{"id":"W4394445814","doi":"10.6084/m9.figshare.19929887","title":"Pose Tracking Codes","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"DNA and Biological Computing","field":"Biochemistry, Genetics and Molecular Biology","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":[0.00106304,0.008068393,0.002572794,0.004460771,0.001271557,0.002629434,0.004098993,0.004358631,0.1402951],"category_scores_gemma":[0.006484886,0.001357542,0.003086376,0.005261693,0.0008069844,0.001746385,0.002377037,0.002802568,0.2020271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001394566,"about_ca_system_score_gemma":0.002327073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0217139,"about_ca_topic_score_gemma":0.04766397,"domain_scores_codex":[0.9982632,0.000188478,0.0001432613,0.0007478944,0.0004002717,0.0002569034],"domain_scores_gemma":[0.9980964,0.0005335937,0.0001037066,0.0006652873,0.000436508,0.0001644258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001260111,0.00006443056,0.0006503342,0.0005175367,0.00003315118,0.00002793104,0.00001152334,0.0009057448,0.0003292947,0.0002470498,0.986791,0.01029605],"study_design_scores_gemma":[0.0007976423,0.0001406773,0.004304737,0.0005095299,0.0001125965,0.0003746167,0.0001397598,0.01025614,0.004519384,0.005377681,0.9733296,0.0001376538],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003785348,0.0002049339,0.0008294426,0.00005987292,0.0001053698,0.00006286553,0.9922591,0.004945066,0.00115479],"genre_scores_gemma":[0.0007348629,0.00008330814,0.001630205,0.00006061668,0.00001194921,0.0001429348,0.9961746,0.0002544915,0.0009070034],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1402951,"threshold_uncertainty_score":0.4693337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04210087602819613,"score_gpt":0.2860973532802154,"score_spread":0.2439964772520193,"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."}}