{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":42,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":42,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"04caa2223bcc","filters":{"venue":"Transportation Planning and Technology"}},"results":[{"id":"W1965106804","doi":"10.1080/03081060500322599","title":"A Trip Reconstruction Tool for GPS-based Personal Travel Surveys","year":2005,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":160,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto","funders":"","keywords":"Global Positioning System; Transport engineering; TRIPS architecture; Map matching; Modal; Matching (statistics); Travel survey; Respondent; Computer science; Downtown; Travel behavior; Software; Geography; Engineering; Telecommunications; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.02263479197427972,"gpt":0.2973810975346593,"spread":0.2747463055603796,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008220739,0.00007331442,0.0001322079,0.0002382117,0.0004581558,0.00002080162,0.00006085867,0.0001805018,0.0001050707],"category_scores_gemma":[0.00007675232,0.00008023026,0.00004685689,0.000322343,0.0002547328,0.00008965096,3.851853e-7,0.00009866911,0.000003026326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003277382,"about_ca_system_score_gemma":0.0001287515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003772034,"about_ca_topic_score_gemma":0.005189905,"domain_scores_codex":[0.9992589,0.00006691657,0.0001999258,0.0002046618,0.0001028334,0.0001668039],"domain_scores_gemma":[0.9995813,0.0001438971,0.00007120554,0.00006063973,0.0001079881,0.000034915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00007321985,0.0001242244,0.2492778,0.00006004665,0.00006889168,0.000002307296,0.01281121,0.0009429875,0.0006640214,0.02027529,0.000164926,0.7155351],"study_design_scores_gemma":[0.009452267,0.0008449164,0.7410422,0.000343098,0.000774627,0.00000851639,0.06879803,0.08186112,0.007907546,0.02229278,0.06467576,0.001999173],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8691348,0.0001318027,0.1256548,0.004360755,0.00004776777,0.0002188915,0.00004716222,0.0001779042,0.0002261605],"genre_scores_gemma":[0.997619,0.00000840438,0.001809329,0.00006924637,0.00006443469,0.00005924349,0.0001151054,0.000005345865,0.0002498615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7135359,"threshold_uncertainty_score":0.352381,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2062433653","doi":"10.1080/715020598","title":"Impact of telecommuting and intelligent transportation systems on residential location choice","year":2003,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":50,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Carleton University","funders":"Science and Engineering Research Board; Natural Sciences and Engineering Research Council of Canada","keywords":"Telecommuting; Mixed logit; Discrete choice; Logit; Preference; Transport engineering; Transportation planning; Estimation; Choice modelling; Urban planning; Public transport; Computer science; Business; Logistic regression; Econometrics; Economics; Engineering; Marketing; Microeconomics; Civil engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.02372102902478775,"gpt":0.3317951124801324,"spread":0.3080740834553446,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003317032,0.0001094467,0.000188178,0.0002353607,0.0002371329,0.00002251105,0.00007262815,0.0001852246,0.00001623316],"category_scores_gemma":[0.00006451152,0.0001058739,0.00003083204,0.0004732585,0.0002333606,0.0001492472,4.13053e-7,0.0001558987,6.187226e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002797233,"about_ca_system_score_gemma":0.0000838258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002834691,"about_ca_topic_score_gemma":0.001678675,"domain_scores_codex":[0.9990327,0.00005162527,0.0003489989,0.0002257686,0.0001560321,0.0001849018],"domain_scores_gemma":[0.9994496,0.00009746521,0.0001722186,0.0001022926,0.0001239128,0.00005449728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002546206,0.00004306256,0.9785208,0.0000538241,0.00002524103,0.000002932796,0.003800495,0.0005206637,0.0002994982,0.01540546,0.00001022226,0.001292402],"study_design_scores_gemma":[0.0003270395,0.000150702,0.9941938,0.0001166971,0.00004522778,4.056455e-7,0.002745174,0.00004238425,0.0008521201,0.00105835,0.0003391761,0.0001289445],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996358,0.0008047679,0.001981828,0.000081295,0.00008014504,0.0002159176,0.00001649457,0.0001048535,0.0003566933],"genre_scores_gemma":[0.9996937,0.00005507951,0.0001198669,0.000004338905,0.00001635613,0.00001139101,0.00005116229,0.000008037126,0.0000400776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01567304,"threshold_uncertainty_score":0.4317412,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2016903344","doi":"10.1080/03081060802364505","title":"Imputation of Missing Traffic Data during Holiday Periods","year":2008,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada; University of Regina","keywords":"Adaptability; Imputation (statistics); Transport engineering; Computer science; Parametric statistics; Data collection; Regression; Missing data; Data mining; Engineering; Statistics; Mathematics; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.01793496878795373,"gpt":0.2359108532562329,"spread":0.2179758844682792,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047338,0.00008293167,0.0001223412,0.0002877495,0.00007223685,0.000004491037,0.0001072856,0.00009470351,0.000002922236],"category_scores_gemma":[0.000004648254,0.00009253828,0.00001047606,0.0002213728,0.00007754061,0.0001382127,0.000004743806,0.0001020138,6.288405e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006363729,"about_ca_system_score_gemma":0.000006406438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002200036,"about_ca_topic_score_gemma":0.000002877649,"domain_scores_codex":[0.9994841,0.000003844682,0.0001981439,0.0001421834,0.0000659003,0.000105822],"domain_scores_gemma":[0.9997524,0.00000830259,0.00003486796,0.0001658511,0.00001680166,0.00002176211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001589516,0.0003007633,0.1204215,0.002725849,0.0006868367,0.001207171,0.02172664,0.2065352,0.1206872,0.006352538,0.01046991,0.5087275],"study_design_scores_gemma":[0.002765703,0.0002162732,0.578272,0.0004431799,0.0001859301,0.0004445893,0.002170875,0.3619033,0.0466307,0.0003686353,0.005647065,0.0009516952],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9504061,0.0004739225,0.04520079,0.00007601432,0.0000526362,0.00007476576,0.00002308468,0.003521204,0.0001715108],"genre_scores_gemma":[0.9959961,0.0001522076,0.003679875,0.000003996398,0.000008694804,0.000005781127,0.0001319133,0.00001321079,0.000008292635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5077758,"threshold_uncertainty_score":0.3773602,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2035670852","doi":"10.1080/03081060008717659","title":"Estimation of time‐dependent, stochastic route travel times using artificial neural networks","year":2000,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Waterloo","funders":"","keywords":"Artificial neural network; Travel time; Estimation; Computer science; Transport engineering; Engineering; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.008304728214769465,"gpt":0.2190699148662046,"spread":0.2107651866514351,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004869196,0.00009634202,0.0001334859,0.0002035084,0.00004271252,0.000007941117,0.00005162959,0.00012151,0.00003828818],"category_scores_gemma":[0.000001823043,0.0001079521,0.00001666298,0.0001857039,0.00005527616,0.00008811045,0.000001149672,0.0001140263,0.00000190612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008548193,"about_ca_system_score_gemma":0.000003122502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007947498,"about_ca_topic_score_gemma":0.000003077309,"domain_scores_codex":[0.9994774,0.000005032767,0.0002210107,0.0001109766,0.00006385839,0.0001216702],"domain_scores_gemma":[0.9998518,0.00001131376,0.00003152562,0.00007358682,0.00001107795,0.0000206823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001050912,0.000009230894,0.0001194139,0.00001600701,0.00001960568,0.000003623983,0.00008746107,0.9270347,0.000712471,0.001042007,0.00006205823,0.07088289],"study_design_scores_gemma":[0.000140235,0.00003265165,0.001357554,0.00003051687,0.00004349776,0.000005753387,0.00004555419,0.9969113,0.0009434593,0.0003872683,0.00001025545,0.00009191585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4284664,0.0001218114,0.5694464,0.00002226186,0.00003965349,0.00009470035,0.00001291876,0.001573679,0.0002222034],"genre_scores_gemma":[0.9985086,0.00001306765,0.001344689,0.000006212682,0.00001127327,0.000006463708,0.00006883308,0.00001371265,0.00002711507],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5700423,"threshold_uncertainty_score":0.4402157,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4396617936","doi":"10.1080/03081060.2024.2348713","title":"Systematic review and research gaps on wildfire evacuations: infrastructure, transportation modes, networks, and planning","year":2024,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Transport engineering; Environmental planning; Geography; Business; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01407127550324491,"gpt":0.2958397439549198,"spread":0.2817684684516749,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003662307,0.000175055,0.0003142215,0.0004701485,0.0001447635,0.00006326212,0.00006218621,0.0002086336,0.0000044467],"category_scores_gemma":[0.00003992606,0.0001646867,0.00001858844,0.0006030076,0.00009465727,0.0001557127,0.000001718955,0.000465043,0.000001866572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002419143,"about_ca_system_score_gemma":0.00001590313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004230891,"about_ca_topic_score_gemma":0.00001224535,"domain_scores_codex":[0.9989178,0.00003128014,0.0004026123,0.0002704323,0.0001704491,0.000207423],"domain_scores_gemma":[0.9995598,0.0001656226,0.00003508079,0.0001292783,0.00005107362,0.00005918168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007261029,0.00005520703,0.02716422,0.4506125,0.001036841,0.0003380036,0.009837498,0.2976426,0.001112902,0.1970757,0.004546915,0.01050493],"study_design_scores_gemma":[0.0009921726,0.00029479,0.04534234,0.1210076,0.001155504,0.00008607981,0.003388712,0.8104931,0.0001499719,0.01532243,0.0007168851,0.001050492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5922796,0.3795337,0.02395881,0.0008297085,0.0001588869,0.001232251,0.00008794879,0.001645286,0.0002737941],"genre_scores_gemma":[0.9895895,0.009564291,0.0003309865,0.00006718202,0.00001651395,0.0001172542,0.0002489256,0.00003200617,0.00003336632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5128504,"threshold_uncertainty_score":0.6715729,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2902266504","doi":"10.1080/03081060.2018.1541279","title":"Validation of an agent-based microscopic pedestrian simulation model in a crowded pedestrian walking environment","year":2018,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of British Columbia; McMaster