{"id":"W2620606889","doi":"10.1371/journal.pcbi.1005581","title":"A motor unit-based model of muscle fatigue","year":2017,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":149,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"AUTO21 Network of Centres of Excellence; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Isometric exercise; Motor unit; Muscle fatigue; Muscle contraction; Population; Computer science; Motor unit recruitment; Physical medicine and rehabilitation; Simulation; Electromyography; Neuroscience; Medicine; Psychology; Physical therapy; Anatomy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002996042,0.00007533944,0.000124773,0.00008589541,0.0001139408,0.000008847142,0.0001374704,0.00004246251,0.00001515119],"category_scores_gemma":[0.00004171952,0.00007330142,0.00004401429,0.00003642926,0.00008793849,0.00004574444,0.00001721803,0.00005523224,0.000001494987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008652039,"about_ca_system_score_gemma":0.00001909759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007344742,"about_ca_topic_score_gemma":0.000005935357,"domain_scores_codex":[0.9996079,0.00001129906,0.0001275351,0.00008793699,0.00005658705,0.0001087741],"domain_scores_gemma":[0.9996184,0.00008909332,0.00005441709,0.0001307137,0.00008325536,0.00002408029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001780176,0.00008992018,0.008957356,0.00007442235,0.0001937541,3.72835e-7,0.00009894169,0.8963606,0.06854511,0.01659923,0.0003397818,0.008722764],"study_design_scores_gemma":[0.0002737764,0.00003711221,0.0715746,0.000008588696,0.000006642113,9.929009e-8,0.000004019809,0.9192532,0.002224683,0.00646604,0.00006977905,0.00008150914],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8293032,0.00005828146,0.1667231,0.0003421954,0.00008774707,0.000125273,0.00006932201,0.0001343328,0.003156544],"genre_scores_gemma":[0.9935179,0.000004787705,0.006322172,0.00006443371,0.00002130071,0.00001790097,0.00003578062,0.000008423605,0.000007323399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1642147,"threshold_uncertainty_score":0.2989145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0638957284567242,"score_gpt":0.2740071510539736,"score_spread":0.2101114225972494,"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."}}