{"meta":{"query_hash":"402c18294807","filters":{"venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board"},"cohort_total":20,"direct_labels_cover":0,"predictions_cover":20,"exported":20,"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/402c18294807","api":"https://metacan.xera.ac/api/v1/cohort?venue=Transportation+Research+Board+85th+Annual+MeetingTransportation+Research+Board"},"results":[{"id":"W2072244638","doi":"","title":"Guidelines for Using Centerline Rumble Strips in Virginia","year":2005,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Transportation Safety and Impact Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Rumble; Crash; Transport engineering; Geography; Engineering; Computer science; Electrical engineering; Programming language","score_opus":0.1433063821469082,"score_gpt":0.4368857479219575,"score_spread":0.2935793657750493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072244638","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9694978,0.0008589605,0.021935016,0.002587939,0.00023816222,0.0023019807,0.0014902452,0.00049192057,0.0005979983],"genre_scores_gemma":[0.9708651,0.0009170429,0.025130698,0.00013636165,0.00054073846,0.00051471294,0.0012315714,0.00019534233,0.00046844158],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9906608,0.0005188482,0.0024353815,0.0009974014,0.003065148,0.002322435],"domain_scores_gemma":[0.992356,0.0010212954,0.00015829843,0.0006110905,0.0051177246,0.0007355723],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0071166926,0.00057823525,0.0008159395,0.0026879683,0.0007377482,0.00017888787,0.0007470276,0.000454588,0.00043420604],"category_scores_gemma":[0.0004890202,0.0006327525,0.0004176456,0.0038259127,0.00039393172,0.0015892844,0.000006561223,0.0018782107,0.00009122804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002461607,0.0007822751,0.09050285,0.0016872142,0.0004822414,0.00012478259,0.015934495,0.8271258,0.02219009,0.0063071693,0.014310592,0.01809087],"study_design_scores_gemma":[0.011041668,0.0009011603,0.5569528,0.0012039918,0.00022565122,0.0000017391935,0.026089786,0.1938314,0.01648305,0.0015341874,0.18936732,0.002367289],"about_ca_topic_score_codex":0.0034195585,"about_ca_topic_score_gemma":0.046429463,"teacher_disagreement_score":0.6332944,"about_ca_system_score_codex":0.00048517587,"about_ca_system_score_gemma":0.00043134877,"threshold_uncertainty_score":0.9996124},"labels":[],"label_agreement":null},{"id":"W3023530164","doi":"","title":"Car Parking Management at Airports: Special Case?","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Business; Work (physics); Quarter (Canadian coin); Marketing; Element (criminal law); Traffic congestion; Engineering; Geography","score_opus":0.07152927735497985,"score_gpt":0.3295047910458579,"score_spread":0.257975513690878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3023530164","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90640545,0.00058870146,0.0010722198,0.0017398526,0.00044367908,0.0012839532,0.0015751179,0.00021333116,0.0866777],"genre_scores_gemma":[0.9781149,0.00026777745,0.0012260774,0.00006399292,0.0013668448,0.0004845458,0.0013683301,0.00011011383,0.016997414],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9918814,0.00039913022,0.002432491,0.0017016337,0.0016140608,0.0019713324],"domain_scores_gemma":[0.9962438,0.00042675785,0.0005784418,0.00084787875,0.0013486352,0.00055448955],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0065865815,0.00048768544,0.00079921196,0.0024070211,0.0020371794,0.00030502325,0.00063737074,0.00044744668,0.0044222833],"category_scores_gemma":[0.000100564605,0.0005783657,0.00045746818,0.0033816488,0.0006532738,0.00086105714,0.00003467858,0.0015107661,0.0012533552],"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":[0.00048652085,0.00062399043,0.598233,0.00037270502,0.000360926,0.00580639,0.0035511246,0.003955956,0.000069304544,0.3273664,0.05741585,0.0017578247],"study_design_scores_gemma":[0.0022640433,0.00026551334,0.63119763,0.00012525603,0.00006215302,0.000011947908,0.006218726,0.00039985596,0.00038687207,0.018821582,0.3393342,0.0009122074],"about_ca_topic_score_codex":0.019436289,"about_ca_topic_score_gemma":0.032507326,"teacher_disagreement_score":0.3085448,"about_ca_system_score_codex":0.00065791013,"about_ca_system_score_gemma":0.00011282255,"threshold_uncertainty_score":0.99966675},"labels":[],"label_agreement":null},{"id":"W561532588","doi":"","title":"Performance Measures for Snow and Ice Control in Province of Alberta, Canada","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Performance measurement; Suite; Snow; Snow removal; Asset (computer security); Environmental resource management; Control (management); Environmental science; Computer science; Business; Meteorology; Geography; Computer