University","funders":"","keywords":"Pedestrian; Computer science; Simulation; Downtown; Calibration; Artificial intelligence; Transport engineering; Engineering; Statistics; Mathematics; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.01541875205711673,"gpt":0.2596092468974919,"spread":0.2441904948403751,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009422129,0.0001004255,0.0001260049,0.0003327731,0.00004278938,0.000009729824,0.00005557048,0.0001554481,0.00001140809],"category_scores_gemma":[0.000007625277,0.0001187364,0.00001292391,0.0001955459,0.00006416934,0.000104661,0.000001295885,0.00009460624,0.000001675191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002706501,"about_ca_system_score_gemma":0.00001654073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001158962,"about_ca_topic_score_gemma":0.00005115921,"domain_scores_codex":[0.9993559,0.00001107495,0.0002817893,0.0001483313,0.00007893094,0.0001240301],"domain_scores_gemma":[0.999756,0.00001998458,0.00005887691,0.0001151651,0.00002278279,0.00002724017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001887528,0.00002507189,0.02481534,0.00005071901,0.000005810184,0.000002211973,0.000767253,0.9477756,0.02371923,0.0001666003,7.837832e-7,0.002652537],"study_design_scores_gemma":[0.0007977177,0.00008329002,0.01736093,0.00004270763,0.00001583644,4.11216e-7,0.0001813803,0.9505392,0.03016721,0.0006773792,0.00002069453,0.0001132101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8671756,0.00004767023,0.1323957,0.0000315154,0.00002799467,0.0001125075,0.00001357041,0.0001582067,0.00003725435],"genre_scores_gemma":[0.9950253,0.0000072645,0.004732829,0.000008910563,0.000008354561,0.00001118492,0.0001842536,0.00001545517,0.000006475501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1278497,"threshold_uncertainty_score":0.4841931,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3192144090","doi":"10.1080/03081060.2021.1956806","title":"Modeling the impacts of electric bicycle purchase incentive program designs","year":2021,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Incentive; Revenue; Incentive program; Yield (engineering); Business; Key (lock); Marketing; Environmental economics; Transport engineering; Public economics; Economics; Microeconomics; Finance; Computer science; Computer security; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03234570102193404,"gpt":0.3314091428295514,"spread":0.2990634418076173,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002163894,0.00006777338,0.0001246519,0.00009852459,0.0002762371,0.00001726179,0.0001072364,0.0001217055,0.00001476015],"category_scores_gemma":[0.00004293671,0.00005512969,0.00002937799,0.000862131,0.0001981348,0.0001048315,0.000002046486,0.0001543105,4.58667e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001134783,"about_ca_system_score_gemma":0.0001773328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000491871,"about_ca_topic_score_gemma":0.0007598388,"domain_scores_codex":[0.9992645,0.0000329955,0.0001988475,0.00017055,0.0001310899,0.000202065],"domain_scores_gemma":[0.9996237,0.00003689485,0.00006276709,0.0001010655,0.0001385635,0.00003705784],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004412382,0.0002079175,0.93783,0.00004946068,0.00005193368,0.00004609156,0.0157504,0.0004046023,0.006939071,0.01280209,0.00001002968,0.02586433],"study_design_scores_gemma":[0.002222335,0.0005184481,0.780231,0.0003375258,0.0004289064,0.000004694789,0.05858642,0.01212409,0.08378778,0.05875291,0.002156398,0.0008495058],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935294,0.001437024,0.003478759,0.0009034698,0.00003014497,0.0001810165,0.00000739916,0.0001592877,0.0002734997],"genre_scores_gemma":[0.9992564,0.0000706256,0.0005681512,0.00001812897,0.00001355056,0.00001885472,0.00002595027,0.000004919536,0.00002341309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.157599,"threshold_uncertainty_score":0.2248124,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1985623578","doi":"10.1080/03081060108717671","title":"A line haul transit technology selection model","year":2001,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Transit (satellite); Selection (genetic algorithm); Transport engineering; Operations research; Event (particle physics); Computer science; Public transport; Value of time; Engineering; Travel time","retraction":null,"screen_n_in":null,"score":{"opus":0.01929156923268107,"gpt":0.2901781560283337,"spread":0.2708865867956527,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000203374,0.0001491955,0.0001937284,0.0007859548,0.0005786088,0.00002805883,0.000123474,0.0004718016,0.00004021568],"category_scores_gemma":[0.00003246532,0.0001683846,0.00002875637,0.001571069,0.0002830199,0.0002136011,0.00000117921,0.0002806692,0.000006674993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002648493,"about_ca_system_score_gemma":0.0001045736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001249094,"about_ca_topic_score_gemma":0.0009881769,"domain_scores_codex":[0.998828,0.00002151506,0.0003010296,0.0003295015,0.0001874356,0.0003325305],"domain_scores_gemma":[0.9995179,0.00002890658,0.0001045944,0.00009598075,0.0001760625,0.00007652475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001830469,0.0001617434,0.5136983,0.00004010691,0.00007980435,0.0000951705,0.01772471,0.2120742,0.002815444,0.230848,0.000340989,0.02193839],"study_design_scores_gemma":[0.01250847,0.001797261,0.1290873,0.001016602,0.001131782,0.0002352131,0.06127993,0.369343,0.008526347,0.199535,0.2107084,0.004830727],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7245941,0.000413213,0.2629358,0.008350751,0.00008607427,0.0002298627,0.00001774662,0.001632745,0.001739701],"genre_scores_gemma":[0.9903151,0.0002654179,0.008176899,0.00009024209,0.00003387066,0.00003705833,0.0001121036,0.0000183197,0.0009509971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3846111,"threshold_uncertainty_score":0.6866523,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4399787718","doi":"10.1080/03081060.2024.2366241","title":"International travel patterns: exploring destination preferences and airfare trends to and from the USA","year":2024,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Texas Department of Transportation","keywords":"Air travel; Economic geography; Geography; Business; Aviation; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.08389209719644905,"gpt":0.3497368021068684,"spread":0.2658447049104193,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001578315,0.00005569232,0.00005861649,0.0002201949,0.0001974423,0.0001263557,0.0001056644,0.00005993665,0.0000648547],"category_scores_gemma":[0.00004051807,0.00004534493,0.000006791927,0.0002140563,0.0001338008,0.0002149319,0.000009077535,0.0001213432,0.000002376296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001002237,"about_ca_system_score_gemma":0.00001607965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002366472,"about_ca_topic_score_gemma":0.002762219,"domain_scores_codex":[0.9994313,0.00001754901,0.00008304619,0.0001941774,0.0001632502,0.0001107406],"domain_scores_gemma":[0.9997414,0.0001318877,0.00001541137,0.00004046179,0.00003214337,0.00003872238],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001339956,0.000008676178,0.5471299,0.00001303037,0.00003879496,0.00006815921,0.02654351,0.000009233584,0.0002084762,0.0324587,0.0002238595,0.3932842],"study_design_scores_gemma":[0.0001290249,0.00004676829,0.9659439,0.0001407476,0.00001781613,0.000001280171,0.02097741,0.0001190731,0.0001694133,0.004085917,0.008278376,0.00009027777],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9830011,0.000355145,0.0004455746,0.01480807,0.0001188841,0.00006261231,0.00004877702,0.0000954632,0.001064431],"genre_scores_gemma":[0.9990855,0.0003108007,0.0003130446,0.00002836232,0.00005498661,0.00002551825,0.00002390897,0.000004000232,0.0001538307],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4188139,"threshold_uncertainty_score":0.3577413,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2018845946","doi":"10.1080/03081060.2010.512225","title":"Bus running time prediction using a statistical pattern recognition technique","year":2010,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Basis (linear algebra); Smoothing; Predictive modelling; Public transport; Data mining; Intelligent transportation system; Arrival time; Real-time data; Machine learning; Automatic vehicle location; Travel time; Artificial intelligence; Real-time computing; Pattern recognition (psychology); Simulation; Engineering; Transport engineering; Computer vision; Global Positioning System","retraction":null,"screen_n_in":null,"score":{"opus":0.00839327067652494,"gpt":0.2164958723375518,"spread":0.2081026016610268,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001036465,0.0001261756,0.0001230728,0.0003732095,0.00008011987,0.00001819954,0.00005596133,0.0002442335,0.00003297745],"category_scores_gemma":[0.000007092595,0.0001431384,0.00001372098,0.0002103094,0.00007163551,0.0001215221,0.000003241647,0.000369697,0.000007594893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001192716,"about_ca_system_score_gemma":0.000006258183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008673662,"about_ca_topic_score_gemma":0.000007518721,"domain_scores_codex":[0.9993539,0.000004949071,0.0002188226,0.000176621,0.00007992347,0.0001657732],"domain_scores_gemma":[0.999779,0.00001478958,0.00003304157,0.0001002121,0.00003133935,0.00004165836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000337646,0.0001074418,0.05183436,0.0003460675,0.0001591006,0.0001460839,0.0007420186,0.002147389,0.4571703,0.002404176,0.004190514,0.4807188],"study_design_scores_gemma":[0.002092529,0.0004392762,0.1043522,0.0006006559,0.0003872346,0.0003558155,0.0005200591,0.7890021,0.08307514,0.006730259,0.01099361,0.001451201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4007171,0.00002740876,0.5914845,0.00003352706,0.0001327965,0.0001968163,0.00008817941,0.006982588,0.0003370871],"genre_scores_gemma":[0.9786021,0.00001549399,0.02096428,0.00001444002,0.00003019474,0.00007062042,0.0002720796,0.00002488329,0.000005971474],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7868546,"threshold_uncertainty_score":0.5837014,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4315486068","doi":"10.1080/03081060.2022.2162518","title":"Who will adopt private automated vehicles and automated shuttle buses? Testing the roles of past experience and performance expectancy","year":2023,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"McMaster University; Toronto Metropolitan University","funders":"Federation for the Humanities and Social Sciences","keywords":"Expectancy theory; Public transport; Transport engineering; Unified theory of acceptance and use of technology; Engineering; Plan (archaeology); Master plan; Operations management; Business; Psychology; Engineering management; Geography; Social psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.01567148060598169,"gpt":0.24061779469822,"spread":0.2249463140922383,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006923097,0.0001128208,0.0001426771,0.0002216153,0.0001191048,0.00001358738,0.00006150695,0.00009593666,0.000001369986],"category_scores_gemma":[0.00001581163,0.00009888067,0.000007507904,0.0008553969,0.0001972507,0.0001431839,0.000003183301,0.0001130903,5.323823e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003960405,"about_ca_system_score_gemma":0.000007277762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004259656,"about_ca_topic_score_gemma":0.00001081098,"domain_scores_codex":[0.999346,0.000005087876,0.0002727891,0.0001505086,0.00007423881,0.0001514157],"domain_scores_gemma":[0.9997035,0.00005896591,0.00005454711,0.0001030323,0.00005632081,0.00002366798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001126087,0.00001206492,0.9413176,0.000242225,0.00003790392,0.000008826034,0.01311467,0.008236297,0.02780617,0.002311568,0.00006397622,0.006837432],"study_design_scores_gemma":[0.0002453561,0.00003940312,0.8682169,0.0001164166,0.00001500892,0.000006152722,0.001836686,0.1252473,0.00392957,0.00007998401,0.0001596769,0.0001075651],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955075,0.000267829,0.0002603771,0.0001675334,0.00003016168,0.0001242842,0.00002633231,0.003590748,0.00002523512],"genre_scores_gemma":[0.9990948,0.0001141046,0.0006664786,0.00001103866,0.000004755112,0.00004248762,0.00004687916,0.0000141213,0.00000527259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.117011,"threshold_uncertainty_score":0.4032237,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4387558843","doi":"10.1080/03081060.2023.2268601","title":"Freight last mile delivery: a literature review","year":2023,"lang":"en","type":"review","venue":"Transportation Planning and Technology","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Mile; Last mile (transportation); Transport engineering; Engineering; Forensic engineering; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.03948716499677697,"gpt":0.2661767225157942,"spread":0.2266895575190173,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008031609,0.0004477918,0.001255841,0.000582072,0.00006302627,0.00002028391,0.0002065363,0.0007633915,0.0000200515],"category_scores_gemma":[0.000008475729,0.0003954902,0.0001510901,0.00133796,0.00008769429,0.00005370246,0.000003319877,0.0007892234,0.00006528661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000223473,"about_ca_system_score_gemma":0.00003188953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001219801,"about_ca_topic_score_gemma":0.00001543797,"domain_scores_codex":[0.9986008,0.00001269229,0.0006154206,0.0003497354,0.0001155659,0.0003057773],"domain_scores_gemma":[0.9994565,0.00005962766,0.00009590948,0.0002688877,0.000047908,0.00007118467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002524271,0.00002606163,0.0001416691,0.4161201,0.0007088333,0.002171503,0.0002267091,0.00003736942,0.000001407504,0.005542676,0.01920914,0.555812],"study_design_scores_gemma":[0.00008757757,0.00002081071,0.00001460428,0.1019021,0.0007772216,0.0000459197,0.000006701464,0.00003052179,5.514125e-7,0.0001440022,0.8966038,0.000366129],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000004829667,0.9960144,0.0003897021,0.00002126084,0.0002261925,0.0003989849,0.0006411005,0.001951808,0.0003517545],"genre_scores_gemma":[0.00002525316,0.9956756,0.0004042259,0.00002327786,0.00005424816,0.0001325348,0.003351283,0.0001083217,0.0002252035],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8773947,"threshold_uncertainty_score":0.9998497,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2113765225","doi":"10.1080/03081060.2015.1059121","title":"Incorporating uncertainty and risk in transportation investment decision-making","year":2015,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"University of Toledo; Michigan Department of Transportation; U.S. Department of Transportation","keywords":"Investment (military); Transport engineering; Poison control; Business; Risk analysis (engineering); Engineering; Economics; Actuarial science; Operations research; Environmental health","retraction":null,"screen_n_in":null,"score":{"opus":0.01991320625798397,"gpt":0.2971534544220996,"spread":0.2772402481641156,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006789703,0.0001400277,0.00019946,0.0004848667,0.0002896575,0.00003970114,0.00008001496,0.0002420007,0.000005355706],"category_scores_gemma":[0.0001754266,0.000151498,0.00001570205,0.0007712733,0.0002518167,0.0002745586,0.00000125789,0.0002414171,0.000001345914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004666457,"about_ca_system_score_gemma":0.0001370394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001250626,"about_ca_topic_score_gemma":0.01120288,"domain_scores_codex":[0.9987259,0.00006646384,0.0004099964,0.0003199298,0.0002469984,0.0002307497],"domain_scores_gemma":[0.999297,0.0001726896,0.0002091545,0.00008628033,0.0001216629,0.0001132626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006549847,0.00002342736,0.9017166,0.00001140426,0.00001096638,0.00003376313,0.02533805,0.03033334,0.000007342328,0.03194476,0.00003986036,0.01047493],"study_design_scores_gemma":[0.002420117,0.0001857918,0.8544792,0.0005175434,0.00009834365,0.000003278793,0.04886995,0.005530517,0.00002761436,0.08410404,0.003229297,0.0005342886],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868384,0.0006030941,0.01095866,0.0004216955,0.00009941971,0.0002230588,0.00003624189,0.0002604611,0.0005589753],"genre_scores_gemma":[0.9868039,0.0001460013,0.01277593,0.00006549931,0.00001948216,0.00002774172,0.0001297993,0.00001243357,0.00001913663],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05215929,"threshold_uncertainty_score":0.625147,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403197003","doi":"10.1080/03081060.2024.2411611","title":"Travel mode choice prediction: developing new techniques to prioritize variables and interpret black-box machine learning techniques","year":2024,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval; Concordia University; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Black box; Mode choice; Mode (computer interface); Machine learning; Computer science; Engineering; Transport engineering; Artificial intelligence; Public transport; Human–computer interaction","retraction":null,"screen_n_in":null,"score":{"opus":0.007807652114184692,"gpt":0.2425755632876937,"spread":0.234767911173509,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000129182,0.0002323666,0.0002236763,0.0007721745,0.00009233318,0.00008157217,0.0001078799,0.0002592166,0.000005936451],"category_scores_gemma":[0.00001766748,0.0002488215,0.00002296078,0.000504208,0.000067229,0.000218613,0.00001452905,0.0004227844,0.000001844552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004360009,"about_ca_system_score_gemma":0.00002325708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005962925,"about_ca_topic_score_gemma":0.00003550199,"domain_scores_codex":[0.9989802,0.00001028323,0.0003211814,0.0003502104,0.0001056011,0.0002325107],"domain_scores_gemma":[0.9997126,0.0000440613,0.00001865003,0.0001143612,0.00002831076,0.00008194133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006430355,0.00003989637,0.01580129,0.002085045,0.0004963398,0.0001674596,0.008269392,0.001589405,0.06960884,0.1179222,0.02654889,0.7574069],"study_design_scores_gemma":[0.000818014,0.0009037029,0.01554466,0.00545576,0.0003814281,0.0001824999,0.001474439,0.1352515,0.2704204,0.009009605,0.5586045,0.001953549],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02148627,0.001521652,0.9452024,0.001219528,0.0001396388,0.0004201131,0.0000529292,0.02866845,0.001289014],"genre_scores_gemma":[0.9410297,0.0009206179,0.05746481,0.00008844248,0.00007891695,0.00009696662,0.00009320723,0.00005231852,0.0001750664],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9195434,"threshold_uncertainty_score":0.9999964,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3162299972","doi":"10.1080/03081060.2021.1927303","title":"An inductive experimental approach to developing a web-based travel survey builder: developing guidelines to design an efficient web-survey platform","year":2021,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Respondent; Usability; Web application; Survey data collection; Web testing; Web survey; Computer science; Survey methodology; World Wide Web; Engineering; Web application security; The Internet; Web development; Human–computer interaction","retraction":null,"screen_n_in":null,"score":{"opus":0.1570949826933775,"gpt":0.386258845181812,"spread":0.2291638624884344,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001656813,0.0002503366,0.0003643417,0.000389627,0.0007070088,0.00009313752,0.0003223146,0.0003156219,0.00001111974],"category_scores_gemma":[0.0001796162,0.0002627284,0.00002913021,0.001688838,0.0001876724,0.0002329406,0.000006977928,0.0002045544,0.000002132664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001149979,"about_ca_system_score_gemma":0.0010855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002183666,"about_ca_topic_score_gemma":0.01039476,"domain_scores_codex":[0.997647,0.0002128635,0.0005487867,0.0007783769,0.0003356578,0.0004773093],"domain_scores_gemma":[0.9987263,0.0001204871,0.0001081104,0.0002385176,0.0005831854,0.000223397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002934591,0.000401779,0.9522477,0.00003561722,0.00004790454,0.00003700933,0.02062854,0.008868183,0.01005436,0.003986124,0.00007708522,0.00332219],"study_design_scores_gemma":[0.0007973371,0.0001590412,0.9566877,0.00009307203,0.00001865476,0.000001181333,0.01522429,0.002119572,0.02396426,0.000171741,0.0001818304,0.0005813412],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7699088,0.00011448,0.2286849,0.0004172219,0.0001131448,0.0003865546,0.00007741015,0.0002462423,0.00005123057],"genre_scores_gemma":[0.8824716,0.000002686577,0.1165983,0.0002760735,0.00002813011,0.00007803181,0.0005084368,0.00002186166,0.00001488663],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1125628,"threshold_uncertainty_score":0.9999825,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1989630095","doi":"10.1080/03081060.2012.671028","title":"A framework for neighbour links travel time estimation in an urban network","year":2012,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of British Columbia","funders":"University of British Columbia","keywords":"Computer science; Travel time; Estimation; Sample (material); Sensor fusion; Data mining; Real-time data; Scheme (mathematics); Transport engineering; Operations research; Engineering; Artificial