{"id":"W1550901011","doi":"10.1002/9780470176535.ch3","title":"Feature Extraction, Selection, and Creation","year":2007,"lang":"en","type":"other","venue":"","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Selection (genetic algorithm); Computer science; Feature selection; Feature (linguistics); Artificial intelligence","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":[0.0008459573,0.001252245,0.001123112,0.002871071,0.0007176956,0.001899309,0.001219273,0.0005280516,0.03578128],"category_scores_gemma":[0.003160632,0.0005209007,0.001100299,0.002954003,0.0002864398,0.001895271,0.0008471225,0.0008202752,0.02064291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005126921,"about_ca_system_score_gemma":0.001119957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002387836,"about_ca_topic_score_gemma":0.002545065,"domain_scores_codex":[0.9992257,0.0000668484,0.00006666111,0.0001944686,0.0003751868,0.00007104936],"domain_scores_gemma":[0.9988428,0.0003918796,0.00005636227,0.0002125086,0.000465757,0.00003058585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007404179,0.00007818253,0.0006287516,0.0002484795,0.00001586667,0.00008670341,0.00005847315,0.0008519968,0.01508309,0.002129322,0.0568601,0.9238849],"study_design_scores_gemma":[0.0001029009,0.0004010948,0.01573759,0.0004323368,0.000192031,0.001423419,0.0003095543,0.06768954,0.2143083,0.02253626,0.6766802,0.0001868199],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01320302,0.003338487,0.902788,0.0007906968,0.0008615279,0.001595952,0.01121817,0.03146689,0.03473724],"genre_scores_gemma":[0.04911388,0.004896154,0.8231074,0.0004692306,0.0005539475,0.002067674,0.03099493,0.003584453,0.08521246],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03578128,"threshold_uncertainty_score":0.1197004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01026283655632646,"score_gpt":0.2800368526749832,"score_spread":0.2697740161186568,"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."}}