{"id":"W4390906038","doi":"10.1109/transai60598.2023.00048","title":"Feature Selection via Independent Domination","year":2023,"lang":"en","type":"article","venue":"","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Feature selection; Selection (genetic algorithm); Computer science; Feature (linguistics); Artificial intelligence; Pattern recognition (psychology)","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":[0.004842603,0.00158594,0.002469787,0.00232318,0.001205516,0.001635911,0.001946885,0.001277202,0.004241859],"category_scores_gemma":[0.01199102,0.0005209941,0.001453189,0.002862746,0.001569335,0.001391296,0.001968215,0.001244773,0.001081136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008802694,"about_ca_system_score_gemma":0.001345788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001134328,"about_ca_topic_score_gemma":0.001390059,"domain_scores_codex":[0.9954038,0.00267637,0.0001704214,0.0005496598,0.0009508199,0.0002489861],"domain_scores_gemma":[0.9946325,0.003709322,0.000242309,0.0005436454,0.0007522252,0.0001200076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002293053,0.0002039289,0.001308863,0.0004485468,0.0002858311,0.0003448296,0.0002550823,0.4103382,0.006082992,0.1122656,0.01390131,0.4543355],"study_design_scores_gemma":[0.0000633724,0.0001249256,0.0003250751,0.00003107664,0.00003885991,0.000123427,0.0000327829,0.90789,0.001795027,0.08525346,0.004297477,0.00002449273],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006935018,0.0002820416,0.9898733,0.0002481289,0.00004863503,0.0001535976,0.00008384951,0.0002106194,0.002164812],"genre_scores_gemma":[0.2805872,0.0005419584,0.7081423,0.0006896174,0.0002790664,0.00117103,0.0007342354,0.0002242431,0.007630476],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004842603,"threshold_uncertainty_score":0.02561045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01107445145980477,"score_gpt":0.2612648775403473,"score_spread":0.2501904260805425,"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."}}