047658463,0.015633127,0.7376235],"study_design_scores_gemma":[0.00020410883,0.0006788387,0.048793327,0.39585736,0.011345843,0.00302397,0.004883876,0.0004250216,0.00032759475,0.009839661,0.52438843,0.00023198807],"about_ca_topic_score_codex":0.0059228996,"about_ca_topic_score_gemma":0.011926968,"teacher_disagreement_score":0.0059228996,"about_ca_system_score_codex":0.0008665374,"about_ca_system_score_gemma":0.0032858162,"threshold_uncertainty_score":0.0117768645},"labels":[],"label_agreement":null},{"id":"W2746190559","doi":"10.1016/j.tbs.2017.07.006","title":"Modelling mode switch associated with the change of residential location","year":2017,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":39,"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; Nova Scotia Department of Energy","keywords":"Relocation; Mode (computer interface); Mode choice; Travel behavior; Preference; Demographic economics; Logit; Work (physics); Psychology; Econometrics; Economics; Public transport; Transport engineering; Microeconomics; Computer science; Engineering","score_opus":0.07286847281003506,"score_gpt":0.32302010008309084,"score_spread":0.2501516272730558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2746190559","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98124725,0.00009127424,0.015231188,0.00020271137,0.00005120685,0.000029160707,0.00083456637,0.00009761816,0.0022149691],"genre_scores_gemma":[0.99665534,0.000035945686,0.0013632129,0.0000104336605,0.000006445179,0.000017625021,0.0002992038,0.000014491687,0.0015973485],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997533,0.00006369185,0.000011191402,0.000071168404,0.00002259609,0.00007798532],"domain_scores_gemma":[0.99783725,0.0015346155,0.00017151749,0.00011933836,0.00014949938,0.00018773628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008753201,0.000543028,0.0005774342,0.00065944425,0.00036243387,0.0011592015,0.0012740527,0.002103136,0.006101748],"category_scores_gemma":[0.0043519996,0.00059431,0.0010705405,0.00077050575,0.0005524002,0.000988384,0.00063824997,0.0015181387,0.0004956448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015891992,0.00010746099,0.015547783,0.000027521282,0.00004695375,0.00011457177,0.00009604176,0.97874135,0.00078125054,0.0015818242,0.0003488566,0.0024474084],"study_design_scores_gemma":[0.000006296848,0.000023333907,0.003332124,0.0000032775497,0.000010861887,0.000014142974,0.00003855301,0.9959187,0.00011325677,0.0004083795,0.00012343281,0.000007797453],"about_ca_topic_score_codex":0.07061495,"about_ca_topic_score_gemma":0.03554811,"teacher_disagreement_score":0.07061495,"about_ca_system_score_codex":0.0011764332,"about_ca_system_score_gemma":0.00090995245,"threshold_uncertainty_score":0.1404078},"labels":[],"label_agreement":null},{"id":"W2754018453","doi":"10.1016/j.tbs.2017.09.002","title":"A spatio-temporal accessibility measure for modelling activity participation in discretionary activities","year":2017,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":51,"is_retracted":false,"has_abstract":false,"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":"Agentschap Innoveren en Ondernemen","keywords":"Aggregate (composite); Measure (data warehouse); Correlation; Econometrics; Distribution (mathematics); Computer science; Psychology; Economics; Mathematics","score_opus":0.08393718504038239,"score_gpt":0.37098945002088696,"score_spread":0.28705226498050457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2754018453","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8126033,0.0001943846,0.17576954,0.000103342274,0.000030376752,0.00014327747,0.007468359,0.0004230553,0.0032643278],"genre_scores_gemma":[0.9807052,0.000036564026,0.016727885,0.000004947307,0.0000076352935,0.00014818148,0.0017987431,0.000017522974,0.0005534567],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992611,0.0002538055,0.00009536378,0.00018284604,0.00013683153,0.00006999415],"domain_scores_gemma":[0.9976655,0.0011630134,0.00040706742,0.0003315709,0.0002583082,0.00017445484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011769213,0.00056475843,0.0005686632,0.0025999683,0.0003823393,0.0011241742,0.000842915,0.0005866351,0.002616608],"category_scores_gemma":[0.005158669,0.00020601605,0.0014150147,0.0028740882,0.00039227336,0.0012806125,0.0009932806,0.00058792054,0.00032480567],"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":[0.000587733,0.00082216447,0.4855675,0.00032898356,0.0009828776,0.00025869493,0.00089252513,0.42564002,0.0035016197,0.01284792,0.001379737,0.067190215],"study_design_scores_gemma":[0.000021025971,0.00040865992,0.243567,0.0000499068,0.00017568853,0.00023565706,0.0005157073,0.74553365,0.001000324,0.006112386,0.0023159978,0.00006404141],"about_ca_topic_score_codex":0.023782508,"about_ca_topic_score_gemma":0.022919113,"teacher_disagreement_score":0.023782508,"about_ca_system_score_codex":0.00070472556,"about_ca_system_score_gemma":0.0006680691,"threshold_uncertainty_score":0.04728818},"labels":[],"label_agreement":null},{"id":"W2803000399","doi":"10.1016/j.tbs.2018.04.004","title":"Children’s life satisfaction and travel satisfaction: Evidence from Canada, Japan, and Sweden","year":2018,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":53,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université Laval","funders":"VINNOVA","keywords":"Life satisfaction; Destinations; Psychology; Path analysis (statistics); Travel behavior; Structural equation modeling; Demography; Social psychology; Geography; Tourism; Transport engineering; Engineering; Sociology; Mathematics","score_opus":0.02807073786689964,"score_gpt":0.28342027811907333,"score_spread":0.2553495402521737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803000399","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98870367,0.006238241,0.000050956456,0.00031565668,0.00002277801,0.000024418645,0.0021616141,0.0000028057443,0.0024799283],"genre_scores_gemma":[0.98868984,0.0079160975,0.00015162343,0.00019097519,0.000017729355,0.000037461992,0.002380791,0.000007231652,0.000608435],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99823976,0.00026949873,0.0001858232,0.00021042574,0.00059833744,0.0004960837],"domain_scores_gemma":[0.9935134,0.000927151,0.001561528,0.00014909991,0.002776717,0.001072085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017128468,0.00065443927,0.0011759738,0.0032106573,0.0022777098,0.002303928,0.000950499,0.0006389338,0.00276369],"category_scores_gemma":[0.0048574796,0.0005139641,0.0015104567,0.012788514,0.0018214128,0.0007115795,0.0013111932,0.0011902807,0.00019222879],"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":[0.00016037111,0.00008008487,0.9877439,0.0003506444,0.00039964958,0.00022919387,0.0031864499,0.000073504736,0.000046020858,0.00015631304,0.0009504367,0.006623324],"study_design_scores_gemma":[0.000013891097,0.00004424246,0.99297994,0.0002401956,0.00032315103,0.00006608719,0.0049743466,0.00003608131,0.000037804348,0.000019613104,0.0012504696,0.000014147902],"about_ca_topic_score_codex":0.9641538,"about_ca_topic_score_gemma":0.98072344,"teacher_disagreement_score":0.035846174,"about_ca_system_score_codex":0.009718053,"about_ca_system_score_gemma":0.016694985,"threshold_uncertainty_score":0.07211453},"labels":[],"label_agreement":null},{"id":"W2806716314","doi":"10.1016/j.tbs.2018.05.005","title":"Appearance and behaviour: Are cyclist physical attributes reflective of their preferences and habits?","year":2018,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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 British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Typology; Casual; Sample (material); Cycling; Psychology; Cluster (spacecraft); Work (physics); Clothing; Causality (physics); Transport engineering; Social psychology; Econometrics; Engineering; Computer science; Mathematics; Geography","score_opus":0.03772171409353899,"score_gpt":0.3175703885948787,"score_spread":0.2798486745013397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806716314","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969078,0.00020062407,0.00011586486,0.00025962087,0.000011758652,0.0000079832835,0.00007794772,0.0000025511195,0.002415923],"genre_scores_gemma":[0.99948704,0.00008009159,0.000057121415,0.000041318577,0.000010116094,0.000004206881,0.000048149886,0.0000019232405,0.00026996518],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995484,0.00016246503,0.000028890892,0.00010248368,0.00007419572,0.000083554725],"domain_scores_gemma":[0.9980616,0.00040033326,0.0007294425,0.00016559339,0.00025263804,0.00039045358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083132257,0.00020262516,0.0002736366,0.00085629104,0.0005373988,0.0015976044,0.000384884,0.0010999107,0.003968864],"category_scores_gemma":[0.0039317044,0.00024831982,0.00037320226,0.000959416,0.0008658552,0.0008504153,0.00046502266,0.0006482148,0.0004987619],"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":[0.000096638374,0.00009059153,0.9943673,0.000021133374,0.00008116175,0.000060979764,0.0009087115,0.000040300627,0.00030446527,0.00009192412,0.000109155815,0.0038276757],"study_design_scores_gemma":[0.0000013671059,0.000037677608,0.9986094,0.000006493641,0.000012171259,0.000054519354,0.0009809375,0.00007037313,0.000022463768,0.00006583311,0.00013537145,0.0000034566067],"about_ca_topic_score_codex":0.016187282,"about_ca_topic_score_gemma":0.025562111,"teacher_disagreement_score":0.016187282,"about_ca_system_score_codex":0.00037852765,"about_ca_system_score_gemma":0.00036029622,"threshold_uncertainty_score":0.03218609},"labels":[],"label_agreement":null},{"id":"W2896425003","doi":"10.1016/j.tbs.2018.09.008","title":"Estimating a Toronto pedestrian route choice model using smartphone GPS data","year":2018,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":76,"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":"Pedestrian; Global Positioning System; Transport engineering; Mixed logit; Revealed preference; Computer science; Discrete choice; Logit; Travel behavior; Geography; Logistic regression; Engineering; Mathematics; Econometrics; Telecommunications; Machine learning","score_opus":0.11669616401461808,"score_gpt":0.38065705715602144,"score_spread":0.26396089314140336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896425003","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9560338,0.00036041712,0.03736899,0.0003845782,0.00004455375,0.000041428822,0.0034912494,0.0003349198,0.001940113],"genre_scores_gemma":[0.9884135,0.00015060238,0.0066173235,0.000017779133,0.000017353721,0.000029350767,0.0021591198,0.000014047295,0.0025810455],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980587,0.000039902563,0.000007728651,0.000078678124,0.00002457367,0.000043264656],"domain_scores_gemma":[0.9995596,0.00023695575,0.00004086654,0.000036740745,0.00008304787,0.000042766995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039431805,0.0006841534,0.0005468034,0.00084496394,0.0006038262,0.000897344,0.0009485372,0.00094833487,0.002943619],"category_scores_gemma":[0.0014986584,0.00084229716,0.0009733365,0.0014161896,0.00039273564,0.00065243896,0.00047928307,0.0007511109,0.0006524408],"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":[0.00018828042,0.00008520004,0.036284234,0.00003938342,0.00010772544,0.0001281892,0.00011238868,0.94597465,0.00072649476,0.0014946058,0.0019488224,0.012909996],"study_design_scores_gemma":[0.000012015979,0.00002324605,0.008255923,0.0000050909825,0.000022374683,0.000014287263,0.00003757385,0.99095285,0.00009847396,0.00031047544,0.0002582163,0.000009387428],"about_ca_topic_score_codex":0.61550707,"about_ca_topic_score_gemma":0.6172949,"teacher_disagreement_score":0.38449293,"about_ca_system_score_codex":0.0033608899,"about_ca_system_score_gemma":0.0026926128,"threshold_uncertainty_score":0.77351457},"labels":[],"label_agreement":null},{"id":"W2941663802","doi":"10.1016/j.tbs.2019.04.008","title":"Voices from the survey margins: Investigating unsolicited comments written in children’s activity-travel diaries","year":2019,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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 British Columbia; University of Toronto","funders":"Canadian Institutes of Health Research; Heart and Stroke Foundation of Canada","keywords":"Psychology; Criminology","score_opus":0.028982517886562635,"score_gpt":0.2907299884550985,"score_spread":0.26174747056853587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2941663802","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9743791,0.0007726176,0.0064234445,0.006632478,0.0003237974,0.0004521874,0.0008295054,0.00011783443,0.010069067],"genre_scores_gemma":[0.98692584,0.000721061,0.00446267,0.0019321749,0.00013767245,0.0008468284,0.00028256094,0.00019648354,0.0044947765],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9597639,0.029974388,0.002066273,0.0015785146,0.0045663095,0.0020505884],"domain_scores_gemma":[0.83845204,0.124805465,0.015891047,0.004911603,0.013238841,0.0027009798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.031218743,0.00080368563,0.000768621,0.0025201412,0.0039979783,0.0038781236,0.0012353831,0.0019160167,0.0027309798],"category_scores_gemma":[0.110354386,0.0007477422,0.00038307114,0.0018753847,0.0037508763,0.003331738,0.0052361856,0.0028908097,0.0009859937],"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":[0.00008200457,0.000023790451,0.008912199,0.00031993914,0.000008643877,0.0008329584,0.9739187,0.00003229752,0.0019590687,0.00086617225,0.0019303939,0.011113868],"study_design_scores_gemma":[0.000008132719,0.00008092152,0.01182968,0.000507466,0.000009664715,0.000434134,0.95221287,0.00018339526,0.0017660706,0.00042661175,0.032503422,0.00003753247],"about_ca_topic_score_codex":0.0031066316,"about_ca_topic_score_gemma":0.0050591244,"teacher_disagreement_score":0.031218743,"about_ca_system_score_codex":0.0029507014,"about_ca_system_score_gemma":0.0023298373,"threshold_uncertainty_score":0.16510242},"labels":[],"label_agreement":null},{"id":"W2951094178","doi":"10.1016/j.tbs.2019.05.009","title":"Generating