{"id":"W3202070111","doi":"10.18280/ts.380402","title":"Function to Flatten Gesture Data for Specific Feature Selection Methods to Improve Classification","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Feature selection; Gesture; Computer science; Selection (genetic algorithm); Pattern recognition (psychology); Artificial intelligence; Function (biology); Feature (linguistics); Machine learning; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001581438,0.001318615,0.0007089725,0.001635736,0.0003940944,0.0006976733,0.000548242,0.0005172865,0.005777682],"category_scores_gemma":[0.004892427,0.0002435106,0.001015423,0.001196144,0.0003555135,0.0006932714,0.0006387046,0.0007630719,0.002074094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004373761,"about_ca_system_score_gemma":0.0007605437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002402778,"about_ca_topic_score_gemma":0.002375016,"domain_scores_codex":[0.9993211,0.0001492518,0.00008299955,0.0001736264,0.0001924424,0.00008058453],"domain_scores_gemma":[0.9982905,0.0007424364,0.00008800291,0.000242537,0.0005806935,0.00005580325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004868275,0.0003319289,0.006360654,0.0001791738,0.0001293221,0.0002005163,0.0002462261,0.04240037,0.08887995,0.002603789,0.003958353,0.8542228],"study_design_scores_gemma":[0.00005176947,0.0005362782,0.01449734,0.00004339189,0.00009561747,0.0002499709,0.0001811268,0.8824419,0.09252682,0.002763594,0.006560721,0.00005146687],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07720673,0.0001289682,0.9169032,0.0001179944,0.00005638435,0.0002139483,0.0004383138,0.004109607,0.0008248484],"genre_scores_gemma":[0.3996041,0.0001331079,0.5935937,0.0001051018,0.0000477779,0.0006810846,0.002068232,0.00040899,0.003357828],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005777682,"threshold_uncertainty_score":0.0193283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07884785000310972,"score_gpt":0.3383465185940114,"score_spread":0.2594986685909016,"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."}}