{"id":"W4399129458","doi":"10.1080/0305215x.2024.2354313","title":"An artificial intelligence-based optimization framework for the optimal composition and thermomechanical processing schedule for specialized micro-alloyed multiphase steels","year":2024,"lang":"en","type":"article","venue":"Engineering Optimization","topic":"Metallurgical Processes and Thermodynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Booth University College; McMaster University","funders":"","keywords":"Thermomechanical processing; Schedule; Composition (language); Materials science; Materials processing; Computer science; Process engineering; Metallurgy; Engineering; Microstructure","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":[],"consensus_categories":[],"category_scores_codex":[0.0002678259,0.0002406617,0.0001986068,0.0001146891,0.0001633012,0.0004094074,0.0001366517,0.0001813299,0.00003177263],"category_scores_gemma":[0.00007610557,0.0002007815,0.00008252838,0.0002777511,0.00002718397,0.0002880848,0.00001079823,0.0001691073,7.599107e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006433533,"about_ca_system_score_gemma":0.00002660191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.170671e-7,"about_ca_topic_score_gemma":2.967089e-7,"domain_scores_codex":[0.998991,0.00001428617,0.0003334207,0.0002886379,0.0001208469,0.0002517981],"domain_scores_gemma":[0.9992804,0.0003612526,0.00003658212,0.00014824,0.00009428553,0.00007925206],"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":[0.00007899486,0.00003653452,5.158237e-8,0.0003797289,0.00004567828,6.986002e-7,0.0001164214,0.9757721,0.006218216,0.01062601,0.00000166497,0.006723843],"study_design_scores_gemma":[0.0001871656,0.00007657265,4.083951e-7,0.0001588585,0.0001004653,0.000002598517,0.00003474029,0.9946127,0.004067588,0.0004324008,0.00007192213,0.0002545658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00227855,0.001005939,0.9945511,0.0001375183,0.0004761786,0.0009159988,0.00003976487,0.0005903544,0.000004616177],"genre_scores_gemma":[0.4441108,0.00004889155,0.5551522,0.00001738721,0.0002627078,0.0001688796,0.0001597238,0.0000777878,0.000001674551],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4418322,"threshold_uncertainty_score":0.8187634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02048555699628485,"score_gpt":0.2714634042971166,"score_spread":0.2509778473008317,"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."}}