walkability from pedestrians’ perspectives using a qualitative GIS method","year":2019,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":26,"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":"Social Sciences and Humanities Research Council of Canada","keywords":"Walkability; Pedestrian; Geospatial analysis; Built environment; Geographic information system; Computer science; Transport engineering; Data science; Geography; Cartography; Engineering; Civil engineering","score_opus":0.06783613473522539,"score_gpt":0.4064497524000661,"score_spread":0.3386136176648407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951094178","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5434968,0.00011890944,0.42325956,0.00047804476,0.00006540827,0.003264691,0.011482047,0.000554819,0.017279677],"genre_scores_gemma":[0.8008175,0.000094715375,0.19085291,0.000048971662,0.000007845401,0.0038279498,0.002571702,0.00008174754,0.0016966801],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.99683964,0.0021408154,0.00016538672,0.00031399075,0.0004005148,0.0001396405],"domain_scores_gemma":[0.98617744,0.011436432,0.00047253649,0.00060648075,0.0011553161,0.00015183036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004086983,0.0006460232,0.00045467724,0.004400884,0.0008283246,0.0014025203,0.0008344707,0.000529818,0.0077656484],"category_scores_gemma":[0.014561858,0.00039663227,0.00088502746,0.0041108895,0.0008694557,0.0013396082,0.0019308187,0.000514265,0.00054442417],"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":[0.0013554958,0.00085006404,0.07585953,0.0076125776,0.00037618165,0.0026856882,0.4130329,0.03190272,0.024913095,0.066002816,0.0090648765,0.36634406],"study_design_scores_gemma":[0.0005532004,0.0010838511,0.07625007,0.0025551068,0.0005397775,0.0010216519,0.56387854,0.16288503,0.031073289,0.07841346,0.08138562,0.0003604273],"about_ca_topic_score_codex":0.0054799295,"about_ca_topic_score_gemma":0.008728287,"teacher_disagreement_score":0.0077656484,"about_ca_system_score_codex":0.001579303,"about_ca_system_score_gemma":0.0018447576,"threshold_uncertainty_score":0.025978684},"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":"W3114207716","doi":"10.1016/j.tbs.2020.12.004","title":"Who are the potential users of shared e-scooters? An examination of socio-demographic, attitudinal and environmental factors","year":2020,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":117,"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","keywords":"TRIPS architecture; Preference; Walkability; Logistic regression; Built environment; Transport engineering; Business; Ordered logit; Environmental health; Travel behavior; Psychology; Applied psychology; Engineering; Computer science; Economics; Medicine; Civil engineering","score_opus":0.031132772831873972,"score_gpt":0.2627787017556568,"score_spread":0.23164592892378286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3114207716","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99782795,0.00013888322,0.00005673194,0.00028165174,0.0000049342216,0.000015885615,0.00012226666,0.0000013225941,0.0015503934],"genre_scores_gemma":[0.9992262,0.00015475356,0.00006440564,0.00005086846,0.00000591429,0.000009477978,0.000057516485,0.000001435986,0.00042932856],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99826956,0.0006574274,0.00019115905,0.00014245593,0.00036686612,0.0003725299],"domain_scores_gemma":[0.99402714,0.0019247098,0.001923929,0.00016386218,0.0008106105,0.0011497473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015849513,0.00021351996,0.00031777285,0.0012314556,0.0014443664,0.002307123,0.0006382537,0.0010549835,0.0041194726],"category_scores_gemma":[0.0071132677,0.00038522226,0.0005106844,0.0015735592,0.0007502714,0.0029907026,0.0011677103,0.0012678734,0.00093986775],"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":[0.000049117374,0.00022553347,0.9886658,0.00002187141,0.00003363278,0.00024180475,0.006319397,0.000032708278,0.00010386424,0.00013951132,0.00016684903,0.0039998502],"study_design_scores_gemma":[0.0000045607894,0.00017457493,0.9170426,0.00004632627,0.000052582374,0.000722711,0.080044776,0.00055187347,0.00008715218,0.00016396359,0.0010875104,0.000021338179],"about_ca_topic_score_codex":0.013936761,"about_ca_topic_score_gemma":0.02555414,"teacher_disagreement_score":0.013936761,"about_ca_system_score_codex":0.00036450283,"about_ca_system_score_gemma":0.00075708475,"threshold_uncertainty_score":0.027711272},"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":"W4292170784","doi":"10.1016/j.tbs.2022.08.001","title":"High-Speed railways and the spread of Covid-19","year":2022,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"COVID-19 epidemiological studies","field":"Mathematics","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":"University of Victoria","funders":"National Natural Science Foundation of China","keywords":"Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Virology; Pandemic; Coronavirus Infections; Poison control; Betacoronavirus; Medical emergency; Business; Medicine; Outbreak; Internal medicine; Infectious disease (medical specialty)","score_opus":0.17164311717022268,"score_gpt":0.38585623705234934,"score_spread":0.21421311988212666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292170784","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9855215,0.003663528,0.00044221274,0.0014401992,0.00005187036,0.000023812707,0.0012329577,0.0000066562957,0.0076172985],"genre_scores_gemma":[0.9982913,0.0008396443,0.00007276623,0.000036009562,0.000024303257,0.000006671278,0.00029173298,0.000002095658,0.00043549662],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982487,0.0009876677,0.00012485999,0.00013006781,0.0001913024,0.00031743912],"domain_scores_gemma":[0.9936854,0.0014580139,0.002797005,0.00057249644,0.00071095,0.0007760516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021467102,0.00026479343,0.00022033205,0.0024205442,0.0007864985,0.0014280071,0.00060694537,0.0007746171,0.0050394884],"category_scores_gemma":[0.010523584,0.00022064759,0.0004115114,0.0045830305,0.0007132228,0.0008243596,0.0015005269,0.0012052441,0.00035105736],"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":[0.00018714086,0.00009862222,0.99057263,0.000044340573,0.00013640741,0.000065728964,0.0009818337,0.00021658759,0.000079785255,0.002237408,0.00076394767,0.004615488],"study_design_scores_gemma":[0.000008974093,0.00011708248,0.99332905,0.000085906104,0.00005673327,0.0001490178,0.003025877,0.00055837515,0.00004275278,0.0006143243,0.002000888,0.000011168398],"about_ca_topic_score_codex":0.042225387,"about_ca_topic_score_gemma":0.025118198,"teacher_disagreement_score":0.042225387,"about_ca_system_score_codex":0.00087056693,"about_ca_system_score_gemma":0.0009787099,"threshold_uncertainty_score":0.08395922},"labels":[],"label_agreement":null},{"id":"W4311401368","doi":"10.1016/j.tbs.2022.11.006","title":"Modeling of machine learning with SHAP approach for electric vehicle charging station choice behavior prediction","year":2022,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":140,"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":"Electric vehicle; Automotive engineering; Engineering; Computer science; Physics","score_opus":0.010389675351507274,"score_gpt":0.20641257936512666,"score_spread":0.19602290401361938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311401368","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17220269,0.0006386718,0.81661403,0.001038326,0.00012836042,0.00010574886,0.00048722915,0.00031019075,0.008474735],"genre_scores_gemma":[0.97258985,0.00019769414,0.01850834,0.00009680028,0.000055091365,0.000104487626,0.00023064498,0.000029548075,0.008187543],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948347,0.00020942907,0.000022827562,0.00012833324,0.000061896666,0.00009400906],"domain_scores_gemma":[0.99665004,0.0025918693,0.00019468214,0.00009186403,0.00036133375,0.00011023599],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001876323,0.0006835473,0.0014103472,0.00091511226,0.0005929171,0.0012395103,0.0018419779,0.0016385395,0.005241581],"category_scores_gemma":[0.0052000848,0.00074920326,0.0009810289,0.0007898697,0.0008542121,0.0013313219,0.0012147363,0.0015581709,0.0004255634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017546921,0.00002955343,0.00095545006,0.000014983164,0.000029074748,0.00002928929,0.000016791922,0.98899186,0.00007427429,0.006200176,0.00024198095,0.0033990708],"study_design_scores_gemma":[0.0000011085083,0.0000032774335,0.00007176116,0.0000012419109,0.0000026704827,0.0000019484226,0.0000018861273,0.9986759,0.0000152675,0.0011890501,0.00003463174,0.0000011464284],"about_ca_topic_score_codex":0.027459936,"about_ca_topic_score_gemma":0.019047776,"teacher_disagreement_score":0.027459936,"about_ca_system_score_codex":0.0015358536,"about_ca_system_score_gemma":0.00135215,"threshold_uncertainty_score":0.05460024},"labels":[],"label_agreement":null},{"id":"W4319231614","doi":"10.1016/j.tbs.2023.01.005","title":"Gender differentials in travel behavior among TOD neighborhoods: Contributions of built environment and residential self-selection","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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 Manitoba","funders":"Ministry of Education, India","keywords":"TRIPS architecture; Built environment; Travel behavior; Typology; Propensity score matching; Public transport; Transport engineering; Geography; Selection (genetic algorithm); Transit-oriented development; Private transport; Matching (statistics); Demographic economics; Business; Psychology; Engineering; Economics; Computer science; Statistics; Mathematics; Civil engineering","score_opus":0.02539515687838148,"score_gpt":0.29985800170652477,"score_spread":0.2744628448281433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319231614","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990778,0.000065050655,0.00003539952,0.00002251807,0.000003780889,0.0000021165404,0.000077364726,7.741853e-7,0.0007150522],"genre_scores_gemma":[0.9996099,0.00001827443,0.000022558055,0.000006941856,9.4471517e-7,0.0000016251964,0.000053779913,0.0000014775527,0.00028440135],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999566,0.00012059975,0.000029613177,0.00007688527,0.000055175897,0.00015160927],"domain_scores_gemma":[0.9991698,0.00020220097,0.00020977047,0.00009627173,0.000112642185,0.0002093318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005950312,0.0001733723,0.00033368668,0.00055584667,0.0007498629,0.0008681133,0.00031319365,0.00033746765,0.003909912],"category_scores_gemma":[0.0023177809,0.00018155343,0.00047638986,0.0005931694,0.0004241562,0.00045931863,0.00068964605,0.00026109148,0.0002551229],"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":[0.00016418187,0.00005713373,0.9962202,0.0000042488946,0.000032181644,0.000080411344,0.0013746078,0.000018063616,0.0003215172,0.00015000654,0.00006418378,0.0015133251],"study_design_scores_gemma":[0.000001844024,0.000036041885,0.99569255,0.000004688867,0.000010731942,0.00006454511,0.0038508729,0.000063682266,0.000057345995,0.000081612816,0.00013364012,0.0000025236905],"about_ca_topic_score_codex":0.030749269,"about_ca_topic_score_gemma":0.07143335,"teacher_disagreement_score":0.030749269,"about_ca_system_score_codex":0.0004775169,"about_ca_system_score_gemma":0.00052180386,"threshold_uncertainty_score":0.061140537},"labels":[],"label_agreement":null},{"id":"W4319746652","doi":"10.1016/j.tbs.2023.02.001","title":"Modeling daily in-home activities using machine learning techniques","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Duration (music); Machine learning; Artificial intelligence; Support vector machine; Computer science; Activities of daily living; Artificial neural network; TRIPS architecture; Regression analysis; Engineering; Psychology; Transport