{"id":"W1976209812","doi":"10.1016/j.ijheatmasstransfer.2005.11.023","title":"Prediction of protective banks in high temperature smelting furnaces by inverse heat transfer","year":2006,"lang":"en","type":"article","venue":"International Journal of Heat and Mass Transfer","topic":"Numerical methods in inverse problems","field":"Mathematics","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Smelting; Brick; Materials science; Mechanics; Temperature gradient; Heat transfer; Inverse; Slag (welding); Conjugate gradient method; Phase (matter); Inverse problem; Environmental science; Composite material; Metallurgy; Computer science; Meteorology; Mathematics; 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":[0.0002825047,0.0006071824,0.0007910297,0.000386036,0.0005789964,0.0008472109,0.0006644067,0.001328578,0.001110308],"category_scores_gemma":[0.001552555,0.0006851024,0.0005198895,0.0002401295,0.0009810737,0.0006732554,0.000394166,0.0008814789,0.0001917068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008607161,"about_ca_system_score_gemma":0.0008497078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01378632,"about_ca_topic_score_gemma":0.007524199,"domain_scores_codex":[0.9999026,0.00002320429,0.000004945467,0.00002554425,0.00002174097,0.00002206382],"domain_scores_gemma":[0.9992273,0.000476471,0.00008830039,0.00004872032,0.00009637244,0.00006283347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001559717,0.00003935377,0.003846776,0.00002191805,0.000009053691,0.00007315325,0.00002695424,0.987919,0.005297334,0.0003705825,0.0001244721,0.002115523],"study_design_scores_gemma":[0.000007687216,0.00001052784,0.0007768883,0.000001324,0.000002139199,0.000004502674,0.000006522936,0.9977058,0.001293818,0.0001721779,0.00001577116,0.000002952886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9235096,0.000149454,0.07384714,0.0001749427,0.00003375427,0.00003554959,0.0001172214,0.0005415417,0.001590676],"genre_scores_gemma":[0.9979171,0.00002414772,0.001709368,0.000003830155,0.000002780893,0.000006620668,0.00002526575,0.00001030098,0.0003005793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01378632,"threshold_uncertainty_score":0.02741212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02467497874050367,"score_gpt":0.2803736947801741,"score_spread":0.2556987160396704,"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."}}