{"id":"W4361216045","doi":"10.1016/j.oregeorev.2023.105403","title":"A study of faults in the Superior province of Ontario and Quebec using the random forest machine learning algorithm: Spatial relationship to gold mines","year":2023,"lang":"en","type":"article","venue":"Ore Geology Reviews","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada; Laurentian University","funders":"Laurentian University","keywords":"Greenstone belt; Lineament; Prospectivity mapping; Geology; Fault (geology); Random forest; Algorithm; Geologic map; Intersection (aeronautics); Seismology; Geochemistry; Cartography; Archean; Artificial intelligence; Geomorphology; Geography; Tectonics; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002946249,0.0002236329,0.0002139842,0.001643381,0.0009419215,0.0006910461,0.00042938,0.0002281531,0.0009918067],"category_scores_gemma":[0.002024638,0.0001107414,0.0002594277,0.003468557,0.0003892156,0.0002180156,0.0002419238,0.0001677892,0.0001370822],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009679002,"about_ca_system_score_gemma":0.01002918,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9925588,"about_ca_topic_score_gemma":0.9955917,"domain_scores_codex":[0.9997494,0.00002462016,0.00001295892,0.00004630654,0.00009255573,0.0000740734],"domain_scores_gemma":[0.9988357,0.0002137996,0.0001549928,0.00004542524,0.0006516998,0.00009830612],"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":[0.00009109038,0.00003029131,0.956252,0.00005724413,0.00006016275,0.0002978746,0.0006438363,0.009711296,0.001594954,0.000425138,0.001218846,0.02961733],"study_design_scores_gemma":[0.000007655384,0.00001515762,0.9740383,0.00001430417,0.00001640792,0.0000705991,0.0007253882,0.02255547,0.0003853863,0.00006396152,0.002096668,0.00001069597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992662,0.0001990903,0.001412402,0.0001102231,0.000003111829,0.00004886204,0.003148254,0.00004622147,0.00237006],"genre_scores_gemma":[0.9948841,0.0001036075,0.001815749,0.000009434613,0.000001748835,0.00001577868,0.001933151,0.000006252215,0.001230073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.990321,"threshold_uncertainty_score":0.07022643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04766924970803159,"score_gpt":0.2787877802406397,"score_spread":0.2311185305326081,"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."}}