{"id":"W2333196156","doi":"10.1093/bioinformatics/btw178","title":"Cell-free DNA fragment-size distribution analysis for non-invasive prenatal CNV prediction","year":2016,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Copy-number variation; Single-nucleotide polymorphism; SNP; Cell-free fetal DNA; Genome; Biology; Genetics; SNP array; Human genome; Computational biology; Prenatal diagnosis; Fetus; Gene; Genotype; Pregnancy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00140062,0.0007900181,0.0006972273,0.002608224,0.0002942451,0.0006503831,0.001097458,0.001028931,0.004787379],"category_scores_gemma":[0.006548434,0.0003964212,0.0006108938,0.001051404,0.0003379285,0.0005316847,0.0007293827,0.0006621103,0.002226553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005701106,"about_ca_system_score_gemma":0.0007084382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004071081,"about_ca_topic_score_gemma":0.005230459,"domain_scores_codex":[0.9991022,0.0001888128,0.00004547599,0.0002678891,0.0003484473,0.00004706125],"domain_scores_gemma":[0.9966543,0.002211479,0.0003639408,0.000211075,0.0004472107,0.0001120726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001421411,0.0002747751,0.1088639,0.001291577,0.0004680255,0.0008645569,0.0003631015,0.05246529,0.1616126,0.003075254,0.016447,0.6528524],"study_design_scores_gemma":[0.0001076241,0.0001783895,0.04120907,0.0001459484,0.0001479502,0.002037741,0.00008485247,0.8569679,0.08087616,0.006434777,0.01165166,0.0001579431],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.10044,0.003139025,0.8648669,0.0005261875,0.0001341431,0.0002793022,0.007440693,0.02071603,0.002457784],"genre_scores_gemma":[0.3185236,0.0008694338,0.6717782,0.0002768891,0.00008177382,0.0003430477,0.005443601,0.0008759862,0.00180747],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004787379,"threshold_uncertainty_score":0.01601541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01048325492405987,"score_gpt":0.2294190667248588,"score_spread":0.2189358118007989,"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."}}