{"id":"W3153855553","doi":"10.1109/jbhi.2021.3073352","title":"Predicted Threshold for Seated Stability: Estimation of Margin of Stability Using Wearable Inertial Sensors","year":2021,"lang":"en","type":"article","venue":"IEEE Journal of Biomedical and Health Informatics","topic":"Spinal Cord Injury Research","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Glenrose Rehabilitation Hospital; Alberta Health Services; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Trunk; Kinematics; Inertial measurement unit; Motion capture; Control theory (sociology); Dynamic balance; Sitting; Stability (learning theory); Simulation; Wearable computer; Computer science; Displacement (psychology); Motion analysis; Engineering; Physics; Motion (physics); Artificial intelligence; Medicine","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":[0.0003466627,0.0005139607,0.0003435031,0.0009157516,0.0001720624,0.0004307005,0.0002875098,0.0005590051,0.0006607758],"category_scores_gemma":[0.002383825,0.0001844592,0.0003508613,0.0003320444,0.0001614309,0.0005115409,0.0004232942,0.0001682302,0.0002571998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001763919,"about_ca_system_score_gemma":0.000197978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001391648,"about_ca_topic_score_gemma":0.001467544,"domain_scores_codex":[0.9997072,0.00004647854,0.00003229179,0.00007880011,0.0001064464,0.00002877978],"domain_scores_gemma":[0.9994878,0.0002014462,0.0001075206,0.0000495932,0.0001239233,0.00002982995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002306898,0.0004492713,0.26815,0.0008205358,0.0002721784,0.0008467523,0.0007941973,0.09376433,0.3951528,0.001075169,0.0008481918,0.2355197],"study_design_scores_gemma":[0.00007637199,0.002285294,0.3992281,0.0001696359,0.000151656,0.001060865,0.0003858365,0.5214912,0.07276262,0.001240416,0.00103353,0.0001144825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8413695,0.000454263,0.1557721,0.00005458858,0.00002210303,0.00006987141,0.0004313885,0.0004500578,0.001376244],"genre_scores_gemma":[0.9901272,0.00007313233,0.00943644,0.00001069755,0.000004440612,0.00004194109,0.0001536443,0.000005817213,0.0001465485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001391648,"threshold_uncertainty_score":0.002767086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1476602738423459,"score_gpt":0.4198328694182582,"score_spread":0.2721725955759123,"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."}}