{"id":"W4388477842","doi":"10.18280/ria.370511","title":"Improved Yoga Pose Detection Using MediaPipe and MoveNet in a Deep Learning Model","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Deep learning; Computer science; Psychology","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":[0.0002655557,0.001327479,0.0008428539,0.0007641973,0.0003069446,0.0006518491,0.00116507,0.0008490105,0.003841464],"category_scores_gemma":[0.0008647919,0.0004115979,0.0007548677,0.0005198301,0.0002722582,0.0007092229,0.0009121426,0.001066109,0.001634844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004971836,"about_ca_system_score_gemma":0.0007545663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01338567,"about_ca_topic_score_gemma":0.02811935,"domain_scores_codex":[0.9998409,0.00001781888,0.000006306983,0.00006530642,0.00003331672,0.00003631689],"domain_scores_gemma":[0.9998853,0.00003546271,0.00001173605,0.00001588506,0.00003623503,0.00001539671],"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":[0.0006996818,0.0004425563,0.004943291,0.0002869928,0.0002079496,0.0003161523,0.0001262655,0.1142398,0.02750829,0.002300095,0.02551179,0.823417],"study_design_scores_gemma":[0.00003171092,0.0001394101,0.001921146,0.00003964836,0.00004008,0.00006032867,0.00004048792,0.989403,0.003807363,0.001348192,0.003149751,0.00001880589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1745226,0.004827944,0.7857769,0.001016254,0.0008254176,0.0002473425,0.003121484,0.01907992,0.01058205],"genre_scores_gemma":[0.7051374,0.001732155,0.2584563,0.001048863,0.0002532798,0.000373734,0.009675935,0.0005133372,0.02280905],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01338567,"threshold_uncertainty_score":0.0266155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04943360256368481,"score_gpt":0.2776899713131007,"score_spread":0.2282563687494159,"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."}}