engineering","score_opus":0.049383880740946726,"score_gpt":0.3265035160855221,"score_spread":0.27711963534457534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319746652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.66086674,0.00046004006,0.33156627,0.00033797233,0.00012006621,0.00008874454,0.0024454724,0.00085599156,0.0032587696],"genre_scores_gemma":[0.9724327,0.00018234257,0.0231507,0.000026489462,0.000035195633,0.000075420736,0.0012662009,0.000038550395,0.002792338],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997552,0.00007291353,0.000018206334,0.00008219118,0.00002883386,0.000042603155],"domain_scores_gemma":[0.9991027,0.000622623,0.00008021341,0.0000645234,0.00008799089,0.000041968116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045445605,0.0006857932,0.00068723096,0.0009628655,0.00031733114,0.0009414918,0.0009486069,0.00085252814,0.0020546468],"category_scores_gemma":[0.00184556,0.00048485858,0.0008897926,0.0012493351,0.00025357283,0.0009212567,0.00039018577,0.000984513,0.00076486176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000071764494,0.00032258427,0.024046725,0.0000383782,0.00013104339,0.00006911865,0.00007008717,0.9382611,0.0004630207,0.0008486183,0.0006615446,0.03501606],"study_design_scores_gemma":[0.0000012359436,0.000006744263,0.0017270732,0.0000021946637,0.0000050629196,0.0000063817297,0.000009887242,0.9975998,0.000048832087,0.0005110718,0.00007949052,0.0000021464796],"about_ca_topic_score_codex":0.033395465,"about_ca_topic_score_gemma":0.039110515,"teacher_disagreement_score":0.033395465,"about_ca_system_score_codex":0.0006211874,"about_ca_system_score_gemma":0.00056124787,"threshold_uncertainty_score":0.0664022},"labels":[],"label_agreement":null},{"id":"W4321768395","doi":"10.1016/j.tbs.2023.100575","title":"Exploring travel patterns of people with disabilities: A multilevel analysis of accessible taxi trips in Toronto, Canada","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; The Scarborough Hospital; Environment and Climate Change Canada; University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"TRIPS architecture; Travel behavior; Transport engineering; Suicide prevention; Human factors and ergonomics; Occupational safety and health; Poison control; Geography; Gerontology; Psychology; Environmental health; Engineering; Medicine","score_opus":0.08158740277579436,"score_gpt":0.31361806204243275,"score_spread":0.2320306592666384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321768395","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99006665,0.0008990648,0.00027784132,0.00033335426,0.00001503624,0.00010028984,0.0070852647,0.000013327318,0.0012091135],"genre_scores_gemma":[0.9945702,0.0007011722,0.00047981084,0.0000657249,0.000006657068,0.00007569905,0.003028661,0.000011710055,0.0010602454],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981127,0.0002071716,0.00017181192,0.00030264733,0.00038827234,0.00081745954],"domain_scores_gemma":[0.99719715,0.00018428925,0.00040712298,0.00016634988,0.0013663071,0.0006786522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009778575,0.00073669106,0.0012329316,0.004136305,0.0058141025,0.0031152274,0.002073417,0.00088605774,0.0031768656],"category_scores_gemma":[0.0030199944,0.00077784166,0.0026266673,0.016435368,0.0011849948,0.0011055829,0.003718038,0.0015900945,0.00038437598],"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":[0.00007657924,0.00005418941,0.98813653,0.00011137964,0.0004263708,0.00015046401,0.0053321337,0.0005306052,0.00016932489,0.00037159916,0.0013425356,0.0032984337],"study_design_scores_gemma":[0.0000043772357,0.000022506298,0.9883366,0.00011544117,0.00009742765,0.00003911398,0.009638561,0.0006478953,0.000032608135,0.000043648615,0.0009969809,0.000024854015],"about_ca_topic_score_codex":0.99779105,"about_ca_topic_score_gemma":0.9989303,"teacher_disagreement_score":0.044373337,"about_ca_system_score_codex":0.044373337,"about_ca_system_score_gemma":0.05089089,"threshold_uncertainty_score":0.32195258},"labels":[],"label_agreement":null},{"id":"W4323108448","doi":"10.1016/j.tbs.2023.100577","title":"A mixed-methods investigation of older adults’ public transit use and travel satisfaction","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":21,"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","funders":"McMaster Institute for Research on Aging, McMaster University; McMaster University","keywords":"Public transport; Thematic analysis; Descriptive statistics; Travel behavior; Gerontology; Service (business); Population; Transit (satellite); Psychology; Medicine; Business; Transport engineering; Environmental health; Engineering; Qualitative research; Marketing; Sociology","score_opus":0.06013086203129311,"score_gpt":0.3276904638901967,"score_spread":0.2675596018589036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323108448","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99839824,0.00019820307,0.00030882758,0.000018167688,0.000010216841,0.00048666808,0.00028186594,0.0000045630786,0.00029321332],"genre_scores_gemma":[0.99292,0.00026916122,0.002277807,0.00015566363,0.000033233282,0.0026925842,0.00051426643,0.0000040012415,0.0011331867],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9970952,0.0015558015,0.00043523416,0.0003486472,0.00034805224,0.00021706584],"domain_scores_gemma":[0.995333,0.0018605865,0.0011237108,0.00057827955,0.0007901227,0.00031418752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004734724,0.0008403383,0.0011437883,0.0016519726,0.0017556488,0.0013377507,0.00088675914,0.0011810496,0.0025752615],"category_scores_gemma":[0.00642101,0.0011020467,0.002000484,0.0020154305,0.0005980765,0.0011415944,0.0009499631,0.0008303097,0.00044700853],"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":[0.0044703134,0.009080317,0.95309234,0.0007499736,0.0015758817,0.00018014727,0.007333638,0.0002103028,0.0009728282,0.0002350222,0.0004722042,0.021626953],"study_design_scores_gemma":[0.0011456059,0.019707683,0.962286,0.00018110558,0.0011953671,0.000343698,0.011369775,0.0013166774,0.0005493876,0.00021621615,0.0016140009,0.00007445548],"about_ca_topic_score_codex":0.011988821,"about_ca_topic_score_gemma":0.019938346,"teacher_disagreement_score":0.011988821,"about_ca_system_score_codex":0.0010538348,"about_ca_system_score_gemma":0.001293803,"threshold_uncertainty_score":0.025039911},"labels":[],"label_agreement":null},{"id":"W4323315316","doi":"10.1016/j.tbs.2023.100574","title":"Nowhere to go – Effects on elderly's travel during Covid-19","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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":"Polytechnique Montréal","funders":"Energimyndigheten","keywords":"Thematic analysis; Pandemic; Feeling; Coronavirus disease 2019 (COVID-19); Psychology; Mental health; Qualitative research; Focus group; Gerontology; 2019-20 coronavirus outbreak; Aging in place; Sociology; Social psychology; Medicine; Disease; Psychiatry; Social science","score_opus":0.03189276242810207,"score_gpt":0.3291834554614452,"score_spread":0.2972906930333431,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323315316","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9951827,0.0005038321,0.000045810208,0.0006995409,0.000023228107,0.000010903752,0.00008763362,0.0000043037476,0.0034420115],"genre_scores_gemma":[0.99896896,0.0003361735,0.000035536574,0.00013832928,0.000007263685,0.000009055963,0.000031677766,0.000002275183,0.00047074698],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.99863535,0.0007191887,0.00009708733,0.00006780148,0.00010631004,0.00037413606],"domain_scores_gemma":[0.9978794,0.00072440715,0.00038597448,0.000072034425,0.00036782993,0.00057032396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016869484,0.00018783359,0.00030837892,0.00047351024,0.0024105085,0.0017107307,0.00041326333,0.00067902997,0.0024817253],"category_scores_gemma":[0.005738408,0.00012740516,0.0005161291,0.00051666785,0.0011675991,0.0012773265,0.002824937,0.00070085604,0.00021397976],"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":[0.0006646745,0.000324146,0.26224166,0.00081430434,0.00014560448,0.0025964791,0.68891484,0.00024196411,0.0009204199,0.0013888432,0.004381885,0.037365124],"study_design_scores_gemma":[0.000008117977,0.00026060268,0.196857,0.00025283132,0.00005248215,0.000320447,0.793108,0.000073092946,0.00013609588,0.00019472094,0.008710835,0.000025830486],"about_ca_topic_score_codex":0.03809104,"about_ca_topic_score_gemma":0.066582866,"teacher_disagreement_score":0.03809104,"about_ca_system_score_codex":0.0014508179,"about_ca_system_score_gemma":0.0014754505,"threshold_uncertainty_score":0.07573861},"labels":[],"label_agreement":null},{"id":"W4366494935","doi":"10.1016/j.tbs.2023.100588","title":"Social equity analysis of public transit accessibility to healthcare might be erroneous when travel time uncertainty impacts are overlooked","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Social Sciences and Humanities Research Council of Canada; Canadian Institutes of Health Research; Western University","keywords":"Equity (law); Business; Health care; Public transport; Transport engineering; Travel time; Social equality; Transit (satellite); Public health; Poison control; Public economics; Actuarial science; Economics; Environmental health; Engineering; Medicine; Political science; Economic growth; Nursing","score_opus":0.0914066952090018,"score_gpt":0.3797493099292855,"score_spread":0.2883426147202837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366494935","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44677958,0.006480023,0.25968298,0.06704116,0.0026281977,0.00040712298,0.0053078444,0.00026599833,0.2114071],"genre_scores_gemma":[0.9913367,0.0003728901,0.004276169,0.0010882112,0.0003186382,0.00004394337,0.00021837096,0.000022836142,0.002322279],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9938693,0.0030619209,0.00037563033,0.0006580291,0.0015001917,0.00053494377],"domain_scores_gemma":[0.97454154,0.017920509,0.0024508683,0.0015386388,0.0031094092,0.00043907363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00951022,0.0005814498,0.001078548,0.0029278328,0.0008555411,0.0031098065,0.001655301,0.00083535095,0.005738237],"category_scores_gemma":[0.044017427,0.00024651474,0.0010713271,0.0023800079,0.0022560367,0.0041038366,0.0024437392,0.002369147,0.00028909664],"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":[0.00029141502,0.00017761019,0.11231833,0.00086425967,0.0013029401,0.00056218123,0.0024325973,0.02619592,0.00047353323,0.715208,0.017493926,0.12267926],"study_design_scores_gemma":[0.000028298264,0.00016287324,0.06396182,0.0007069057,0.0004999082,0.00031096642,0.0043567917,0.061118785,0.0010591306,0.84280807,0.024940118,0.000046238998],"about_ca_topic_score_codex":0.023259066,"about_ca_topic_score_gemma":0.016875178,"teacher_disagreement_score":0.023259066,"about_ca_system_score_codex":0.0021458757,"about_ca_system_score_gemma":0.0021843985,"threshold_uncertainty_score":0.050295472},"labels":[],"label_agreement":null},{"id":"W4366765055","doi":"10.1016/j.tbs.2023.100594","title":"Does the squeaky wheel get the complaint? Linking bus performance, sociodemographic characteristics, and customer comments","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":2,"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 Saskatchewan; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Complaint; Service (business); Customer satisfaction; Public transport; Level of service; Business; Transport engineering; Service quality; Marketing; Engineering","score_opus":0.020096562722563552,"score_gpt":0.2718789517036039,"score_spread":0.25178238898104033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366765055","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99657357,0.0000975218,0.00008123236,0.000666459,0.000023468752,0.000013239022,0.0006022729,0.000005623655,0.0019365499],"genre_scores_gemma":[0.99876523,0.00007469619,0.00007157081,0.000115636896,0.000021946484,0.000011072925,0.00031020766,0.0000047165245,0.0006249456],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983613,0.00072052283,0.00017132482,0.000117321986,0.00033969324,0.00028985398],"domain_scores_gemma":[0.98101074,0.008183178,0.0062320647,0.00060552335,0.002431338,0.0015372348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024555847,0.00023897857,0.00033648845,0.0012309713,0.00071622245,0.0021106356,0.00058588246,0.0013057404,0.00848741],"category_scores_gemma":[0.016440433,0.00023482574,0.0006428776,0.0018402982,0.00051336794,0.0010891665,0.000756346,0.001406513,0.0013366994],"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":[0.00007931727,0.00010736457,0.9964616,0.000018623638,0.00006375613,0.000049800572,0.00066622486,0.000053593867,0.000029470428,0.000028907312,0.0005951791,0.0018461507],"study_design_scores_gemma":[0.000004412977,0.00009975017,0.9872995,0.000039247116,0.0000690101,0.0000998842,0.010854702,0.00056702667,0.000060933507,0.00006953849,0.0008169574,0.000019022771],"about_ca_topic_score_codex":0.01372922,"about_ca_topic_score_gemma":0.017143872,"teacher_disagreement_score":0.01372922,"about_ca_system_score_codex":0.0005172054,"about_ca_system_score_gemma":0.000773946,"threshold_uncertainty_score":0.028393209},"labels":[],"label_agreement":null},{"id":"W4376120074","doi":"10.1016/j.tbs.2023.100590","title":"Microsimulation of activity generation, activity scheduling and shared travel choices within an activity-based travel demand modelling system","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Transportation Planning and Optimization","field":"Social Sciences","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":"Dalhousie University","funders":"Division of Human Resource Management; Natural