{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001924473,0.0002839802,0.0004323613,0.0007755757,0.0006992457,0.00006053099,0.0002082135,0.000197102,0.0001197328],"category_scores_gemma":[0.0001124915,0.0002475716,0.00007185894,0.001270456,0.0005445587,0.0008949553,0.000006775427,0.00118699,0.000009820739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001257818,"about_ca_system_score_gemma":0.0001803596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009123957,"about_ca_topic_score_gemma":0.005343781,"domain_scores_codex":[0.9962689,0.0002785038,0.0006733452,0.000480337,0.00145789,0.0008410651],"domain_scores_gemma":[0.9964679,0.001069557,0.0001112361,0.0002675418,0.001663766,0.0004200286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00207296,0.0007219333,0.7308579,0.003646005,0.0009830563,0.0002002172,0.07945301,0.05163309,0.06660284,0.002265851,0.02834884,0.03321426],"study_design_scores_gemma":[0.003005905,0.001126964,0.8602093,0.0008163395,0.00005160577,0.000006154107,0.01312103,0.01791577,0.03137235,0.00009901638,0.07149497,0.0007805665],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966649,0.0004514797,0.0002653781,0.0007376156,0.00007360966,0.0007011549,0.0003536155,0.0002000226,0.0005522047],"genre_scores_gemma":[0.9941931,0.002928047,0.0008650756,0.00001517051,0.00007779028,0.0001740431,0.0001097364,0.0000656281,0.001571383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1293514,"threshold_uncertainty_score":0.9999977,"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."}}