{"id":"W4402558731","doi":"10.1016/j.gim.2024.101272","title":"A Genomic Counseling Model for Population-Based Sequencing: A Pre-Post Intervention Study","year":2024,"lang":"en","type":"article","venue":"Genetics in Medicine","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children; SickKids Foundation; Schwartz/Reisman Emergency Medicine Institute; York Central Hospital; University Health Network; Women's College Hospital; Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; Ontario Genomics; Sinai Health System; Public Health Ontario; William Osler Health System","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Genetic counseling; Intervention (counseling); Medicine; Genomic sequencing; Computational biology; Biology; Genetics; Genome; Nursing; 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":[0.009048382,0.0009330231,0.0009613609,0.0005724486,0.00196063,0.001238795,0.001559675,0.002663924,0.01235762],"category_scores_gemma":[0.02464224,0.0004896477,0.0008943344,0.0007686723,0.001404977,0.002964773,0.001538819,0.002196892,0.001726049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002114791,"about_ca_system_score_gemma":0.005474348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009599881,"about_ca_topic_score_gemma":0.006152467,"domain_scores_codex":[0.990542,0.006860446,0.0002427063,0.0008363661,0.0008737188,0.0006448849],"domain_scores_gemma":[0.9879766,0.006355205,0.0007796739,0.00168542,0.001319095,0.001884059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.05206439,0.1054742,0.2889908,0.0007910141,0.001197445,0.002045355,0.008034041,0.008026916,0.003114598,0.02752569,0.01482279,0.4879127],"study_design_scores_gemma":[0.01740676,0.2746598,0.5455508,0.001693109,0.003976143,0.00232937,0.01239377,0.03844987,0.007508701,0.05236292,0.04314834,0.0005204254],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9435361,0.0007403148,0.02401251,0.008770988,0.0006120778,0.006161191,0.001490464,0.0002707297,0.01440551],"genre_scores_gemma":[0.9792461,0.0003074194,0.009646518,0.002217487,0.0001461585,0.004603156,0.000490279,0.00003810455,0.00330472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01235762,"threshold_uncertainty_score":0.04785299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0218244303209799,"score_gpt":0.3197687993142782,"score_spread":0.2979443689932982,"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."}}