{"id":"W2160340638","doi":"10.1101/gr.5629106","title":"Genome-wide detection of human copy number variations using high-density DNA oligonucleotide arrays","year":2006,"lang":"en","type":"article","venue":"Genome Research","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":210,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"Core Research for Evolutional Science and Technology; Japan Science and Technology Agency; Canadian Institutes of Health Research; National Institute of Biomedical Innovation; Ministry of Education, Culture, Sports, Science and Technology; Howard Hughes Medical Institute","keywords":"Biology; Human genome; Genome; Copy-number variation; Oligonucleotide; Genetics; DNA; Computational biology; Gene","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":[0.001191716,0.0004011979,0.0004914503,0.001286791,0.0002412404,0.0005083515,0.0003698603,0.0004746176,0.0009771683],"category_scores_gemma":[0.002471428,0.0002895996,0.000406082,0.0009375433,0.000247696,0.0003269628,0.0004034698,0.000508118,0.0006464371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002842837,"about_ca_system_score_gemma":0.0002323213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000845797,"about_ca_topic_score_gemma":0.00215141,"domain_scores_codex":[0.9987288,0.0004094703,0.0000953719,0.0004210681,0.0002921418,0.00005314927],"domain_scores_gemma":[0.999233,0.0004495204,0.00007291361,0.0001000847,0.0001120885,0.00003243223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000223673,0.00005420867,0.01497116,0.0001705012,0.0001333956,0.000118545,0.0001161608,0.00214938,0.8921253,0.001000884,0.0005188529,0.08841803],"study_design_scores_gemma":[0.0001103582,0.0007569244,0.2484185,0.00004454001,0.0003827898,0.001924669,0.0001327439,0.07384686,0.6531162,0.004024395,0.01710547,0.0001366455],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4513992,0.003441432,0.5321901,0.0003727293,0.00009127037,0.0006289504,0.003818712,0.002674534,0.005383031],"genre_scores_gemma":[0.3878726,0.001006023,0.6058668,0.0002858485,0.00004197573,0.0006305577,0.002559507,0.00006335052,0.001673341],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001286791,"threshold_uncertainty_score":0.006302476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02617769039413231,"score_gpt":0.2946731669375831,"score_spread":0.2684954765434508,"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."}}