{"id":"W4380869773","doi":"10.1172/jci.insight.163856","title":"Individual transcriptomic response to strength training for patients with myotonic dystrophy type 1","year":2023,"lang":"en","type":"article","venue":"JCI Insight","topic":"Genetic Neurodegenerative Diseases","field":"Neuroscience","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Université du Québec à Chicoutimi","funders":"National Institutes of Health; National Institute of Neurological Disorders and Stroke; AFM-Téléthon; Agios Pharmaceuticals; Fonds de Recherche du Québec - Santé; University of Florida; Fondation du Grand défi Pierre Lavoie; Myotonic Dystrophy Foundation","keywords":"Myotonic dystrophy; Transcriptome; RNA splicing; Strength training; Muscular dystrophy; Squat; Gene; Wasting; Medicine; Gene expression; Biology; Physical medicine and rehabilitation; Bioinformatics; Genetics; Internal medicine; RNA","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":[0.0000987697,0.0002024588,0.000180954,0.0002562219,0.0001926174,0.00007704273,0.0003054494,0.00004101345,0.00003837599],"category_scores_gemma":[0.0007254922,0.0001685268,0.00005820757,0.000860971,0.00006295893,0.00009954353,0.00004447702,0.00009154456,0.0001351294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003018208,"about_ca_system_score_gemma":0.0001735884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001009395,"about_ca_topic_score_gemma":0.000004671976,"domain_scores_codex":[0.9982141,0.0001879328,0.0001932903,0.0005708752,0.0004047954,0.0004289647],"domain_scores_gemma":[0.9990047,0.0003735218,0.00005206322,0.0002940887,0.00008179431,0.0001938984],"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":[0.006550125,0.0004209305,0.002398092,0.00003535001,0.00003026207,0.00004982379,0.008230769,0.0009109731,0.9728855,0.000437466,0.004151185,0.003899462],"study_design_scores_gemma":[0.003793148,0.00471602,0.1960825,0.00004592749,0.00007122168,0.000002431519,0.000238255,0.0002709813,0.7567652,0.0001133855,0.03728159,0.0006193419],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977201,0.000006112691,0.00005708082,0.000281422,0.0003931605,0.0008693028,0.0003697467,0.0001631155,0.0001399453],"genre_scores_gemma":[0.9979815,0.000002872084,0.0003905834,0.0008844795,0.00005412159,0.0001589895,0.00003740994,0.00005484262,0.0004352031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2161203,"threshold_uncertainty_score":0.6872323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06180217994328411,"score_gpt":0.2819339461866557,"score_spread":0.2201317662433716,"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."}}