{"id":"W4403439362","doi":"10.4236/ti.2024.154011","title":"Applying Machine Learning Techniques to Analyze and Explore Precious Metals","year":2024,"lang":"en","type":"article","venue":"Technology and Investment","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001203474,0.0001281749,0.0001441566,0.0004711324,0.00008750241,0.00005051244,0.00005532596,0.0001128001,0.000008193368],"category_scores_gemma":[0.00001890357,0.000110493,0.00001340948,0.000342221,0.00005417947,0.0000784099,0.00006910854,0.0002635951,0.000008506689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002279266,"about_ca_system_score_gemma":0.000003837474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004474689,"about_ca_topic_score_gemma":0.000002532151,"domain_scores_codex":[0.9994635,0.000007116351,0.0001186691,0.0001948118,0.00004750354,0.0001683931],"domain_scores_gemma":[0.9998347,0.0000154876,0.000008361866,0.00008277321,0.000006477021,0.00005223334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009201094,0.00002739888,0.002028135,0.00115087,0.0003644903,0.0001347612,0.00238362,0.001435087,0.1953735,0.1287655,0.001970702,0.6663567],"study_design_scores_gemma":[0.0002367641,0.0004257663,0.0001304077,0.0008859239,0.0001478182,0.0003187389,0.0006250396,0.07663511,0.2421532,0.05799967,0.619579,0.0008625195],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9590417,0.02956695,0.003527725,0.0007459984,0.00008943871,0.0003413496,0.000002616812,0.00354333,0.003140955],"genre_scores_gemma":[0.9923654,0.000371401,0.006417618,0.0001684173,0.00002737618,0.0002752288,0.00000344768,0.00002341483,0.0003476712],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6654941,"threshold_uncertainty_score":0.4505773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01611346990039834,"score_gpt":0.2490811539280162,"score_spread":0.2329676840276178,"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."}}