{"id":"W4220928647","doi":"10.1016/j.apergo.2022.103757","title":"K-score: A novel scoring system to quantify fatigue-related ergonomic risk based on joint angle measurements via wearable inertial measurement units","year":2022,"lang":"en","type":"article","venue":"Applied Ergonomics","topic":"Ergonomics and Musculoskeletal Disorders","field":"Psychology","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; University of Alberta","funders":"","keywords":"Kinematics; Physical medicine and rehabilitation; Wearable computer; Inertial measurement unit; Physical therapy; Muscle fatigue; Work (physics); Joint (building); Motion capture; Electromyography; Motion (physics); Simulation; Computer science; Medicine; Engineering; Artificial intelligence; Structural engineering; Mechanical engineering","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":[0.001017745,0.001642981,0.001086758,0.002617812,0.000293574,0.0009158542,0.0007023705,0.0008279297,0.004064083],"category_scores_gemma":[0.003116592,0.0002973696,0.0009513652,0.001221977,0.0002566044,0.001001418,0.00130098,0.0004316189,0.002104128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003062959,"about_ca_system_score_gemma":0.0004503379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001775542,"about_ca_topic_score_gemma":0.004599877,"domain_scores_codex":[0.9987631,0.0002194927,0.0001912734,0.0001871413,0.0005535102,0.00008546343],"domain_scores_gemma":[0.9981467,0.0003356776,0.0005274107,0.00008547513,0.0007665469,0.0001383379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00333383,0.0006749745,0.4956254,0.001482271,0.001154048,0.0003027714,0.000467444,0.003914754,0.04989325,0.0008007734,0.01465064,0.4276997],"study_design_scores_gemma":[0.0003318353,0.002890233,0.9234838,0.0003777778,0.0007608567,0.002275984,0.0005931832,0.04025744,0.01437781,0.001412201,0.01283711,0.0004017444],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7264201,0.004557523,0.2313249,0.0004157087,0.0006206698,0.001867408,0.01756714,0.003850272,0.01337627],"genre_scores_gemma":[0.878513,0.001986357,0.1019218,0.0003651275,0.0002628138,0.001522322,0.008331137,0.0002275924,0.006869763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004064083,"threshold_uncertainty_score":0.0135957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08269780790322509,"score_gpt":0.2637480491080118,"score_spread":0.1810502412047867,"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."}}