{"id":"W1596081110","doi":"10.1002/mus.24092","title":"Anconeus motor unit number estimates using decomposition‐based quantitative electromyography","year":2013,"lang":"en","type":"article","venue":"Muscle & Nerve","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Motor unit; Electromyography; Elbow; Elbow flexion; Root mean square; Mathematics; Physical medicine and rehabilitation; Anatomy; Medicine; Physics","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":[0.001314946,0.0005097584,0.0002910519,0.001023006,0.0001245853,0.000437974,0.0002536219,0.000238388,0.002091445],"category_scores_gemma":[0.004926023,0.0001464821,0.0001478585,0.0004363541,0.000193774,0.0004101023,0.0003059965,0.0002159227,0.0003920259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001626193,"about_ca_system_score_gemma":0.0001305645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001030176,"about_ca_topic_score_gemma":0.001584007,"domain_scores_codex":[0.999644,0.0001117641,0.00003231779,0.00009525041,0.00009953801,0.00001715822],"domain_scores_gemma":[0.9989076,0.0006028124,0.0001902254,0.0000941542,0.0001732159,0.00003207682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001431031,0.0001563388,0.1557892,0.0006296262,0.0003047017,0.0002691565,0.0003909598,0.01541809,0.3008148,0.001081529,0.001223205,0.5224913],"study_design_scores_gemma":[0.000116738,0.001007335,0.7114751,0.0001642901,0.0002116594,0.002535754,0.0002128702,0.2065505,0.07070559,0.003478299,0.003399724,0.00014203],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6706368,0.001194825,0.324004,0.00007594773,0.0000238812,0.0001613968,0.0008307151,0.000563043,0.002509387],"genre_scores_gemma":[0.9166857,0.0002186509,0.08177251,0.00002142242,0.00001559019,0.0001020879,0.0004508222,0.00003366449,0.0006996188],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002091445,"threshold_uncertainty_score":0.006996572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02274927909763316,"score_gpt":0.2737545012207576,"score_spread":0.2510052221231245,"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."}}