{"id":"W2182081311","doi":"","title":"A probabilistic framework for the automated analysis of the exposure to road collision","year":2008,"lang":"en","type":"other","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Probabilistic logic; Collision; Computer science; Data collection; Work (physics); Collision avoidance; Risk analysis (engineering); Transport engineering; Computer security; Artificial intelligence; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003199981,0.0004656742,0.000786502,0.0007654001,0.000219529,0.00002943273,0.001199397,0.001284288,0.00006947202],"category_scores_gemma":[0.000354316,0.0003166199,0.0005137327,0.002241516,0.0001850974,0.00003013124,0.0001894433,0.0006629051,0.000008159816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000315824,"about_ca_system_score_gemma":0.0001315366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001797104,"about_ca_topic_score_gemma":0.005205058,"domain_scores_codex":[0.9981664,0.00006818135,0.0005467137,0.000392454,0.0002786229,0.0005475919],"domain_scores_gemma":[0.9974458,0.0003004741,0.0002680753,0.001809697,0.00007142568,0.000104569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009707503,0.0002019849,0.002624172,0.0002889248,0.004522263,0.00001320426,0.0006153485,0.6733201,0.0004275055,0.02527348,0.2760069,0.01660898],"study_design_scores_gemma":[0.0002916647,0.0001397205,0.02362389,0.0003253653,0.001612555,0.00001814861,0.00005818201,0.9157422,0.001174571,0.0009011966,0.05540307,0.0007094191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007151002,0.006967437,0.9598287,0.002373473,0.0005392561,0.006131698,0.00106935,0.01081602,0.00512304],"genre_scores_gemma":[0.8151102,0.001771273,0.1262862,0.00142412,0.0003413774,0.006375933,0.000126812,0.001627341,0.04693678],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8335425,"threshold_uncertainty_score":0.9999286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007406733293453597,"score_gpt":0.2218259113169136,"score_spread":0.21441917802346,"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."}}