{"id":"W4409627386","doi":"10.17268/rev.cyt.2025.01.06","title":"Machine Learning aplicado a la exploración minera usando matriz de confusión","year":2025,"lang":"en","type":"article","venue":"Revista Ciencia y Tecnología","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"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":[],"consensus_categories":[],"category_scores_codex":[0.0004528443,0.0002246247,0.00030081,0.0002493907,0.0001873488,0.0001784447,0.0003101089,0.0001579537,0.0000681398],"category_scores_gemma":[0.0002827646,0.000208405,0.00008494784,0.0006445737,0.00008356405,0.0001306029,0.00007824679,0.0005319873,0.00004873097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001126283,"about_ca_system_score_gemma":0.00006157243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002013937,"about_ca_topic_score_gemma":0.000002865735,"domain_scores_codex":[0.9987754,0.00006474052,0.0002936415,0.0002802326,0.0001309143,0.000455111],"domain_scores_gemma":[0.9994641,0.0001247059,0.00004962583,0.0002414013,0.00003599465,0.00008416398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007983371,0.000200992,0.05195558,0.003586367,0.0002961267,0.0002689345,0.001898916,0.03617778,0.4868907,0.07310733,0.02298668,0.3225507],"study_design_scores_gemma":[0.001057256,0.00006007254,0.00259686,0.0007457074,0.00009796175,0.0001074798,0.0002314802,0.1265883,0.006771533,0.0007091555,0.8602503,0.0007839382],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8800074,0.01162979,0.0231196,0.0004582713,0.0001777702,0.0002623043,0.00001117765,0.001834448,0.08249927],"genre_scores_gemma":[0.993452,0.0004800723,0.001251205,0.0001169712,0.00006334753,0.00003194716,0.000009767996,0.0000305989,0.004564075],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8372636,"threshold_uncertainty_score":0.8498508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007017739681289861,"score_gpt":0.2347902551750458,"score_spread":0.227772515493756,"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."}}