security","score_opus":0.016785291447667085,"score_gpt":0.27856071890037637,"score_spread":0.26177542745270926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W561532588","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952625,0.000042647025,0.00037243654,0.00076800236,0.00011558658,0.002213178,0.0003070068,0.000030112606,0.00088853005],"genre_scores_gemma":[0.99771786,0.000056461253,0.0010162069,0.00003301383,0.00007205509,0.00047971963,0.0001690848,0.000047003785,0.00040858088],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99391264,0.00048690592,0.0010589536,0.0007839844,0.0026141934,0.0011433493],"domain_scores_gemma":[0.99727035,0.00129129,0.00019910553,0.00031714916,0.00067045103,0.00025167246],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0038959086,0.00027112197,0.00043327772,0.000419332,0.00042446546,0.00005364321,0.00038254223,0.00017705337,0.00016642098],"category_scores_gemma":[0.00032845826,0.00028033226,0.00007274075,0.0009983365,0.00091886206,0.00064051204,0.000011403498,0.00051504077,0.00001207329],"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":[0.0013474188,0.00012260096,0.9768799,0.0003506771,0.000018448814,0.000019415318,0.0008315741,0.0050529623,0.009871385,0.0006554619,0.0026269848,0.002223166],"study_design_scores_gemma":[0.002069814,0.00033458736,0.9764827,0.00013736714,0.000017370723,5.6184774e-7,0.0009931305,0.0010585522,0.008485637,0.00034364598,0.00979904,0.00027761701],"about_ca_topic_score_codex":0.9227732,"about_ca_topic_score_gemma":0.99021095,"teacher_disagreement_score":0.06743772,"about_ca_system_score_codex":0.00038446355,"about_ca_system_score_gemma":0.000654576,"threshold_uncertainty_score":0.9999649},"labels":[],"label_agreement":null},{"id":"W568737822","doi":"","title":"Climate Change and its Potential Impact on Winter-Road Maintenance: Temporal Trends in Hazardous Temperature Days in the United States and Canada","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Climate change; Environmental science; Hazard; Air temperature; Physical geography; Mean radiant temperature; Spatial distribution; Maximum temperature; Climatology; Geography; Meteorology; Ecology; Geology","score_opus":0.023860230251881564,"score_gpt":0.3104489887715985,"score_spread":0.28658875851971694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W568737822","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99479973,0.000065794105,0.0000016115148,0.0027603216,0.0001101996,0.0011763152,0.0008421624,0.000042205276,0.00020167363],"genre_scores_gemma":[0.99750483,0.00038020438,0.00006200652,0.00014584351,0.00010470647,0.00031785073,0.0013650194,0.000047357153,0.00007216774],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99317193,0.0011143546,0.0008163173,0.00088917284,0.0025298998,0.0014782997],"domain_scores_gemma":[0.99871385,0.00029718113,0.00013460267,0.0003042533,0.00027445224,0.0002756305],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00393627,0.0003837311,0.00038335272,0.0011336415,0.0005274053,0.00021389796,0.00039824197,0.00021648651,0.00026110045],"category_scores_gemma":[0.000067074114,0.00029916293,0.00007212106,0.0022507645,0.00060297386,0.00065780414,0.000022824728,0.0012252866,0.00001348154],"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":[0.0017887146,0.00019740823,0.98073584,0.00012527136,0.000014565834,0.00066843524,0.004540337,0.004192939,0.0023978315,0.00036696153,0.003394672,0.0015769955],"study_design_scores_gemma":[0.0014712466,0.00043052773,0.9901494,0.00016227855,0.000009496504,0.0000042764796,0.005138453,0.00091670506,0.00036638774,0.00021298131,0.0008450007,0.0002932502],"about_ca_topic_score_codex":0.90606815,"about_ca_topic_score_gemma":0.95752805,"teacher_disagreement_score":0.051459882,"about_ca_system_score_codex":0.0004549427,"about_ca_system_score_gemma":0.000119107004,"threshold_uncertainty_score":0.99994606},"labels":[],"label_agreement":null},{"id":"W573159193","doi":"","title":"Building Online ITS Research and Training Facility: ITS Centre and Testbed Database and Platform","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Testbed; Computer science; Database; Architecture; Research center; Data center; Software; Scheme (mathematics); Knowledge base; Interface (matter); Systems engineering; World Wide Web; Engineering; Operating system","score_opus":0.0842659758508265,"score_gpt":0.35777366997523763,"score_spread":0.2735076941244111,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W573159193","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9883325,0.0020573048,0.0017907247,0.0011344953,0.0000888807,0.0020420037,0.0020220147,0.0016685507,0.00086349243],"genre_scores_gemma":[0.9894151,0.004378014,0.004292406,0.000025841917,0.00015819521,0.00023361358,0.0009974916,0.0000914464,0.00040787837],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99255735,0.00042844558,0.0010107959,0.0011655674,0.0029720506,0.0018658163],"domain_scores_gemma":[0.9957189,0.0011421395,0.00007152813,0.0004045216,0.0019161296,0.0007468052],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0063307397,0.00045304224,0.00050502794,0.0020450046,0.0011954985,0.00036432288,0.00038646275,0.00033686418,0.00005997372],"category_scores_gemma":[0.00033239,0.00048874447,0.00006623952,0.0018658969,0.000993696,0.00135985,0.000046157704,0.002274261,0.000016347823],"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":[0.0040601487,0.0026078634,0.10138333,0.019986166,0.001046746,0.0021755602,0.061031528,0.009442866,0.23176457,0.17668174,0.0983967,0.29142278],"study_design_scores_gemma":[0.00900859,0.0019836626,0.7036172,0.003081787,0.00015958425,0.0000130998305,0.053194184,0.06697361,0.019679751,0.00631287,0.13316621,0.002809455],"about_ca_topic_score_codex":0.0019840994,"about_ca_topic_score_gemma":0.009752003,"teacher_disagreement_score":0.6022339,"about_ca_system_score_codex":0.00014993318,"about_ca_system_score_gemma":0.00014708616,"threshold_uncertainty_score":0.9997564},"labels":[],"label_agreement":null},{"id":"W574829362","doi":"","title":"Crash, Sled, and