{"id":"W4319302811","doi":"10.1007/978-3-031-22524-6_6","title":"Computational Design of an Ultra-Strong High-Entropy Alloy","year":2023,"lang":"en","type":"book-chapter","venue":"˜The œminerals, metals & materials series","topic":"High Entropy Alloys Studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Alloy; Materials science; Microstructure; Precipitation hardening; High entropy alloys; Ultimate tensile strength; Entropy (arrow of time); Configuration entropy; Strain hardening exponent; Thermodynamics; Composite material; Metallurgy; 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":[0.0002977722,0.0002881786,0.0007521234,0.0002945985,0.0006238394,0.001126716,0.001284661,0.001311371,0.006794014],"category_scores_gemma":[0.0009695085,0.0004602535,0.0004842228,0.0002808775,0.001011566,0.0006795397,0.001126286,0.000840903,0.0005844137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005672262,"about_ca_system_score_gemma":0.0008460032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001620037,"about_ca_topic_score_gemma":0.002216656,"domain_scores_codex":[0.9999171,0.00002634645,0.000002640454,0.000009870727,0.0000278309,0.00001622543],"domain_scores_gemma":[0.9997824,0.0001217196,0.00001321155,0.00002398265,0.00003036358,0.00002831155],"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":[0.00006011355,0.0000265887,0.0002660243,0.00006511843,0.00002216739,0.00007437219,0.00002454383,0.8987854,0.001383283,0.09349871,0.001261159,0.004532588],"study_design_scores_gemma":[0.00001151339,0.000009964062,0.00005174962,0.00000502809,0.000003938223,0.000009348264,0.000008352268,0.9834169,0.0002056006,0.01534005,0.0009344151,0.000003208625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.260161,0.002330505,0.5296991,0.00333087,0.0007626019,0.0001427103,0.0007536932,0.0006401234,0.2021793],"genre_scores_gemma":[0.8954356,0.000567914,0.08565058,0.0003643792,0.000140018,0.0002394952,0.0002695374,0.0001584415,0.01717401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006794014,"threshold_uncertainty_score":0.0227282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02490702795922437,"score_gpt":0.223462870635878,"score_spread":0.1985558426766537,"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."}}