{"id":"W2151009639","doi":"10.1007/s00439-010-0837-0","title":"Outcome of array CGH analysis for 255 subjects with intellectual disability and search for candidate genes using bioinformatics","year":2010,"lang":"en","type":"article","venue":"Human Genetics","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia Hospital; Kingston Health Sciences Centre; University of British Columbia; Royal Columbian Hospital; Child and Family Research Institute; Queen's University","funders":"National Institute of General Medical Sciences; Canadian Institutes of Health Research; Autism Speaks","keywords":"Candidate gene; Biology; Gene; Copy-number variation; Genetics; Computational biology; Bioinformatics; Genome","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":[0.0001906438,0.0001311397,0.0002095033,0.00005385797,0.0001629562,0.00003241632,0.0001207871,0.00009672866,0.00001387485],"category_scores_gemma":[0.00002728526,0.0001115818,0.00009787062,0.00009158129,0.0002368179,0.000003740051,0.00005264073,0.0000500504,1.522416e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008848219,"about_ca_system_score_gemma":0.00005202639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000590041,"about_ca_topic_score_gemma":0.001009771,"domain_scores_codex":[0.999214,0.00001508374,0.0003026559,0.000189978,0.00007721932,0.0002010972],"domain_scores_gemma":[0.9993296,0.00003903282,0.00009215093,0.0003082849,0.0001708545,0.00006005282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009503005,0.00006166229,0.5739771,0.0002124913,0.0004000002,6.689114e-8,0.0007876381,0.00141399,0.4225067,0.0001878624,0.00001151492,0.0003458717],"study_design_scores_gemma":[0.001223529,0.0009562842,0.0438555,0.000006610492,0.0007060334,0.00001057161,0.001139341,0.006859398,0.943188,0.0001102307,0.001528069,0.0004164757],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.950241,0.00007815929,0.04905203,0.00001248763,0.00003741049,0.000328187,0.0002142786,0.000003954906,0.00003250599],"genre_scores_gemma":[0.9664118,0.00001907438,0.03316207,0.00001779406,0.00009290701,0.00002073684,0.0001926367,0.00001549478,0.00006753322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5301216,"threshold_uncertainty_score":0.4550173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03135481552760623,"score_gpt":0.2923835952152795,"score_spread":0.2610287796876733,"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."}}