{"id":"W3047104380","doi":"10.1007/s11663-020-01908-7","title":"Computational Thermodynamic Calculations: FactSage from CALPHAD Thermodynamic Database to Virtual Process Simulation","year":2020,"lang":"en","type":"article","venue":"Metallurgical and Materials Transactions B","topic":"Metallurgical Processes and Thermodynamics","field":"Engineering","cited_by":203,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Ministry of Science and ICT, South Korea; National Research Foundation of Korea; Rio Tinto; Doosan Heavy Industries and Construction; National Research Foundation; JFE Steel Corporation; Tata Steel","keywords":"CALPHAD; Process (computing); Software; Steelmaking; Process engineering; Materials science; Computer science; Database; Metallurgy; Phase diagram; Engineering; Phase (matter); Chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009633501,0.0003014548,0.0004176696,0.0000607396,0.0001646846,0.0001687775,0.0001626169,0.0001293169,0.002419677],"category_scores_gemma":[0.00001853642,0.0002734544,0.00008405346,0.0002712891,0.00005906353,0.000343166,0.00001673958,0.0001644542,0.000115583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002951172,"about_ca_system_score_gemma":0.00001860691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007565173,"about_ca_topic_score_gemma":0.00002855082,"domain_scores_codex":[0.9985021,0.00006109084,0.0004687135,0.0004230249,0.0002770275,0.0002680081],"domain_scores_gemma":[0.9992852,0.0001331361,0.00004511524,0.0001441176,0.00005878253,0.0003337095],"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":[0.0000742885,0.00005024523,1.677044e-7,0.00007441829,0.00010975,0.00001058396,0.0002665132,0.9842552,0.01344063,0.0005635311,9.823924e-7,0.001153693],"study_design_scores_gemma":[0.0005140685,0.0000541253,0.0004156707,0.00002644951,0.0001020651,0.000005362177,0.00005997196,0.9969274,0.0001902555,0.0009738137,0.0003858753,0.0003449229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4408744,0.00005708987,0.5578053,0.0001213871,0.0001061421,0.0002397702,0.0004675205,0.0002225797,0.0001057785],"genre_scores_gemma":[0.9975285,0.00004990671,0.001494632,0.0002338452,0.00008991547,0.00006253718,0.0004513821,0.00005906426,0.0000302381],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.556654,"threshold_uncertainty_score":0.9999717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01709155635760733,"score_gpt":0.2433745617224164,"score_spread":0.2262830053648091,"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."}}