{"id":"W1998125424","doi":"10.1016/j.cmpb.2010.06.010","title":"Scaling analysis of baseline dual-axis cervical accelerometry signals","year":2010,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"Dysphagia Assessment and Management","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; Toronto Rehabilitation Institute; University of Toronto","funders":"","keywords":"Accelerometer; QUIET; Swallowing; Medicine; Baseline (sea); Physical medicine and rehabilitation; Vibration; Detrended fluctuation analysis; Scaling; Audiology; Acoustics; Mathematics; Physics; Geology; Surgery; Geometry","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":[],"consensus_categories":[],"category_scores_codex":[0.007270237,0.0001890446,0.0007719574,0.001064106,0.0001219382,0.00001420355,0.0001929472,0.0002008477,0.0005859034],"category_scores_gemma":[0.0001205455,0.0001402902,0.00009962625,0.002718882,0.0001769355,0.00007014164,0.0003549611,0.0005950104,0.000003039655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001863326,"about_ca_system_score_gemma":0.00003581331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001726229,"about_ca_topic_score_gemma":0.00006967072,"domain_scores_codex":[0.9971517,0.0008513097,0.000908468,0.0004032575,0.0002644681,0.0004207856],"domain_scores_gemma":[0.9975407,0.001499087,0.0002620154,0.000377437,0.0001360424,0.0001847121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00003049472,0.0002281342,0.1315855,0.0003057915,0.0005214973,0.000009107868,0.000884566,0.0000044292,0.003662509,0.0008850132,0.0002988183,0.8615842],"study_design_scores_gemma":[0.00437377,0.000837305,0.6507464,0.0005714447,0.00217229,0.000002825663,0.001621144,0.2285839,0.0002829937,0.002232821,0.1079524,0.0006226238],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4015853,0.0003297836,0.5937465,0.001436224,0.001403247,0.0007991997,0.000006370677,0.00007672751,0.0006167243],"genre_scores_gemma":[0.3925105,0.0001102796,0.6059933,0.0007109222,0.0003869869,0.00006050975,0.0000981383,0.00001495983,0.0001144431],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8609616,"threshold_uncertainty_score":0.6415232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1138185894633792,"score_gpt":0.5040360068577572,"score_spread":0.390217417394378,"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."}}