{"id":"W2166470369","doi":"10.1109/iembs.1994.415467","title":"Information based feature selection for supervised motor unit action potential classification","year":2002,"lang":"en","type":"article","venue":"","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pattern recognition (psychology); Artificial intelligence; Linear discriminant analysis; Discriminative model; Computer science; Principal component analysis; Cluster analysis; Classifier (UML); Discriminant; Linear classifier; Feature selection; Statistical classification; Motor unit; Dimensionality reduction; Feature extraction; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001255977,0.00008667936,0.00008053328,0.0001553389,0.0002476347,0.0002781902,0.0001815487,0.0000793517,0.000161539],"category_scores_gemma":[0.00002776509,0.00007733153,0.00008901986,0.0004484868,0.000008279852,0.001839938,0.00001669109,0.00006813185,0.0000468072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004053503,"about_ca_system_score_gemma":0.00001357338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002087492,"about_ca_topic_score_gemma":0.00001238528,"domain_scores_codex":[0.9993653,0.00002231705,0.000168531,0.0001265834,0.0001642096,0.0001530122],"domain_scores_gemma":[0.9994412,0.00002155189,0.0001050947,0.0001686469,0.0002190305,0.00004446587],"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":[0.00008041017,0.0001608184,0.001161899,0.00009592508,0.00006936872,2.142844e-7,0.0006069096,0.007120998,0.03881697,0.02689283,0.02029247,0.9047012],"study_design_scores_gemma":[0.0002991427,0.00008465242,0.00297173,0.000003017696,0.00001221027,0.000002409665,0.00006869464,0.9813675,0.001529378,0.00005933772,0.01350585,0.00009604526],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008958149,0.000005633798,0.9875125,0.001858892,0.0001531443,0.0002015497,0.000002939033,0.0001885378,0.001118699],"genre_scores_gemma":[0.925963,0.000003535614,0.07197633,0.0002768849,0.0001047679,0.00003415055,0.00005711243,0.00000493561,0.001579237],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9742466,"threshold_uncertainty_score":0.3153488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04196474014968908,"score_gpt":0.2353010102375752,"score_spread":0.1933362700878862,"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."}}