intelligence; Mathematics; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.01161398284727,"gpt":0.2519358899149414,"spread":0.2403219070676714,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001076104,0.00009185453,0.0001153306,0.0002037649,0.00003931766,0.000009178102,0.00005111316,0.0003135567,0.000004475066],"category_scores_gemma":[0.000006216017,0.0001033248,0.00001265495,0.0002100525,0.0000215201,0.0001669803,0.000001106587,0.0002145227,0.000002094337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001129693,"about_ca_system_score_gemma":0.000002590732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001102858,"about_ca_topic_score_gemma":0.000003225581,"domain_scores_codex":[0.9994786,0.000004538183,0.0001659784,0.00009897726,0.00003858742,0.0002133271],"domain_scores_gemma":[0.999822,0.00002641155,0.00002403921,0.00007970216,0.00001037217,0.00003742616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007483375,0.0001593435,0.245494,0.0002843058,0.00008996934,0.000008370155,0.005046887,0.09076008,0.001284691,0.5399781,0.006583073,0.1102363],"study_design_scores_gemma":[0.0009402215,0.0002333571,0.3088894,0.0002616715,0.00007518411,0.000005115133,0.000456191,0.6651911,0.001076859,0.01743645,0.004927635,0.0005068943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1919193,0.0003688187,0.8041343,0.0001093109,0.0001056107,0.0002209763,0.00001011249,0.002943461,0.0001880826],"genre_scores_gemma":[0.9487761,0.00001545034,0.05089615,0.00003386999,0.00004413734,0.00008996982,0.0001157161,0.00001735126,0.00001129173],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7568567,"threshold_uncertainty_score":0.4213465,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4393990604","doi":"10.1080/03081060.2024.2335514","title":"Temporal analysis of factors affecting injury severities of expressway rear-end crashes during weekdays and weekends","year":2024,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Traffic and Road Safety","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"Natural Science Foundation of Tibet Autonomous Region","keywords":"Transport engineering; Psychology; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.005737905651148587,"gpt":0.2155619513152312,"spread":0.2098240456640826,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005777469,0.0001089334,0.0002694295,0.0006611719,0.0000407874,0.000007273929,0.00003919318,0.0001387969,0.0000106557],"category_scores_gemma":[0.000003767563,0.0001031457,0.00004044742,0.0005768444,0.0001030543,0.00008707144,0.000003329795,0.0001426262,8.170612e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004459614,"about_ca_system_score_gemma":0.000005860053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003861546,"about_ca_topic_score_gemma":0.00005218174,"domain_scores_codex":[0.999429,0.000005392993,0.0002439454,0.0001425023,0.00006684594,0.0001123247],"domain_scores_gemma":[0.9998037,0.00005249352,0.00003398333,0.00007367742,0.00001490113,0.00002127201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002260715,0.00001319587,0.9503058,0.00106723,0.0009086252,0.00002203758,0.00793684,0.01109574,0.02538842,0.000735276,0.000011995,0.002492237],"study_design_scores_gemma":[0.0001494255,0.00005241994,0.9610969,0.0002491619,0.0003934826,0.000002966899,0.004321645,0.0037874,0.02964796,0.00006532451,0.00007441107,0.00015886],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962619,0.002197722,0.0007680231,0.00001405123,0.00005739549,0.00003870827,0.0001086362,0.000445095,0.0001084573],"genre_scores_gemma":[0.9995325,0.0001327037,0.0002242327,3.72977e-7,0.000005814899,0.000002401092,0.00006656818,0.00001325112,0.00002216673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01079115,"threshold_uncertainty_score":0.4206161,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3159799002","doi":"10.1080/03081060.2021.1919350","title":"Does the use of smartphones affect discretionary trips? An analysis of smartphone use data from Halifax, Nova Scotia","year":2021,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Dalhousie University; McMaster University","funders":"","keywords":"TRIPS architecture; Nova scotia; Advertising; Perception; Smartphone application; Affect (linguistics); Travel behavior; Transport engineering; Business; Geography; Psychology; Engineering; Computer science; Multimedia","retraction":null,"screen_n_in":null,"score":{"opus":0.09042516334321465,"gpt":0.3379171986758825,"spread":0.2474920353326678,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000295797,0.0001099547,0.0003563539,0.0002301497,0.0001615305,0.00003671088,0.0003142121,0.0001777505,0.0001913477],"category_scores_gemma":[0.0001193023,0.00007142432,0.00006396598,0.001482671,0.0006797567,0.0006143017,0.00001136458,0.0001386127,5.223235e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006909694,"about_ca_system_score_gemma":0.00009295715,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02408772,"about_ca_topic_score_gemma":0.1668355,"domain_scores_codex":[0.9987096,0.0001169983,0.0003989339,0.0003920543,0.0002277231,0.0001546505],"domain_scores_gemma":[0.9985973,0.0003978618,0.0002166224,0.0005901533,0.0001547017,0.00004332512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005144828,0.00008791794,0.9942052,0.00001367712,0.0002880425,0.00001490529,0.002556163,0.0001184075,0.001226971,0.0006543435,0.00004153283,0.0007413678],"study_design_scores_gemma":[0.0002094622,0.00001995983,0.9928001,0.00003510353,0.0008031682,1.049575e-7,0.002905597,0.0003593425,0.001655183,0.0004348333,0.0006777197,0.00009941759],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946938,0.0003080171,0.001737746,0.0008560714,0.0001289009,0.0001087144,0.002084219,0.00007275164,0.000009801432],"genre_scores_gemma":[0.9941607,0.0000593984,0.001306983,0.00002553617,0.00002003199,0.000002239343,0.004350824,0.000006586378,0.00006769728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1427478,"threshold_uncertainty_score":0.982411,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2063184644","doi":"10.1080/03081060802334995","title":"Analysis of Characteristics of the Dynamic Flow-Density Relation and its Application to Traffic Flow Models","year":2008,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Traffic control and management","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Relation (database); Traffic flow (computer networking); Flow (mathematics); Microscopic traffic flow model; Computer science; Three-phase traffic theory; Traffic generation model; Simulation; Mechanics; Data mining; Engineering; Transport engineering; Traffic congestion reconstruction with Kerner's three-phase theory; Traffic congestion; Real-time computing; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.00573569939270616,"gpt":0.1869191892492623,"spread":0.1811834898565561,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003740244,0.00005884466,0.0001594165,0.0002380762,0.00003747211,0.00000106428,0.00004073295,0.00006635054,7.030975e-7],"category_scores_gemma":[0.000003108307,0.000053331,0.00002115334,0.0004444838,0.00002469466,0.00003036493,0.000002301673,0.00005555117,1.623242e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006080988,"about_ca_system_score_gemma":0.000003063956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002916215,"about_ca_topic_score_gemma":0.00004587462,"domain_scores_codex":[0.9996027,0.000003527401,0.0001840977,0.00009413703,0.00005642159,0.00005912823],"domain_scores_gemma":[0.9998082,0.00001154136,0.00004440801,0.00009003894,0.00003202803,0.00001377726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009673382,0.00000942782,0.006622334,0.00004100556,0.0001240118,8.349634e-7,0.001078087,0.9654566,0.002530087,0.0006272037,0.000001821892,0.02349892],"study_design_scores_gemma":[0.00008935564,0.000008742657,0.3975459,0.000008037374,0.0001422187,4.818742e-7,0.00003189628,0.6020045,0.00009604813,0.00002886226,0.00001153349,0.00003248769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9349018,0.0001443784,0.06457332,0.00008565217,0.00001961799,0.0001298409,0.00003185543,0.0001023912,0.00001110157],"genre_scores_gemma":[0.999441,0.0000587209,0.0004213849,0.000004270906,0.000001592614,0.00001132424,0.00004959398,0.000004842772,0.000007318711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3909235,"threshold_uncertainty_score":0.2174775,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2892388188","doi":"10.1080/03081060.2018.1526879","title":"Strategies to achieve deep reductions in metropolitan transportation GHG emissions: the case of Philadelphia","year":2018,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto; McGill University","funders":"Drexel University","keywords":"Greenhouse gas; Metropolitan area; Market penetration; Electricity; Public transport; Baseline (sea); Transport engineering; Battery electric vehicle; Electric vehicle; Population; Engineering; Environmental science; Environmental engineering; Environmental economics; Agricultural economics; Business; Natural resource economics; Economics; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.024030226483588,"gpt":0.3428979237618753,"spread":0.3188676972782873,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003046876,0.0001072277,0.0001732534,0.0003362377,0.0004465955,0.00001973596,0.0001563342,0.0001756675,0.00005336579],"category_scores_gemma":[0.00002794714,0.00008909764,0.00003083454,0.001236896,0.0007926381,0.0002309094,0.000001209374,0.0001885992,0.000001327965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003266179,"about_ca_system_score_gemma":0.00009979969,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00523898,"about_ca_topic_score_gemma":0.06744499,"domain_scores_codex":[0.9989799,0.00004141351,0.0003793161,0.0002523414,0.000113179,0.0002338755],"domain_scores_gemma":[0.9994787,0.00006179552,0.0001032457,0.0001570423,0.0001334729,0.00006574929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002504275,0.0002031887,0.4068917,0.00007379428,0.00006334648,0.000262517,0.1398685,0.0001579189,0.002842347,0.4420951,0.0001755242,0.007115668],"study_design_scores_gemma":[0.0007224233,0.0004088951,0.3924419,0.0001413816,0.0001333629,0.00001242152,0.5167015,0.00006878783,0.002161467,0.083985,0.002853516,0.0003693295],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895754,0.0002924972,0.002408128,0.006412861,0.00009674205,0.0002666503,0.00003854456,0.0001179977,0.0007911598],"genre_scores_gemma":[0.9989761,0.0000213798,0.0008248938,0.00003002497,0.00004707294,0.0000306361,0.00003102073,0.000007707386,0.00003116822],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.376833,"threshold_uncertainty_score":0.9495717,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403616101","doi":"10.1080/03081060.2024.2416248","title":"An Impact Assessment of Cordon Pricing Relaxation on Modal Shift During the COVID-19 Pandemic","year":2024,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Energy, Environment, and Transportation Policies","field":"Energy","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Pandemic; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Modal; Virology; Medicine; Chemistry","retraction":null,"screen_n_in":null,"score":{"opus":0.02306435570919276,"gpt":0.3287401140258828,"spread":0.3056757583166901,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001877706,0.0001597217,0.0001720659,0.0003606706,0.0001765972,0.00002153091,0.0001052286,0.0001686132,0.00004220743],"category_scores_gemma":[0.00001103328,0.0001203391,0.00004724974,0.0003416365,0.0001472364,0.000134058,0.000001639615,0.0002592001,0.000001574639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007661297,"about_ca_system_score_gemma":0.00005653679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008189942,"about_ca_topic_score_gemma":0.0004797546,"domain_scores_codex":[0.9989922,0.00003503172,0.000331213,0.0002803112,0.0001755162,0.0001857041],"domain_scores_gemma":[0.9994821,0.0001142506,0.0001225808,0.0002014525,0.00001293585,0.00006665741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000438266,0.00004271595,0.6292284,0.0001203367,0.000080846,0.00002802238,0.003703128,0.2323721,0.008603101,0.1246846,0.00000597244,0.00108702],"study_design_scores_gemma":[0.0004701996,0.0002510574,0.9882593,0.00006975328,0.00006860935,0.00001307058,0.0007288211,0.002859766,0.001510372,0.004676578,0.0009298144,0.0001626918],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924932,0.0002780825,0.005759931,0.0005381704,0.00006808111,0.0001133937,0.00003985343,0.0004305492,0.0002787977],"genre_scores_gemma":[0.9992883,0.0001236594,0.0001507674,0.00008060274,0.00002426288,0.00003375892,0.0002247545,0.00002398192,0.00004994442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3590309,"threshold_uncertainty_score":0.4907286,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4407666926","doi":"10.1080/03081060.2025.2465557","title":"Assessing