{"id":"W4395463679","doi":"10.18280/isi.290226","title":"Unifying Variable Importance Scores from Different Machine Learning Models Using Simulated Annealing","year":2024,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Variable (mathematics); Machine learning; Computer science; Psychology; Cognitive psychology; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005020957,0.001105668,0.001389972,0.001418162,0.0005762733,0.001181224,0.0009795472,0.0009083712,0.001326947],"category_scores_gemma":[0.01197963,0.0008574471,0.001482716,0.001020282,0.0006050896,0.001531581,0.0009305692,0.001706541,0.0003183663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009972194,"about_ca_system_score_gemma":0.001342164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003580471,"about_ca_topic_score_gemma":0.003750044,"domain_scores_codex":[0.9977729,0.001157225,0.0001355875,0.0002587332,0.0005181666,0.0001574313],"domain_scores_gemma":[0.99583,0.002657062,0.000304412,0.0004304053,0.000695192,0.0000830322],"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":[0.0001200695,0.0001284248,0.002968257,0.0001159603,0.0001484403,0.00005003665,0.0001569398,0.8624823,0.00438048,0.007708707,0.0004895522,0.1212508],"study_design_scores_gemma":[0.00001027992,0.00004915925,0.0003431516,0.00000754316,0.00001523416,0.000009249267,0.00001291458,0.9954244,0.00167517,0.002124212,0.0003201541,0.000008463954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02927257,0.000104701,0.9692076,0.00007292096,0.00003573105,0.0001056876,0.00001268335,0.0002814038,0.0009066027],"genre_scores_gemma":[0.3995744,0.0001312599,0.5983989,0.00006659851,0.00003081163,0.00032793,0.0001085882,0.0001631356,0.001198343],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005020957,"threshold_uncertainty_score":0.02655369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03358331488182129,"score_gpt":0.2471989636941943,"score_spread":0.213615648812373,"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."}}