Performance Testing of Rear-Facing Securement Systems in Urban Low-Floor Buses for Passengers in Wheelchairs","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Automotive and Human Injury Biomechanics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Wheelchair; Crash; Accelerometer; Engineering; Collision; Hybrid III; Automotive engineering; Crash test; Simulation; Structural engineering; Computer science","score_opus":0.0594524897623075,"score_gpt":0.35211700804449575,"score_spread":0.29266451828218826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W574829362","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99439657,0.00048847107,0.000300807,0.00037028838,0.00009155643,0.003560084,0.00029313486,0.000082391394,0.00041666997],"genre_scores_gemma":[0.9960493,0.00025200378,0.0019367118,0.000020274862,0.00019408723,0.0007090405,0.00037860504,0.000085006075,0.0003749688],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9930107,0.00044808694,0.0016885147,0.00095023087,0.002469026,0.0014334627],"domain_scores_gemma":[0.99511135,0.00091584446,0.0002723688,0.00037036132,0.003009372,0.00032071958],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0064264475,0.0003663612,0.0007876311,0.0023856503,0.0003627025,0.000078311496,0.00025586013,0.00030757967,0.000036411482],"category_scores_gemma":[0.00044106424,0.00037411405,0.00012432472,0.0023212812,0.0005278655,0.000500937,0.000011548738,0.0011648475,0.000007685496],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003380591,0.00077014294,0.9432661,0.0068828827,0.000067746936,0.00016527585,0.008144792,0.0018914309,0.029648593,0.002698759,0.0009337414,0.0021499614],"study_design_scores_gemma":[0.00480174,0.00214633,0.9630219,0.0027451948,0.000041642837,9.631908e-7,0.010023662,0.005528904,0.010129677,0.0003126915,0.0008611109,0.00038619214],"about_ca_topic_score_codex":0.015279944,"about_ca_topic_score_gemma":0.013376733,"teacher_disagreement_score":0.01975581,"about_ca_system_score_codex":0.000332018,"about_ca_system_score_gemma":0.00058649626,"threshold_uncertainty_score":0.9998711},"labels":[],"label_agreement":null},{"id":"W579905602","doi":"","title":"Driver Response Analysis in Car-Following Scenarios Using Differential Global Positioning System","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Traffic control and management","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Headway; Simulation; Advanced driver assistance systems; Acceleration; Computer science; Global Positioning System; Speed limit; Driving simulator; Engineering; Automotive engineering; Transport engineering; Aerospace engineering; Telecommunications","score_opus":0.019593772048406437,"score_gpt":0.3106612583238988,"score_spread":0.29106748627549234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W579905602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98622644,0.0002638499,0.009594383,0.00020117516,0.00030365528,0.0014871795,0.00042718032,0.00066950417,0.0008266395],"genre_scores_gemma":[0.99733794,0.000030250923,0.0013612628,0.000009884223,0.00017737978,0.00028370257,0.0005459383,0.000089531684,0.00016411647],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9904189,0.0012995625,0.0014974307,0.0010471804,0.0036826772,0.002054248],"domain_scores_gemma":[0.9972537,0.00058664253,0.000113683105,0.00056747143,0.0010368573,0.00044163776],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0045881765,0.0005115079,0.0008056671,0.0027710812,0.00074908976,0.00032256832,0.00059495616,0.00034093048,0.00010412823],"category_scores_gemma":[0.000076178985,0.00057236775,0.00054333307,0.00645704,0.0002736437,0.0007333622,0.000017250533,0.0012324206,0.000044217988],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017606574,0.00024016466,0.15360571,0.0005896486,0.00060211134,0.0010365763,0.0025013585,0.82397556,0.0112817725,0.0033061637,0.0004571175,0.00064314256],"study_design_scores_gemma":[0.0025161887,0.0001459676,0.93134695,0.00033025886,0.00033840296,5.5417905e-7,0.0056583467,0.058072608,0.00033302663,0.00010957167,0.0005647366,0.0005833889],"about_ca_topic_score_codex":0.02759437,"about_ca_topic_score_gemma":0.054074567,"teacher_disagreement_score":0.77774125,"about_ca_system_score_codex":0.0014293825,"about_ca_system_score_gemma":0.00026874893,"threshold_uncertainty_score":0.9996728},"labels":[],"label_agreement":null},{"id":"W580991404","doi":"","title":"Measuring Benefits of Adaptive Traffic Signal Control: Case Study of Mill Plain Boulevard, Vancouver, Washington","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Boulevard; Intersection (aeronautics); SIGNAL (programming language); Signal timing; Traffic signal; Adaptive control; Transport engineering; Control (management); Mill; Computer science; Geography; Environmental science; Real-time computing; Engineering; Archaeology; Artificial