{"id":"W3091792859","doi":"10.32866/001c.17386","title":"How Data Imputation Affects Crash Modeling Results","year":2020,"lang":"en","type":"article","venue":"Findings","topic":"Traffic and Road Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Missing data; Crash; Imputation (statistics); Computer science; Statistics; Econometrics; Data mining; Mathematics; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.4202324,0.001647103,0.002153397,0.002222974,0.003947251,0.008928781,0.00635168,0.002886559,0.01166414],"category_scores_gemma":[0.7765167,0.001783547,0.005382543,0.006274652,0.004274503,0.007544038,0.005441205,0.006460961,0.002757757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003046699,"about_ca_system_score_gemma":0.005845946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02022713,"about_ca_topic_score_gemma":0.01377585,"domain_scores_codex":[0.4156684,0.5275783,0.01505159,0.02211989,0.01460143,0.004980436],"domain_scores_gemma":[0.1930983,0.7259929,0.01668554,0.04539247,0.01758787,0.001242947],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002693991,0.0007174082,0.6317539,0.001700153,0.01158955,0.001103766,0.01872954,0.04415383,0.0007877565,0.06017525,0.0617702,0.1648246],"study_design_scores_gemma":[0.001153707,0.001852317,0.2526126,0.005614091,0.01054301,0.001927302,0.01921358,0.3086528,0.008884494,0.2667346,0.1220146,0.0007969372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3342631,0.003705971,0.5773972,0.03287516,0.003011509,0.002183984,0.01656121,0.002676219,0.02732555],"genre_scores_gemma":[0.8432172,0.0005218966,0.1366159,0.005864859,0.000440504,0.002245385,0.005901122,0.001709956,0.003483193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5797676,"threshold_uncertainty_score":0.7149567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04448710579232729,"score_gpt":0.225650458825685,"score_spread":0.1811633530333577,"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."}}