{"id":"W4404643250","doi":"10.2196/65578","title":"Effectiveness of Using a Digital Wearable Plantar Pressure Device to Detect Muscle Fatigue: Within-Subject, Repeated Measures Experimental Design","year":2024,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Lower Extremity Biomechanics and Pathologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Wearable computer; Plantar pressure; Subject (documents); Wearable technology; Computer science; Physical medicine and rehabilitation; Engineering; Pressure sensor; Medicine; Mechanical engineering; Embedded system; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002347307,0.0002674052,0.0002819972,0.0002231275,0.00008648704,0.0001924684,0.0002022446,0.0001273729,0.00006913306],"category_scores_gemma":[0.00002824783,0.000235737,0.00009720773,0.0003279492,0.0000286029,0.0002682653,0.00006518477,0.0001689475,0.00001112484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009758201,"about_ca_system_score_gemma":0.00002614502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000548634,"about_ca_topic_score_gemma":0.000005816967,"domain_scores_codex":[0.9988227,0.00007555922,0.0002435941,0.000328385,0.0002572924,0.0002724529],"domain_scores_gemma":[0.9994377,0.0001658901,0.00003063918,0.0002428553,0.00003591356,0.00008703272],"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":[0.000046571,0.00002735305,0.0002389394,0.000555243,0.0001440329,0.0000374531,0.002473813,0.01356067,0.9822788,0.00002168359,0.0001121813,0.0005032266],"study_design_scores_gemma":[0.0001855491,0.0002008974,0.001660706,0.0008655171,0.00003607811,0.00001011658,0.0003163103,0.005780699,0.9900314,0.000101024,0.0004246892,0.0003870293],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889148,0.0009010964,0.008299438,4.673034e-7,0.0003274836,0.0005845125,0.0001789862,0.0005681663,0.0002249736],"genre_scores_gemma":[0.9993709,0.000002467551,0.0004349213,0.000001424324,0.00002387176,0.00004991212,0.00002988032,0.00006095799,0.00002566701],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01045602,"threshold_uncertainty_score":0.9613075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06053573502049949,"score_gpt":0.2900802418201238,"score_spread":0.2295445067996243,"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."}}