intelligence","score_opus":0.04609363778497049,"score_gpt":0.2987576315662785,"score_spread":0.252663993781308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W580991404","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98754215,0.00035315705,0.005242692,0.00004193898,0.00020675965,0.003087624,0.00079774595,0.0017045176,0.0010234049],"genre_scores_gemma":[0.9976633,0.00016421104,0.0011706585,0.0000069201756,0.00012681453,0.0005046828,0.00013765665,0.00013247957,0.000093229755],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99091643,0.0008946718,0.0019379428,0.0008302136,0.004114555,0.0013061707],"domain_scores_gemma":[0.9949559,0.0009028627,0.0002608057,0.0005675142,0.0029473666,0.00036553887],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005346579,0.0004896247,0.0008201476,0.0021694032,0.00047253096,0.000064661384,0.000618185,0.00031577074,0.00006823807],"category_scores_gemma":[0.000083758416,0.00053140544,0.00025759693,0.0022105142,0.0004953762,0.000714245,0.000012988143,0.0014208193,0.0000079502815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021793477,0.0025950852,0.02197629,0.0016278672,0.0006199966,0.0013553037,0.018566271,0.90674454,0.0028555626,0.0020527036,0.025029568,0.014397449],"study_design_scores_gemma":[0.034302168,0.0147596495,0.53577477,0.0025646528,0.00092337705,0.000021358685,0.23288497,0.13492782,0.032718834,0.0008842306,0.0065127118,0.003725469],"about_ca_topic_score_codex":0.019449685,"about_ca_topic_score_gemma":0.12826456,"teacher_disagreement_score":0.77181673,"about_ca_system_score_codex":0.00021048753,"about_ca_system_score_gemma":0.00017357813,"threshold_uncertainty_score":0.9997138},"labels":[],"label_agreement":null},{"id":"W627730921","doi":"","title":"Age-Based Analysis of Travel by Children in Calgary, Canada","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Travel behavior; Geography; Travel time; Leisure time; Mode choice; Psychology; Demography; Advertising; Transport engineering; Sociology; Physical activity; Public transport; Business; Medicine; Engineering","score_opus":0.031184705247467012,"score_gpt":0.35950781607725446,"score_spread":0.32832311082978743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W627730921","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9897491,0.00030923684,0.00050771295,0.0016484006,0.000086128195,0.0017486239,0.0017906025,0.00008519756,0.0040750373],"genre_scores_gemma":[0.99387413,0.00007902331,0.00044495534,0.00007584156,0.00009923807,0.00023570219,0.003847442,0.00005528585,0.0012884062],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98612195,0.0018257293,0.0018946715,0.0012320586,0.0068114405,0.0021141632],"domain_scores_gemma":[0.9943809,0.0013793758,0.0003101781,0.0006086149,0.0026902375,0.0006306787],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.007977572,0.00039797876,0.0009552791,0.002507525,0.0009919103,0.00013361512,0.0011396874,0.00040804784,0.0007287935],"category_scores_gemma":[0.00028104332,0.00043388153,0.0003819089,0.010585739,0.0018412374,0.0005940351,0.000006427917,0.0015085328,0.000006498726],"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":[0.00046437036,0.00058814493,0.9826428,0.00012126163,0.00018163043,0.00011736803,0.003773862,0.0027193993,0.0007877162,0.002850375,0.00529161,0.00046145936],"study_design_scores_gemma":[0.0012788025,0.000116396084,0.98837614,0.00007951603,0.0001522801,8.233379e-9,0.004266818,0.00026912615,0.0014120941,0.0004953284,0.003147988,0.0004055295],"about_ca_topic_score_codex":0.9908744,"about_ca_topic_score_gemma":0.9980398,"teacher_disagreement_score":0.008258978,"about_ca_system_score_codex":0.0006803091,"about_ca_system_score_gemma":0.0038732209,"threshold_uncertainty_score":0.9998113},"labels":[],"label_agreement":null},{"id":"W629106418","doi":"","title":"Spatial Variety in Weekly, Weekday-to-Weekend, and Day-to-Day Patterns of Activity-Travel Behavior: Initial Results from Toronto Travel-Activity Panel Survey","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Travel behavior; Flexibility (engineering); Travel survey; Geography; Variety (cybernetics); Spatial ecology; Psychology; Computer science; Transport engineering; Ecology; Statistics; Engineering","score_opus":0.09632988109739747,"score_gpt":0.40275033401753146,"score_spread":0.306420452920134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W629106418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9762632,0.000059199487,0.003702053,0.0012932401,0.00031249496,0.0037359037,0.013162112,0.00011816392,0.0013535806],"genre_scores_gemma":[0.9958105,0.0001592897,0.00052471156,0.000039270915,0.00044768432,0.00055059005,0.0018057305,0.00010711918,0.0005551095],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98209214,0.0050894367,0.002078515,0.0022590102,0.0059433933,0.002537532],"domain_scores_gemma":[0.98984593,0.004461005,0.0004042125,0.00088500476,0.0030350965,0.0013687408],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.019069608,0.0006567579,0.0011773932,0.0011163604,0.0012066013,0.00030852703,0.0011792448,0.0007303836,0.0004641004],"category_scores_gemma":[0.0013264357,0.000737237,0.00027220137,0.0025284893,0.0011834617,0.0017089293,0.000039016493,0.001878902,0.000027826967],"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":[0.0050927326,0.001621586,0.92933095,0.00017915478,0.000055486053,0.00016453798,0.04439621,0.00011888221,0.00943695,0.0003974522,0.00038850747,0.008817576],"study_design_scores_gemma":[0.0026548766,0.00064818637,0.9781331,0.00025169973,0.000046518533,4.7829303e-8,0.010533433,0.00004413954,0.006024138,0.00028197042,0.0006894428,0.00069248595],"about_ca_topic_score_codex":0.9461202,"about_ca_topic_score_gemma":0.98011893,"teacher_disagreement_score":0.048802137,"about_ca_system_score_codex":0.0006520055,"about_ca_system_score_gemma":0.0015386026,"threshold_uncertainty_score":0.99950784},"labels":[],"label_agreement":null},{"id":"W636413766","doi":"","title":"Groundside