{"id":"W4386106659","doi":"10.2139/ssrn.4540923","title":"The Use of Artificial Intelligence (AI) in Gold Recovery: A Case Study of Refractory Sulfide-Bearing Ore Biooxidation Using &lt;i&gt;Feroplasma Acidophilum&lt;/i&gt;","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Refractory (planetary science); Sulfide; Bearing (navigation); Metallurgy; Chemistry; Materials science; Artificial intelligence; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.003322549,0.0003965114,0.0005785307,0.0006786444,0.0001875223,0.0001963059,0.0004198692,0.00032879,0.000007562535],"category_scores_gemma":[0.0004240333,0.0003407905,0.0002411463,0.0005657368,0.00006107362,0.0003875115,0.0002316883,0.00457629,0.000006286711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001412027,"about_ca_system_score_gemma":0.0008366572,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007559211,"about_ca_topic_score_gemma":0.03057426,"domain_scores_codex":[0.9959531,0.0003786751,0.001529499,0.0003863295,0.0005235553,0.001228791],"domain_scores_gemma":[0.9981714,0.0003413885,0.0007102666,0.000504891,0.0001866607,0.0000853548],"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":[0.0003236545,0.0004132525,0.0003843012,0.0001790899,0.0009239193,0.0002909187,0.001400864,0.6083664,0.1792846,0.002721248,0.00002911624,0.2056826],"study_design_scores_gemma":[0.001908624,0.002896065,0.002190291,0.003121301,0.001278588,0.009948135,0.02709479,0.848581,0.02212839,0.07444021,0.002830263,0.003582398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9743639,0.001034201,0.02257055,0.0000366451,0.001423861,0.0004661558,0.00001082053,0.00007667935,0.0000171624],"genre_scores_gemma":[0.9949713,0.004349129,0.0002121251,0.000004225597,0.0002503631,0.00001082068,0.000009239041,0.00008513937,0.0001077058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2402145,"threshold_uncertainty_score":0.9999044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07460310744259872,"score_gpt":0.2903817299362738,"score_spread":0.215778622493675,"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."}}