{"id":"W4385507060","doi":"10.1016/j.calphad.2023.102593","title":"The power of computational thermochemistry in high-temperature process design and optimization: Part 1 — Unit operations","year":2023,"lang":"en","type":"article","venue":"Calphad","topic":"Iron and Steelmaking Processes","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Thermochemistry; Pyrometallurgy; Process engineering; Context (archaeology); Work (physics); Unit operation; Process (computing); Mechanical engineering; Smelting; Nuclear engineering; Computer science; Materials science; Thermodynamics; Metallurgy; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009789864,0.0006787466,0.001036416,0.0003522675,0.0008821229,0.001502643,0.001367119,0.0008213041,0.003784454],"category_scores_gemma":[0.005116243,0.0006397725,0.000665834,0.0008674596,0.0008502476,0.001732748,0.0006438945,0.002079028,0.0005659876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007295173,"about_ca_system_score_gemma":0.002034146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006134515,"about_ca_topic_score_gemma":0.005643297,"domain_scores_codex":[0.999668,0.0001642163,0.00001311498,0.00003136081,0.0001010567,0.00002223403],"domain_scores_gemma":[0.9983463,0.00114707,0.0000695811,0.0002087912,0.000191254,0.00003690462],"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":[0.00004917244,0.00004636642,0.000487549,0.000100588,0.00002611967,0.00001597609,0.00002051983,0.9568405,0.0008772805,0.0152085,0.0006885057,0.02563892],"study_design_scores_gemma":[0.00001146063,0.0000114895,0.00006421899,0.000006419772,0.000003457837,0.000002913155,0.000004769955,0.9938508,0.0005780305,0.004796849,0.0006663034,0.00000331723],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07809857,0.00199627,0.8736347,0.001781036,0.0003205903,0.0001394365,0.0004059921,0.0008852351,0.04273823],"genre_scores_gemma":[0.7156981,0.001304047,0.278193,0.0003260055,0.0001318151,0.0003318168,0.000309691,0.0004644619,0.003241051],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006134515,"threshold_uncertainty_score":0.01266026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0135899375081666,"score_gpt":0.2398759325575386,"score_spread":0.2262859950493721,"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."}}