{"id":"W2155490166","doi":"10.1016/j.knee.2014.11.006","title":"The effect of coordinate system variation on in vivo patellofemoral kinematic measures","year":2014,"lang":"en","type":"article","venue":"The Knee","topic":"Lower Extremity Biomechanics and Pathologies","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"Vancouver Coastal Health; Vancouver Coastal Health Research Institute; University of British Columbia","funders":"Canadian Institutes of Health Research; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Canadian HIV Trials Network, Canadian Institutes of Health Research; Michael Smith Health Research BC","keywords":"Kinematics; Patella; Coordinate system; Orthodontics; Anatomy; Reference frame; Patellofemoral pain syndrome; Computer science; Tilt (camera); Biomechanics; Range of motion; Medicine; Mathematics; Geodesy; Computer vision; Frame (networking); Geology; Geometry; Physics; Physical therapy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001928354,0.0005516123,0.0005112572,0.0007077884,0.0002755945,0.001005414,0.0003041415,0.0005172739,0.001102358],"category_scores_gemma":[0.01956196,0.0003613592,0.0004381715,0.001057689,0.0006073079,0.0004483058,0.000480797,0.0004724672,0.0002672486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002762906,"about_ca_system_score_gemma":0.0003134855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002037664,"about_ca_topic_score_gemma":0.00200986,"domain_scores_codex":[0.9973061,0.001271365,0.0002461633,0.0005228047,0.0004875078,0.0001659415],"domain_scores_gemma":[0.9869178,0.009796212,0.00103669,0.001065481,0.001002448,0.000181274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.01979182,0.0007297848,0.2141137,0.001009076,0.001367015,0.000826219,0.001683819,0.09934081,0.5265171,0.00115254,0.001377118,0.1320911],"study_design_scores_gemma":[0.00009432619,0.002930619,0.8550905,0.00004013714,0.0005385733,0.001503437,0.0003049465,0.05780776,0.07941668,0.0004425833,0.0017107,0.0001197525],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.969156,0.0004004791,0.02854992,0.00005690596,0.00007712383,0.000036164,0.0007472999,0.0001881149,0.0007879906],"genre_scores_gemma":[0.9962513,0.00008539333,0.002776621,0.00002187864,0.00001577494,0.00001933528,0.0004137855,0.0001158881,0.0003000344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002037664,"threshold_uncertainty_score":0.01019824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006195642667627697,"score_gpt":0.1845608247305495,"score_spread":0.1783651820629218,"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."}}