Sciences and Engineering Research Council of Canada","keywords":"Microsimulation; Travel survey; Heuristics; Travel behavior; Computer science; Scheduling (production processes); Econometrics; Markov chain Monte Carlo; Operations research; Transport engineering; Statistics; Monte Carlo method; Economics; Mathematics; Engineering; Operations management","score_opus":0.06601907584715652,"score_gpt":0.31089138950974876,"score_spread":0.24487231366259224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376120074","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5564377,0.00020807955,0.4277463,0.00049440085,0.0000619428,0.00010190373,0.0010118315,0.0003803554,0.013557508],"genre_scores_gemma":[0.9880987,0.00006296845,0.0072395387,0.000029722469,0.000009586249,0.00009377566,0.00021538464,0.000035595127,0.0042148177],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997358,0.00008897448,0.0000137980405,0.000059476337,0.000031679087,0.00007020729],"domain_scores_gemma":[0.9992698,0.00043493867,0.00009621858,0.00004014891,0.000093116054,0.00006569169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004367187,0.0005001356,0.00091162603,0.00041175017,0.00042965182,0.00086319115,0.0010697071,0.00097215024,0.003566923],"category_scores_gemma":[0.0013170808,0.000532698,0.0008506905,0.00050068967,0.00063922553,0.00066493446,0.0009373597,0.0006252111,0.00025610605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012385761,0.000010163474,0.0001915983,0.0000050335593,0.000007646942,0.000008982125,0.000011636766,0.9978562,0.00014686065,0.0013061229,0.00003258835,0.00041085223],"study_design_scores_gemma":[0.0000018573841,0.000004316921,0.00008506636,6.6379897e-7,0.0000022314362,0.0000010659684,0.0000032243624,0.9994948,0.000027882174,0.00033847408,0.000039171315,0.0000012328992],"about_ca_topic_score_codex":0.04894564,"about_ca_topic_score_gemma":0.029228723,"teacher_disagreement_score":0.04894564,"about_ca_system_score_codex":0.0012754824,"about_ca_system_score_gemma":0.001329165,"threshold_uncertainty_score":0.09732151},"labels":[],"label_agreement":null},{"id":"W4382045623","doi":"10.1016/j.tbs.2023.100624","title":"How daily activities and built environment affect health? A latent segmentation-based random parameter logit modeling approach","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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":"Simon Fraser University; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Michael Smith Health Research BC","keywords":"Random effects model; Affect (linguistics); Logit; Econometrics; Logistic regression; Segmentation; Discrete choice; Random forest; Mixed logit; Investment (military); Latent variable; Duration (music); Travel behavior; Business; Computer science; Statistics; Transport engineering; Economics; Psychology; Mathematics; Engineering; Medicine; Meta-analysis; Machine learning","score_opus":0.06363606102809782,"score_gpt":0.3037221483336487,"score_spread":0.24008608730555087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382045623","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5441295,0.0010208718,0.4394336,0.0041926997,0.00017451838,0.0005221199,0.0048703398,0.0008770027,0.0047793426],"genre_scores_gemma":[0.97203845,0.00034197362,0.017324086,0.0001888591,0.00007591337,0.0004651948,0.0017023114,0.000058192425,0.007805025],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9963642,0.0022833953,0.0001046663,0.0006524964,0.000133823,0.00046151128],"domain_scores_gemma":[0.99429435,0.004443257,0.00049129146,0.00026797905,0.0002819321,0.00022108093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042609936,0.0012254087,0.0022373984,0.0016117732,0.000758845,0.0027214861,0.003590527,0.0030479827,0.009181644],"category_scores_gemma":[0.0073808394,0.0012256346,0.0028569184,0.0023557206,0.0016690396,0.0026458672,0.0021774191,0.0021977131,0.0012487164],"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":[0.0021061758,0.002075403,0.19405688,0.00057249883,0.0029292642,0.0009401075,0.0037341989,0.5852336,0.0017135798,0.15726674,0.006310617,0.04306091],"study_design_scores_gemma":[0.00013185214,0.00025910648,0.017450757,0.00006698018,0.00049209787,0.00012099559,0.0007574018,0.9365871,0.00018961863,0.0421581,0.0017093823,0.000076594726],"about_ca_topic_score_codex":0.03161044,"about_ca_topic_score_gemma":0.024090996,"teacher_disagreement_score":0.03161044,"about_ca_system_score_codex":0.0017946861,"about_ca_system_score_gemma":0.0018400301,"threshold_uncertainty_score":0.06285286},"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":"W4386323152","doi":"10.1016/j.tbs.2023.100663","title":"Shared 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":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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":"The Scarborough Hospital; University of Toronto","funders":"Southeastern Transportation Research, Innovation, Development and Education Center; University Transportation Center, Missouri University of Science and Technology; Ford Motor Company; U.S. Department of Transportation","keywords":"Mile; Travel behavior; Last mile (transportation); Public transport; Transit (satellite); Transport engineering; Equity (law); Payment; Business; Sustainable transport; Advertising; Engineering; Marketing; Geography; Finance; Political science; Sustainability","score_opus":0.028328844267963088,"score_gpt":0.29022981955011873,"score_spread":0.2619009752821556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386323152","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93821466,0.00069848535,0.00049241266,0.011485897,0.0000486523,0.000024778334,0.00050187693,0.000024951203,0.048508286],"genre_scores_gemma":[0.9938611,0.00044263797,0.0003141861,0.0003059833,0.000011044509,0.000011898116,0.00016741896,0.000010536835,0.0048752325],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996043,0.00013845673,0.000010970574,0.00004447284,0.000050452083,0.00015138692],"domain_scores_gemma":[0.99915504,0.00014244692,0.00013312811,0.000042487292,0.00023509907,0.00029169675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045650537,0.0001233941,0.00014471907,0.0004443609,0.001328431,0.0028100768,0.00053153577,0.0005913847,0.010326173],"category_scores_gemma":[0.0020064283,0.000107834436,0.00017186692,0.0011080708,0.000550508,0.003106711,0.0009436219,0.00078228285,0.00065973186],"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":[0.0008238625,0.0020994383,0.42457396,0.00043437327,0.0001988515,0.00083255226,0.04481503,0.004237539,0.0013367125,0.061336886,0.11015236,0.34915847],"study_design_scores_gemma":[0.000112393136,0.0005524515,0.46213374,0.0006085943,0.00017789699,0.00032958342,0.35054857,0.011302062,0.00058900856,0.006669061,0.16690466,0.000072038696],"about_ca_topic_score_codex":0.16072075,"about_ca_topic_score_gemma":0.49898985,"teacher_disagreement_score":0.16072075,"about_ca_system_score_codex":0.0025790588,"about_ca_system_score_gemma":0.002532377,"threshold_uncertainty_score":0.31957054},"labels":[],"label_agreement":null},{"id":"W4386874041","doi":"10.1016/j.tbs.2023.100678","title":"Evaluating transit mode choice in the context of the COVID-19 pandemic – A stated preference approach","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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":"Carleton University; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Motor Association Foundation for Traffic Safety; University of Calgary","keywords":"Multinomial logistic regression; Pandemic; Business; Public transport; Context (archaeology); Attractiveness; Transit (satellite); Demographic economics; Geography; Transport engineering; Coronavirus disease 2019 (COVID-19); Economics; Medicine; Psychology; Computer science; Engineering","score_opus":0.26579505975361045,"score_gpt":0.42267683918230997,"score_spread":0.15688177942869952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386874041","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9741759,0.00036189787,0.02276201,0.00030858224,0.000038077844,0.0003126526,0.0003595577,0.000015243204,0.0016661866],"genre_scores_gemma":[0.9906035,0.00015730683,0.008457362,0.00004234231,0.000019350831,0.00014466513,0.0002205129,0.000006188272,0.00034866508],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.98033154,0.016956724,0.00056506135,0.00061587704,0.0009248461,0.0006058918],"domain_scores_gemma":[0.926527,0.068315804,0.0019952448,0.00065087026,0.0014836747,0.001027343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01779562,0.0010905536,0.0017545308,0.0020157075,0.0005833288,0.003606758,0.0015400948,0.0026216889,0.004590217],"category_scores_gemma":[0.041838866,0.00065696146,0.0033324235,0.0024187036,0.0011106863,0.0027101198,0.0011927078,0.00225671,0.00034171712],"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":[0.022298966,0.011170461,0.2783013,0.0031360271,0.0071492447,0.001567216,0.004550295,0.51365286,0.006915613,0.026905667,0.0020262403,0.1223261],"study_design_scores_gemma":[0.00040525556,0.009349042,0.03572953,0.00013953091,0.0008469886,0.00014101554,0.004600346,0.9346266,0.0011964324,0.01215178,0.0006305339,0.00018300842],"about_ca_topic_score_codex":0.009898676,"about_ca_topic_score_gemma":0.013323838,"teacher_disagreement_score":0.01779562,"about_ca_system_score_codex":0.002632449,"about_ca_system_score_gemma":0.0020731408,"threshold_uncertainty_score":0.09411335},"labels":[],"label_agreement":null},{"id":"W4386990787","doi":"10.1016/j.tbs.2023.100686","title":"How do young people move around in urban spaces?: Exploring trip patterns of generation-Z in urban areas by examining travel histories on Google Maps Timeline","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":33,"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":"Timeline; Metropolitan area; TRIPS architecture; Trip generation; Geography; Travel behavior; Quarter (Canadian coin); Population; Public transport; Transport engineering; Advertising; Business; Engineering; Demography; Sociology","score_opus":0.06505933765668513,"score_gpt":0.277256125531599,"score_spread":0.21219678787491386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386990787","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986572,0.00007383487,0.00004646317,0.0000895344,0.0000027805681,0.00001070832,0.00048316107,0.0000019601016,0.00063431513],"genre_scores_gemma":[0.99854666,0.00017806499,0.000102188125,0.000036559235,0.0000024063077,0.000020023295,0.00045108525,0.000003080627,0.000659925],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997365,0.00005394829,0.000029726294,0.000045841636,0.00004204752,0.00009193496],"domain_scores_gemma":[0.99919933,0.00011176954,0.00032396443,0.000038852915,0.0001267293,0.00019927508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044241664,0.0001839164,0.00019710851,0.001270706,0.00073098426,0.0019302067,0.00049553125,0.0005687477,0.0021872472],"category_scores_gemma":[0.0020401515,0.00028220296,0.00043824041,0.0020975051,0.00045495926,0.0022966005,0.00165023,0.0005587139,0.00083635683],"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":[0.000031832973,0.000032707117,0.96519065,0.00003390943,0.00002642184,0.00009417625,0.02948461,0.000028148175,0.00015089072,0.0000871139,0.00027187564,0.0045676366],"study_design_scores_gemma":[0.0000012300947,0.00004403692,0.8941215,0.00003060491,0.000014918587,0.00011663008,0.104357235,0.000088314264,0.00004857231,0.00004791888,0.0011211699,0.000007769175],"about_ca_topic_score_codex":0.06549465,"about_ca_topic_score_gemma":0.1331274,"teacher_disagreement_score":0.06549465,"about_ca_system_score_codex":0.0005345191,"about_ca_system_score_gemma":0.0006199394,"threshold_uncertainty_score":0.13022685},"labels":[],"label_agreement":null},{"id":"W4387631280","doi":"10.1016/j.tbs.2023.100690","title":"A behavioural analysis of post-pandemic modality profiles for non-commuting trips in the greater Toronto Area","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":6,"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; TRIPS architecture; Multinomial logistic regression; Descriptive statistics; Demographic economics; Paratransit; Psychological resilience; Coronavirus disease 2019 (COVID-19); Business; Public transport; Geography; Psychology; Socioeconomics; Economics; Transport engineering; Medicine; Social psychology; Engineering; Computer