traffic vulnerability to climate hazards in cold regions: the impact of harsh winters conditions on highway traffic volumes","year":2025,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Traffic and Road Safety","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Vulnerability (computing); Transport engineering; Environmental science; Traffic volume; Poison control; Road traffic; Engineering; Forensic engineering; Computer science; Computer security; Environmental health","retraction":null,"screen_n_in":null,"score":{"opus":0.01158800666160509,"gpt":0.2943748748688494,"spread":0.2827868682072443,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001549915,0.0001399317,0.0002308747,0.000428487,0.0001104616,0.00001724636,0.0001070873,0.000156188,0.000005547989],"category_scores_gemma":[0.00001741194,0.0001112273,0.00004955183,0.0007079989,0.000128156,0.00008130944,0.000002507266,0.0002833688,0.000001167262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004345966,"about_ca_system_score_gemma":0.00003732918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001492985,"about_ca_topic_score_gemma":0.0001186999,"domain_scores_codex":[0.9991972,0.00002208111,0.0003208444,0.0001853832,0.00006273983,0.000211785],"domain_scores_gemma":[0.9996214,0.0001150019,0.00003748009,0.0001681299,0.00002954033,0.00002848014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00003373111,0.00005988193,0.0195968,0.0000795909,0.00005826145,0.00000871072,0.0009822011,0.9678556,0.0009342514,0.00372875,0.0005494219,0.006112854],"study_design_scores_gemma":[0.001006718,0.0001980022,0.9509873,0.0006419352,0.00005133603,0.000004013469,0.002567268,0.04272237,0.0008717665,0.000227054,0.0004665871,0.0002556031],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971246,0.0002028767,0.001083155,0.0005392859,0.0001002884,0.0002192369,0.00008871379,0.000465272,0.0001766318],"genre_scores_gemma":[0.999715,0.00002733967,0.0001186843,0.00001956315,0.000004802615,0.00003934108,0.00004958437,0.00001147597,0.00001424498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9313905,"threshold_uncertainty_score":0.4535716,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2039479607","doi":"10.1080/03081060.2011.651878","title":"A GPS-aided survey for assessing trip reporting accuracy and travel of students without telephone land lines","year":2012,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto","funders":"","keywords":"TRIPS architecture; Global Positioning System; Travel behavior; Transport engineering; Sample (material); Geography; Travel survey; Computer science; Engineering; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.0704727557759861,"gpt":0.3207575826559606,"spread":0.2502848268799745,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004424465,0.0001442136,0.0003417572,0.0001882849,0.00006207234,0.00001583397,0.00006247655,0.0001799815,0.000001601465],"category_scores_gemma":[0.0001412763,0.0001384632,0.00002217396,0.0001943451,0.00008419686,0.0001384616,0.000001910174,0.0001393909,1.808049e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006015656,"about_ca_system_score_gemma":0.00001028124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003458709,"about_ca_topic_score_gemma":0.00005620373,"domain_scores_codex":[0.9988927,0.00000836035,0.000631076,0.0001428791,0.00009284481,0.0002320905],"domain_scores_gemma":[0.9993888,0.0001488873,0.0002460322,0.00009616809,0.00006542965,0.00005471959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002211593,0.00002786066,0.9939218,0.0001820269,0.00005236643,0.000004524677,0.0006444544,0.0001657033,0.003611787,0.0001410518,0.00001632835,0.001209955],"study_design_scores_gemma":[0.000814671,0.00003614559,0.9932116,0.00008543206,0.00007890318,0.00001148166,0.0003113558,0.001095842,0.003963766,0.0001253543,0.0001013635,0.000164087],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9483817,0.001380498,0.04964863,0.00001340038,0.0001123576,0.0001760131,0.00007019472,0.0001872668,0.00002988888],"genre_scores_gemma":[0.9948167,0.00007207238,0.004791391,0.000005327806,0.00002810225,0.00001897275,0.0002262249,0.00002486736,0.00001630011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04643499,"threshold_uncertainty_score":0.5646367,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W561637617","doi":"10.1080/03081060903257053","title":"GIS-based travel demand modeling for estimating traffic on low-class roads","year":2009,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Cochrane; University of New Brunswick","funders":"","keywords":"Transport engineering; Computer science; Traffic count; Class (philosophy); Traffic volume; Floating car data; Traffic congestion; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01085530553225771,"gpt":0.2366938050231089,"spread":0.2258384994908512,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008529786,0.0001425759,0.0001605287,0.0003416158,0.00008843499,0.0000157089,0.00007035511,0.0001615248,0.000001168691],"category_scores_gemma":[0.000007084166,0.0001531592,0.00002985523,0.0001645892,0.00002193942,0.00005775188,5.131818e-7,0.0001458623,7.503964e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001457283,"about_ca_system_score_gemma":0.000006210192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.679626e-7,"about_ca_topic_score_gemma":0.000001772342,"domain_scores_codex":[0.9993298,0.000003252709,0.0002229177,0.0001845579,0.00007040594,0.0001890555],"domain_scores_gemma":[0.9997984,0.00002131856,0.00002772654,0.00009691375,0.00002171949,0.0000339569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001968628,0.0000229193,0.00003932026,0.0000644516,0.00001323418,0.000004684943,0.0001701205,0.9513348,0.0007332197,0.003051016,0.000444801,0.0441017],"study_design_scores_gemma":[0.0006143399,0.0001665051,0.0004100489,0.0001242331,0.00002577262,0.000001168287,0.0001076094,0.9961468,0.001652717,0.0004519614,0.0001459015,0.0001529646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2826463,0.00008136619,0.7122631,0.0002994377,0.00007889495,0.0001959044,0.00001083523,0.004243722,0.0001804835],"genre_scores_gemma":[0.9729938,0.000008502416,0.02672539,0.00009141468,0.00002317629,0.0000511418,0.00008153872,0.00001786374,0.00000717091],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6903476,"threshold_uncertainty_score":0.6245652,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4384408061","doi":"10.1080/03081060.2023.2230969","title":"Communication and mobility issues of visually impaired pedestrians with connected autonomous vehicles","year":2023,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"CNIB Foundation; University of Toronto","funders":"","keywords":"Pedestrian; Structural equation modeling; Context (archaeology); Computer science; Visually impaired; Confirmatory factor analysis; Latent variable; Econometrics; Transport engineering; Artificial intelligence; Human–computer interaction; Engineering; Machine learning; Mathematics; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.01362594107256283,"gpt":0.2575904927464965,"spread":0.2439645516739337,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009737318,0.00009401406,0.0001564989,0.0002700506,0.00005858941,0.000007784066,0.00005473506,0.0001102031,0.000005326525],"category_scores_gemma":[0.000008939381,0.00009426654,0.000009615082,0.0006479537,0.0001732251,0.00007901428,0.000001481168,0.0001115684,8.532559e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006025583,"about_ca_system_score_gemma":0.00001658477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003838556,"about_ca_topic_score_gemma":0.0001566055,"domain_scores_codex":[0.9994433,0.000008058108,0.0002548656,0.0001253463,0.00005939439,0.0001090664],"domain_scores_gemma":[0.9996503,0.00005337974,0.00004497563,0.0001471415,0.00008006049,0.00002411616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001344707,0.000176667,0.8414671,0.0007560451,0.0003029486,0.00002651375,0.01837519,0.02495821,0.03275375,0.06226877,0.00025084,0.01852946],"study_design_scores_gemma":[0.0008489389,0.0001443771,0.9820872,0.00008478589,0.00005017559,0.00000394176,0.00298034,0.005277427,0.005815232,0.001844452,0.0006850074,0.0001781133],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966938,0.0002942259,0.001084478,0.0004445811,0.00001347606,0.0001702946,0.00005953395,0.001176118,0.00006344126],"genre_scores_gemma":[0.998508,0.0001161124,0.0009727866,0.000006379381,0.000002136343,0.00003768121,0.0003198448,0.00001288159,0.00002416653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1406201,"threshold_uncertainty_score":0.3844078,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1973615193","doi":"10.1080/0308106042000263078","title":"The origin-destination matrix as an indicator of intrahousehold travel allocation","year":2004,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Daytime; Destinations; Context (archaeology); Metropolitan area; Residence; Matrix (chemical analysis); Geography; Economics; Demographic economics; Tourism","retraction":null,"screen_n_in":null,"score":{"opus":0.0194657646989776,"gpt":0.3208854141429901,"spread":0.3014196494440125,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003619139,0.00007290269,0.0001027122,0.000131853,0.0004205389,0.00002147998,0.0001654151,0.0001620338,0.000007944909],"category_scores_gemma":[0.00003187426,0.00006128976,0.00001692505,0.0003791985,0.0004696306,0.0002004958,9.842796e-7,0.000132622,0.000001866359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000023135,"about_ca_system_score_gemma":0.0001505001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009885271,"about_ca_topic_score_gemma":0.001597123,"domain_scores_codex":[0.9992216,0.00001998273,0.0002487217,0.0001804354,0.0001726629,0.0001565862],"domain_scores_gemma":[0.9995849,0.00004053297,0.000139004,0.0001162011,0.00007283414,0.00004659355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004192437,0.00009322396,0.5175719,0.00002339838,0.00001647351,0.000006103691,0.01185259,0.00008183581,0.001967967,0.4599783,0.000006613363,0.008359723],"study_design_scores_gemma":[0.0007446613,0.0001771161,0.8791999,0.00004736829,0.0000539471,0.000001178025,0.01057404,0.00001372398,0.008326563,0.09917196,0.001510664,0.0001788574],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954032,0.0002513972,0.001836178,0.001826534,0.00006023145,0.0001665339,0.000007993815,0.000161472,0.0002864402],"genre_scores_gemma":[0.99926,0.00005565626,0.00053303,0.00001507313,0.00002273484,0.00001442054,0.00004202767,0.000006617947,0.00005045152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.361628,"threshold_uncertainty_score":0.3234487,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4402567823","doi":"10.1080/03081060.2024.2401507","title":"What