{"id":"W3119495095","doi":"10.1002/nbm.4466","title":"The muscle twitch profile assessed with motor unit magnetic resonance imaging","year":2021,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"NIHR Newcastle Biomedical Research Centre; Medical Research Council; Medical Research Council Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Muscular Dystrophy UK; Department of Health and Social Care; Newcastle University; National Institute for Health and Care Research","keywords":"Contraction (grammar); Nuclear magnetic resonance; Muscle contraction; Skeletal muscle; Magnetic resonance imaging; Ultrasound; Intraclass correlation; Anatomy; Chemistry; Materials science; Biomedical engineering; Physics; Medicine; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001180417,0.0004431545,0.0003775618,0.0005109751,0.0001534039,0.000321337,0.0002601572,0.0003902584,0.001131187],"category_scores_gemma":[0.003974007,0.0001648526,0.0002853775,0.0003388012,0.0002524574,0.0003503367,0.0003114595,0.0002141116,0.0003133376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001977618,"about_ca_system_score_gemma":0.0001076255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001834875,"about_ca_topic_score_gemma":0.001741476,"domain_scores_codex":[0.9997748,0.00006527645,0.00002690903,0.00006318502,0.00004731775,0.00002253507],"domain_scores_gemma":[0.9988005,0.0003223275,0.0004545128,0.0001108967,0.0002259964,0.00008576375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004229815,0.0002283038,0.7882961,0.000438745,0.0004836457,0.002419033,0.001044001,0.003685087,0.1508887,0.0002895315,0.0002192651,0.0477777],"study_design_scores_gemma":[0.00002760897,0.00250326,0.9819816,0.00002305758,0.0001273791,0.002145125,0.0001897608,0.004342907,0.008101823,0.0001018666,0.0004376778,0.00001797033],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961743,0.0002729235,0.00275038,0.000008716832,0.000002116906,0.00007249844,0.0001334707,0.00002362096,0.0005620016],"genre_scores_gemma":[0.9987262,0.00008927779,0.000698093,0.000005461115,0.000001933112,0.00003539493,0.0001506538,0.000008021862,0.0002849755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001834875,"threshold_uncertainty_score":0.006242692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008230694422744177,"score_gpt":0.2248175969249435,"score_spread":0.2165869025021993,"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."}}