{"id":"W2068959684","doi":"10.1016/j.ssci.2011.02.014","title":"Possibilistic regression analysis of influential factors for occupational health and safety management systems","year":2011,"lang":"en","type":"article","venue":"Safety Science","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Occupational safety and health; Regression analysis; Poison control; Human factors and ergonomics; Injury prevention; Risk analysis (engineering); Engineering; Environmental health; Computer science; Medicine; Machine learning","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":[0.01763014,0.001727524,0.002086576,0.00509285,0.001465555,0.00306052,0.002739721,0.001582909,0.004472433],"category_scores_gemma":[0.06150185,0.001311191,0.003461954,0.002306212,0.001410455,0.002733846,0.001766487,0.001903528,0.0004068129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002259965,"about_ca_system_score_gemma":0.002556951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007973265,"about_ca_topic_score_gemma":0.005109531,"domain_scores_codex":[0.989641,0.007146415,0.0003880952,0.0008280955,0.00149109,0.0005052928],"domain_scores_gemma":[0.9344621,0.05943682,0.001743807,0.0008261936,0.002937632,0.000593464],"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":[0.0005106693,0.000215627,0.005116028,0.0003072896,0.0004598367,0.0001983417,0.0002174459,0.9357515,0.001351422,0.03057787,0.0004103907,0.02488367],"study_design_scores_gemma":[0.000009591652,0.00006024792,0.0005804348,0.00001113816,0.00004828101,0.00001667933,0.00002402818,0.9924816,0.0002301584,0.006443079,0.00007987058,0.00001494058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1548698,0.000358012,0.8414785,0.0003152853,0.0000382687,0.0002315855,0.0001830162,0.0001965842,0.002328976],"genre_scores_gemma":[0.9246314,0.000193933,0.07341631,0.00003006943,0.00002774917,0.0002591202,0.0001972906,0.00004793864,0.001196162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01763014,"threshold_uncertainty_score":0.09323823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2469128877088869,"score_gpt":0.4607089107667947,"score_spread":0.2137960230579078,"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."}}