{"id":"W4414378015","doi":"10.1002/mgea.70030","title":"Machine learning‐based research of new refractory high‐entropy alloys using guided multiobjectives search strategy","year":2025,"lang":"en","type":"article","venue":"Materials Genome Engineering Advances","topic":"High Entropy Alloys Studies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Refractory (planetary science); Particle swarm optimization; Refractory metals; Alloy; Space (punctuation); Titanium alloy; Variety (cybernetics)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006517306,0.0003731803,0.0006358856,0.0006840759,0.0001595429,0.00008369274,0.0003735072,0.0001272789,0.0001854613],"category_scores_gemma":[0.0002096034,0.0003855103,0.00007286516,0.0006729017,0.0001013907,0.0002435071,0.0001349102,0.0003952761,0.00001575789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003463648,"about_ca_system_score_gemma":0.0001111176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003384577,"about_ca_topic_score_gemma":0.00001049735,"domain_scores_codex":[0.9976433,0.0001445415,0.0006217787,0.0003965392,0.0004384845,0.0007553518],"domain_scores_gemma":[0.9990103,0.0002513147,0.00006176358,0.0003670453,0.0001972896,0.0001122662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002677445,0.00001760474,0.00005962751,0.0003792457,0.00008590129,0.000005040788,0.0001189762,0.5195016,0.4793467,0.0002193628,0.00001754088,0.0002216252],"study_design_scores_gemma":[0.001594312,0.0002032298,0.003715174,0.000400442,0.00005856809,0.000003399595,0.0002621712,0.1001321,0.8715394,0.0001630177,0.02122893,0.0006992519],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9548088,0.01334668,0.02909688,0.00003409309,0.001122064,0.0005256316,0.00008174334,0.0006808082,0.0003033049],"genre_scores_gemma":[0.9876415,0.001175704,0.01039005,0.000003774629,0.0002286187,0.00003302764,0.00003738776,0.00009224462,0.0003977078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4193695,"threshold_uncertainty_score":0.9998597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05654353701885354,"score_gpt":0.3297832604771596,"score_spread":0.273239723458306,"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."}}