Interview Survey Concepts and Design: Toronto Pearson International Airport, June 2005","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Data collection; Transport engineering; Survey data collection; Schedule; International airport; Operations research; Computer science; Engineering; Geography; Statistics","score_opus":0.13908055251226167,"score_gpt":0.3786503701220191,"score_spread":0.2395698176097574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W636413766","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89337915,0.010622136,0.038205717,0.014126608,0.0016846914,0.0036208087,0.0063838954,0.0005380525,0.031438947],"genre_scores_gemma":[0.98030037,0.0016368103,0.0018561993,0.00010185324,0.00037680092,0.0003245539,0.0022177275,0.00009084275,0.013094848],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99248993,0.0010751446,0.0021702508,0.0014503637,0.0013444631,0.0014698668],"domain_scores_gemma":[0.99551946,0.0009429469,0.000561579,0.0005699813,0.00186934,0.00053667405],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0148533555,0.00044093153,0.00079758157,0.001054611,0.0008266219,0.00044654982,0.00074980257,0.0004132172,0.0034551155],"category_scores_gemma":[0.0003979298,0.0005072127,0.0002597493,0.0013393549,0.00069327705,0.0016772173,0.000027735483,0.0012367013,0.00029598165],"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":[0.0007612252,0.00076893443,0.82006484,0.00023859047,0.0004308804,0.00016413908,0.0040122694,0.0019613993,0.00015221714,0.09253698,0.076069124,0.0028394046],"study_design_scores_gemma":[0.0015294765,0.00022887968,0.88771534,0.00010984077,0.000021567754,9.153338e-7,0.002357032,0.0009576823,0.00014132286,0.005431324,0.100972675,0.00053397345],"about_ca_topic_score_codex":0.091510795,"about_ca_topic_score_gemma":0.15821487,"teacher_disagreement_score":0.087105654,"about_ca_system_score_codex":0.00047424182,"about_ca_system_score_gemma":0.00020584307,"threshold_uncertainty_score":0.999738},"labels":[],"label_agreement":null},{"id":"W640397212","doi":"","title":"Data Organization Pattern for Microscopic Freight Demand Models","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Market segmentation; Commodity; Supply and demand; Industrial organization; Commodity market; Operations research; Economics; Computer science; Business; Microeconomics; Engineering; Finance","score_opus":0.10361310295082042,"score_gpt":0.33630820852411913,"score_spread":0.2326951055732987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W640397212","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4615389,0.0014306536,0.51463723,0.0007158094,0.00064907456,0.004115183,0.013033167,0.00133003,0.0025499633],"genre_scores_gemma":[0.9736316,0.0006297805,0.005861676,0.00004810293,0.0005956483,0.00037248287,0.017817583,0.00029487582,0.0007482036],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9918839,0.00033188393,0.0015630181,0.0013742627,0.0027684974,0.0020784903],"domain_scores_gemma":[0.9934576,0.000881176,0.00012731252,0.0013042254,0.0037051744,0.0005244919],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0034929444,0.000586025,0.0006476511,0.0011563599,0.0009920999,0.0003063813,0.0015419269,0.0005249356,0.0002672039],"category_scores_gemma":[0.00013879358,0.0006276793,0.0001556821,0.002459182,0.00067690946,0.0014289862,0.000019997167,0.0014044188,0.0001001915],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010829984,0.0018213168,0.27297175,0.007905568,0.00082875625,0.0006033699,0.009574789,0.29369465,0.031774826,0.051100224,0.31986472,0.008777053],"study_design_scores_gemma":[0.010460728,0.001191563,0.5909582,0.0010029348,0.00045879383,0.0000032955381,0.0046767406,0.1886213,0.023711259,0.028713314,0.1464358,0.0037660764],"about_ca_topic_score_codex":0.004293574,"about_ca_topic_score_gemma":0.023400566,"teacher_disagreement_score":0.5120927,"about_ca_system_score_codex":0.00023681384,"about_ca_system_score_gemma":0.00034951876,"threshold_uncertainty_score":0.99961746},"labels":[],"label_agreement":null},{"id":"W648111471","doi":"","title":"Freeway Travel Time Prediction and Route Recommendation via Cell Phone","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Testbed; Phone; The Internet; Travel time; Real-time computing; Wireless; Real-time data; Interface (matter); Service (business); Transport engineering; Traffic congestion; Computer network; Telecommunications; Engineering; World Wide