influences intention to use a first-mile/last-mile automated shuttle service in a suburban area? A case study in Toronto, Canada","year":2024,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto","funders":"","keywords":"Mile; Last mile (transportation); Transport engineering; Vehicle miles of travel; Service (business); Engineering; Business; Geography; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.01602389775136318,"gpt":0.2625840019962353,"spread":0.2465601042448722,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009236383,0.0001506124,0.0001751696,0.00043858,0.00003926891,0.00006778995,0.00006450072,0.0001130172,0.00002298315],"category_scores_gemma":[0.00001133746,0.0001662527,0.00001116144,0.001313961,0.00001675076,0.0005557126,0.000002082491,0.0001896834,0.00000134527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001817145,"about_ca_system_score_gemma":0.00007342255,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4258066,"about_ca_topic_score_gemma":0.995447,"domain_scores_codex":[0.999018,0.000008557106,0.0004176855,0.0002560946,0.00010012,0.0001995897],"domain_scores_gemma":[0.9996958,0.00005534013,0.00001890975,0.0001208226,0.00006431007,0.00004477287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002143865,0.00009892826,0.9146239,0.0002684933,0.00006449921,0.003629447,0.03157061,0.04692179,0.0004632168,0.0004670429,0.0001716936,0.001698963],"study_design_scores_gemma":[0.0006280253,0.00009440562,0.8921034,0.0005678263,0.00003412998,0.00008186354,0.06308468,0.04151735,0.0001055838,0.00003527712,0.001450617,0.0002968456],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972284,0.0004070227,0.0002014976,0.0003881846,0.000262486,0.0004287398,0.00005170854,0.001020804,0.0000111278],"genre_scores_gemma":[0.9994231,0.00002440867,0.0001377595,0.00006553662,0.000002864419,0.000200446,0.0001164706,0.00001746395,0.00001190979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5696405,"threshold_uncertainty_score":0.6779589,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4394608731","doi":"10.1080/03081060.2024.2338873","title":"Optimization of E-bike networks","year":2024,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure; Group for Research in Decision Analysis","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transport engineering; Poison control; Engineering; Computer science; Medical emergency; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.006393701261182617,"gpt":0.2181879870261782,"spread":0.2117942857649956,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003934462,0.0000656182,0.00008456686,0.0002779174,0.00001784358,0.000007670481,0.00003060512,0.0001082381,0.00002485191],"category_scores_gemma":[0.000001957654,0.0000697538,0.00001366116,0.0005666518,0.00004902717,0.00007200699,3.666544e-7,0.0001096426,8.632879e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004691971,"about_ca_system_score_gemma":0.000007824106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002252675,"about_ca_topic_score_gemma":0.000006396695,"domain_scores_codex":[0.9995846,0.000001660878,0.0002025699,0.00009189727,0.00004118822,0.00007812535],"domain_scores_gemma":[0.9998615,0.00001768481,0.00001229513,0.00006036123,0.00003350385,0.00001460746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002130561,0.000005460649,0.006692716,0.0001063431,0.00003378763,0.000005955413,0.0004227651,0.9524121,0.0006202423,0.0351769,0.0001020641,0.004419546],"study_design_scores_gemma":[0.0003077202,0.0000556292,0.02941723,0.0002241577,0.00008468148,0.000007756996,0.0004379529,0.959527,0.002756891,0.001268634,0.00567083,0.0002414932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2813644,0.001980856,0.7145445,0.0001707346,0.0001950002,0.00008469012,0.00002997589,0.001255573,0.0003742351],"genre_scores_gemma":[0.996788,0.0001015926,0.002874683,0.000007153663,0.000008453465,0.00001109475,0.000174578,0.00001251193,0.00002195226],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7154236,"threshold_uncertainty_score":0.2844477,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4398142670","doi":"10.1080/03081060.2024.2354492","title":"Development of a dynamic traffic microsimulator for on-demand transit operations within an integrated modelling system","year":2024,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Dalhousie University","funders":"","keywords":"Transit (satellite); Transport engineering; Transit system; Computer science; Public transport; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.02269753070049225,"gpt":0.2947177015103841,"spread":0.2720201708098918,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003342795,0.0001230536,0.0001789946,0.0003981415,0.0004087063,0.00004729075,0.00008041112,0.0002103018,0.00000313437],"category_scores_gemma":[0.000006464143,0.0001215032,0.0000282503,0.0004530313,0.0001079843,0.0001547091,3.501611e-7,0.0001280849,9.103575e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003882948,"about_ca_system_score_gemma":0.0002353206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004061218,"about_ca_topic_score_gemma":0.0008883302,"domain_scores_codex":[0.9989897,0.00002251706,0.0004160181,0.000281238,0.0001296893,0.000160855],"domain_scores_gemma":[0.9996479,0.00005683138,0.00005009289,0.00007033764,0.0001209994,0.00005385546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000051815,0.00003274638,0.0001219231,0.0001706544,0.00003884538,0.000004883987,0.08389954,0.8792318,0.0007395445,0.0322782,0.000003444384,0.003426557],"study_design_scores_gemma":[0.0005966692,0.0001445944,0.0003724651,0.0007889864,0.00009914801,0.00000167866,0.02685797,0.9681674,0.001114735,0.0001126235,0.001479295,0.0002644344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6171846,0.0001987663,0.3816769,0.000108691,0.00009587374,0.0002303049,0.00007216242,0.000417954,0.00001469889],"genre_scores_gemma":[0.9345433,0.00001046961,0.06478256,0.000007551851,0.000009400216,0.00005351333,0.0005171217,0.00001746521,0.00005864024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3173586,"threshold_uncertainty_score":0.4954756,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4408274031","doi":"10.1080/03081060.2025.2476083","title":"Battery electric bus transit system optimization with battery degradation and energy consumption uncertainty","year":2025,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Automotive engineering; Battery (electricity); Energy consumption; Public transport; Transit (satellite); Battery electric vehicle; Engineering; Automotive battery; Computer science; Transport engineering; Electrical engineering; Power (physics)","retraction":null,"screen_n_in":null,"score":{"opus":0.007037931855640836,"gpt":0.2191290755670798,"spread":0.212091143711439,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005615862,0.0001693976,0.000197342,0.0008062291,0.0001133467,0.00002478402,0.00008201559,0.0002384855,0.000004733336],"category_scores_gemma":[0.000005879537,0.0001653525,0.00001017276,0.0006750711,0.0001058169,0.000151641,0.000003726783,0.0002217356,6.035982e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006382886,"about_ca_system_score_gemma":0.00001541704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001074795,"about_ca_topic_score_gemma":0.00002102439,"domain_scores_codex":[0.9991655,0.00001284807,0.0002243763,0.0002669232,0.0000943873,0.0002359124],"domain_scores_gemma":[0.9996732,0.00006059349,0.00003768564,0.0001464131,0.00005633336,0.00002577013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001047771,0.00001765656,0.04025656,0.0006695222,0.0001313172,0.00005398757,0.0001194575,0.8883711,0.009285687,0.007182162,0.0001045881,0.05370326],"study_design_scores_gemma":[0.002702527,0.0003905132,0.04064041,0.001036338,0.0002034929,0.0001322926,0.001715051,0.9218348,0.02892645,0.0006969724,0.0008547351,0.0008663623],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4210651,0.0007593163,0.5765648,0.0002517557,0.00003516724,0.00008675546,0.00000930778,0.001118966,0.000108864],"genre_scores_gemma":[0.9960409,0.0003457589,0.003312423,0.00002399683,0.000004768538,0.00007806845,0.0001323021,0.00001953464,0.00004221432],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5749758,"threshold_uncertainty_score":0.674288,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4402378021","doi":"10.1080/03081060.2024.2399635","title":"Access to green and gray urban nature amenities: exploring equity in Montreal's built environment","year":2024,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Urban Green Space and Health","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Polytechnique Montréal; McGill University","funders":"Mitacs","keywords":"Transport engineering; Equity (law); Built environment; Regional science; Geography; Engineering; Business; Environmental planning; Political science; Civil engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.04094525229263528,"gpt":0.3085293609977384,"spread":0.2675841087051031,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001025196,0.0001159273,0.000135293,0.0002115603,0.00007122544,0.00003361442,0.0001122622,0.0001518502,0.00007170878],"category_scores_gemma":[0.000002588377,0.0001104003,0.0000104757,0.0002826231,0.00009811207,0.0002628707,0.00003685362,0.000312206,0.00001932735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005611152,"about_ca_system_score_gemma":0.000005611167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003503209,"about_ca_topic_score_gemma":0.01069146,"domain_scores_codex":[0.9991476,0.000007814422,0.0001554348,0.0003379981,0.0001197246,0.0002314599],"domain_scores_gemma":[0.9997751,0.00002473481,0.00002153819,0.0001035282,0.000001576017,0.00007358695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001340447,0.00001216995,0.970429,0.00004974038,0.000005983472,0.00008324003,0.003253018,0.0001538125,0.0003524899,0.0004257601,0.0004224413,0.02479892],"study_design_scores_gemma":[0.0001795266,0.0001086003,0.985361,0.0001188329,0.00001451853,0.000005492773,0.000769116,0.000206127,0.0002149244,0.002596925,0.01025802,0.0001669512],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950349,0.001311147,0.0003221237,0.002600119,0.00004344114,0.0001752743,0.00001859417,0.000126091,0.0003683248],"genre_scores_gemma":[0.9990075,0.000237915,0.0002542189,0.0001831491,0.00001399447,0.00006734874,0.00001552114,0.0000105666,0.0002097469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02463197,"threshold_uncertainty_score":0.5966084,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4408904924","doi":"10.1080/03081060.2025.2480692","title":"Quantifying emergency response system risk caused by grade crossing blockages","year":2025,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Manitoba","funders":"Mitacs; University of Manitoba","keywords":"Emergency response; Level crossing; Transport engineering; Poison