{"id":"W623566820","doi":"","title":"Using GPS and GIS Technologies to Analyze Truck Drivers' Compliance with Traffic Regulations","year":2007,"lang":"en","type":"article","venue":"Transportation Research Board 86th Annual MeetingTransportation Research Board","topic":"Safety Warnings and Signage","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Truck; Transport engineering; Global Positioning System; Pedestrian; Computer science; Engineering; Automotive engineering; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001262811,0.0002791414,0.0002232831,0.002677925,0.0004833795,0.000662538,0.0003336822,0.0002718582,0.0005142196],"category_scores_gemma":[0.004645328,0.0001427661,0.000200516,0.002758356,0.0003493477,0.0003807637,0.0004622978,0.0002518405,0.0001847784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001308754,"about_ca_system_score_gemma":0.001802524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3092238,"about_ca_topic_score_gemma":0.3581819,"domain_scores_codex":[0.9985909,0.0003922282,0.00009408315,0.0001168856,0.000655235,0.0001507158],"domain_scores_gemma":[0.9980361,0.0004494011,0.0004098227,0.0001288933,0.0008869247,0.00008874759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001059712,0.0001036676,0.9587983,0.00002265172,0.00004441586,0.00006647395,0.003443848,0.001166319,0.001704552,0.0001974508,0.0003132196,0.03403306],"study_design_scores_gemma":[0.00001335375,0.0002095887,0.9807352,0.000009985063,0.00003009689,0.0001236976,0.009494118,0.006623104,0.001148964,0.0001104115,0.001482105,0.00001935895],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971373,0.00002695107,0.00139847,0.00003406003,0.00000206395,0.0000357399,0.0001618767,0.00001324485,0.001190309],"genre_scores_gemma":[0.9959502,0.00007718332,0.002621865,0.0000164725,0.000002863052,0.00004430076,0.0005212066,0.000003082337,0.0007628648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3092238,"threshold_uncertainty_score":0.6148479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1035143748442116,"score_gpt":0.4242187860543142,"score_spread":0.3207044112101026,"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."}}