{"id":"W3089222493","doi":"10.1049/iet-smt.2019.0488","title":"Improved solutions to a TEAM problem for multi‐objective optimisation in magnetics","year":2020,"lang":"en","type":"article","venue":"IET Science Measurement & Technology","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science","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":[0.0005572367,0.0001120872,0.000148187,0.0003977079,0.0001036057,0.00002660363,0.0003276444,0.00007886119,0.00000381312],"category_scores_gemma":[0.0003104179,0.0001051474,0.00003360508,0.002636446,0.00007603734,0.00008762052,0.00003875547,0.0001317179,0.000006082619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003971779,"about_ca_system_score_gemma":0.00008804988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001456709,"about_ca_topic_score_gemma":0.000156088,"domain_scores_codex":[0.9987906,0.000008017588,0.0002037934,0.0003092235,0.0002564517,0.0004318983],"domain_scores_gemma":[0.9995413,0.000008421194,0.00002665731,0.0001302546,0.0002073195,0.00008603012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004986533,0.00003367155,0.0002098278,0.0000142761,0.000008812751,2.965062e-7,0.0003341287,0.006955373,0.9550701,0.0001822903,0.0001783609,0.03700785],"study_design_scores_gemma":[0.0004126384,0.0003568526,0.0003450414,0.00001595406,0.00001851201,8.585179e-7,0.0001543777,0.9131507,0.08442938,0.0003092907,0.0006196081,0.0001867747],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04025837,0.0002297103,0.9524726,0.004010243,0.00009219754,0.001809949,0.000007122464,0.000742619,0.0003771927],"genre_scores_gemma":[0.9092189,0.000009319368,0.09030166,0.00009799141,0.00001792102,0.0003371738,7.652377e-7,0.00000764648,0.000008612343],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9061953,"threshold_uncertainty_score":0.4287785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04760980542691118,"score_gpt":0.2473354394121009,"score_spread":0.1997256339851897,"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."}}