{"id":"W4294891768","doi":"10.1145/3552312","title":"BodyTrak","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Torso; Computer vision; Artificial intelligence; Computer science; RGB color model; Sitting; Pose; Computer graphics (images); Medicine; Anatomy","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":[0.000586878,0.001341068,0.0008235431,0.001031801,0.0006001439,0.001790116,0.002110642,0.001224847,0.05749986],"category_scores_gemma":[0.002741386,0.0006906373,0.0009390107,0.0006984976,0.0004517238,0.003270617,0.004243928,0.001100276,0.04027796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003624323,"about_ca_system_score_gemma":0.0007363426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002239098,"about_ca_topic_score_gemma":0.002886561,"domain_scores_codex":[0.9991673,0.0000611158,0.00005053927,0.0002547704,0.0003723743,0.00009398919],"domain_scores_gemma":[0.999189,0.0001247245,0.00006115635,0.0003402674,0.0002219501,0.00006304611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001164249,0.0001579471,0.003875125,0.00107383,0.0002297436,0.0005603707,0.0003454548,0.004277956,0.03427445,0.01048435,0.2136025,0.7299541],"study_design_scores_gemma":[0.0001789612,0.0004514599,0.009688006,0.0004064823,0.0002245721,0.003329128,0.0002286422,0.07342374,0.05575967,0.01354541,0.8424298,0.0003339897],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0187687,0.003807014,0.6927877,0.0009403692,0.00255537,0.0007404128,0.01419717,0.1666685,0.09953478],"genre_scores_gemma":[0.2967718,0.004568272,0.4279304,0.003942482,0.0005723135,0.001410989,0.04717056,0.01987455,0.1977587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05749986,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01053466421300405,"score_gpt":0.2365708682135916,"score_spread":0.2260362040005876,"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."}}