{"id":"W3105826940","doi":"10.3390/pr8111478","title":"Quantitative Methods to Support Data Acquisition Modernization within Copper Smelters","year":2020,"lang":"en","type":"article","venue":"Processes","topic":"Metallurgical Processes and Thermodynamics","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Merck Canada Inc. (Canada); McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Automation; Process (computing); Smelting; Computer science; Data acquisition; Process control; Process engineering; Systems engineering; Engineering; Mechanical engineering; Materials science","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":[0.0001743067,0.0001491934,0.0001845146,0.00003693836,0.00004350946,0.00006792677,0.0003590643,0.00004972314,0.0001383224],"category_scores_gemma":[0.0003363095,0.0001327547,0.0000149463,0.0004801269,0.00001718573,0.0004511717,0.0001043805,0.00009264178,0.0001206174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001565163,"about_ca_system_score_gemma":0.00004315699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002601639,"about_ca_topic_score_gemma":0.0000055275,"domain_scores_codex":[0.9991526,0.00002402701,0.00022192,0.0002915308,0.0001500821,0.0001598268],"domain_scores_gemma":[0.9994188,0.00007080744,0.00003770973,0.000202607,0.0001225494,0.000147512],"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":[0.0001676364,0.00006111169,0.00004890939,0.005753154,0.0001812971,0.00001279575,0.006562368,0.9495588,0.01955517,0.003085374,0.002302377,0.012711],"study_design_scores_gemma":[0.0001231262,0.0001110301,0.00001067039,0.0000235068,0.00003083934,0.000002169669,0.0002044649,0.9906967,0.003391288,0.001016476,0.004178544,0.000211229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01051344,0.0005580292,0.9855961,0.0004452119,0.0001075404,0.0001653212,0.00006308748,0.0003313482,0.002219979],"genre_scores_gemma":[0.8877436,0.0001373066,0.110929,0.0007777248,0.000062377,0.00001650581,0.0002673963,0.0000444064,0.00002169825],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8772302,"threshold_uncertainty_score":0.541358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1011143590295787,"score_gpt":0.3569974577751231,"score_spread":0.2558830987455444,"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."}}