{"id":"W4317582100","doi":"10.1101/2023.01.19.524736","title":"Rare disease research workflow using multilayer networks elucidates the molecular determinants of severity in Congenital Myasthenic Syndromes","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Myasthenia Gravis and Thymoma","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; Children's Hospital of Eastern Ontario; University of Ottawa","funders":"Barcelona Supercomputing Center; Newcastle University","keywords":"Biology; Disease; Neuromuscular junction; Phenotype; Computational biology; Gene; Acetylcholine receptor; Neuroscience; Bioinformatics; Genetics; Medicine; Receptor; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002169087,0.00106092,0.0006532183,0.003793054,0.0006011841,0.002366808,0.0007261318,0.0005860729,0.004768752],"category_scores_gemma":[0.0045928,0.0004878583,0.001539659,0.001457505,0.000262564,0.001142073,0.001834173,0.0007630202,0.002123062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008717821,"about_ca_system_score_gemma":0.001392064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004554522,"about_ca_topic_score_gemma":0.006689137,"domain_scores_codex":[0.9991608,0.0001429376,0.00009693038,0.0003316548,0.0001976286,0.00007010263],"domain_scores_gemma":[0.9984718,0.0004501316,0.0002117057,0.0003568823,0.0003259566,0.0001834573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002988917,0.0004171442,0.1608336,0.002267506,0.001835331,0.00317461,0.002045386,0.0771555,0.2364886,0.02998383,0.06711756,0.415692],"study_design_scores_gemma":[0.000198398,0.0002976141,0.09486842,0.0003760943,0.0006602134,0.001758661,0.00100089,0.6149921,0.1055263,0.09364885,0.08636116,0.0003113103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1628841,0.001509859,0.6957502,0.002340114,0.0004389386,0.0005054017,0.07199563,0.05677615,0.007799607],"genre_scores_gemma":[0.3444429,0.001808793,0.5866552,0.0003454879,0.0001510598,0.0005660149,0.05731183,0.002955244,0.005763417],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004768752,"threshold_uncertainty_score":0.01595306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05703778896537704,"score_gpt":0.313679353082191,"score_spread":0.256641564116814,"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."}}