{"id":"W2913027812","doi":"10.1002/ana.25426","title":"Variation in <i>SIPA1L2</i> is correlated with phenotype modification in Charcot– Marie– Tooth disease type 1A","year":2019,"lang":"en","type":"article","venue":"Annals of Neurology","topic":"Hereditary Neurological Disorders","field":"Neuroscience","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke; Medical Research Council; National Institutes of Health; Medical Research Council Canada; Eunice Kennedy Shriver National Institute of Child Health and Human Development; University College London; National Institute for Health and Care Research; Muscular Dystrophy Association; Charcot-Marie-Tooth Association","keywords":"Gene knockdown; Chromatin immunoprecipitation; Immunoprecipitation; Phenotype; Genetics; Genetic variation; Biology; Copy-number variation; Gene; Gene expression; Medicine; Molecular biology; Genome","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001552334,0.000159684,0.0002499798,0.0002033669,0.00002004543,0.000009140669,0.0002850534,0.0001314628,0.0002657231],"category_scores_gemma":[0.0006481521,0.0001436408,0.00003225615,0.000764831,0.0001109989,0.0002148449,0.00005876217,0.0003451016,0.000200899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004745229,"about_ca_system_score_gemma":0.00006677048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009246627,"about_ca_topic_score_gemma":0.00002683677,"domain_scores_codex":[0.9981172,0.0003601464,0.0003410484,0.0006040887,0.0002208639,0.0003566701],"domain_scores_gemma":[0.9988902,0.0004187008,0.0001547457,0.0003892617,0.00005986324,0.00008719452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.02874995,0.003170198,0.4413067,0.0001989984,0.00002313798,0.0007756651,0.001537614,0.04755048,0.4534558,0.01763554,0.001783388,0.003812484],"study_design_scores_gemma":[0.001278494,0.002197757,0.96347,0.00001214081,0.000007878712,0.00000484433,0.000003852341,0.0226136,0.002429441,0.005473785,0.00227256,0.0002355786],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883311,0.00004696543,0.00001787879,0.00952803,0.0002049253,0.0004623233,0.00001772006,0.00003920811,0.00135179],"genre_scores_gemma":[0.9791638,0.0001547003,0.00000657745,0.02053876,0.00001373984,0.0000150425,0.000008799541,0.00002038308,0.00007817992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5221633,"threshold_uncertainty_score":0.5857502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06774442585708847,"score_gpt":0.2941810837806736,"score_spread":0.2264366579235851,"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."}}