{"id":"W4318224794","doi":"10.1287/trsc.2023.1197","title":"In Memoriam: Bernard Gendron,1966–2022","year":2023,"lang":"en","type":"article","venue":"Transportation Science","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Université du Québec à Montréal","funders":"","keywords":"Download; Library science; Management; Economics; Computer science; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00165201,0.00008035137,0.0001013961,0.0004863067,0.0005228986,0.00006707757,0.0003175939,0.00005474581,0.0003239709],"category_scores_gemma":[0.00007959738,0.00008966598,0.000033663,0.004520275,0.0004005579,0.00100657,0.00000152426,0.00009783204,0.00018862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007280846,"about_ca_system_score_gemma":0.0004104251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001176224,"about_ca_topic_score_gemma":0.005694222,"domain_scores_codex":[0.9980509,0.00004121197,0.0002815958,0.0003283368,0.0009028856,0.0003950682],"domain_scores_gemma":[0.9994662,0.00006701777,0.00007534969,0.000124149,0.0001358845,0.0001313554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007090751,0.0001265837,0.4160204,0.00004041014,0.000009724602,0.0002018529,0.2851169,0.07201643,0.003872984,0.2094655,0.00900446,0.00405394],"study_design_scores_gemma":[0.0004867594,0.00002005771,0.939397,0.00002204852,0.000009003617,3.001953e-7,0.008242411,0.001246681,0.0004922245,0.00201855,0.04781385,0.0002511534],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9819987,0.00002221871,0.00168122,0.003332828,0.002173969,0.0002794497,0.00003068648,0.0003998701,0.01008102],"genre_scores_gemma":[0.9963207,0.0001582002,0.0007385615,0.0001745545,0.0001179856,0.00002336673,0.00006540008,0.000008349591,0.00239286],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5233766,"threshold_uncertainty_score":0.4021766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03042451283329796,"score_gpt":0.3448065800910194,"score_spread":0.3143820672577215,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}