{"id":"W3171269018","doi":"10.1016/j.jbiomech.2021.110549","title":"IMU-based knee flexion, abduction and internal rotation estimation during drop landing and cutting tasks","year":2021,"lang":"en","type":"article","venue":"Journal of Biomechanics","topic":"Knee injuries and reconstruction techniques","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Inertial measurement unit; ACL injury; Anterior cruciate ligament; Orientation (vector space); Rotation (mathematics); Computer science; Internal rotation; Orthodontics; Mathematics; Computer vision; Medicine; Engineering; Surgery; Geometry","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":[0.0002660052,0.0005832693,0.0004705144,0.0009548081,0.0001553647,0.0004724231,0.0001950573,0.0005247321,0.001553232],"category_scores_gemma":[0.001337167,0.0001612037,0.0002177798,0.0006383053,0.0001023094,0.0002914062,0.0003261443,0.0001951922,0.0009172243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007333683,"about_ca_system_score_gemma":0.0001396755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002049566,"about_ca_topic_score_gemma":0.003716765,"domain_scores_codex":[0.9997957,0.00004600259,0.00001779538,0.00003706907,0.00004874766,0.00005471546],"domain_scores_gemma":[0.9996037,0.000120819,0.00006012347,0.00001996711,0.0001460348,0.0000493011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.008368471,0.0005691404,0.2448721,0.0008792698,0.0004845177,0.001053842,0.0009500557,0.009550319,0.275571,0.0001395192,0.003647638,0.4539142],"study_design_scores_gemma":[0.00006180221,0.0009909003,0.9178256,0.00009034442,0.0002206646,0.001438524,0.0006772837,0.05516452,0.02217147,0.0001024305,0.001196136,0.0000604413],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817228,0.0008381537,0.01390589,0.00006809324,0.0001315262,0.00005720333,0.00152329,0.0001979667,0.001555125],"genre_scores_gemma":[0.9958771,0.0002005327,0.002645398,0.00003430174,0.00004426664,0.00003414143,0.0004678357,0.00001873283,0.0006776036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002049566,"threshold_uncertainty_score":0.005196095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007163265759044924,"score_gpt":0.2679684383544009,"score_spread":0.260805172595356,"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."}}