{"id":"W4394327368","doi":"10.6084/m9.figshare.14997816","title":"Pose tracking Data","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Human Motion and Animation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"","keywords":"Computer science; Tracking (education); Artificial intelligence; Computer vision; Psychology","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":[0.0007796948,0.004808386,0.002233595,0.00303391,0.001040992,0.001272962,0.002836902,0.003032949,0.03739664],"category_scores_gemma":[0.003267491,0.000955436,0.002149691,0.004147478,0.0006219083,0.0009028754,0.002074347,0.002051928,0.1065732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007972087,"about_ca_system_score_gemma":0.001799795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02543437,"about_ca_topic_score_gemma":0.05588987,"domain_scores_codex":[0.998715,0.0001078043,0.00009400185,0.0004809148,0.0004207982,0.0001814954],"domain_scores_gemma":[0.9984815,0.000171896,0.0001072799,0.0005622977,0.0005629185,0.0001142938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003418399,0.0002013729,0.001781416,0.001014446,0.00007884672,0.0001140874,0.000054285,0.001789384,0.0028827,0.0003563245,0.9527453,0.03864004],"study_design_scores_gemma":[0.000457851,0.0002445382,0.02240525,0.0004690111,0.0001844333,0.0007082785,0.0001932579,0.008319424,0.01205184,0.001908002,0.9528555,0.0002026937],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001662413,0.0002843252,0.001735493,0.00004160295,0.0001237417,0.0001092267,0.9893059,0.004787804,0.001949451],"genre_scores_gemma":[0.001647765,0.00008841472,0.001726531,0.00003412546,0.00001055004,0.000196088,0.9945999,0.0001538766,0.001542674],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03739664,"threshold_uncertainty_score":0.1251042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1263804192253824,"score_gpt":0.2887147041721153,"score_spread":0.1623342849467329,"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."}}