{"id":"W2338344442","doi":"10.1101/034165","title":"Human copy number variants are enriched in regions of low mappability","year":2015,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University and Génome Québec Innovation Centre; Université du Québec à Chicoutimi; Montreal Neurological Institute and Hospital; Centre Hospitalier de l’Université de Montréal; McGill University; Ontario Genomics","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Compute Canada","keywords":"Copy-number variation; Genome; Human genome; Genetics; Biology; Segmental duplication; Structural variation; Germline; Computational biology; Gene duplication; Transposable element; Gene; Gene family","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002760042,0.0001790466,0.0003362229,0.001328762,0.0001874856,0.0004387301,0.0001652623,0.0003356676,0.002117663],"category_scores_gemma":[0.001398233,0.0001262227,0.0002316296,0.001063628,0.0002568394,0.00016229,0.0003250129,0.000239074,0.0002812502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000136342,"about_ca_system_score_gemma":0.000106717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006279234,"about_ca_topic_score_gemma":0.001087968,"domain_scores_codex":[0.9996771,0.00003708394,0.00002389565,0.0001391033,0.00008439859,0.00003845829],"domain_scores_gemma":[0.9992653,0.0003829365,0.0002038971,0.00006780226,0.00003650545,0.00004360914],"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":[0.0008268339,0.00003779366,0.2724161,0.0001860807,0.0002466922,0.001791008,0.0002594873,0.001567848,0.693095,0.0006769971,0.0004758223,0.02842032],"study_design_scores_gemma":[0.00004044091,0.0001483203,0.8929299,0.00001854436,0.0002136439,0.004378756,0.00009953849,0.004228569,0.09393296,0.0016411,0.002343679,0.00002446854],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960569,0.000413269,0.002125126,0.00003801651,0.000003847503,0.000005754086,0.0008084507,0.00008211001,0.0004665077],"genre_scores_gemma":[0.9976943,0.00009590358,0.001344603,0.00002280901,0.000005945967,0.000004736435,0.0005752132,0.00001669306,0.0002397911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002117663,"threshold_uncertainty_score":0.00708431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01464044298121206,"score_gpt":0.2338529822353752,"score_spread":0.2192125392541631,"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."}}