{"id":"W4401608652","doi":"10.1109/tbme.2024.3416378","title":"Dynamic Soft Tissue Artifacts during Impulsive Loads: Measurement Errors Vary With Wearable Inertial Measurement Unit Sensor Design","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Inertial measurement unit; Wearable computer; Computer science; Units of measurement; Observational error; Inertial frame of reference; System of measurement; Accelerometer; Acoustics; Artificial intelligence; Embedded system; Physics; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001013746,0.0003728803,0.0003532147,0.0004488225,0.0003833815,0.00003254047,0.0001634679,0.0003094899,0.00008139058],"category_scores_gemma":[0.00003188821,0.0003152162,0.0001056795,0.0006755057,0.00006906728,0.0002121104,0.000004114519,0.001234679,0.0002830063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000877142,"about_ca_system_score_gemma":0.0004135765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000954436,"about_ca_topic_score_gemma":0.00007890425,"domain_scores_codex":[0.996619,0.0001943743,0.0006043567,0.0005206857,0.001258496,0.0008030664],"domain_scores_gemma":[0.9988981,0.0001331948,0.00007095648,0.0003064259,0.0001910533,0.0004002041],"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":[0.0004148194,0.0007012842,0.000004749244,0.001892368,0.0006027209,0.000185188,0.001235381,0.03632151,0.9382507,0.00001175738,0.0001814421,0.02019811],"study_design_scores_gemma":[0.0109287,0.002913515,0.008512799,0.03068402,0.001290673,0.0002195931,0.002145441,0.876743,0.04002862,0.0001247979,0.02312297,0.003285901],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04114287,0.0005460889,0.9533125,0.0005491312,0.002338191,0.0009638785,0.0000235097,0.001073336,0.00005050719],"genre_scores_gemma":[0.9957729,0.0002079069,0.002969,0.00006609769,0.0001755481,0.0003304795,0.000005681289,0.000122687,0.0003496943],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.95463,"threshold_uncertainty_score":0.99993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03188428334922346,"score_gpt":0.2950855278034315,"score_spread":0.2632012444542081,"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."}}