{"id":"W2920973327","doi":"","title":"A Novel Cluster of Quarter Feature Selection Based on Symmetrical Uncertainty","year":2018,"lang":"en","type":"article","venue":"DergiPark (Istanbul University)","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Feature selection; Data mining; Feature (linguistics); Computer science; Dimensionality reduction; Filter (signal processing); Curse of dimensionality; Pattern recognition (psychology); Artificial intelligence; Selection (genetic algorithm); Feature vector; Naive Bayes classifier; Machine learning; Support vector machine; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001078401,0.0001226045,0.0001393636,0.0005427084,0.0001538448,0.00003909377,0.0003915765,0.0001243366,0.00005183049],"category_scores_gemma":[0.00003770026,0.0001177222,0.00008629997,0.001505528,0.00007305062,0.0002784693,0.00006963296,0.0001464966,0.00005039453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001100739,"about_ca_system_score_gemma":0.00007956466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003948669,"about_ca_topic_score_gemma":0.00003395357,"domain_scores_codex":[0.9990127,0.00007613015,0.0001000646,0.0003386848,0.0002664741,0.0002059306],"domain_scores_gemma":[0.9991655,0.0001235185,0.00009427855,0.0002821632,0.0002449601,0.00008958219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00702444,0.005611103,0.0046859,0.0003985914,0.0004425131,0.0002532723,0.007545442,0.02628019,0.07198939,0.1413523,0.6853371,0.04907975],"study_design_scores_gemma":[0.004161864,0.001601264,0.003383846,0.0001972891,0.00004006598,0.00001795513,0.0005331734,0.7599625,0.01519623,0.000407523,0.2138802,0.00061809],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04590843,0.000003592893,0.9205301,0.00188228,0.0003134088,0.0001773956,0.00001381323,0.0001460847,0.03102487],"genre_scores_gemma":[0.9821343,0.000001711553,0.01567067,0.0006005028,0.00006007433,5.792343e-7,0.0000081931,0.000006123911,0.001517789],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.936226,"threshold_uncertainty_score":0.4800572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009705218735710692,"score_gpt":0.2040180812145723,"score_spread":0.1943128624788616,"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."}}