Web","score_opus":0.01870814263311337,"score_gpt":0.28344045053881584,"score_spread":0.26473230790570246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W648111471","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8578592,0.0005135439,0.09756717,0.0015655519,0.0005383521,0.0039426843,0.002100665,0.0068524615,0.029060371],"genre_scores_gemma":[0.9909572,0.000847482,0.0031422258,0.00003458271,0.00029271454,0.0005677406,0.0026722325,0.00014130991,0.0013445322],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9939354,0.00048667434,0.0011745568,0.00089739886,0.0021596288,0.0013463587],"domain_scores_gemma":[0.9974574,0.00038255544,0.00011104405,0.00041796343,0.0011823968,0.00044866622],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003512,0.00045021623,0.000443311,0.0016083797,0.00071656454,0.00021574588,0.00039022678,0.0003894042,0.00035770205],"category_scores_gemma":[0.000041017356,0.00050558517,0.00014555198,0.0017218379,0.0004533769,0.0011328853,0.000013644471,0.0014430393,0.00019235413],"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":[0.0014635043,0.0016240916,0.057510704,0.003151431,0.0003987578,0.00023340527,0.009917946,0.019703493,0.18921445,0.006718222,0.64112705,0.06893693],"study_design_scores_gemma":[0.004195467,0.00087314774,0.8095883,0.00029377296,0.00011588507,0.0000020926166,0.0035651082,0.05968491,0.03361174,0.0021127171,0.084727414,0.0012294446],"about_ca_topic_score_codex":0.004765354,"about_ca_topic_score_gemma":0.0041117324,"teacher_disagreement_score":0.7520776,"about_ca_system_score_codex":0.0002695713,"about_ca_system_score_gemma":0.00010163697,"threshold_uncertainty_score":0.9997396},"labels":[],"label_agreement":null},{"id":"W651670351","doi":"","title":"Effects of Winter Weather and Maintenance Treatments on Highway Safety","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Highway maintenance; Transport engineering; Snow; Crash; Engineering; Meteorology; Computer science; Geography","score_opus":0.014352410958118282,"score_gpt":0.2941335734512942,"score_spread":0.2797811624931759,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W651670351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99356526,0.000057120633,0.0002928531,0.00050164707,0.00018687098,0.0017009893,0.00022947096,0.00011362356,0.0033521333],"genre_scores_gemma":[0.99654955,0.00016081217,0.001248902,0.000037427726,0.00010516541,0.0002809604,0.00015957541,0.000072798175,0.001384798],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99319696,0.00079858676,0.000960671,0.0009981691,0.0028696842,0.0011759495],"domain_scores_gemma":[0.997673,0.0009145066,0.00020769227,0.0004255269,0.0004540672,0.00032520448],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0023573828,0.0003674504,0.00046541743,0.00054405653,0.0005430857,0.000074234515,0.00038343674,0.00024020438,0.00063794025],"category_scores_gemma":[0.00015521848,0.00033554665,0.00014887392,0.0011265165,0.0015294857,0.0005600542,0.00002192141,0.0006499755,0.0002579793],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003989297,0.0008793333,0.8689954,0.000571375,0.00011952096,0.00020373792,0.0033798376,0.0011615522,0.10172775,0.007191765,0.0077633755,0.0040170494],"study_design_scores_gemma":[0.002184037,0.0007769886,0.9425642,0.00023427363,0.000034962744,7.59281e-7,0.0005760755,0.000039468145,0.044095416,0.00225342,0.0069535724,0.00028684174],"about_ca_topic_score_codex":0.0209297,"about_ca_topic_score_gemma":0.010250629,"teacher_disagreement_score":0.073568776,"about_ca_system_score_codex":0.0003166895,"about_ca_system_score_gemma":0.00007313111,"threshold_uncertainty_score":0.99990964},"labels":[],"label_agreement":null},{"id":"W65289889","doi":"","title":"Protecting Critical Infrastructure by Blocking Suspicious Vehicle with Probabilistic Route Choice Behavior","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Traffic and Road Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Blocking (statistics); Computer science; Probabilistic logic; Block (permutation group theory); Path (computing); Reliability (semiconductor); Scheme (mathematics); Monte Carlo method; Mathematical optimization; Computer network; Artificial intelligence","score_opus":0.018788058540910427,"score_gpt":0.3167470598232971,"score_spread":0.29795900128238667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W65289889","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99041176,0.00035068428,0.002159119,0.0005067186,0.00021717318,0.0028110147,0.0007097269,0.0010977112,0.0017360925],"genre_scores_gemma":[0.99447894,0.00005131324,0.0024143965,0.000022521948,0.0004430337,0.0013013826,0.0006711557,0.00022192324,0.00039536168],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9906192,0.00066948234,0.0012418006,0.0011502267,0.0038919642,0.002427331],"domain_scores_gemma":[0.99369293,0.0014916074,0.00010316441,0.00058787764,0.0034734001,0.0006510265],"candidate_categories":["metaepi_narrow","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0027630448,0.0006110302,0.0005976407,0.0007963382,0.0015160547,0.00029380526,0.00067422254,0.00049586303,0.00020067848],"category_scores_gemma":[0.00053631654,0.00057769276,0.00017229935,0.0023755978,0.001067516,0.0008284515,0.000012689845,0.0036298288,0.000051263338],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016780546,0.0013022401,0.6401362,0.0038662073,0.00029124093,0.0009374811,0.011561732,0.27499202,0.022049632,0.0066763577,0.02393613,0.0125727095],"study_design_scores_gemma":[0.0025716356,0.00084276305,0.9602699,0.0005000859,0.00011769165,0.0000028189993,0.0043021757,0.0045302655,0.0049060755,0.00056385127,0.020260649,0.0011320559],"about_ca_topic_score_codex":0.0080835745,"about_ca_topic_score_gemma":0.016132759,"teacher_disagreement_score":0.32013375,"about_ca_system_score_codex":0.000428044,"about_ca_system_score_gemma":0.00037742234,"threshold_uncertainty_score":0.9997838},"labels":[],"label_agreement":null},{"id":"W658833082","doi":"","title":"Work Trips: Are There Still Gender Differences? Case of Quebec Metropolitan Area, 1991 and 2001","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Metropolitan