{"id":"W2891962703","doi":"10.1016/b978-0-08-102201-6.00010-8","title":"Nonrecovery and Heat recovery cokemaking technology","year":2018,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"ArcelorMittal; United Nations Development Programme; McMaster University","keywords":"Coke; Engineering; Steel mill; Flexibility (engineering); Mill; Process engineering; Footprint; Power station; Product (mathematics); Ecological footprint; Manufacturing engineering; Waste management; Environmental science; Mechanical engineering; Electrical engineering; Metallurgy; Materials science; Sustainability; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001577177,0.0008048935,0.0004467676,0.0007164686,0.0004569567,0.001568158,0.0009325258,0.0007925394,0.01472809],"category_scores_gemma":[0.0001536119,0.0003062507,0.0003472253,0.0007669774,0.0005633606,0.002084656,0.0006678613,0.001130991,0.00559513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000807142,"about_ca_system_score_gemma":0.0004430698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006317105,"about_ca_topic_score_gemma":0.00135402,"domain_scores_codex":[0.9998131,0.000009930351,0.000006452172,0.00004178685,0.0001103533,0.00001832494],"domain_scores_gemma":[0.9999458,0.00002057793,0.000003384369,0.00001144341,0.0000156248,0.000003292369],"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":[0.0001323459,0.0001606911,0.0001342403,0.001965436,0.00001949237,0.0002961495,0.0002100519,0.003460231,0.1738773,0.1361197,0.01826677,0.6653576],"study_design_scores_gemma":[0.00001128971,0.00008244225,0.0005869149,0.000272175,0.00001959249,0.0008160615,0.0001105102,0.005501546,0.1577919,0.04190687,0.7928675,0.00003318045],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.02793308,0.1141812,0.102519,0.001029681,0.002102779,0.00008731859,0.000193417,0.0006773554,0.7512762],"genre_scores_gemma":[0.08521114,0.04036245,0.01943903,0.000279351,0.0002634937,0.00004629165,0.0002652447,0.0002587951,0.8538742],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01472809,"threshold_uncertainty_score":0.04927039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007676828921971661,"score_gpt":0.1960611932664202,"score_spread":0.1883843643444485,"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."}}