science","score_opus":0.0722541332858057,"score_gpt":0.34207619521171917,"score_spread":0.26982206192591346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387631280","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988927,0.00002323034,0.00004957682,0.000017525133,8.3211273e-7,0.000017901642,0.0006895869,0.0000019256047,0.00030678924],"genre_scores_gemma":[0.9985297,0.00004321681,0.00009783238,0.000009190698,0.0000014053817,0.000018945353,0.00078491453,0.0000016150905,0.000513202],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99973065,0.000065305765,0.000021057538,0.00004392218,0.000053528558,0.00008551424],"domain_scores_gemma":[0.99918777,0.00013027688,0.00018342503,0.000040904124,0.0002907634,0.00016680217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003407916,0.00023192378,0.0001740675,0.001142332,0.00089702266,0.0008227704,0.0003489725,0.00035624736,0.0019370007],"category_scores_gemma":[0.001524708,0.00015548474,0.00042034333,0.0022289061,0.0002862001,0.00034608366,0.00061944267,0.00030960116,0.00028179216],"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":[0.00014415917,0.000060636026,0.98383254,0.000043441658,0.00006654333,0.00011035888,0.00945888,0.0002994977,0.0013858933,0.00007254691,0.00040094677,0.004124501],"study_design_scores_gemma":[6.5318477e-7,0.000031313946,0.9963605,0.000004976155,0.0000066004627,0.000019298495,0.0031858936,0.00017634711,0.00004042063,0.0000040578893,0.0001663167,0.000003714903],"about_ca_topic_score_codex":0.77262497,"about_ca_topic_score_gemma":0.86554986,"teacher_disagreement_score":0.22737503,"about_ca_system_score_codex":0.0032082896,"about_ca_system_score_gemma":0.0021600924,"threshold_uncertainty_score":0.45742816},"labels":[],"label_agreement":null},{"id":"W4388176904","doi":"10.1016/j.tbs.2023.100703","title":"Geographic identity and perceptions of walkable space","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":8,"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":"Mitacs","keywords":"Walkability; Pedestrian; Built environment; Perception; Space (punctuation); Poison control; Urban design; Transport engineering; Geography; Psychology; Computer science; Engineering; Urban planning; Civil engineering; Environmental health; Medicine","score_opus":0.026716016568760183,"score_gpt":0.3200925253142019,"score_spread":0.29337650874544174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388176904","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9946655,0.000048153903,0.00009755281,0.00014596253,0.0000058946216,0.000005159264,0.000019166688,0.000001489993,0.005011207],"genre_scores_gemma":[0.9995202,0.000026799951,0.000039745682,0.000014392997,0.0000023566433,0.000002142019,0.000017466227,0.0000011569284,0.0003758389],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992719,0.0002808389,0.000055312743,0.000058069618,0.00014448311,0.00018939242],"domain_scores_gemma":[0.9952864,0.0009261189,0.0016702366,0.00018983608,0.0006351782,0.0012923806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094653486,0.00018340383,0.00020197185,0.0012442186,0.001534343,0.0028416016,0.00035257405,0.0007704543,0.0051550358],"category_scores_gemma":[0.005076375,0.00017589661,0.0003522391,0.00084814173,0.0018087529,0.0015070187,0.0017515793,0.0009653686,0.000286891],"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":[0.0003003615,0.00065533165,0.8797135,0.000070604416,0.00009816831,0.0005467666,0.10009736,0.000415969,0.001034986,0.0063148765,0.00043067863,0.010321404],"study_design_scores_gemma":[0.000015844218,0.00016843989,0.7915163,0.000055235443,0.000030629257,0.00026587406,0.20248587,0.00073861436,0.00017583209,0.0019783962,0.0025365306,0.000032426928],"about_ca_topic_score_codex":0.02944406,"about_ca_topic_score_gemma":0.03880812,"teacher_disagreement_score":0.02944406,"about_ca_system_score_codex":0.0009109714,"about_ca_system_score_gemma":0.0007057475,"threshold_uncertainty_score":0.05854535},"labels":[],"label_agreement":null},{"id":"W4388403869","doi":"10.1016/j.tbs.2023.100704","title":"Disabled people’s accessible taxi experiences in Toronto, Canada","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Centre for Addiction and Mental Health; Holland Bloorview Kids Rehabilitation Hospital; Toronto Rehabilitation Institute; University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Paratransit; TRIPS architecture; Thematic analysis; Disabled people; Public relations; Service (business); Complaint; Business; Perspective (graphical); Psychology; Sociology; Applied psychology; Marketing; Qualitative research; Political science; Transport engineering; Engineering; Computer science","score_opus":0.022361503295037947,"score_gpt":0.3077263689366032,"score_spread":0.28536486564156527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388403869","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97869885,0.0014995583,0.000038813247,0.0027593395,0.000070823604,0.000041850297,0.00082667335,0.000006830968,0.01605724],"genre_scores_gemma":[0.99128485,0.0013361117,0.000057476955,0.00028604906,0.0000113275155,0.000023676166,0.0002447816,0.000006977828,0.006748683],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9988607,0.00013450472,0.00004380468,0.00005568049,0.00018797579,0.00071731163],"domain_scores_gemma":[0.99748814,0.00016388728,0.0002170605,0.00003386249,0.00063998264,0.001457142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047576812,0.00029520132,0.0005407419,0.0013272808,0.017881803,0.004263586,0.0010453475,0.0006685083,0.0065713115],"category_scores_gemma":[0.0014862325,0.00036951038,0.00045335636,0.004283615,0.002456919,0.0012637958,0.0037470898,0.00199991,0.00034821252],"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":[0.00023275016,0.00021696003,0.24199973,0.00044466776,0.000085112966,0.0030685612,0.70754266,0.0003319694,0.00060333614,0.0046805195,0.018192133,0.022601614],"study_design_scores_gemma":[0.000009560931,0.00004232569,0.27067357,0.00027083314,0.00002474776,0.00023717452,0.7090668,0.00009453992,0.00007092087,0.000116383046,0.019350488,0.000042599193],"about_ca_topic_score_codex":0.9958662,"about_ca_topic_score_gemma":0.99915314,"teacher_disagreement_score":0.062998526,"about_ca_system_score_codex":0.062998526,"about_ca_system_score_gemma":0.06339698,"threshold_uncertainty_score":0.4570884},"labels":[],"label_agreement":null},{"id":"W4390227943","doi":"10.1016/j.tbs.2023.100736","title":"Are all bike lanes built equal? Using bike share GPS data to quantify cycling infrastructure investments’ ridership effects in Hamilton, Ontario","year":2023,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":7,"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","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cycling; Transport engineering; Psychological intervention; Matching (statistics); Poison control; Transportation infrastructure; Business; Environmental science; Computer science; Geography; Engineering; Statistics; Mathematics; Environmental health; Psychology","score_opus":0.21678924442676412,"score_gpt":0.3862479996084281,"score_spread":0.16945875518166398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390227943","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996323,0.00016244844,0.00014317209,0.00019457686,0.0000038581115,0.000019042283,0.001493868,0.0000056586955,0.0016544997],"genre_scores_gemma":[0.99784005,0.000121928606,0.00015112854,0.000027363947,0.0000020926564,0.0000120958,0.00067700504,0.0000036560325,0.0011647098],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990319,0.00015943409,0.00005515725,0.00017395313,0.00024444613,0.00033510843],"domain_scores_gemma":[0.9982033,0.00031213413,0.0003965883,0.00010938761,0.00066121534,0.000317359],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073966174,0.00025515916,0.00039918514,0.0007944408,0.0013253399,0.0014594558,0.00094077806,0.0003594096,0.0014002263],"category_scores_gemma":[0.002993983,0.00044658326,0.0006219122,0.0039868685,0.0010819229,0.00073081494,0.0011609199,0.0005139976,0.00020469632],"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":[0.00008453819,0.00003257479,0.988943,0.000044384255,0.00013380076,0.00007176497,0.0033907702,0.00065252394,0.0002157758,0.00030269293,0.00093280646,0.005195463],"study_design_scores_gemma":[0.0000036299423,0.000010434398,0.99629045,0.000014410636,0.000027626249,0.000007568848,0.002391742,0.00039440472,0.00003305215,0.000027494147,0.0007934295,0.000005806343],"about_ca_topic_score_codex":0.9961067,"about_ca_topic_score_gemma":0.9987436,"teacher_disagreement_score":0.020776251,"about_ca_system_score_codex":0.020776251,"about_ca_system_score_gemma":0.017580185,"threshold_uncertainty_score":0.15074295},"labels":[],"label_agreement":null},{"id":"W4391512659","doi":"10.1016/j.tbs.2024.100746","title":"Toward understanding waiting time in an intercity station: A hazard-based approach","year":2024,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Transportation Planning and Optimization","field":"Social Sciences","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 Calgary","funders":"","keywords":"Hazard; Transport engineering; Computer science; Forensic engineering; Engineering","score_opus":0.09428655033751372,"score_gpt":0.32046427131090677,"score_spread":0.22617772097339306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391512659","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22607556,0.0005069245,0.7616995,0.0010451649,0.000057228033,0.00007906609,0.00065943005,0.00014376729,0.009733456],"genre_scores_gemma":[0.95562094,0.0004559877,0.040594723,0.00006131343,0.000059679296,0.00006174931,0.00028359887,0.000047556256,0.002814477],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996593,0.00011043564,0.000019310553,0.00007558304,0.000055776265,0.00007965729],"domain_scores_gemma":[0.998694,0.0006505669,0.00022363015,0.00009491056,0.00020456173,0.00013243305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008078565,0.00075200194,0.0008187036,0.0022873562,0.0007821867,0.0021889606,0.002315709,0.0012954348,0.0054088593],"category_scores_gemma":[0.0031068735,0.0006053463,0.0011568861,0.002014091,0.000839724,0.0031076977,0.0017645899,0.0013797639,0.00035322356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038054488,0.000100054094,0.011085387,0.000072425915,0.00006844179,0.00009225101,0.0003483845,0.90894115,0.0012494387,0.06459802,0.0006087618,0.012797633],"study_design_scores_gemma":[0.0000040309496,0.000025939004,0.0035057021,0.0000139685635,0.000031730193,0.000029577119,0.0003617606,0.95583177,0.00015057101,0.039373472,0.0006537651,0.000017743638],"about_ca_topic_score_codex":0.035021134,"about_ca_topic_score_gemma":0.02421687,"teacher_disagreement_score":0.035021134,"about_ca_system_score_codex":0.0016271941,"about_ca_system_score_gemma":0.0020952646,"threshold_uncertainty_score":0.06963456},"labels":[],"label_agreement":null},{"id":"W4392792511","doi":"10.1016/j.tbs.2024.100784","title":"Uncovering suppressed travel: A scoping review of surveys measuring unmet transportation need","year":2024,"lang":"en","type":"review","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Transport engineering; Business; Environmental health; Engineering; Medicine","score_opus":0.09052714048739678,"score_gpt":0.3776755933822044,"score_spread":0.2871484528948076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392792511","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":[0.0015839697,0.990343,0.0013635635,0.0017799211,0.0005009152,0.0015330577,0.001610577,0.000030385358,0.0012546172],"genre_scores_gemma":[0.009534973,0.98287004,0.002113842,0.0010060739,0.0001567373,0.0030403147,0.0010166699,0.000026196554,0.00023513981],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.94320154,0.018169707,0.027211493,0.002507957,0.008016863,0.0008924964],"domain_scores_gemma":[0.6988018,0.2405394,0.025459904,0.004650936,0.029497629,0.0010502193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06539288,0.0022415475,0.007901607,0.04029468,0.001765203,0.00744796,0.0034271243,0.0038566364,0.004369311],"category_scores_gemma":[0.27398878,0.0025618905,0.008943515,0.04167429,0.0024174545,0.006737487,0.0045753475,0.0025251207,0.0008445643],"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":[0.00009478971,0.000015856622,0.00082992535,0.9176845,0.0022165168,0.00011265899,0.0016152861,0.00015284859,0.00014187208,0.000758844,0.0033525075,0.0730245],"study_design_scores_gemma":[0.000021186734,0.00004758403,0.0012399331,0.9748669,0.004572572,0.00009283809,0.0008109759,0.000045494988,0.000096762255,0.0003817835,0.017800122,0.000023862993],"about_ca_topic_score_codex":0.017894017,"about_ca_topic_score_gemma":0.03658138,"teacher_disagreement_score":0.06539288,"about_ca_system_score_codex":0.008580373,"about_ca_system_score_gemma":0.042581484,"threshold_uncertainty_score":0.34583473},"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":"W4402685925","doi":"10.1016/j.tbs.2024.100905","title":"Unveiling mobility patterns beyond home/work activities: A topic modeling approach using transit smart card and land-use data","year":2024,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","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 Calgary","funders":"","keywords":"Smart card; Transit (satellite); Work (physics); Land use; Public transport; Transport engineering; Travel behavior; Computer science; Computer security; Business; Data science; Engineering; Civil