{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":2,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":2,"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","author_layer_release":"2026-06-26"},"query_hash":"9a65208e581e","filters":{"venue":"European Transport/Trasporti Europei"}},"results":[{"id":"W4380354817","doi":"10.48295/et.2023.93.5","title":"Basic characteristics of floating car data from the perspective of traffic loss during the COVID-19 pandemic","year":2023,"lang":"en","type":"article","venue":"European Transport/Trasporti Europei","topic":"Transport and Logistics Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Transport Canada","funders":"","keywords":"Czech; Coronavirus disease 2019 (COVID-19); Data source; Data quality; Pandemic; Quality (philosophy); 2019-20 coronavirus outbreak; Computer science; Big data; Transport engineering; Database; Engineering; Data mining; Operations management","authors":[{"name":"Zuzana Purkrábková","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07591558174272521,"gpt":0.2714123059895672,"spread":0.1954967242468419,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001187271,0.0003446288,0.0004364755,0.0001262488,0.0002422135,0.00001994005,0.001533561,0.00005741682,0.0001527791],"category_scores_gemma":[0.000188923,0.0002514208,0.0001466418,0.00113689,0.0004390044,0.0001410462,0.00005891982,0.0006047271,0.00005818323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005422509,"about_ca_system_score_gemma":0.00009275576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001738081,"about_ca_topic_score_gemma":0.000276913,"domain_scores_codex":[0.9972841,0.0001386381,0.001222613,0.0004936246,0.0004356858,0.0004253124],"domain_scores_gemma":[0.9976131,0.0003147313,0.0003143134,0.00148304,0.0001475133,0.000127293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002292999,0.0002172947,0.7668238,0.0009534389,0.001036877,0.001835829,0.03210074,0.1620619,0.02698932,0.002511515,0.002434539,0.002805467],"study_design_scores_gemma":[0.0005666367,0.00002310768,0.985853,0.00007575106,0.0002181858,0.00001746381,0.001712726,0.001374932,0.0001432587,0.00002895495,0.009663505,0.0003224516],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899337,0.0002739155,0.001993362,0.0002085663,0.0004282917,0.0003379727,0.003861417,0.0006831686,0.002279549],"genre_scores_gemma":[0.9971065,0.0005990989,0.00008848447,0.0001003027,0.0003327467,0.000003375617,0.001483457,0.0001535077,0.0001325432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2190293,"threshold_uncertainty_score":0.9999938,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4392907614","doi":"10.48295/et.2024.96.6","title":"Distraction Effects of Manual Texting and Voice Messaging When Approaching Pedestrian Crossings on Urban Roads: a Driving Simulator Study","year":2024,"lang":"en","type":"article","venue":"European Transport/Trasporti Europei","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Queen's University; Massachusetts Institute of Technology","keywords":"Distraction; Pedestrian; Driving simulator; Text messaging; Computer science; Simulation; Transport engineering; Engineering; Psychology; World Wide Web","authors":[{"name":"Alessandro Calvi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01613992574077786,"gpt":0.3198886546407975,"spread":0.3037487289000196,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001397066,0.0004628107,0.0004640395,0.0003765012,0.0003626886,0.0002433881,0.0002701184,0.00006911637,0.0004246037],"category_scores_gemma":[0.00009117884,0.0004413058,0.0002016291,0.0002956351,0.0001274613,0.0005011341,0.00003042692,0.0008488256,0.0002771763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005419799,"about_ca_system_score_gemma":0.00003277493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001246742,"about_ca_topic_score_gemma":0.00002908584,"domain_scores_codex":[0.9961472,0.0006910657,0.001231135,0.001001159,0.0004667469,0.0004627013],"domain_scores_gemma":[0.9984201,0.0003773017,0.0004138312,0.0005061109,0.00006308885,0.0002195625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009498782,0.004164651,0.4913785,0.002357867,0.001585696,0.01037052,0.36831,0.001630296,0.007684948,0.003075604,0.002945475,0.1055466],"study_design_scores_gemma":[0.001315757,0.0004490216,0.9727334,0.000683299,0.0002578618,0.00006905728,0.004452242,0.0007268628,0.0001255831,0.000009917817,0.01869347,0.000483528],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9253374,0.0002438222,0.002783477,0.00007654498,0.001235622,0.0006838539,0.00001386315,0.0006716134,0.06895375],"genre_scores_gemma":[0.993197,0.000008071654,0.00007398353,0.0001111696,0.0003612566,0.00001365425,0.00004149807,0.0001830097,0.006010373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4813549,"threshold_uncertainty_score":0.9998039,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}