{"id":"W2965149626","doi":"","title":"Закономерности изменения качества кокса в зависимости от сырьевой базы ЦОФ “Кузнецкая” и ОУОУ ЕЗСМК","year":2017,"lang":"ru","type":"article","venue":"ЧЕРНАЯ МЕТАЛЛУРГИЯ. Бюллетень научно-технической и экономической информации","topic":"Coal and Coke Industries Research","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"EVRAZ (Canada)","funders":"","keywords":"Raw material; Coal; Environmental science; Waste management; Base (topology); Coal preparation plant; Pulp and paper industry; Mining engineering; Engineering; Chemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008749932,0.0003185451,0.0002648538,0.001500233,0.001052484,0.002117769,0.0004549612,0.0005115833,0.0113774],"category_scores_gemma":[0.00147358,0.0004859915,0.0004352634,0.001224199,0.001681035,0.0009918234,0.0006809151,0.00119392,0.003196487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007426993,"about_ca_system_score_gemma":0.001334906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003824774,"about_ca_topic_score_gemma":0.006414896,"domain_scores_codex":[0.9989361,0.0001064606,0.00006963236,0.0001987626,0.0005865571,0.0001024401],"domain_scores_gemma":[0.9990976,0.0002074837,0.0001734275,0.0001563205,0.0003216798,0.00004355386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000275379,0.0001655825,0.006090869,0.0006998897,0.00005014182,0.001348839,0.004248223,0.002838165,0.4447305,0.15677,0.003387058,0.3793954],"study_design_scores_gemma":[0.00005493319,0.0004010186,0.02452967,0.0002164111,0.0001411873,0.002495048,0.00319458,0.004230274,0.4864311,0.04760075,0.4304672,0.0002378848],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3661032,0.01346377,0.2434764,0.001843814,0.002128451,0.0004038445,0.001561789,0.001112724,0.369906],"genre_scores_gemma":[0.8193061,0.004874453,0.1303165,0.0001254451,0.000177781,0.0003076952,0.0003102754,0.0002302477,0.04435144],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0113774,"threshold_uncertainty_score":0.0380612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09143539626621368,"score_gpt":0.3495756845192387,"score_spread":0.258140288253025,"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."}}