{"id":"W618236167","doi":"","title":"Association of Highway Traffic Volumes with Cold and Snow and Their Interactions","year":2008,"lang":"en","type":"article","venue":"Transportation Research Board 87th Annual MeetingTransportation Research Board","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Snow; Environmental science; Meteorology; Precipitation; Traffic flow (computer networking); Traffic volume; Volume (thermodynamics); Cold front; Geography; Transport engineering; Engineering; Computer science","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":[0.0004900432,0.0002666136,0.0002642459,0.00122996,0.0002018459,0.0007365412,0.0003134601,0.0002054253,0.0015624],"category_scores_gemma":[0.002132373,0.0001534078,0.0004566525,0.0013054,0.0002996417,0.0002692942,0.0003720305,0.00034282,0.0001737163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008114506,"about_ca_system_score_gemma":0.0008971457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0869546,"about_ca_topic_score_gemma":0.1265633,"domain_scores_codex":[0.9994119,0.0001264245,0.0000383142,0.00008365614,0.0002153008,0.0001242967],"domain_scores_gemma":[0.9976672,0.0007526632,0.0008787994,0.0001088044,0.0004059171,0.0001867157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004892322,0.00001292723,0.9965473,0.000005769527,0.00005356598,0.00003154427,0.00004773817,0.001036231,0.0001970414,0.00004603926,0.0001012406,0.001871775],"study_design_scores_gemma":[6.008879e-7,0.0000175246,0.9984928,0.000001883838,0.00001180273,0.00003455101,0.00008385433,0.001011241,0.00007940849,0.0000335823,0.0002299984,0.000002886604],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974987,0.0001595529,0.0004509998,0.00002809852,0.000005042411,0.000006638935,0.0006477393,0.0000135292,0.001189678],"genre_scores_gemma":[0.9982367,0.00007781869,0.0001582157,0.000004248215,0.00000833682,0.000005268467,0.0009341218,0.000004280546,0.0005710635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0869546,"threshold_uncertainty_score":0.1728969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02827488910743681,"score_gpt":0.2982643170228421,"score_spread":0.2699894279154053,"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."}}