{"id":"W4388984248","doi":"10.32339/0135-5910-2021-12-1227-1238","title":"FORECASTING OF INDUSTRIAL COKE QUALITY AT JSC EVRAZ NTMK BASED ON DATA OF PASSIVE INDUSTRIAL EXPERIMENT","year":2022,"lang":"en","type":"article","venue":"Ferrous Metallurgy Bulletin of Scientific Technical and Economic Information","topic":"Coal and Coke Industries Research","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"EVRAZ (Canada)","funders":"","keywords":"Coke; Quenching (fluorescence); Process engineering; Quality (philosophy); Environmental science; Metallurgy; Engineering; Waste management; Materials science; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004250872,0.000451483,0.0003250563,0.0007833896,0.0001320071,0.0004112617,0.0004133961,0.000490558,0.0004425065],"category_scores_gemma":[0.001082726,0.0001534983,0.0003798501,0.0006966388,0.0001543638,0.0004081581,0.0002381926,0.0003298865,0.0001828256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006166409,"about_ca_system_score_gemma":0.0003857897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01642978,"about_ca_topic_score_gemma":0.01415514,"domain_scores_codex":[0.9997624,0.00003142862,0.0000151583,0.00007289805,0.00009234673,0.00002586708],"domain_scores_gemma":[0.9995387,0.0001367843,0.00006420417,0.00006011709,0.000170428,0.00002982135],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001023314,0.0002223803,0.2022951,0.0001997729,0.0001162378,0.0005095235,0.0002234342,0.6917619,0.06189162,0.0005190893,0.0007535212,0.04048418],"study_design_scores_gemma":[0.0000352603,0.0002174576,0.1904199,0.00001123071,0.00003016577,0.00004552512,0.0001416961,0.78571,0.02220995,0.000234473,0.0009122555,0.00003212628],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913266,0.00003537037,0.006866846,0.0000238238,0.000006532398,0.00003594636,0.0008616108,0.0001568915,0.0006863746],"genre_scores_gemma":[0.9958965,0.00003311877,0.002870426,0.000002540511,0.000002566855,0.00001936438,0.0008893939,0.000007657412,0.0002783461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01642978,"threshold_uncertainty_score":0.03266829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1547529623344638,"score_gpt":0.2965658853134737,"score_spread":0.14181292297901,"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."}}