{"id":"W4410603244","doi":"10.1093/hmg/ddaf077","title":"Improving genetic diagnostic yield in familial and sporadic cerebral cavernous malformations: detection of copy number and deep Intronic variants","year":2025,"lang":"en","type":"article","venue":"Human Molecular Genetics","topic":"Vascular Malformations Diagnosis and Treatment","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Ottawa Mental Health Centre","funders":"National Health and Medical Research Council; Medical Research Council; University of Melbourne; Monash University; Austin Medical Research Foundation; Norman Beischer Medical Research Foundation; Australian Government","keywords":"Germline; Biology; Genetics; Genetic testing; Cavernous malformations; Copy-number variation; Somatic cell; Exon; Gene; Pathology; Genome; Medicine; Lesion","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":[0.005284388,0.0008386496,0.0007850538,0.003218524,0.0003127965,0.001237804,0.0008222445,0.0008282891,0.001257348],"category_scores_gemma":[0.01352824,0.0004008613,0.0004111163,0.001255945,0.0006364274,0.0005144405,0.001161814,0.0006867471,0.0004579838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003433039,"about_ca_system_score_gemma":0.000502956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001425688,"about_ca_topic_score_gemma":0.003017767,"domain_scores_codex":[0.9966378,0.001104368,0.0003175007,0.0008265864,0.0008150475,0.0002987192],"domain_scores_gemma":[0.9940076,0.003478596,0.0006634567,0.0005141391,0.0009198402,0.0004163109],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009218317,0.0001873001,0.6948797,0.0002819608,0.0002804583,0.002819041,0.0006848068,0.002501609,0.1697273,0.0004294881,0.001047392,0.1262392],"study_design_scores_gemma":[0.0001004332,0.001087616,0.797366,0.0001362778,0.0005162689,0.01562181,0.0007485471,0.03462256,0.1417796,0.002273134,0.005617373,0.000130379],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9706557,0.002077233,0.0240665,0.0005380884,0.00003717673,0.000115956,0.0006048662,0.0004342591,0.001470169],"genre_scores_gemma":[0.9630173,0.0007220487,0.03482664,0.0001911914,0.00004355329,0.00006482011,0.0006717189,0.00009863218,0.000364165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005284388,"threshold_uncertainty_score":0.02794683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005962734398107712,"score_gpt":0.2373586191961884,"score_spread":0.2313958847980807,"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."}}