engineering","score_opus":0.09025104478436981,"score_gpt":0.32189883412383485,"score_spread":0.23164778933946506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402685925","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2603863,0.0012190324,0.72948235,0.0010711487,0.00016246746,0.00028908992,0.0044575073,0.0008607718,0.002071296],"genre_scores_gemma":[0.8508458,0.00079882186,0.13723348,0.00012542131,0.00027973414,0.000397623,0.0072405552,0.000096682386,0.002981763],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9990804,0.00029751996,0.00006809043,0.00036581483,0.000090448084,0.000097715565],"domain_scores_gemma":[0.99820554,0.0012441177,0.00017074619,0.00014109195,0.00017567165,0.00006279364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018518558,0.0009156308,0.00093494164,0.0036673185,0.0005296554,0.0013304264,0.0014862799,0.0010809401,0.0009710121],"category_scores_gemma":[0.0028407357,0.0005953392,0.0023308906,0.0029964708,0.0004506849,0.0016841585,0.00096783624,0.0013378507,0.0005614919],"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":[0.00063405617,0.0009435676,0.17649452,0.0007598847,0.0012611817,0.0007363714,0.0031461224,0.48397338,0.010545284,0.017894361,0.007897751,0.29571348],"study_design_scores_gemma":[0.000011721696,0.00004367383,0.011398001,0.000023754517,0.00008052206,0.00008563219,0.00031254356,0.9811576,0.00049132056,0.004411892,0.001955539,0.00002777815],"about_ca_topic_score_codex":0.015077173,"about_ca_topic_score_gemma":0.020074435,"teacher_disagreement_score":0.015077173,"about_ca_system_score_codex":0.0007705795,"about_ca_system_score_gemma":0.0007401546,"threshold_uncertainty_score":0.029978812},"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":"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":"W4403350198","doi":"10.1016/j.tbs.2024.100922","title":"Heterogeneity in route choice during peak hours: Implications on travel demand management","year":2024,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Transportation Planning and Optimization","field":"Social Sciences","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":"National Natural Science Foundation of China","keywords":"Demand management; Business; Transport engineering; Economics; Engineering","score_opus":0.02668054870868127,"score_gpt":0.31716815101043044,"score_spread":0.2904876023017492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403350198","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97889155,0.00027161182,0.015672086,0.0010098468,0.000027193642,0.0000407984,0.0005820862,0.000033602,0.0034712392],"genre_scores_gemma":[0.9984621,0.00006030452,0.00065473083,0.000040918643,0.000017145057,0.000009808223,0.00011667503,0.0000087758,0.00062958576],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984067,0.0006619489,0.00007774219,0.00037472448,0.00015376843,0.000325148],"domain_scores_gemma":[0.98738223,0.008815241,0.0013719945,0.0010677516,0.0006133543,0.0007494551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028892981,0.0002493471,0.001044897,0.0009922576,0.00079049804,0.0028047161,0.0013581067,0.0013945472,0.006612805],"category_scores_gemma":[0.014070373,0.0004633198,0.00094774994,0.0015588544,0.0011971747,0.0017817247,0.00095558935,0.0009225765,0.00031908555],"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":[0.001722051,0.0009725497,0.70466465,0.00025946123,0.0011285213,0.001001515,0.0024903992,0.16442323,0.005761257,0.076371,0.0041050008,0.037100285],"study_design_scores_gemma":[0.00013621208,0.00031522394,0.6027406,0.00006408378,0.00027314853,0.0006592074,0.00789578,0.25633088,0.00080585893,0.12771839,0.002928953,0.00013164032],"about_ca_topic_score_codex":0.016866012,"about_ca_topic_score_gemma":0.019773409,"teacher_disagreement_score":0.016866012,"about_ca_system_score_codex":0.0013626032,"about_ca_system_score_gemma":0.00078111445,"threshold_uncertainty_score":0.03353566},"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":"W4405695388","doi":"10.1016/j.tbs.2024.100969","title":"What type of person is at different stages of change for cycling? A case study of Montreal","year":2024,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":6,"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; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Fonds de Recherche du Québec-Société et Culture","keywords":"Cycling; Psychology; History","score_opus":0.138808644044637,"score_gpt":0.37789115061702494,"score_spread":0.23908250657238794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405695388","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98779684,0.0005717607,0.00043696168,0.0032637184,0.000033973683,0.00018323014,0.0001901745,0.000016972697,0.007506313],"genre_scores_gemma":[0.99331266,0.0005725208,0.0007280087,0.0005678872,0.0000112819425,0.00006898595,0.000087605775,0.00001404217,0.0046370137],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.99854976,0.0005888996,0.000028239885,0.00017517837,0.00014813019,0.000509806],"domain_scores_gemma":[0.9990453,0.00018224465,0.00008980818,0.000031514995,0.00019403394,0.00045711122],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001521339,0.0005758908,0.0003317037,0.0009984171,0.010435957,0.0018323908,0.0019587704,0.0013805703,0.004408085],"category_scores_gemma":[0.0033394073,0.00026897708,0.00042992036,0.0014643206,0.002658144,0.0010964867,0.0016555042,0.0013415323,0.00019921882],"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":[0.00037170865,0.0013938404,0.3180697,0.00045079854,0.0001319257,0.05904466,0.5092854,0.001252665,0.0050881635,0.011414747,0.016467711,0.07702873],"study_design_scores_gemma":[0.00006377996,0.000666398,0.32774833,0.00042456482,0.00010856955,0.0042298282,0.6231167,0.0022885576,0.0007907972,0.001104501,0.039292432,0.00016554233],"about_ca_topic_score_codex":0.92726105,"about_ca_topic_score_gemma":0.97449476,"teacher_disagreement_score":0.072738945,"about_ca_system_score_codex":0.029986367,"about_ca_system_score_gemma":0.012252293,"threshold_uncertainty_score":0.21756732},"labels":[],"label_agreement":null},{"id":"W4407366781","doi":"10.1016/j.tbs.2025.100998","title":"Integrating machine learning and discrete choice modeling for enhanced shopping destination choice model","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","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":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Environment and Climate Change Canada","keywords":"Discrete choice; Computer science; Artificial intelligence; Machine learning","score_opus":0.030773679777924674,"score_gpt":0.2978366956926167,"score_spread":0.26706301591469206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407366781","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03705748,0.00015111586,0.9588487,0.00056585233,0.000036763624,0.00010468708,0.00037632487,0.00019440502,0.0026646827],"genre_scores_gemma":[0.7459322,0.00029834095,0.24657664,0.00024674507,0.00008213669,0.00043143108,0.00070334575,0.00004259895,0.0056866053],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998706,0.0007684861,0.000054833952,0.00020665837,0.0001680821,0.00009588636],"domain_scores_gemma":[0.99715483,0.002173592,0.00022791424,0.00013458527,0.00023320208,0.00007589787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022523808,0.0005141246,0.0008403719,0.0008996988,0.00028415336,0.0010998689,0.0012792062,0.00085018366,0.0038243055],"category_scores_gemma":[0.0057068,0.00032580463,0.0011659947,0.0012815294,0.0004398079,0.0012267411,0.0008957842,0.0015632088,0.0006046633],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005190294,0.00017418757,0.006306947,0.000071610484,0.000092770155,0.00010253464,0.000086817185,0.9102834,0.0003277221,0.0530973,0.00093771314,0.028467126],"study_design_scores_gemma":[0.0000040791824,0.000011905457,0.0003494383,0.0000034004604,0.000005114285,0.000006987706,0.0000061087694,0.99269,0.00003972996,0.0065374076,0.00034120234,0.000004683376],"about_ca_topic_score_codex":0.010245255,"about_ca_topic_score_gemma":0.010076527,"teacher_disagreement_score":0.010245255,"about_ca_system_score_codex":0.0013588896,"about_ca_system_score_gemma":0.001215095,"threshold_uncertainty_score":0.020371258},"labels":[],"label_agreement":null},{"id":"W4407424808","doi":"10.1016/j.tbs.2025.100996","title":"Quantifying physical activity during active commuting to school: A comparison of methodologies","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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 Lethbridge","funders":"Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía; Junta de Andalucía; Ministerio de Economía y Competitividad; Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España; Universidad de Granada; Ministerio de Ciencia e Innovación; European Regional Development Fund; Federación Española de Enfermedades Raras","keywords":"Physical activity; Poison control; Human factors and ergonomics; Injury prevention; Transport engineering; Environmental health; Environmental science; Psychology; Forensic engineering; Engineering; Medicine; Physical medicine and rehabilitation","score_opus":0.1681880310208778,"score_gpt":0.4596274574665245,"score_spread":0.2914394264456467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407424808","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7557759,0.017740296,0.20986079,0.0003750693,0.0004914115,0.0030038564,0.0033544847,0.00058044324,0.008817744],"genre_scores_gemma":[0.7411792,0.007879325,0.2409585,0.00028767562,0.00016007575,0.00493072,0.0027883581,0.00017248171,0.0016437183],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9780993,0.0122093735,0.0022511173,0.0034451573,0.003678914,0.0003160777],"domain_scores_gemma":[0.98542154,0.006489686,0.0021849053,0.0013568171,0.004298001,0.00024905722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017758643,0.0011538585,0.0011379702,0.002768674,0.00036584592,0.0016662095,0.0014914668,0.0011454162,0.0010114523],"category_scores_gemma":[0.026627388,0.0005050886,0.0016208382,0.0024009724,0.00047597275,0.0008059992,0.0013824326,0.00053475914,0.00047011892],"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":[0.003550684,0.00066931895,0.5676795,0.0062177507,0.004371135,0.00016448137,0.0046573244,0.0031605477,0.014968062,0.00094607373,0.0013670509,0.39224812],"study_design_scores_gemma":[0.00038878032,0.0036272958,0.94108284,0.0019127809,0.0028164897,0.0010900869,0.0041651335,0.017109785,0.011506412,0.0017546386,0.014258183,0.00028757885],"about_ca_topic_score_codex":0.0040813037,"about_ca_topic_score_gemma":0.00692952,"teacher_disagreement_score":0.017758643,"about_ca_system_score_codex":0.00058034447,"about_ca_system_score_gemma":0.0008915785,"threshold_uncertainty_score":0.09391779},"labels":[],"label_agreement":null},{"id":"W4408237539","doi":"10.1016/j.tbs.2025.101019","title":"Understanding the impact of COVID-19 on travel mode choices and predicting the modal shift after the pandemic","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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":"McGill University; Université de Montréal; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Modal; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Modal shift; Mode (computer interface); Psychology; Medicine; Transport engineering; Computer science; Engineering; Virology; Chemistry; Public transport","score_opus":0.07845551062543496,"score_gpt":0.37054028386110566,"score_spread":0.2920847732356707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408237539","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99562293,0.00016065725,0.0002850928,0.0006515234,0.000034005967,0.000016076214,0.0016771622,0.000007039627,0.0015454243],"genre_scores_gemma":[0.997875,0.0001268558,0.00022675651,0.000067745714,0.000016688937,0.000014300379,0.0012396547,0.000005932701,0.00042715794],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998939,0.00031776074,0.000064151514,0.00015723698,0.00010382664,0.00041805164],"domain_scores_gemma":[0.99674064,0.0010381634,0.0007627919,0.00022284096,0.000524618,0.0007109039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016275476,0.0004917821,0.00043754312,0.0008313285,0.00066517404,0.0017619191,0.0006802596,0.0009884222,0.005263548],"category_scores_gemma":[0.0077628945,0.00034968453,0.0012551257,0.0011243551,0.00042221538,0.0015975944,0.0014623696,0.0018310132,0.0008549706],"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":[0.00015689916,0.00015798397,0.99141264,0.000018799004,0.000106661464,0.000036280046,0.00030098093,0.0016356076,0.00013075143,0.00024939276,0.000640151,0.0051539126],"study_design_scores_gemma":[0.0000033917916,0.00010063641,0.9897988,0.000039272614,0.000047765174,0.000025896985,0.0016237472,0.0071946364,0.00008674011,0.00042103144,0.00064362324,0.000014438607],"about_ca_topic_score_codex":0.10521065,"about_ca_topic_score_gemma":0.13934222,"teacher_disagreement_score":0.10521065,"about_ca_system_score_codex":0.0011981135,"about_ca_system_score_gemma":0.0018130773,"threshold_uncertainty_score":0.20919651},"labels":[],"label_agreement":null},{"id":"W4408341573","doi":"10.1016/j.tbs.2025.101018","title":"The effect of incentives on the actions transit riders make in response to crowding","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Traffic and Road Safety","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":"Incentive; Crowding; Transit (satellite); Transport engineering; Crowding out; Business; Economics; Engineering; Microeconomics; Psychology; Public transport; Monetary