{"id":"W2883772165","doi":"10.1016/j.rehab.2018.05.1124","title":"Agreement analysis between Vive and Vicon tracking systems to monitor lumbar postural changes","year":2018,"lang":"en","type":"article","venue":"Annals of Physical and Rehabilitation Medicine","topic":"Musculoskeletal pain and rehabilitation","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre hospitalier universitaire de Québec","funders":"","keywords":"Motion capture; Computer science; Pelvis; Orientation (vector space); Match moving; Computer vision; Artificial intelligence; Motion (physics); Medicine; Mathematics; Surgery","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":[0.01163727,0.0007288622,0.0007613436,0.002399151,0.0005309269,0.001546189,0.001023361,0.001372551,0.002079892],"category_scores_gemma":[0.03402684,0.0003802525,0.0007281778,0.0012071,0.0004428899,0.001614747,0.001597858,0.0005979908,0.0009478357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005399151,"about_ca_system_score_gemma":0.0007377315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003342971,"about_ca_topic_score_gemma":0.003974417,"domain_scores_codex":[0.98981,0.003437998,0.0009238668,0.001909058,0.00339614,0.0005229262],"domain_scores_gemma":[0.9661392,0.01623713,0.001370349,0.001698777,0.01421784,0.0003366607],"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":[0.01164583,0.0005291711,0.3756796,0.001575934,0.002263817,0.000532261,0.003384144,0.02222125,0.1528685,0.003612836,0.005112755,0.4205738],"study_design_scores_gemma":[0.0003320608,0.002496233,0.4559504,0.0002093607,0.001144121,0.00178597,0.002344958,0.4444025,0.08132115,0.00252846,0.007111667,0.0003730596],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7305852,0.001624366,0.2578171,0.0001865447,0.0003633723,0.000336599,0.001263892,0.001460748,0.006362175],"genre_scores_gemma":[0.9588473,0.0001662619,0.0382314,0.00009095496,0.00003837871,0.0001275768,0.000877876,0.0001610143,0.001459194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01163727,"threshold_uncertainty_score":0.06154448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03201652201691783,"score_gpt":0.3628713112680647,"score_spread":0.3308547892511468,"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."}}