{"id":"W2403953427","doi":"","title":"Sit to Stand Detection and Analysis.","year":2008,"lang":"en","type":"article","venue":"","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Balance (ability); Physical medicine and rehabilitation; Work (physics); Computer science; Stability (learning theory); Term (time); Functional impairment; Psychology; Engineering; Machine learning; Medicine","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":[0.0002673439,0.0007751487,0.0005222109,0.001499613,0.0003128117,0.0006167232,0.0005791597,0.0008224789,0.02078947],"category_scores_gemma":[0.0009186408,0.0002899778,0.0004237403,0.0006495079,0.000146431,0.0004851449,0.000455381,0.000375405,0.01217783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001733188,"about_ca_system_score_gemma":0.0003232478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002866262,"about_ca_topic_score_gemma":0.008065908,"domain_scores_codex":[0.9997064,0.00002864193,0.00001811938,0.00007354442,0.0001219922,0.00005116392],"domain_scores_gemma":[0.9996502,0.00004944112,0.00004182482,0.00004039984,0.0001674032,0.00005061412],"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":[0.001423315,0.0004733722,0.04059185,0.0005831775,0.0002100506,0.0008204028,0.0001473202,0.004443549,0.1607634,0.00168364,0.05731843,0.7315415],"study_design_scores_gemma":[0.0001982883,0.001137118,0.3345547,0.0001864484,0.0003032235,0.005888255,0.0008646177,0.3701096,0.2090295,0.005379145,0.07214153,0.0002074691],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2604232,0.00287114,0.6331588,0.0006476039,0.0011356,0.001385099,0.02285451,0.02489124,0.05263275],"genre_scores_gemma":[0.6966486,0.001100505,0.2375132,0.0005228492,0.0002311871,0.00103972,0.02007927,0.0009227531,0.04194192],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02078947,"threshold_uncertainty_score":0.06954771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01938887676179432,"score_gpt":0.2291428326668687,"score_spread":0.2097539559050744,"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."}}