{"id":"W6969222585","doi":"10.5683/sp3/js7703","title":"Autoscoper Tutorial for Foot, Knee, and Shoulder Tracking","year":2025,"lang":"en","type":"dataset","venue":"Borealis","topic":"Knee injuries and reconstruction techniques","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Troubleshooting; Tracking (education); Software; Process (computing); MATLAB; Filter (signal processing); Set (abstract data type); Tracking system","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":[0.001953398,0.002481997,0.00125666,0.002293027,0.0005525011,0.002008607,0.00268665,0.0009873455,0.2311703],"category_scores_gemma":[0.006353351,0.001053503,0.001432545,0.002270826,0.0003368113,0.001879212,0.002630116,0.001746465,0.2957648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007102401,"about_ca_system_score_gemma":0.001458168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005361411,"about_ca_topic_score_gemma":0.01876506,"domain_scores_codex":[0.9992214,0.000135407,0.00009183301,0.0002403279,0.0002306208,0.00008040921],"domain_scores_gemma":[0.997698,0.0007747426,0.0001314245,0.0006708496,0.0005344055,0.000190546],"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":[0.00003041654,0.00001332877,0.0002121202,0.0002386585,0.00001192161,0.00001266473,0.00001326953,0.000209361,0.0003047969,0.0002255941,0.9835246,0.01520327],"study_design_scores_gemma":[0.0001332869,0.00003425833,0.002134443,0.0003222386,0.00002309678,0.0001774013,0.00003842035,0.002698718,0.002468895,0.003269408,0.9886629,0.00003700286],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008043763,0.0006502159,0.02391884,0.0003539875,0.0004626692,0.0002914812,0.8700076,0.08720154,0.01630931],"genre_scores_gemma":[0.001459102,0.0003452023,0.02489178,0.0004036358,0.00006975002,0.000938178,0.9473881,0.01208849,0.01241571],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2311703,"threshold_uncertainty_score":0.7733418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0166720647699552,"score_gpt":0.3236956856379573,"score_spread":0.3070236208680021,"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."}}