{"id":"W4220712189","doi":"10.3390/mining2010008","title":"Integrated Artificial Neural Network and Discrete Event Simulation Framework for Regional Development of Refractory Gold Systems","year":2022,"lang":"en","type":"article","venue":"Mining","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial neural network; Refractory (planetary science); Process engineering; Engineering; Artificial intelligence; Materials science; Metallurgy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002248203,0.00008501776,0.0001257801,0.00004632548,0.0001600278,0.00002218507,0.00004852686,0.00003591764,0.000006060182],"category_scores_gemma":[0.00002812321,0.00008581695,0.00002056253,0.0001192764,0.000009912279,0.00004614885,0.00002680475,0.0001328636,1.850642e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006035805,"about_ca_system_score_gemma":0.00001822338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002819973,"about_ca_topic_score_gemma":0.000002068017,"domain_scores_codex":[0.9993433,0.00001983121,0.0002584996,0.0001096778,0.0001165216,0.0001521149],"domain_scores_gemma":[0.99968,0.0001533209,0.00006470807,0.00005380327,0.00001939624,0.00002880943],"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":[0.00002434283,0.000004296724,0.0002512839,0.00008313624,0.00001671137,5.327491e-7,0.001538375,0.9839706,0.0005269797,0.0002101475,0.0002202553,0.01315334],"study_design_scores_gemma":[0.00008167677,0.00003277932,0.0002748583,0.0001373089,0.000008554279,0.000001813708,0.001004088,0.9911987,0.00004730968,0.0001808555,0.006915831,0.0001162693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9161465,0.0006236607,0.0825555,0.00001314748,0.0004523814,0.000102434,0.000005325681,0.00006357696,0.00003751815],"genre_scores_gemma":[0.9883496,8.094245e-7,0.01131221,0.000009211962,0.0001715949,0.00004332272,0.00003601156,0.00001892536,0.00005837965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07220308,"threshold_uncertainty_score":0.3499514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04485035785824144,"score_gpt":0.2768632598508939,"score_spread":0.2320129019926525,"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."}}