control; Engineering; Environmental science; Computer science; Risk analysis (engineering); Medical emergency; Business; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.008397392064182068,"gpt":0.2539094855262507,"spread":0.2455120934620686,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001305925,0.0001397573,0.0001650406,0.0002997436,0.000276135,0.00002633712,0.00007419241,0.0001829427,0.000002029393],"category_scores_gemma":[0.00001803071,0.0001433427,0.00002186669,0.0003745214,0.00005770183,0.00006099632,0.000002567252,0.0002571993,0.000001044597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000303297,"about_ca_system_score_gemma":0.0000129504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002083064,"about_ca_topic_score_gemma":0.00001253435,"domain_scores_codex":[0.9992708,0.00001489457,0.000256426,0.0001743194,0.00005710374,0.0002264489],"domain_scores_gemma":[0.999745,0.00003397591,0.00004606857,0.0001216862,0.00003025467,0.00002301083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009823103,0.00001183071,0.7420044,0.0006441893,0.0001907415,0.00008826959,0.002694486,0.0116887,0.2295512,0.003556859,0.001989162,0.007481916],"study_design_scores_gemma":[0.00225427,0.0001218358,0.6596696,0.001591654,0.0003232473,0.00002242259,0.01149502,0.0159787,0.2871723,0.001173156,0.01912054,0.001077222],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9737592,0.002294671,0.02203668,0.00007751315,0.0005612135,0.00008133977,0.00003151408,0.001076085,0.00008174581],"genre_scores_gemma":[0.99929,0.00006662439,0.0004991969,0.000002992226,0.00001589186,0.00001789876,0.00001871286,0.00001672807,0.00007194984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08233479,"threshold_uncertainty_score":0.5845345,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2979733112","doi":"10.1080/03081060.2019.1675321","title":"GIS-based transit trip allocation methods converting stop-level boarding and alighting trips into TAZ trips","year":2019,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"TRIPS architecture; Transport engineering; Transit (satellite); Computer science; Public transport; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03381816516095198,"gpt":0.352525553319223,"spread":0.318707388158271,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001370476,0.0001904026,0.0003603169,0.0003494606,0.0005277276,0.00005248628,0.0001633867,0.0003687468,0.00004783844],"category_scores_gemma":[0.00008505221,0.000195796,0.00005466719,0.0006247674,0.0003036536,0.0003245466,0.000002803875,0.0003067609,0.000002539577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003913746,"about_ca_system_score_gemma":0.0001188137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007323892,"about_ca_topic_score_gemma":0.0005110461,"domain_scores_codex":[0.9983134,0.0001262504,0.0005012889,0.0004970414,0.0002133022,0.0003487159],"domain_scores_gemma":[0.9991794,0.0002425608,0.000211168,0.0001592099,0.0001115028,0.00009621301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001230829,0.00004716825,0.8940461,0.0001936663,0.000049079,0.00001157183,0.01942826,0.0001006288,0.01692986,0.006490922,0.00001344621,0.06256616],"study_design_scores_gemma":[0.008892489,0.0004752401,0.8377091,0.0007528393,0.0005607958,0.000003843068,0.04917135,0.006994121,0.05675313,0.0163891,0.02048157,0.001816375],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9481206,0.0009374064,0.04722774,0.002319612,0.000168683,0.0003871576,0.00001124779,0.000377273,0.0004502819],"genre_scores_gemma":[0.9848158,0.00002514828,0.0147134,0.0001052963,0.00003304848,0.00002441446,0.00007261448,0.00001733464,0.0001929618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06074979,"threshold_uncertainty_score":0.7984331,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4404430951","doi":"10.1080/03081060.2024.2422400","title":"Electric vehicle drivers’ choices of expressway usage and peak avoidance: an empirical analysis considering the random effects among individuals","year":2024,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Transport engineering; Poison control; Human factors and ergonomics; Empirical research; Electric vehicle; Engineering; Psychology; Statistics; Mathematics; Environmental health; Power (physics); Medicine; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.01265863129777163,"gpt":0.2984256965670166,"spread":0.2857670652692449,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005069224,0.000112028,0.0002372536,0.0005154934,0.0003788561,0.00007426919,0.0001016215,0.0001814942,0.00001156636],"category_scores_gemma":[0.00006230463,0.00009066431,0.00004057826,0.001394459,0.0003618216,0.0002821118,0.000002179783,0.0002113394,4.527953e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007880695,"about_ca_system_score_gemma":0.00004225545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002566533,"about_ca_topic_score_gemma":0.0003675988,"domain_scores_codex":[0.9989784,0.0001193516,0.0002473066,0.0002713049,0.0001985166,0.0001851392],"domain_scores_gemma":[0.999145,0.0005581485,0.00009650845,0.0000940976,0.00004906733,0.0000571307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001754978,0.00001184409,0.966893,0.00005990043,0.0001740541,0.00001689012,0.02573855,0.002995246,0.0007187698,0.00183873,0.00002427182,0.00151125],"study_design_scores_gemma":[0.0007313051,0.0001060946,0.9826646,0.0001196097,0.0007711224,0.00000106653,0.004406498,0.007819043,0.001572942,0.0006500565,0.0009770181,0.0001806089],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922379,0.001971456,0.004740731,0.0003726205,0.0000518919,0.0001892325,0.00001607992,0.0002777145,0.0001423413],"genre_scores_gemma":[0.9992684,0.0002043195,0.0003413273,0.00002072821,0.00001772564,0.00002341275,0.00005857168,0.000008416496,0.00005711561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02133206,"threshold_uncertainty_score":0.3697183,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4404050854","doi":"10.1080/03081060.2024.2423013","title":"Robust evaluation of big data-driven winter weather traffic models using six weigh-in-motion sites as testbeds in Alberta's highway network","year":2024,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Transport Systems and Technology","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Transport engineering; Meteorology; Environmental science; Big data; Computer science; Geography; Engineering; Data mining","retraction":null,"screen_n_in":null,"score":{"opus":0.06445988452619943,"gpt":0.2633297745500006,"spread":0.1988698900238011,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003291044,0.000189675,0.0003155076,0.0006484722,0.00001908156,0.00001001529,0.0001584292,0.0003896961,0.0000209394],"category_scores_gemma":[0.000007811898,0.0001957165,0.00002574662,0.0006942606,0.00007179446,0.0002248737,0.000005169064,0.0003062954,0.000002419711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007437816,"about_ca_system_score_gemma":0.00004455479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002828955,"about_ca_topic_score_gemma":0.004443797,"domain_scores_codex":[0.9986739,0.00002134799,0.0005170249,0.000370302,0.0001574596,0.0002599324],"domain_scores_gemma":[0.9995606,0.00005652094,0.00005130067,0.0002676829,0.00004132547,0.00002256861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008922335,0.00002271309,0.03337234,0.0001630117,0.00004891669,0.00003557429,0.0007843345,0.9521165,0.001299964,0.003734321,0.00003491309,0.008378423],"study_design_scores_gemma":[0.0005321678,0.00004094273,0.007525786,0.0006300944,0.0001003703,0.00002195501,0.0001945325,0.9881514,0.0001772797,0.002132749,0.0002916405,0.0002011099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812102,0.004146202,0.01320903,0.0001118812,0.0003461268,0.0002776001,0.00002722708,0.0004928387,0.0001788535],"genre_scores_gemma":[0.9985028,0.00006224588,0.001021639,0.000003285714,0.00004099567,0.00002945838,0.0002868403,0.00004008582,0.00001263474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03603481,"threshold_uncertainty_score":0.7981086,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4406000960","doi":"10.1080/03081060.2024.2447571","title":"RecoMap – a semi-automated tool for analysing railway accident recommendations across jurisdictions and over time","year":2025,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Transport engineering; Accident (philosophy); Human factors and ergonomics; Business; Occupational safety and health; Poison control; Engineering; Medical emergency; Political science; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.03203620102346983,"gpt":0.4701292598408613,"spread":0.4380930588173915,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005198012,0.0001148207,0.0002364512,0.0005313318,0.001497679,0.00001375088,0.00006861627,0.0003090447,0.00009353458],"category_scores_gemma":[0.0001215756,0.0001145524,0.00002958167,0.0008092295,0.00007846653,0.0001172834,0.00001240149,0.0003844528,0.000008821022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005518487,"about_ca_system_score_gemma":0.0001565045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007221953,"about_ca_topic_score_gemma":0.0001632387,"domain_scores_codex":[0.9986415,0.0000725445,0.0005170163,0.0002899068,0.00008655924,0.0003924632],"domain_scores_gemma":[0.9987169,0.0007621604,0.0001280384,0.0001419726,0.0001871768,0.00006374953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001976957,0.00004018325,0.959402,0.0002277173,0.00008484268,0.000002330995,0.001485958,0.00005380545,0.0003143287,0.005924691,0.008075629,0.02419088],"study_design_scores_gemma":[0.001597085,0.00008507166,0.9476407,0.0003221458,0.00005594721,0.000001414852,0.0008179417,0.01127704,0.00003783591,0.002291389,0.03573329,0.0001401054],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9746462,0.0003840527,0.00796522,0.01423871,0.0002202293,0.0008719902,0.000352441,0.0007778667,0.0005433439],"genre_scores_gemma":[0.9942424,0.0001039514,0.001705177,0.000338616,0.00003003479,0.0004926903,0.0009401939,0.00001313756,0.002133844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02765767,"threshold_uncertainty_score":0.9998022,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4381571936","doi":"10.1080/03081060.2023.2214144","title":"Lane-based analysis of the saturation flow rate considering traffic composition","year":2023,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Traffic control and management","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"Qatar National Library","keywords":"Intersection (aeronautics); Transport engineering; Outcome (game theory); Saturation (graph theory); Metric (unit); Traffic flow (computer networking); Computer science; Econometrics; Simulation; Engineering; Mathematics; Economics; Computer security; Operations