{"id":"W4213276639","doi":"10.1016/j.jbiomech.2022.111000","title":"The validation of a low-cost inertial measurement unit system to quantify simple and complex upper-limb joint angles","year":2022,"lang":"en","type":"article","venue":"Journal of Biomechanics","topic":"Shoulder Injury and Treatment","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Mitacs","keywords":"Inertial measurement unit; Range of motion; Elbow; Motion capture; Shoulder joint; Physical medicine and rehabilitation; Upper limb; Elbow flexion; Movement (music); Rotation (mathematics); Functional movement; Mathematics; Simulation; Computer science; Medicine; Motion (physics); Physical therapy; Physics; Surgery; Computer vision; Geometry; Acoustics","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":[0.004384644,0.001206475,0.0006031087,0.001215868,0.0004054623,0.001137994,0.001477827,0.001794262,0.001767123],"category_scores_gemma":[0.008047084,0.0003773829,0.0004183105,0.0007505518,0.0007225399,0.0009160073,0.0009529115,0.0005673446,0.001248507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003597605,"about_ca_system_score_gemma":0.00124571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002088451,"about_ca_topic_score_gemma":0.002662082,"domain_scores_codex":[0.996813,0.0009404059,0.0003012489,0.0004694629,0.001366576,0.0001094055],"domain_scores_gemma":[0.99508,0.001553218,0.0003775444,0.0005502605,0.00228826,0.0001507012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00247902,0.002175762,0.1663595,0.0007794279,0.000459759,0.000243139,0.0005482945,0.005493328,0.5130267,0.0009959893,0.003639937,0.303799],"study_design_scores_gemma":[0.001190296,0.01721844,0.5411779,0.0002894088,0.0009499338,0.003441675,0.0006328062,0.1517312,0.265349,0.001279558,0.01643134,0.0003084825],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5772527,0.0009870891,0.4129221,0.000507807,0.0007028219,0.0016818,0.001687,0.001264052,0.002994661],"genre_scores_gemma":[0.8428633,0.0003759074,0.1507022,0.0007517349,0.0001866795,0.001218044,0.001613731,0.0001582251,0.002130203],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.004384644,"threshold_uncertainty_score":0.02318853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1098099265626575,"score_gpt":0.3257576460748552,"score_spread":0.2159477195121977,"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."}}