{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","open_science","research_integrity","insufficient_payload"],"category_scores_codex":[0.006199815,0.008034377,0.007833726,0.003010806,0.01270702,0.01014443,0.0202489,0.007212545,0.05683558],"category_scores_gemma":[0.006651889,0.008347606,0.00502582,0.003458043,0.007330157,0.006230636,0.01223498,0.01241808,0.04922894],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002841924,"about_ca_system_score_gemma":0.005704938,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02479342,"about_ca_topic_score_gemma":0.008632564,"domain_scores_codex":[0.9563293,0.00314246,0.007778069,0.009936212,0.009359851,0.01345406],"domain_scores_gemma":[0.9610876,0.002471496,0.005447465,0.0203201,0.003675051,0.006998327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006605641,0.007467649,0.02341836,0.00265089,0.009267566,0.007309275,0.004314832,0.002286177,0.01206548,0.06239034,0.3768458,0.4853779],"study_design_scores_gemma":[0.01434712,0.002798988,0.04232583,0.00261212,0.002584731,0.0009615486,0.002683293,0.006324099,0.01346345,0.012806,0.8881968,0.01089602],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2000448,0.02209148,0.001139019,0.03380764,0.02462924,0.00905089,0.005095106,0.004269111,0.6998727],"genre_scores_gemma":[0.764533,0.00647566,0.000921507,0.002809566,0.01252026,0.001212908,0.001003573,0.001953927,0.2085696],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5644882,"threshold_uncertainty_score":0.9999318,"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."}}