{"id":"W1971280951","doi":"10.3141/2083-17","title":"Two-Level Nested Logit Model to Identify Traffic Flow Parameters Affecting Crash Occurrence on Freeway Ramps","year":2008,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Traffic and Road Safety","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Florida Department of Transportation","keywords":"Crash; Traffic flow (computer networking); Transport engineering; Traffic volume; Line (geometry); Environmental science; Statistics; Engineering; Computer science; Mathematics; Computer network","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":[0.006774062,0.001381198,0.001733898,0.00207166,0.0005622489,0.001881585,0.002481518,0.001626726,0.005386611],"category_scores_gemma":[0.01604238,0.001049918,0.002220041,0.001077465,0.0008860066,0.002328123,0.00161376,0.002078526,0.001387803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001434843,"about_ca_system_score_gemma":0.001472625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01662932,"about_ca_topic_score_gemma":0.01136003,"domain_scores_codex":[0.9952189,0.002931563,0.000159661,0.000705878,0.0003458745,0.0006381146],"domain_scores_gemma":[0.9894986,0.007837026,0.001019263,0.0003948821,0.0008392484,0.0004109356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.002289047,0.001651281,0.1385308,0.0002382264,0.00110715,0.001344571,0.0009922797,0.7990766,0.001797667,0.02488156,0.002105154,0.02598562],"study_design_scores_gemma":[0.00007476438,0.0002014738,0.005254876,0.000009831861,0.00005947919,0.00008563811,0.00009074667,0.9893571,0.0001569705,0.004266663,0.0004115238,0.000030931],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6686617,0.0004295218,0.324741,0.000508795,0.0001122014,0.000371911,0.001912825,0.0008265917,0.002435516],"genre_scores_gemma":[0.9737704,0.0001116314,0.02007673,0.00005639298,0.00003267157,0.0003002548,0.001045904,0.00004294208,0.004563147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01662932,"threshold_uncertainty_score":0.03582513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1745739593717823,"score_gpt":0.3861543358495226,"score_spread":0.2115803764777403,"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."}}