{"id":"W2265696903","doi":"10.1145/2799648","title":"Gestures à Go Go","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Intelligent Systems and Technology","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Gesture; Computer science; Bootstrapping (finance); Human–computer interaction; Gesture recognition; Quality (philosophy); 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":[0.0004530615,0.001310029,0.0005902264,0.0006199438,0.0004869363,0.0009619436,0.0009276263,0.001279601,0.02926515],"category_scores_gemma":[0.002811519,0.0004395971,0.0008708477,0.0003956148,0.0006666384,0.001188679,0.00185684,0.0008710274,0.01350349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002807752,"about_ca_system_score_gemma":0.0005652614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002019043,"about_ca_topic_score_gemma":0.004075712,"domain_scores_codex":[0.9995646,0.0000714858,0.00002551021,0.00010838,0.000180191,0.00004988005],"domain_scores_gemma":[0.9992203,0.0002191463,0.00003216232,0.000290665,0.000127818,0.0001099851],"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":[0.002505293,0.000418348,0.008415665,0.001071233,0.0001663836,0.00256606,0.001705291,0.0188077,0.2553137,0.0150434,0.08726716,0.6067199],"study_design_scores_gemma":[0.0003522456,0.002158852,0.02844608,0.0003547924,0.0001936282,0.006584088,0.001565329,0.3193706,0.161912,0.02360934,0.4551016,0.0003514467],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1756312,0.0007508908,0.613137,0.001282353,0.0008723991,0.001497286,0.007319026,0.1402951,0.05921464],"genre_scores_gemma":[0.5351655,0.0006132449,0.3801419,0.001562536,0.000104051,0.001462547,0.01195294,0.008319393,0.06067795],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02926515,"threshold_uncertainty_score":0.09790164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04107652253546483,"score_gpt":0.2715265347485359,"score_spread":0.230450012213071,"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."}}