{"id":"W4390584655","doi":"10.2174/0126662558277567231201063458","title":"Supervised Rank Aggregation (SRA): A Novel Rank AggregationApproach for Ensemble-based Feature Selection","year":2024,"lang":"en","type":"article","venue":"Recent Advances in Computer Science and Communications","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto; Princess Margaret Cancer Centre","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Feature selection; Categorical variable; Computer science; Feature (linguistics); Rank (graph theory); Machine learning; Artificial intelligence; Data mining; Ensemble learning; Selection (genetic algorithm); Pattern recognition (psychology); Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003903648,0.001724468,0.002297335,0.002559247,0.0009012046,0.001341368,0.001888722,0.001083578,0.001911764],"category_scores_gemma":[0.006393378,0.0004734139,0.001976738,0.002437929,0.0006257637,0.001359422,0.001519005,0.001713771,0.0009088857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000568087,"about_ca_system_score_gemma":0.001318896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003095027,"about_ca_topic_score_gemma":0.003815527,"domain_scores_codex":[0.9963749,0.001220432,0.0002593639,0.000642031,0.001299785,0.0002034155],"domain_scores_gemma":[0.9957416,0.001669189,0.0005288264,0.0007563842,0.001164858,0.000139197],"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":[0.0002041273,0.0002738964,0.006650364,0.0002302506,0.0005797575,0.0001712943,0.0001504426,0.2281773,0.00772039,0.007898689,0.01065681,0.7372866],"study_design_scores_gemma":[0.00001798884,0.000124233,0.001269993,0.00001740737,0.00006439391,0.000105085,0.00001927423,0.9881493,0.002039045,0.005672093,0.002494189,0.00002704821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008154362,0.0005034769,0.9898443,0.0001239078,0.00006153965,0.00006263312,0.0001239822,0.0005557383,0.0005700616],"genre_scores_gemma":[0.352435,0.0007903726,0.6416485,0.0002658462,0.0004848643,0.0004217451,0.001278926,0.0001952008,0.002479642],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003903648,"threshold_uncertainty_score":0.02064466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03293109741034664,"score_gpt":0.3043938891665709,"score_spread":0.2714627917562242,"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."}}