{"id":"W2163671213","doi":"10.1111/j.1399-0004.2004.00241.x","title":"A new model for prediction of the age of onset and penetrance for Huntington's disease based on CAG length","year":2004,"lang":"en","type":"article","venue":"Clinical Genetics","topic":"Genetic Neurodegenerative Diseases","field":"Neuroscience","cited_by":827,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute of Neurological Disorders and Stroke","keywords":"Penetrance; Age of onset; Cohort; Trinucleotide repeat expansion; Confidence interval; Disease; Huntington's disease; Medicine; Predictive testing; Internal medicine; Pediatrics; Psychology; Genetics; Biology; Allele; Phenotype","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":[0.005168104,0.001380471,0.001921293,0.001459312,0.0006612451,0.00167595,0.002980786,0.002203346,0.004908675],"category_scores_gemma":[0.01219504,0.0007196434,0.001600095,0.0008824743,0.001254806,0.001543887,0.001181802,0.002417618,0.0009841893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001360686,"about_ca_system_score_gemma":0.001415778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01769939,"about_ca_topic_score_gemma":0.009857039,"domain_scores_codex":[0.998557,0.0005703472,0.00006089183,0.0004339403,0.0001293223,0.0002484307],"domain_scores_gemma":[0.9902043,0.008115663,0.0006128005,0.0001987514,0.0006413883,0.0002270832],"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":[0.0004186515,0.0001239598,0.01714857,0.00005665294,0.000185898,0.0003296364,0.0002013826,0.9502444,0.0005868357,0.01188342,0.002286832,0.0165338],"study_design_scores_gemma":[0.00004385086,0.00004851501,0.001135264,0.00001035226,0.0000315736,0.0000775071,0.00001381966,0.9936899,0.00007038041,0.004625544,0.0002379456,0.00001539461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2731362,0.0009192214,0.7135822,0.003483875,0.0002180913,0.0002200255,0.003136473,0.0009731964,0.004330796],"genre_scores_gemma":[0.9470208,0.0005111013,0.03818127,0.0004078727,0.0001861843,0.000509717,0.002282823,0.0001086566,0.01079147],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01769939,"threshold_uncertainty_score":0.03519273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1074478642820187,"score_gpt":0.3513736233857898,"score_spread":0.2439257591037711,"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."}}