{"id":"W4399563504","doi":"10.1109/cogsima61085.2024.10553924","title":"Injury Prediction for Canadian Mineral Exploration Using Machine Learning","year":2024,"lang":"en","type":"article","venue":"","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Computer science; Mineral exploration; Machine learning; Artificial intelligence; Geology; Geochemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006643008,0.0008674655,0.0003950206,0.003034116,0.0008519016,0.0007201033,0.001286693,0.0005357598,0.001957569],"category_scores_gemma":[0.002260429,0.0002112395,0.0007682827,0.002475357,0.000306369,0.0003014834,0.0006293739,0.0006216087,0.0006150678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01402546,"about_ca_system_score_gemma":0.01740875,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9773108,"about_ca_topic_score_gemma":0.9838941,"domain_scores_codex":[0.9996077,0.00002783203,0.00002050292,0.00007925175,0.0001596331,0.0001050541],"domain_scores_gemma":[0.9988688,0.000129569,0.0001239605,0.00004582278,0.0007324334,0.00009939653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006023024,0.0005114095,0.6421458,0.000246887,0.0002323209,0.0003812021,0.0002487304,0.2091431,0.001626701,0.001083761,0.01604627,0.1277315],"study_design_scores_gemma":[0.0000239598,0.0001031009,0.2956703,0.00005960668,0.00005872942,0.00007564769,0.000650786,0.6975563,0.00146172,0.0005334984,0.003762877,0.0000434855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.966103,0.0005332272,0.01020112,0.0006417228,0.000041844,0.0001335265,0.0188546,0.0006099787,0.002881025],"genre_scores_gemma":[0.9697993,0.0003767071,0.007114079,0.00006032011,0.00001198648,0.00005616204,0.01943121,0.0000222273,0.003128013],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02268916,"threshold_uncertainty_score":0.1017624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.191593991797833,"score_gpt":0.5105708209037512,"score_spread":0.3189768291059181,"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."}}