{"id":"W2618209500","doi":"10.1186/s12864-017-3671-0","title":"Comprehensive whole genome sequence analyses yields novel genetic and structural insights for Intellectual Disability","year":2017,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children's & Women's Health Centre of British Columbia; Child and Family Research Institute; Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"Canadian Institutes of Health Research; Terveyden ja hyvinvoinnin laitos; Trinity College Dublin; Michael Smith Health Research BC","keywords":"Indel; Biology; Genetics; Whole genome sequencing; Intellectual disability; Structural variation; Genome; Exome sequencing; Copy-number variation; Computational biology; Gene; Sequence assembly; INDEL Mutation; Reference genome; DNA sequencing; DNA microarray; Mutation; Single-nucleotide polymorphism; Genotype; Transcriptome","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003606195,0.0002179047,0.0002177861,0.00002127936,0.0004870031,0.0001545612,0.0003905347,0.0001365709,0.000007293896],"category_scores_gemma":[0.0001735771,0.0001986052,0.000138342,0.00001782996,0.0004186067,0.000007094768,0.0003310177,0.00005997952,0.00000323677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003098065,"about_ca_system_score_gemma":0.0001195874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007985326,"about_ca_topic_score_gemma":0.0002340846,"domain_scores_codex":[0.9989281,0.00001833049,0.0002263246,0.0005104547,0.00006324231,0.0002536032],"domain_scores_gemma":[0.9988319,0.00004688872,0.000141083,0.0007201154,0.0001199112,0.0001400932],"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":[0.0001413453,0.00003187644,0.003419447,0.00006408511,0.00007927428,0.000001348773,0.0002552155,0.0009595852,0.9940522,0.00002317048,0.00004405007,0.0009283441],"study_design_scores_gemma":[0.004156693,0.00115924,0.6734259,0.00002629543,0.0004074446,0.0001633943,0.001499519,0.01448622,0.1119387,0.002024399,0.188651,0.002061246],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924725,0.001775454,0.004562301,0.00005023455,0.0002020592,0.0003696894,0.0005237446,0.000007377379,0.0000366955],"genre_scores_gemma":[0.9925674,0.0001819656,0.006346477,0.0001326469,0.0002945555,0.00002471544,0.0003059783,0.00002708977,0.0001191215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8821135,"threshold_uncertainty_score":0.8098886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07916574211285611,"score_gpt":0.327530364372378,"score_spread":0.2483646222595219,"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."}}