{"id":"W4412799337","doi":"10.26603/001c.141870","title":"Between-Day Reliability of Kinematic Variables Using Markerless Motion Capture for Single-Leg Squat and Single-Leg Landing Tasks","year":2025,"lang":"en","type":"article","venue":"International Journal of Sports Physical Therapy","topic":"Knee injuries and reconstruction techniques","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Physiotherapy Association","funders":"University of Salford Manchester","keywords":"Squat; Kinematics; Reliability (semiconductor); Motion (physics); Motion capture; Computer science; Physical medicine and rehabilitation; Artificial intelligence; Physics; 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":[0.004170779,0.0004519194,0.0004896118,0.0007413607,0.0003461104,0.0006832819,0.0004971261,0.0005240206,0.0008676072],"category_scores_gemma":[0.01402498,0.0003040805,0.0004356567,0.0005907836,0.0005564211,0.0004447505,0.000712537,0.0003614656,0.00048175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001874348,"about_ca_system_score_gemma":0.0002611572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001216808,"about_ca_topic_score_gemma":0.002867707,"domain_scores_codex":[0.9956945,0.001303674,0.0005354115,0.001037417,0.001252625,0.0001763713],"domain_scores_gemma":[0.9860196,0.004892218,0.002374229,0.002018812,0.004342992,0.0003521155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003663143,0.0003859563,0.8835737,0.0004392946,0.000851481,0.0001108543,0.002902789,0.00128524,0.04452159,0.0001153211,0.0006974434,0.06145321],"study_design_scores_gemma":[0.00002795346,0.0008969572,0.9933993,0.00002115034,0.0000969781,0.0001434592,0.0002517604,0.001408249,0.003234047,0.00005325071,0.0004489348,0.00001807883],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891058,0.0002672343,0.009046491,0.00001985571,0.00004359182,0.000123358,0.0004053758,0.00007211429,0.0009161233],"genre_scores_gemma":[0.9955899,0.00005788131,0.003294371,0.00001730755,0.00001938829,0.0001165048,0.0005564924,0.00002761654,0.0003207207],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004170779,"threshold_uncertainty_score":0.02205741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02276766051173747,"score_gpt":0.3201536875716068,"score_spread":0.2973860270598694,"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."}}