{"id":"W2793780291","doi":"10.1002/mgg3.377","title":"Association of common candidate variants with vascular malformations and intracranial hemorrhage in hereditary hemorrhagic telangiectasia","year":2018,"lang":"en","type":"article","venue":"Molecular Genetics & Genomic Medicine","topic":"Vascular Anomalies and Treatments","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; St. Michael's Hospital","funders":"National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke; National Institutes of Health; Rare Diseases Clinical Research Network","keywords":"Telangiectasia; Medicine; Arteriovenous malformation; Phenotype; Intracerebral hemorrhage; ACVRL1; Pathology; Lung; Vascular malformation; Endoglin; Candidate gene; Intracranial Arteriovenous Malformations; Internal medicine; Gene; Biology; Genetics; Subarachnoid hemorrhage; Cerebral angiography","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":[0.000434193,0.0005991346,0.0004481048,0.00128374,0.0004720717,0.0003662539,0.0004119435,0.0007278718,0.003091374],"category_scores_gemma":[0.001374558,0.0001887064,0.0005576961,0.001522889,0.000446744,0.000155755,0.0003529214,0.0003726249,0.0001934226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002107269,"about_ca_system_score_gemma":0.0002503249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00393451,"about_ca_topic_score_gemma":0.005011275,"domain_scores_codex":[0.9994354,0.00009350901,0.00009826857,0.0002216555,0.00009163464,0.00005951837],"domain_scores_gemma":[0.9988253,0.0003705045,0.0005019078,0.00007504649,0.00007691758,0.0001504223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008566617,0.00005622361,0.9823789,0.00004887327,0.0005416182,0.0035706,0.0001493618,0.0002446023,0.008047066,0.0001188331,0.0002702648,0.00371693],"study_design_scores_gemma":[0.00005927831,0.0001589057,0.9913844,0.00001644176,0.000298682,0.005877125,0.00006711048,0.0007134876,0.0009468677,0.0001423074,0.0003244587,0.00001098882],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988237,0.0002136107,0.0002544927,0.00002486918,0.000006282968,0.00000830794,0.0003805525,0.000009267676,0.0002790021],"genre_scores_gemma":[0.9993037,0.00004589697,0.0002593705,0.00001493935,0.000008027964,0.000007431262,0.000253446,0.00000388334,0.0001032326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00393451,"threshold_uncertainty_score":0.01034164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004608652918598346,"score_gpt":0.224430275892361,"score_spread":0.2198216229737626,"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."}}