area; Work (physics); Demographic economics; Journey to work; Distribution (mathematics); Geography; Demography; Sociology; Economics; Public transport; Transport engineering; Mathematics; Engineering","score_opus":0.097073166274176,"score_gpt":0.39427332444386215,"score_spread":0.29720015816968615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W658833082","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98832273,0.001372367,0.0002606854,0.0012732936,0.00015424257,0.0019832568,0.0008750903,0.00021208085,0.005546262],"genre_scores_gemma":[0.993531,0.00044859303,0.000952119,0.00003184757,0.00032877785,0.00026223622,0.00038248242,0.0000798015,0.0039831414],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9877533,0.002165737,0.0017247907,0.0014097254,0.004509441,0.0024370372],"domain_scores_gemma":[0.99159867,0.0019000899,0.00049493083,0.0006866257,0.0043101436,0.0010095423],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.008520666,0.0005246388,0.00090749416,0.0013835897,0.0018547799,0.00030762103,0.00083897315,0.0005727402,0.001163538],"category_scores_gemma":[0.0005376068,0.00050117663,0.00032625298,0.004085633,0.0039695227,0.0012187469,0.000016412923,0.0017213081,0.00002307585],"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":[0.00085717137,0.0006059002,0.9625239,0.00048283354,0.000099361896,0.0012525102,0.015337469,0.00005004187,0.00019590961,0.013273394,0.0040052896,0.0013162269],"study_design_scores_gemma":[0.0012629678,0.00018993094,0.9031696,0.00023765134,0.000072672185,5.7572794e-7,0.0838206,0.000023068833,0.00022401576,0.0054003396,0.0051115276,0.00048709384],"about_ca_topic_score_codex":0.66867363,"about_ca_topic_score_gemma":0.842126,"teacher_disagreement_score":0.17345239,"about_ca_system_score_codex":0.00050435873,"about_ca_system_score_gemma":0.0009230651,"threshold_uncertainty_score":0.99974954},"labels":[],"label_agreement":null},{"id":"W67186546","doi":"","title":"Effect of Geometry of Entrance Terminals on Freeway Merging Behavior","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Traffic control and management","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Merge (version control); Lagging; Acceleration; Geometric design; Upstream (networking); Geometry; Computer science; Transport engineering; Simulation; Engineering; Mathematics; Physics; Telecommunications","score_opus":0.016544581670384157,"score_gpt":0.3254484257201317,"score_spread":0.3089038440497476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W67186546","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9929201,0.00047799974,0.000545822,0.00013290813,0.00020328141,0.0020557328,0.0005213702,0.0002736245,0.0028691376],"genre_scores_gemma":[0.9978376,0.00023812735,0.00042326935,0.0000065579534,0.0001328852,0.0006315858,0.00026290314,0.00009884863,0.00036824105],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99218893,0.00065880344,0.0014513002,0.00068104715,0.0036679595,0.0013519753],"domain_scores_gemma":[0.9961108,0.0015154844,0.00017764172,0.000600137,0.0013010825,0.00029486234],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0050804936,0.0004279044,0.00077683595,0.0018863869,0.0002527605,0.000049041235,0.0006408948,0.00024632466,0.00021795147],"category_scores_gemma":[0.00014020031,0.00041719002,0.00032829517,0.0021563084,0.0005611459,0.00036762166,0.000008727154,0.0010917857,0.00003494966],"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":[0.00695736,0.0023467285,0.21671592,0.014538144,0.00072383374,0.00080270617,0.0074337726,0.39182612,0.20376198,0.019280981,0.012906531,0.12270593],"study_design_scores_gemma":[0.0038062618,0.002681266,0.8554056,0.00074355473,0.00015455284,3.6538123e-7,0.0011477422,0.0011893671,0.12768923,0.00017926749,0.006413195,0.00058954593],"about_ca_topic_score_codex":0.004280776,"about_ca_topic_score_gemma":0.0033278272,"teacher_disagreement_score":0.63868976,"about_ca_system_score_codex":0.0001384051,"about_ca_system_score_gemma":0.00010188754,"threshold_uncertainty_score":0.999828},"labels":[],"label_agreement":null},{"id":"W73491776","doi":"","title":"Intelligent Transportation Systems Investment Evaluation: To Purchase or Lease","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Life Cycle Costing Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Lease; Asset management; Investment (military); Asset (computer security); Net present value; Order (exchange); Computer science; Return on investment; Term (time); Risk analysis (engineering); Operations research; Transport engineering; Actuarial science; Business; Operations management; Finance; Engineering; Economics; Production (economics); Computer