{"id":"W2586734568","doi":"10.1007/978-3-319-51541-0_114","title":"Critical Role of Thermal Management During Cast Start-Up of the DC Casting Process","year":2017,"lang":"en","type":"book-chapter","venue":"The minerals, metals & materials series","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Rio Tinto (Canada)","funders":"","keywords":"Ingot; Casting; Process (computing); Materials science; Liquid metal; Mechanical engineering; Process engineering; Engineering; Metallurgy; Computer science","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"],"consensus_categories":[],"category_scores_codex":[0.00038403,0.0007096296,0.001125768,0.00009809237,0.0003101199,0.0002103209,0.001096188,0.0002689492,0.0005884742],"category_scores_gemma":[0.00004540972,0.0004474091,0.0002210466,0.00002558584,0.0008461588,0.0003743106,0.0005554979,0.0002736129,0.00001955414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000521584,"about_ca_system_score_gemma":0.00003900268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007697067,"about_ca_topic_score_gemma":0.00009605574,"domain_scores_codex":[0.9975104,0.00007319412,0.001035895,0.0003835057,0.0005026514,0.0004943487],"domain_scores_gemma":[0.997973,0.00004775821,0.0005136008,0.001183228,0.0002273588,0.00005511044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001144895,0.000006908758,0.000005151768,0.003331637,0.0005020422,0.00001620234,0.001310114,0.0005050618,0.9903485,0.003641603,0.00005519075,0.0001631033],"study_design_scores_gemma":[0.0002804724,0.00004174786,0.0002458908,0.0009903162,0.0005672322,0.0001240334,0.0003860733,0.00001639235,0.9880306,0.003218128,0.005489369,0.0006097374],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9416776,0.003595253,0.000005582137,0.00006825609,0.002522226,0.001021732,0.0006536406,0.0001696156,0.05028604],"genre_scores_gemma":[0.9224564,0.0001292199,0.0001681898,0.00001181246,0.0003916767,0.00006043087,0.00001812497,0.0002134371,0.07655068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02626465,"threshold_uncertainty_score":0.9997978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01337619947371808,"score_gpt":0.2147196206663019,"score_spread":0.2013434211925839,"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."}}