economics","score_opus":0.008047820221827994,"score_gpt":0.24605794220423025,"score_spread":0.23801012198240226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408341573","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9905143,0.00006464019,0.00036758182,0.00035382446,0.000025968204,0.000019727833,0.000077612254,0.000009339356,0.008567094],"genre_scores_gemma":[0.99877304,0.000029674262,0.00011937204,0.000036460588,0.000007865695,0.0000050910626,0.00002348762,0.000004419945,0.0010006157],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979519,0.001121656,0.00011027393,0.00016437162,0.00013474165,0.0005169857],"domain_scores_gemma":[0.9394831,0.043774743,0.0071793515,0.0018879704,0.0029257035,0.0047491933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038369314,0.00027882654,0.0003355521,0.00051268045,0.0006327119,0.001855837,0.00046814146,0.0013972431,0.010396366],"category_scores_gemma":[0.032459747,0.00028404797,0.00037068754,0.00034483772,0.0009492799,0.0010435227,0.0009172768,0.0010661026,0.0005643134],"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":[0.02781015,0.009293829,0.66007537,0.0006757404,0.00084300886,0.0015411502,0.0045142984,0.09879239,0.04285407,0.047573384,0.00562353,0.10040311],"study_design_scores_gemma":[0.0004440198,0.0029399304,0.9250136,0.000085566964,0.0003191153,0.00020348985,0.0063210153,0.04024756,0.003930896,0.015282634,0.005097691,0.00011449416],"about_ca_topic_score_codex":0.008346005,"about_ca_topic_score_gemma":0.01025812,"teacher_disagreement_score":0.010396366,"about_ca_system_score_codex":0.001054002,"about_ca_system_score_gemma":0.0011787916,"threshold_uncertainty_score":0.03477931},"labels":[],"label_agreement":null},{"id":"W4410191905","doi":"10.1016/j.tbs.2025.101042","title":"Green stormwater infrastructure and active mobility: A case study investigating the effects of bioswales on individuals’ perceptions","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de Recherche du Québec-Société et Culture; Transportation Association of Canada Foundation","keywords":"Stormwater; Green infrastructure; Business; Stormwater management; Perception; Environmental planning; Environmental health; Environmental science; Psychology; Medicine; Ecology; Surface runoff","score_opus":0.016945156686398042,"score_gpt":0.30850926282364644,"score_spread":0.29156410613724837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410191905","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99798214,0.00004503932,0.00022848022,0.00016416854,0.000004018313,0.000036834346,0.00002073986,0.0000024620115,0.0015159916],"genre_scores_gemma":[0.99800473,0.00015511918,0.0006473753,0.000048515118,0.0000030799595,0.000028038634,0.00001733088,0.0000019690942,0.0010938443],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.99894434,0.0005175813,0.000032357624,0.00010061886,0.00015310416,0.00025199246],"domain_scores_gemma":[0.9988318,0.00046896582,0.00019416407,0.000069410286,0.0001680217,0.00026758687],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013799511,0.00031337704,0.00021864864,0.0006595854,0.004641648,0.0015961454,0.0007929009,0.00095504423,0.0022409395],"category_scores_gemma":[0.0018439868,0.00020280838,0.00045729938,0.00085060013,0.0022094124,0.0013284074,0.0020539283,0.00073665136,0.00015369085],"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":[0.0001345288,0.0013441347,0.1438952,0.00044446724,0.000050035807,0.013830306,0.79030764,0.00074869883,0.0045834985,0.0026124248,0.001513079,0.04053607],"study_design_scores_gemma":[0.000016598224,0.00060002983,0.0543371,0.00011003275,0.000040044335,0.0013398955,0.9308245,0.0006515909,0.0011308271,0.00027664896,0.010636782,0.00003601975],"about_ca_topic_score_codex":0.05938125,"about_ca_topic_score_gemma":0.15770262,"teacher_disagreement_score":0.05938125,"about_ca_system_score_codex":0.0028939052,"about_ca_system_score_gemma":0.0026439617,"threshold_uncertainty_score":0.1180712},"labels":[],"label_agreement":null},{"id":"W4410586476","doi":"10.1016/j.tbs.2025.101054","title":"Using Realtime GTFS to generate easy-to-use transit accessibility measures under travel time uncertainty","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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":"Western University","funders":"","keywords":"Transit (satellite); Travel time; Transport engineering; Computer science; Business; Computer security; Public transport; Engineering","score_opus":0.07142856185731147,"score_gpt":0.3494304302318764,"score_spread":0.278001868374565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410586476","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20146438,0.00015638671,0.63786435,0.00078082137,0.00029023318,0.00179396,0.12566525,0.01146193,0.020522708],"genre_scores_gemma":[0.5056108,0.00015793247,0.38912472,0.00016249252,0.00007764095,0.0031497185,0.09695163,0.0015687098,0.0031962758],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9948598,0.0020467718,0.00066108105,0.00086548773,0.001375423,0.00019151272],"domain_scores_gemma":[0.9756925,0.010918132,0.0031443725,0.0050205854,0.0049980483,0.00022640916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00717196,0.001140412,0.0005355763,0.004373956,0.0005737533,0.0018867913,0.0012008625,0.0006700835,0.0096506635],"category_scores_gemma":[0.054447144,0.00050003885,0.0015058538,0.00584759,0.0006098578,0.0021407707,0.0020408225,0.0011280935,0.0024342164],"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":[0.0007444013,0.00047569725,0.2380107,0.001584346,0.0006068975,0.0005823842,0.0040650205,0.21795572,0.004904164,0.04826193,0.08080441,0.4020044],"study_design_scores_gemma":[0.00034831735,0.00079315755,0.22870076,0.00078286615,0.00025026393,0.00055868516,0.0054476284,0.4680617,0.020752052,0.07610446,0.19778797,0.00041219345],"about_ca_topic_score_codex":0.02777399,"about_ca_topic_score_gemma":0.025830625,"teacher_disagreement_score":0.02777399,"about_ca_system_score_codex":0.0015251769,"about_ca_system_score_gemma":0.0021342277,"threshold_uncertainty_score":0.055224657},"labels":[],"label_agreement":null},{"id":"W4410636189","doi":"10.1016/j.tbs.2025.101074","title":"Getting around on foot: Older adults’ walking experiences and perspectives on neighbourhood walkability across Canada","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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":"Concordia University; McGill University","funders":"National Research Council Canada; Fonds de Recherche du Québec-Société et Culture","keywords":"Walkability; Neighbourhood (mathematics); Gerontology; Human factors and ergonomics; Injury prevention; Suicide prevention; Poison control; Geography; Psychology; Physical medicine and rehabilitation; Environmental health; Medicine; Physical activity","score_opus":0.014337459902598299,"score_gpt":0.2917850856429994,"score_spread":0.27744762574040105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410636189","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99597013,0.00038122345,0.000044610333,0.00054169213,0.000010718209,0.0000135756645,0.000092812836,0.00000274493,0.002942549],"genre_scores_gemma":[0.99853086,0.00036783126,0.000047036217,0.0001374898,0.0000023990285,0.000007968192,0.000050696537,0.000002566899,0.00085310393],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9988918,0.00019547726,0.00007448405,0.00010099802,0.0002614243,0.00047580613],"domain_scores_gemma":[0.99785066,0.00028689663,0.00023141451,0.000042823838,0.00064300763,0.00094519556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013438239,0.00027632594,0.0005034824,0.00087342015,0.00860892,0.0028147227,0.000856457,0.0006734421,0.0016854329],"category_scores_gemma":[0.0031083124,0.00025019248,0.00034429753,0.0016088523,0.0024666826,0.0012573986,0.0029783016,0.0011780972,0.00010940234],"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":[0.000080635895,0.0000663585,0.12028093,0.0001346936,0.000019512843,0.00057527475,0.86538255,0.00007870069,0.00055939396,0.00071011,0.0014124716,0.010699457],"study_design_scores_gemma":[0.0000037063112,0.000042801665,0.12592101,0.0001418349,0.000013416453,0.00009412268,0.86887866,0.0000910569,0.000063722255,0.00006831544,0.004650073,0.000031259613],"about_ca_topic_score_codex":0.97027963,"about_ca_topic_score_gemma":0.98657644,"teacher_disagreement_score":0.029720366,"about_ca_system_score_codex":0.014035213,"about_ca_system_score_gemma":0.019054223,"threshold_uncertainty_score":0.101833045},"labels":[],"label_agreement":null},{"id":"W4411124104","doi":"10.1016/j.tbs.2025.101073","title":"Transportation access equity analysis in two US cities using Bayesian inference-based logsum compensating variation metrics","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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":"Metropolitan Council","keywords":"Equity (law); Inference; Variation (astronomy); Bayesian probability; Econometrics; Bayesian inference; Computer science; Economics; Artificial intelligence; Political science","score_opus":0.07243983377327674,"score_gpt":0.410694166096962,"score_spread":0.3382543323236853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411124104","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9768406,0.00006388266,0.021604065,0.0002397427,0.000007850223,0.000021695447,0.00053656305,0.00008496558,0.00060080236],"genre_scores_gemma":[0.993937,0.000017771325,0.0050845514,0.000013989398,0.000004364601,0.000014348762,0.00070698856,0.00001310098,0.00020786209],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99823004,0.0010356359,0.000072146104,0.00029127917,0.00018447838,0.00018646115],"domain_scores_gemma":[0.9909429,0.006335855,0.00069661747,0.00060517056,0.0011874501,0.00023204256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043280628,0.00041097627,0.00072996406,0.001689048,0.00048203394,0.0011317256,0.0012264105,0.00089461135,0.0011089921],"category_scores_gemma":[0.013616288,0.00036799625,0.0011247863,0.0022067155,0.00060948764,0.0011884952,0.0009999484,0.0010511536,0.000099470264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073462544,0.0005828602,0.37287265,0.00006883013,0.00060614984,0.0001965667,0.0006731973,0.5678788,0.0006990768,0.02028185,0.0030163378,0.03238908],"study_design_scores_gemma":[0.000024004741,0.000047599606,0.06773447,0.000007731556,0.000059004735,0.000015787242,0.00020775988,0.92751664,0.00016754535,0.0039055322,0.00028923605,0.000024644945],"about_ca_topic_score_codex":0.17634097,"about_ca_topic_score_gemma":0.1466041,"teacher_disagreement_score":0.17634097,"about_ca_system_score_codex":0.002209894,"about_ca_system_score_gemma":0.0015825643,"threshold_uncertainty_score":0.3506291},"labels":[],"label_agreement":null},{"id":"W4413160238","doi":"10.1016/j.tbs.2025.101112","title":"Grocery shopping and related access trips by mode in Canadian time use surveys","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","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":"University of Toronto; Université du Québec à Montréal","funders":"Social Sciences and Humanities Research Council; Social Sciences and Humanities Research Council of Canada; Canada Research Chairs","keywords":"TRIPS architecture; Transport engineering; Business; Poison control; Human factors and ergonomics; Environmental health; Engineering; Medicine","score_opus":0.025324950648700485,"score_gpt":0.3128963004438993,"score_spread":0.2875713497951988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413160238","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7370445,0.0012298666,0.0016354766,0.0003615431,0.000048912152,0.0007934045,0.23197983,0.00015364109,0.026752802],"genre_scores_gemma":[0.8772704,0.0015134405,0.0041641197,0.00021045381,0.000014024119,0.0006880738,0.10679342,0.00007863424,0.009267358],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99744415,0.00021060744,0.00021019789,0.0003072496,0.001344849,0.00048295446],"domain_scores_gemma":[0.99536043,0.00038223254,0.0009899109,0.00024383339,0.0024236252,0.0005998664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001441439,0.0004361084,0.00034902926,0.0068422155,0.0019542824,0.0016805697,0.0013441042,0.00036142446,0.006131094],"category_scores_gemma":[0.007828375,0.0004286565,0.0010015592,0.020719808,0.0004363005,0.0007453149,0.0013166881,0.0005496992,0.00088059035],"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":[0.000140653,0.00006732824,0.9498011,0.000465367,0.00012047911,0.00009413648,0.0031220908,0.0006447614,0.00034086645,0.000999323,0.017805379,0.026398554],"study_design_scores_gemma":[0.0000024619503,0.000011658729,0.99149793,0.0000580485,0.00001337408,0.000023371615,0.0012052502,0.00023510092,0.00005502771,0.000026784239,0.0068524648,0.00001841221],"about_ca_topic_score_codex":0.992454,"about_ca_topic_score_gemma":0.9950252,"teacher_disagreement_score":0.018938147,"about_ca_system_score_codex":0.018938147,"about_ca_system_score_gemma":0.019500142,"threshold_uncertainty_score":0.13740653},"labels":[],"label_agreement":null},{"id":"W4413963310","doi":"10.1016/j.tbs.2025.101127","title":"Spatial dynamics of home delivery and pick-up in online shopping","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban and Freight Transport Logistics","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":"Taylor College and Seminary; University of British Columbia, Okanagan Campus","funders":"Natural Sciences and Engineering Research Council of Canada; Environment and Climate Change Canada","keywords":"Dynamics (music); Computer science; Transport engineering; Computer