security","score_opus":0.11356369019889653,"score_gpt":0.38484844068243107,"score_spread":0.2712847504835345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W73491776","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9760497,0.00046900817,0.0038230706,0.0047201724,0.0006730739,0.0064674183,0.00048789915,0.00064703246,0.0066625844],"genre_scores_gemma":[0.9860353,0.00006743385,0.0013045355,0.00081879855,0.002142655,0.0029393872,0.0036306356,0.0002083942,0.002852868],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9817138,0.00076273584,0.0025903194,0.0020934276,0.010073731,0.0027660036],"domain_scores_gemma":[0.98485994,0.00085734937,0.00055497634,0.001138918,0.012111221,0.000477586],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.015467258,0.00079969346,0.0009133585,0.0045221774,0.0019179046,0.0012341357,0.0012587137,0.0004155583,0.0014067312],"category_scores_gemma":[0.0013785163,0.000763277,0.00041506445,0.00873083,0.00062316726,0.0030365237,0.000029380164,0.0015852118,0.0017380695],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010760893,0.0044179466,0.2677256,0.0055632293,0.00088876754,0.001786993,0.010520296,0.34541026,0.0077441656,0.15274827,0.17144473,0.02098887],"study_design_scores_gemma":[0.0057595493,0.0007434982,0.556679,0.0012505087,0.0007295512,0.0000013029212,0.024950884,0.019296618,0.0013725726,0.0066013755,0.3802062,0.0024089508],"about_ca_topic_score_codex":0.0979105,"about_ca_topic_score_gemma":0.06922365,"teacher_disagreement_score":0.32611364,"about_ca_system_score_codex":0.00072325167,"about_ca_system_score_gemma":0.00087743485,"threshold_uncertainty_score":0.9998027},"labels":[],"label_agreement":null},{"id":"W752194057","doi":"","title":"Climate Impacts and Adaptations on Roads in Northern Canada","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Climate change; Permafrost; Precipitation; Environmental science; Flooding (psychology); Cold climate; Physical geography; Climatology; Geography; Hydrology (agriculture); Geology; Meteorology; Oceanography","score_opus":0.02280337211402372,"score_gpt":0.30303635303082554,"score_spread":0.2802329809168018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W752194057","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9937026,0.00005999149,0.000027264423,0.0014009121,0.00017541916,0.001257621,0.00037199937,0.000094937386,0.0029092534],"genre_scores_gemma":[0.99806213,0.00016594636,0.0006833035,0.00007002642,0.00011277764,0.0002936493,0.00038807478,0.00007090727,0.00015320124],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9918267,0.0007925745,0.0010563008,0.0010344271,0.003561169,0.0017288089],"domain_scores_gemma":[0.9977749,0.0006862218,0.0001665344,0.00043349995,0.0004653995,0.00047343798],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003544548,0.00036252092,0.00038569575,0.0006995829,0.0008330583,0.00015204129,0.00039259405,0.00021380605,0.00050554995],"category_scores_gemma":[0.00021245143,0.0003758049,0.00007722845,0.0019447127,0.0008058852,0.0007018592,0.000022260008,0.0010333383,0.00016385893],"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":[0.0005738259,0.0001621982,0.98111707,0.00009682456,0.0000113601145,0.00016445745,0.0012393838,0.0072661103,0.004724086,0.0015745758,0.0015858313,0.001484299],"study_design_scores_gemma":[0.0011291183,0.0002701275,0.9890444,0.00013966698,0.000009900858,9.925452e-7,0.0024854145,0.00021637579,0.0016375888,0.0007608895,0.003957129,0.0003483507],"about_ca_topic_score_codex":0.89824927,"about_ca_topic_score_gemma":0.9962918,"teacher_disagreement_score":0.09804255,"about_ca_system_score_codex":0.0008283896,"about_ca_system_score_gemma":0.00044758123,"threshold_uncertainty_score":0.9998694},"labels":[],"label_agreement":null},{"id":"W757701294","doi":"","title":"Temporal Transferability and Updating of Safety Planning Models","year":2006,"lang":"en","type":"article","venue":"Transportation Research Board 85th Annual MeetingTransportation Research Board","topic":"Traffic and Road Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transferability; Calibration; Context (archaeology); Bayesian probability; Computer science; Sample (material); Statistical model; Sensitivity (control systems); Predictive modelling; Econometrics; Data mining; Machine learning; Statistics; Artificial intelligence; Geography; Engineering; Mathematics","score_opus":0.04219145936165196,"score_gpt":0.32800816334612154,"score_spread":0.28581670398446957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W757701294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9785404,0.0008273075,0.011412489,0.00033587022,0.0001256655,0.0013230182,0.0007760082,0.000512394,0.0061467974],"genre_scores_gemma":[0.99415547,0.0003546415,0.0042622318,0.0000100157995,0.0001476747,0.000149585,0.0006479015,0.00011642352,0.00015607662],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99245226,0.00061133725,0.0017348542,0.00086086045,0.0028292465,0.0015114084],"domain_scores_gemma":[0.99628496,0.00097600283,0.000107347514,0.0004803705,0.0016997172,0.000451603],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0052222754,0.00044692316,0.00070971786,0.0009981011,0.00071508763,0.00008685418,0.0004641826,0.0003883197,0.00011421016],"category_scores_gemma":[0.00007409718,0.00046178824,0.00020331028,0.001752281,0.0009886259,0.000955463,0.000010030525,0.0017025506,0.000011528288],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001993361,0.0004963269,0.29420742,0.003286272,0.00023587201,0.0001623831,0.019860873,0.6218307,0.007391573,0.03931723,0.0032677744,0.007950237],"study_design_scores_gemma":[0.0026880999,0.00045304798,0.94437015,0.0005393218,0.000054792108,0.0000011694261,0.011978086,0.024132982,0.0040845247,0.006528339,0.00435349,0.00081598916],"about_ca_topic_score_codex":0.007107425,"about_ca_topic_score_gemma":0.0068842885,"teacher_disagreement_score":0.65016276,"about_ca_system_score_codex":0.00015472976,"about_ca_system_score_gemma":0.00024508595,"threshold_uncertainty_score":0.9997834},"labels":[],"label_agreement":null}]}