{"id":"W2129975229","doi":"10.5399/osu/jtrf.53.3.4243","title":"Factors Contributing to Police Attendance at Motor Vehicle Crash Scenes","year":2014,"lang":"en","type":"article","venue":"Journal of the Transportation Research Forum","topic":"Traffic and Road Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Crash; Attendance; Motor vehicle crash; Logistic regression; Transport engineering; Engineering; Human factors and ergonomics; Poison control; Computer security; Computer science; Environmental health; Political science; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008083371,0.00009439194,0.0001653448,0.000113982,0.000302419,0.00002329965,0.0003296621,0.00005466534,0.00003060134],"category_scores_gemma":[0.00006560572,0.00006021305,0.0001368435,0.0002748393,0.00004355038,0.0001277779,0.00001215898,0.0003530737,0.00001482672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001263942,"about_ca_system_score_gemma":0.00002653747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007086679,"about_ca_topic_score_gemma":0.001129889,"domain_scores_codex":[0.9984435,0.00007233762,0.0003434304,0.00007733146,0.0005715685,0.0004918607],"domain_scores_gemma":[0.999173,0.0002002277,0.00006723502,0.0001422286,0.0002421767,0.0001751158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001556957,0.00004800996,0.8360615,0.0001043246,0.0001100143,0.000003809056,0.002752816,0.1071534,0.04035131,0.0008370174,0.008658007,0.003764118],"study_design_scores_gemma":[0.0003806406,0.0000794005,0.9756937,0.00008194242,0.000009109204,9.998702e-7,0.0004661831,0.001908419,0.009091254,0.00005213279,0.01215677,0.0000794605],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944213,0.00005930967,0.002690684,0.002139395,0.0003555093,0.0001372332,0.00002952283,0.00003236076,0.0001346583],"genre_scores_gemma":[0.9993812,0.00001846908,0.0001155109,0.00006308787,0.0001222004,0.000002215126,0.000001781639,0.00002009792,0.0002754161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1396322,"threshold_uncertainty_score":0.2455417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03025756320018038,"score_gpt":0.2969591871914382,"score_spread":0.2667016239912578,"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."}}