{"id":"W4200224248","doi":"10.1109/embc46164.2021.9629726","title":"Improving Accuracy and Runtime of Skeletal Tracking of Lower Limbs for Athletic Jump Mechanics Assessment","year":2021,"lang":"en","type":"article","venue":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","topic":"Knee injuries and reconstruction techniques","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Jump; Inference; Pose; Key (lock); Tracking (education); Estimation; Function (biology); Biomechanics","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":[0.0009327515,0.0009561231,0.000681448,0.0007537244,0.0002794573,0.0007682358,0.001082058,0.0009375557,0.003586016],"category_scores_gemma":[0.005376935,0.0004181845,0.0005116499,0.000415232,0.0002310387,0.0006876867,0.001073058,0.00084437,0.002193086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004391921,"about_ca_system_score_gemma":0.0008791437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008485797,"about_ca_topic_score_gemma":0.01779754,"domain_scores_codex":[0.9990658,0.0001022135,0.00004764337,0.0003766853,0.0003074763,0.0001001687],"domain_scores_gemma":[0.9990178,0.0003464553,0.00008490528,0.0001984523,0.0002749719,0.00007732373],"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":[0.0006436366,0.0001801942,0.01820372,0.0002942759,0.0001737523,0.0002043372,0.0001818241,0.09727242,0.05698808,0.001221643,0.008302654,0.8163335],"study_design_scores_gemma":[0.00003291354,0.0001662012,0.01224011,0.00004884117,0.00004897825,0.0002388243,0.0000504958,0.9629352,0.01948678,0.001353441,0.003371002,0.00002715684],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1410204,0.001422993,0.8331689,0.000367435,0.0003971923,0.0001240538,0.001014659,0.01722578,0.005258532],"genre_scores_gemma":[0.7277439,0.0004081321,0.2644703,0.0002010093,0.00007582196,0.00008908716,0.001702748,0.0007588313,0.004550208],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008485797,"threshold_uncertainty_score":0.01687282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02852995410621542,"score_gpt":0.3317008725997819,"score_spread":0.3031709184935665,"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."}}