{"id":"W2562297636","doi":"10.1080/00084433.2016.1261501","title":"A systems approach to mineral processing based on mathematical programming","year":2016,"lang":"en","type":"article","venue":"Canadian Metallurgical Quarterly","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Concentrator; Computer science; Profitability index; Representation (politics); Mineral processing; Sample (material); Product (mathematics); Industrial engineering; Engineering; Mathematics","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":[0.0002193968,0.0002028217,0.0002740084,0.0002120643,0.00005392752,0.0001430645,0.0002098036,0.0001232202,0.0000743265],"category_scores_gemma":[0.00001505556,0.0001470231,0.00007699909,0.000136041,0.00002885875,0.00008674012,0.00000339186,0.0001006033,0.0001907031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002585544,"about_ca_system_score_gemma":0.00006439503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003306776,"about_ca_topic_score_gemma":0.0003760664,"domain_scores_codex":[0.9987791,0.00001983449,0.0002826754,0.0002635578,0.0001106072,0.0005442267],"domain_scores_gemma":[0.9988689,0.00003598016,0.0000203314,0.0002739703,0.00002208928,0.0007786573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007499309,0.0002855034,0.00008174887,0.001390676,0.0001716285,0.0003120799,0.001886432,0.03315703,0.001069733,0.08668174,0.01241759,0.8624709],"study_design_scores_gemma":[0.0004129197,0.000404999,0.00005999243,0.0002875781,0.00002326675,0.0000516447,0.0001157788,0.8866984,0.00001503918,0.0003912374,0.1109262,0.0006129767],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07738995,0.00005315334,0.849422,0.0006170908,0.0002516991,0.001031933,0.00004375616,0.0009467479,0.07024366],"genre_scores_gemma":[0.9708403,2.622103e-7,0.02835825,0.0001299415,0.0001144898,0.0002177348,0.00000466038,0.00005116018,0.0002831504],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8934504,"threshold_uncertainty_score":0.5995429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01459290698159385,"score_gpt":0.1967110143943479,"score_spread":0.1821181074127541,"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."}}