{"id":"W3152080211","doi":"10.2139/ssrn.3037874","title":"The Accident Externality from Trucking","year":2017,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Traffic and Road Safety","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"National Energy Technology Laboratory; Sid W. Richardson Foundation; Smith Richardson Foundation","keywords":"Truck; Externality; Accident (philosophy); Transport engineering; Business; Collision; Actuarial science; Economics; Engineering; Automotive engineering; Microeconomics; Computer science; Computer security","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":[],"consensus_categories":[],"category_scores_codex":[0.001130091,0.0003223772,0.0006521381,0.001758109,0.001119667,0.002137971,0.0004393548,0.001776256,0.02536215],"category_scores_gemma":[0.009357185,0.0002262684,0.0007377054,0.001726759,0.001063513,0.001906833,0.002862009,0.002259939,0.00145163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000887322,"about_ca_system_score_gemma":0.0008912206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00992669,"about_ca_topic_score_gemma":0.01070144,"domain_scores_codex":[0.9989243,0.0002931826,0.00006527207,0.0001721797,0.0002645761,0.000280422],"domain_scores_gemma":[0.9932301,0.002129228,0.002119983,0.0006161511,0.001030356,0.0008741899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002915263,0.0009712462,0.5004836,0.0008600851,0.00112152,0.005946536,0.00489585,0.02749961,0.002221896,0.2849617,0.05837296,0.1097498],"study_design_scores_gemma":[0.000140107,0.0008011261,0.5143132,0.0005323528,0.0006187312,0.003268319,0.0110472,0.012513,0.001180781,0.3783241,0.07708421,0.0001769279],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7829729,0.001730493,0.005874467,0.01223477,0.0003750033,0.00005569678,0.002180845,0.0001194818,0.1944563],"genre_scores_gemma":[0.9886263,0.0008594638,0.0001156514,0.0004384432,0.0002106663,0.000008601304,0.0005035882,0.00002430708,0.009212909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02536215,"threshold_uncertainty_score":0.08484477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009842181404743989,"score_gpt":0.2383580794933015,"score_spread":0.2285158980885575,"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."}}