{"id":"W1967620733","doi":"10.4018/ijsds.2014100101","title":"The HRA-Based Road Crash Data","year":2014,"lang":"en","type":"article","venue":"International Journal of Strategic Decision Sciences","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Crash; Reliability (semiconductor); Human error; Data collection; Human reliability; Computer science; Risk assessment; Risk analysis (engineering); Process (computing); Transport engineering; Engineering; Computer security; Business; Statistics","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":[0.001002103,0.0006033062,0.0005363592,0.003168162,0.0003928883,0.0008569583,0.0009446617,0.0008264451,0.006446682],"category_scores_gemma":[0.005476916,0.0002065467,0.0005918262,0.002929962,0.000172185,0.0008636839,0.0005724969,0.0007153326,0.006850068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006131872,"about_ca_system_score_gemma":0.001046326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02135042,"about_ca_topic_score_gemma":0.01592679,"domain_scores_codex":[0.998365,0.0002341179,0.0002551187,0.0003114659,0.0007234414,0.00011074],"domain_scores_gemma":[0.9941372,0.0006851203,0.0003659495,0.00126397,0.003379373,0.0001684547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001756959,0.001672244,0.3803291,0.001240206,0.0006758327,0.001681383,0.0007286276,0.1239955,0.02272165,0.003913067,0.1258096,0.3354759],"study_design_scores_gemma":[0.0001122237,0.0008580109,0.5753463,0.000175109,0.0002274722,0.001033478,0.0009621365,0.2951504,0.0241167,0.002535178,0.09920123,0.0002818282],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3567217,0.0005030112,0.02276126,0.000786442,0.0003185435,0.0008412564,0.5961726,0.004773637,0.01712154],"genre_scores_gemma":[0.6003432,0.0003222094,0.01843368,0.0001039921,0.00007057228,0.0006062631,0.3746368,0.0001302912,0.005353071],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02135042,"threshold_uncertainty_score":0.04245228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3530296351452024,"score_gpt":0.489073995124313,"score_spread":0.1360443599791106,"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."}}