security; Psychology; Engineering","score_opus":0.013966746758762857,"score_gpt":0.20911460193745462,"score_spread":0.19514785517869176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413963310","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970541,0.000101580124,0.0010539739,0.00013561703,0.0000023998252,0.0000126282275,0.00034737863,0.0000141434975,0.0012782296],"genre_scores_gemma":[0.9981805,0.00006211298,0.0004815232,0.000007873205,0.0000028185902,0.000009353613,0.00028670864,0.000006012551,0.00096309773],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994141,0.00023576026,0.000026822396,0.00011162364,0.00008917636,0.00012244679],"domain_scores_gemma":[0.99624085,0.0020726896,0.00083758734,0.00024365468,0.00029946037,0.00030564755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007352729,0.00014347259,0.00037115838,0.0011034502,0.00045058137,0.0015556797,0.00064931595,0.00059244194,0.0076415157],"category_scores_gemma":[0.004827568,0.00039246172,0.0006671628,0.0015657389,0.0006870974,0.0014223048,0.0010264071,0.0004930294,0.00082280184],"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":[0.0005188887,0.0005476691,0.93963504,0.00011059173,0.00013672335,0.00078931113,0.0036446042,0.021720333,0.0024744857,0.011491242,0.0017216465,0.017209465],"study_design_scores_gemma":[0.000024899111,0.00012034655,0.8805499,0.000039280774,0.000046092184,0.00031142312,0.0064780833,0.10520256,0.0004164624,0.004597881,0.0021590635,0.000053966218],"about_ca_topic_score_codex":0.029322008,"about_ca_topic_score_gemma":0.04063735,"teacher_disagreement_score":0.029322008,"about_ca_system_score_codex":0.0011338319,"about_ca_system_score_gemma":0.00042815678,"threshold_uncertainty_score":0.05830264},"labels":[],"label_agreement":null},{"id":"W4415898015","doi":"10.1016/j.tbs.2025.101169","title":"Spherical fuzzy evidential reasoning for vehicle-to-grid enabled electric vehicle adoption: A data-driven analysis of public perception","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Electric Vehicles and Infrastructure","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":"Laurentian University; University of British Columbia, Okanagan Campus","funders":"Mitacs","keywords":"Respondent; Perception; Skepticism; Key (lock); Psychological intervention; Fuzzy logic; Poison control; Causation","score_opus":0.01846271005537564,"score_gpt":0.2638930256710431,"score_spread":0.24543031561566747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415898015","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9110896,0.000095175514,0.085294776,0.00028770164,0.000009621494,0.00016892746,0.00086404424,0.000088738554,0.002101267],"genre_scores_gemma":[0.98346126,0.000027736989,0.015970238,0.000012119403,0.0000022518043,0.00005105799,0.00035483018,0.0000033985705,0.00011717356],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980496,0.00090394716,0.00013908868,0.0002796671,0.00047040213,0.00015724747],"domain_scores_gemma":[0.9829118,0.013529338,0.0011985437,0.00056640117,0.0016344782,0.00015940923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0062751276,0.00038954613,0.00045966505,0.0018435374,0.000511109,0.0018625833,0.0007338235,0.0005932955,0.0017826936],"category_scores_gemma":[0.020001998,0.00020746053,0.0016226557,0.0016224718,0.00061100244,0.0013736972,0.00089347846,0.000998187,0.00015174814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010687395,0.0011084897,0.28486878,0.0006775965,0.00052841543,0.0010867615,0.008585987,0.49750283,0.0058608996,0.060368456,0.0020223556,0.13632075],"study_design_scores_gemma":[0.000015721349,0.000105980405,0.027260378,0.00003200491,0.00003998837,0.000059945156,0.0019695149,0.9594515,0.000896838,0.00958162,0.00056004716,0.000026395432],"about_ca_topic_score_codex":0.0239435,"about_ca_topic_score_gemma":0.012762197,"teacher_disagreement_score":0.0239435,"about_ca_system_score_codex":0.0024913182,"about_ca_system_score_gemma":0.0012993353,"threshold_uncertainty_score":0.047608316},"labels":[],"label_agreement":null},{"id":"W4416259015","doi":"10.1016/j.tbs.2025.101191","title":"Exposure to green and blue spaces during travel does not have immediate effect on subjective happiness and stress: evidence from a GPS survey in England","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Urban Green Space and Health","field":"Environmental Science","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":"Western University","funders":"European Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Happiness; TRIPS architecture; Subjective well-being; Travel behavior; Poison control; Global Positioning System; Well-being; Human factors and ergonomics","score_opus":0.018342865929726705,"score_gpt":0.2620791283276113,"score_spread":0.24373626239788462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416259015","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9972025,0.0006973296,0.0001373179,0.00013044379,0.00000790816,0.000013894179,0.0007546098,0.0000023519592,0.0010536077],"genre_scores_gemma":[0.99837685,0.00067745766,0.000088170986,0.00007286183,0.0000055406604,0.00003275835,0.00031080795,0.0000035375006,0.00043201997],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99881727,0.0004553059,0.0001330897,0.0002358128,0.00019769129,0.0001608243],"domain_scores_gemma":[0.9947871,0.0015331563,0.0018291428,0.00033654683,0.0010775159,0.00043653985],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010062826,0.00022784749,0.00044768784,0.0007976323,0.00062526565,0.001146818,0.00054102624,0.00044802064,0.0024150868],"category_scores_gemma":[0.0042967475,0.00043853605,0.0005594189,0.0016333526,0.000765398,0.0008254522,0.001237381,0.0004353344,0.00038868163],"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":[0.00016115302,0.000037059785,0.98542076,0.0002762389,0.00011003628,0.0002728577,0.008509618,0.00004930325,0.0003175327,0.000060688,0.00044123997,0.0043435465],"study_design_scores_gemma":[0.000003033425,0.000052752803,0.9960748,0.00004074283,0.000023965504,0.00004763029,0.003232577,0.000022634258,0.000021311986,0.000009939617,0.00046537272,0.0000052283585],"about_ca_topic_score_codex":0.21255971,"about_ca_topic_score_gemma":0.25862405,"teacher_disagreement_score":0.21255971,"about_ca_system_score_codex":0.0010110504,"about_ca_system_score_gemma":0.0007270205,"threshold_uncertainty_score":0.4226449},"labels":[],"label_agreement":null},{"id":"W4416396310","doi":"10.1016/j.tbs.2025.101171","title":"Analyzing sequential activity and travel decisions with interpretable deep inverse reinforcement learning","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Transportation Planning and Optimization","field":"Social Sciences","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":"Singapore-MIT Alliance for Research and Technology Centre; University of Florida","keywords":"Interpretability; Reinforcement learning; Travel behavior; Function (biology); Multinomial logistic regression; TRIPS architecture; Artificial neural network; Behavioral modeling; Deep learning","score_opus":0.019240713605036992,"score_gpt":0.2930527176155078,"score_spread":0.2738120040104708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416396310","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40303877,0.00048774327,0.59243304,0.00079293153,0.000082944265,0.000039219314,0.00040594448,0.0005106855,0.0022088203],"genre_scores_gemma":[0.98486197,0.000058805697,0.013618463,0.00004444245,0.00001939415,0.000025881947,0.00017989412,0.000023377619,0.001167788],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997683,0.00007763372,0.0000087179,0.00006859703,0.000027860322,0.000048812522],"domain_scores_gemma":[0.998415,0.0011880789,0.00014559248,0.00007290806,0.00010370808,0.00007475771],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068464293,0.0007023966,0.0009433442,0.00052472536,0.00024184468,0.0007285786,0.0010368743,0.001028566,0.0017286489],"category_scores_gemma":[0.0038016003,0.00070484745,0.0006625781,0.00051627326,0.0007725831,0.0009563176,0.0007542274,0.0015265383,0.00019537473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000426311,0.00004844203,0.0017939911,0.000014885259,0.000023846698,0.00002698245,0.00001887363,0.98810357,0.00024147189,0.0017902935,0.00024876426,0.0076462342],"study_design_scores_gemma":[0.0000010526752,0.0000026318648,0.00011149365,7.5206987e-7,0.0000010519387,0.0000011227415,0.0000016655765,0.99875975,0.000025412284,0.0010808114,0.00001353862,7.823534e-7],"about_ca_topic_score_codex":0.025123926,"about_ca_topic_score_gemma":0.025065668,"teacher_disagreement_score":0.025123926,"about_ca_system_score_codex":0.0011297528,"about_ca_system_score_gemma":0.0010442407,"threshold_uncertainty_score":0.049955368},"labels":[],"label_agreement":null},{"id":"W7081907808","doi":"10.1016/j.tbs.2025.101122","title":"Decoding the first-and-last mile: Analyzing the transit connecting bike share GPS routes in Hamilton, Ontario with spatiotemporal distance decay","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Decoding methods; Global Positioning System; Transit (satellite); Path (computing); Public transport; Assisted GPS; Transit system","score_opus":0.013192340451328513,"score_gpt":0.2206779806564788,"score_spread":0.2074856402051503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7081907808","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996546,0.00007610529,0.00045191345,0.0002031891,0.0000038183684,0.000008637196,0.0020965051,0.000013707752,0.00060017436],"genre_scores_gemma":[0.9954526,0.000064161795,0.00038894187,0.00001726501,0.0000031595098,0.0000063525326,0.0028430575,0.000011007766,0.0012134362],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995864,0.00006413919,0.0000202534,0.00008605105,0.000094654264,0.00014858395],"domain_scores_gemma":[0.99828064,0.00049518456,0.0002598981,0.00012530977,0.00065476727,0.00018427057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005435544,0.00031150965,0.0003806714,0.0010000865,0.0008851818,0.0011557384,0.0010435754,0.00068883545,0.0010191256],"category_scores_gemma":[0.00463959,0.00029385937,0.00034882783,0.0033463608,0.0008226897,0.00058327377,0.0008048218,0.00054314936,0.00037122561],"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":[0.00013556494,0.000044782573,0.9690535,0.00003203874,0.00010069672,0.00020628884,0.0019280871,0.012059638,0.0009560474,0.001070118,0.0031916045,0.011221742],"study_design_scores_gemma":[0.000009897953,0.00002276198,0.9352255,0.000022751174,0.00005313975,0.000056132543,0.0059070955,0.055337828,0.00031824945,0.00039288896,0.0026284296,0.000025340232],"about_ca_topic_score_codex":0.9765944,"about_ca_topic_score_gemma":0.9873352,"teacher_disagreement_score":0.023405612,"about_ca_system_score_codex":0.0062780124,"about_ca_system_score_gemma":0.008334773,"threshold_uncertainty_score":0.047086835},"labels":[],"label_agreement":null},{"id":"W7117315719","doi":"10.1016/j.tbs.2025.101213","title":"Independent ageing, climate risks and automobile dependence in the Canadian prairies: Evidence from the Canadian Longitudinal Study on Aging","year":2025,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Older Adults Driving Studies","field":"Health Professions","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 Manitoba","funders":"Economic and Social Research Council; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada Foundation for Innovation","keywords":"Context (archaeology); Longitudinal study; Social connectedness; Differential (mechanical device); Life course approach; Adaptation (eye); Psychological resilience; Individual mobility; Climate change; Poison control","score_opus":0.16968213887838768,"score_gpt":0.4464949676059261,"score_spread":0.27681282872753843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117315719","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9631954,0.013584474,0.00042747418,0.0026332857,0.000111454836,0.00017463848,0.01195351,0.000018516623,0.007901191],"genre_scores_gemma":[0.9863961,0.00720551,0.0005394881,0.00038406486,0.000026835058,0.000094506795,0.003885608,0.000010465643,0.0014574907],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982072,0.0001901921,0.0001414585,0.00027682396,0.0006734579,0.00051079225],"domain_scores_gemma":[0.9917367,0.00054535083,0.0014051751,0.00044291996,0.004391518,0.001478235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028743835,0.0005485903,0.0006441689,0.0031139054,0.00569884,0.0016867354,0.0021671206,0.0008702853,0.0027287977],"category_scores_gemma":[0.006901681,0.00046224875,0.0016994608,0.009769016,0.0011836445,0.0010723998,0.0019403786,0.001343543,0.00034355375],"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":[0.000057385423,0.000047188933,0.9838022,0.0002352466,0.00024089467,0.000072558374,0.0037373407,0.00006394625,0.000055056924,0.0003027666,0.0025419258,0.008843531],"study_design_scores_gemma":[0.00000507751,0.000014210288,0.995609,0.00014627776,0.00008253265,0.00001874989,0.0022203377,0.00007728052,0.000013989311,0.00004481316,0.0017510245,0.000016732381],"about_ca_topic_score_codex":0.99748224,"about_ca_topic_score_gemma":0.9985266,"teacher_disagreement_score":0.020607227,"about_ca_system_score_codex":0.020607227,"about_ca_system_score_gemma":0.04153814,"threshold_uncertainty_score":0.14951658},"labels":[],"label_agreement":null}]}