management; Microeconomics","retraction":null,"screen_n_in":null,"score":{"opus":0.00752674181485991,"gpt":0.200282180319996,"spread":0.1927554385051361,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006213342,0.00006040568,0.0001201066,0.0003920169,0.00004470494,0.000005705235,0.00003927158,0.00005547591,0.000003713466],"category_scores_gemma":[0.000002577573,0.0000514106,0.00003193971,0.0009757386,0.00003066308,0.00002258923,0.00000116539,0.00006578718,9.56724e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005671829,"about_ca_system_score_gemma":0.000003939767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002725719,"about_ca_topic_score_gemma":0.00007220307,"domain_scores_codex":[0.9996395,0.000007609101,0.0001408745,0.00008112703,0.00004866787,0.00008222991],"domain_scores_gemma":[0.9998316,0.00003362589,0.00002810065,0.00008191847,0.00001517994,0.000009599884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005241152,0.000003425215,0.003252317,0.00003251275,0.0001422867,0.000003639828,0.0002007624,0.9852108,0.005436992,0.0004605106,0.00004631334,0.005205232],"study_design_scores_gemma":[0.0003082992,0.00001100696,0.2820936,0.00002466854,0.0002972609,2.513121e-7,0.0001355099,0.7153844,0.001395602,0.00004725688,0.0002363573,0.00006578929],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930018,0.00008835744,0.005628528,0.0004125897,0.00007188309,0.00008543736,0.00002303558,0.0006576586,0.00003074111],"genre_scores_gemma":[0.9995682,0.000009139448,0.0002173511,0.00001302104,0.000003305003,0.000011999,0.0001647656,0.000005511991,0.000006767754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2788413,"threshold_uncertainty_score":0.2096463,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4381851880","doi":"10.1080/03081060.2023.2226636","title":"A fuzzy rule-based system for terrain classification in highway design","year":2023,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Terrain; Classifier (UML); Fuzzy logic; Data mining; Computer science; Artificial intelligence; Fuzzy rule; Machine learning; Fuzzy set; Geography; Cartography","retraction":null,"screen_n_in":null,"score":{"opus":0.0196060814482312,"gpt":0.2400947796796594,"spread":0.2204886982314282,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001141478,0.00008300015,0.0001097234,0.0004158346,0.00004193588,0.000007560086,0.00004709231,0.000138308,2.913924e-7],"category_scores_gemma":[0.000007233249,0.00008508004,0.00001225072,0.0003664907,0.00002066704,0.00003633135,5.734783e-7,0.0000924912,0.000002125963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000030163,"about_ca_system_score_gemma":0.0000100199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003520208,"about_ca_topic_score_gemma":0.000005200582,"domain_scores_codex":[0.9994942,0.000004762602,0.0001627985,0.0001228334,0.00003926819,0.0001761474],"domain_scores_gemma":[0.9998298,0.00004229937,0.00002279231,0.00007042473,0.00001963676,0.00001507228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001821145,0.00002065066,0.1172636,0.001919076,0.00007824295,0.0001466669,0.004163259,0.5747737,0.2049904,0.0441058,0.001299884,0.05105654],"study_design_scores_gemma":[0.004585302,0.0002367158,0.4114054,0.001253599,0.00007225987,0.00001312533,0.008857269,0.4525984,0.1064474,0.01025686,0.003348995,0.0009246878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8392578,0.00009103676,0.1577687,0.0001906846,0.0002940102,0.0003014979,0.0000216316,0.001937158,0.0001374485],"genre_scores_gemma":[0.9956765,0.000003475716,0.003998292,0.000004256893,0.00002142705,0.0001810808,0.00008791776,0.00001727504,0.000009816818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2941418,"threshold_uncertainty_score":0.3469463,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4412137856","doi":"10.1080/03081060.2025.2527323","title":"Modernizing Montreal’s household travel survey: adapting to evolving travel trends and technological shifts","year":2025,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Travel behavior; Transport engineering; Vehicle miles of travel; Engineering; Regional science; Geography; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.04116264578458948,"gpt":0.3046008978114259,"spread":0.2634382520268364,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006886525,0.0001853432,0.0003257007,0.0007030107,0.0006844921,0.00006423051,0.0002130069,0.0004248606,0.00001339995],"category_scores_gemma":[0.0001197863,0.0001861558,0.00003144458,0.001304965,0.000478008,0.0001750785,0.000009306451,0.0003347844,4.60826e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002626886,"about_ca_system_score_gemma":0.00005734677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003694311,"about_ca_topic_score_gemma":0.01368582,"domain_scores_codex":[0.9984975,0.00005335213,0.0003591923,0.0005205914,0.0001658925,0.0004034973],"domain_scores_gemma":[0.9994432,0.0001546492,0.00008087014,0.0001583772,0.00006700838,0.00009588499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000387957,0.00004186856,0.925087,0.00002382501,0.00002492449,0.00001994806,0.003210225,0.00003755689,0.0005943038,0.009400022,0.00006985225,0.06145162],"study_design_scores_gemma":[0.0003437771,0.00003481299,0.9902663,0.00009244731,0.00003648844,3.375618e-7,0.004744524,0.0001952366,0.0002489238,0.003715608,0.0001267492,0.0001948364],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9796863,0.001069451,0.01274049,0.002556915,0.00006635116,0.0001728817,0.00006275347,0.0005155058,0.003129387],"genre_scores_gemma":[0.9983197,0.00003341048,0.001050653,0.00007703492,0.00001273535,0.0000270109,0.00004101853,0.00001181845,0.0004265579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0651792,"threshold_uncertainty_score":0.763701,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4407260520","doi":"10.1080/03081060.2025.2462970","title":"Are online shoppers ready to use smart mobile city bus lockers?","year":2025,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transport engineering; Advertising; Engineering; Business; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.03731538928802592,"gpt":0.2868559746397734,"spread":0.2495405853517475,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005857802,0.0001437647,0.000211215,0.0006262247,0.0001690338,0.00005501298,0.0001029126,0.0001123028,0.00001780339],"category_scores_gemma":[0.00005277114,0.0001471138,0.00002274312,0.0007544894,0.00008190834,0.0002044503,0.00002010215,0.0001532414,0.00001401284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001336245,"about_ca_system_score_gemma":0.000008017692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00041584,"about_ca_topic_score_gemma":0.002703433,"domain_scores_codex":[0.9992299,0.000002235565,0.000210342,0.000284875,0.00007917573,0.0001934744],"domain_scores_gemma":[0.9995722,0.00002661127,0.00010437,0.000158619,0.0001293076,0.000008914805],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000247372,0.00003879741,0.9851614,0.00004698689,0.00002968918,0.00003373697,0.00004432832,0.00001210785,0.0001750389,0.001467976,0.000478579,0.01248658],"study_design_scores_gemma":[0.000307737,0.00000955315,0.9413976,0.0001062611,0.0001159259,6.739978e-7,0.001562759,0.00004338807,0.00003371693,0.00008150607,0.05618915,0.0001517011],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965495,0.0002525926,0.0002344914,0.001893301,0.000131932,0.0002388175,0.0000293307,0.0004666665,0.0002033195],"genre_scores_gemma":[0.9987387,0.000008752367,0.0002368602,0.000371892,0.000009447009,0.00006056942,0.0001119963,0.00001074934,0.0004510515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05571058,"threshold_uncertainty_score":0.5999128,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403800979","doi":"10.1080/03081060.2024.2420384","title":"Editorial","year":2024,"lang":"en","type":"editorial","venue":"Transportation Planning and Technology","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Engineering; Transport engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.009646726440714076,"gpt":0.3077637884339975,"spread":0.2981170619932834,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.000396679,0.0002130763,0.0003189985,0.0003561103,0.0003201865,0.00009637168,0.0002586027,0.002223343,0.00005168192],"category_scores_gemma":[0.000150406,0.0002156968,0.00005866257,0.0005165705,0.000486569,0.0001284869,0.000004238109,0.001213347,0.00002772281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004310635,"about_ca_system_score_gemma":0.0004788742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007745262,"about_ca_topic_score_gemma":0.001701512,"domain_scores_codex":[0.9982281,0.00002392359,0.0003245846,0.0005118851,0.0005874571,0.0003239926],"domain_scores_gemma":[0.9992533,0.0001923395,0.0001076808,0.0001602011,0.0002063893,0.00008013195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001567642,0.00001276643,0.003690815,0.0001089889,0.00003142321,0.00002680023,0.002000984,4.670842e-7,0.000004019499,0.001851821,0.9915298,0.0007264905],"study_design_scores_gemma":[0.0001662418,0.00003150714,0.0001618062,0.0001594534,0.0001182524,3.288935e-8,0.0005847752,6.6655e-7,0.000006127319,0.009085352,0.9894605,0.0002253076],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00279225,0.002381836,0.00003946305,0.0005563881,0.9909374,0.0001603129,0.0002731284,0.0009169315,0.001942318],"genre_scores_gemma":[0.0248588,0.000193088,0.00006998394,0.00000501291,0.9718363,0.00003251539,0.0007924662,0.00003051612,0.002181285],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.02206655,"threshold_uncertainty_score":0.999072,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4407892403","doi":"10.1080/03081060.2025.2467453","title":"Development of a microsimulation-based mass evacuation model for persons needing mobility assistance","year":2025,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Dalhousie University","funders":"","keywords":"Microsimulation; Transport engineering; Computer science; Operations research; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01538430181326102,"gpt":0.2667969423084246,"spread":0.2514126404951636,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009704931,0.00007693924,0.000111641,0.0002282985,0.00007477745,0.000006075334,0.00004192459,0.0001139716,0.000001243277],"category_scores_gemma":[0.00001250707,0.00008894486,0.00001786491,0.0002321866,0.0000290462,0.00004033423,6.419466e-7,0.00006131351,1.162785e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003275007,"about_ca_system_score_gemma":0.00005290148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.897216e-7,"about_ca_topic_score_gemma":0.00001970052,"domain_scores_codex":[0.9995013,0.000001954897,0.0002455873,0.0001125406,0.0000483625,0.00009025681],"domain_scores_gemma":[0.9997667,0.00004204846,0.00003967496,0.00006579914,0.00007335167,0.00001243969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002661477,0.00001764029,0.01966475,0.0003084827,0.00003070079,1.372866e-7,0.001189614,0.9146452,0.05369977,0.007042496,0.00002388144,0.003350741],"study_design_scores_gemma":[0.0004358821,0.000005855804,0.008384239,0.00006526895,0.000021408,3.612447e-8,0.0003479929,0.9773156,0.01215682,0.001089231,0.0001019589,0.00007569047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4487551,0.00007325098,0.5507972,0.00005630542,0.00002040456,0.000100757,0.00002038572,0.0001359398,0.00004062711],"genre_scores_gemma":[0.9139614,0.000001327022,0.08581197,0.00001215846,0.000001385205,0.00005834634,0.0001099427,0.000006877607,0.00003660242],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4652062,"threshold_uncertainty_score":0.3627066,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}