{"id":"W2004513049","doi":"10.1145/1639601.1639619","title":"Device agnostic 3D gesture recognition using hidden Markov models","year":2009,"lang":"en","type":"article","venue":"","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Hidden Markov model; Gesture; Gesture recognition; Computer science; Accelerometer; Artificial intelligence; Speech recognition; Pattern recognition (psychology); Motion (physics); Computer vision; Signature recognition; Feature extraction","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":[0.0003057424,0.0001889604,0.0002083271,0.0001530214,0.0001343758,0.0002389383,0.0004407942,0.0001396953,0.00005596601],"category_scores_gemma":[0.00005305099,0.0001642991,0.00007082365,0.0005029755,0.00001299696,0.001068245,0.00006321103,0.0001367763,0.0002894901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005881962,"about_ca_system_score_gemma":0.00006861528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003538737,"about_ca_topic_score_gemma":0.00001846071,"domain_scores_codex":[0.9984506,0.0001279553,0.0003073172,0.0004394643,0.0003489025,0.0003257413],"domain_scores_gemma":[0.998982,0.0001382308,0.0001071969,0.0003973022,0.0002292004,0.0001461366],"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":[0.000007946911,0.00011582,0.0000497737,0.00002683295,0.00002408891,0.00008469253,0.0006090895,0.0003184794,0.001236488,0.001305464,0.002670982,0.9935504],"study_design_scores_gemma":[0.001655331,0.0002858386,0.001934318,0.0006307454,0.00008515684,0.001412645,0.0001421245,0.913372,0.003182072,0.07158912,0.004155821,0.001554868],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02469305,0.0002460271,0.9245106,0.001202793,0.0004619618,0.0003685308,0.000004572503,0.0004689091,0.04804355],"genre_scores_gemma":[0.7370021,0.00002350506,0.2598934,0.002408825,0.0002508993,0.000008838912,0.00001086037,0.00001039566,0.0003911592],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9919955,"threshold_uncertainty_score":0.6699923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05703407982085332,"score_gpt":0.2706525375026988,"score_spread":0.2136184576818455,"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."}}