{"id":"W2613901005","doi":"10.20286/jeas.v3i4.27","title":"Prediction of Workplace Accidents with Knowledge Discovery Approach Using Weka Software","year":2016,"lang":"en","type":"article","venue":"Nova Journal of Engineering and Applied Sciences","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Engineering; Population; Occupational safety and health; Order (exchange); Occupational accident; Forensic engineering; Operations management; Business; Risk analysis (engineering); Environmental health; Occupational medicine; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001226233,0.0009720196,0.00077003,0.004820922,0.0007127082,0.001221963,0.0009981589,0.000561944,0.002157264],"category_scores_gemma":[0.006670343,0.0005063641,0.001997132,0.002071779,0.0002637825,0.000732524,0.0006491739,0.0008577392,0.0005995947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008180077,"about_ca_system_score_gemma":0.002233121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01514602,"about_ca_topic_score_gemma":0.01061574,"domain_scores_codex":[0.9990402,0.0001995613,0.000253968,0.0001850794,0.0002393594,0.00008190041],"domain_scores_gemma":[0.9954568,0.003423539,0.0004010965,0.0001797386,0.0004885582,0.00005025425],"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":[0.0005810584,0.001333317,0.05888562,0.002961813,0.001153232,0.00149911,0.0007973519,0.4898118,0.008767443,0.003293723,0.01174898,0.4191665],"study_design_scores_gemma":[0.00007947842,0.0003134061,0.01468277,0.0002537696,0.00048981,0.0003282322,0.0004683906,0.9627178,0.01018897,0.004361908,0.006043119,0.00007236406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3559665,0.0008565096,0.607425,0.001156346,0.0001378009,0.002618726,0.01230102,0.01340307,0.006134976],"genre_scores_gemma":[0.6046594,0.0007556003,0.3808273,0.0001224161,0.0000281176,0.00193542,0.009886318,0.00009656697,0.001688889],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01514602,"threshold_uncertainty_score":0.03011572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1760857870703401,"score_gpt":0.3984276914316152,"score_spread":0.2223419043612751,"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."}}