{"id":"W4382198943","doi":"10.1093/genetics/iyad119","title":"Characterization of direct and/or indirect genetic associations for multiple traits in longitudinal studies of disease progression","year":2023,"lang":"en","type":"article","venue":"Genetics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Western University; Hospital for Sick Children; Public Health Ontario; University of Toronto; Lunenfeld-Tanenbaum Research Institute","funders":"University of Toronto; Canada Foundation for Innovation; Canadian Institutes of Health Research; Government of Ontario","keywords":"Biology; Single-nucleotide polymorphism; SNP; Genetic architecture; Quantitative trait locus; Genetics; Genome-wide association study; Genetic association; Random effects model; Proportional hazards model; Statistics; Internal medicine; Mathematics; Medicine; Gene; Meta-analysis; Genotype","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":[0.04384074,0.0007396046,0.001342113,0.001111079,0.0006609698,0.001876473,0.001515629,0.001485986,0.001854647],"category_scores_gemma":[0.122654,0.0005983485,0.002085746,0.001441554,0.001477175,0.002081219,0.002281552,0.00209028,0.0001951372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006858286,"about_ca_system_score_gemma":0.002229664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002833824,"about_ca_topic_score_gemma":0.006239035,"domain_scores_codex":[0.9857825,0.0109347,0.0007206407,0.001408742,0.0008865363,0.0002668755],"domain_scores_gemma":[0.8764457,0.107389,0.005113554,0.008656096,0.001745612,0.0006499588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009962948,0.0002967124,0.525132,0.0007092892,0.00348949,0.0007842824,0.001385192,0.2076868,0.009984735,0.09877032,0.001261669,0.1495033],"study_design_scores_gemma":[0.0001226654,0.000668684,0.09913772,0.0001456325,0.0007493328,0.000468745,0.000203573,0.7685597,0.003165129,0.1244101,0.002279969,0.00008877343],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1580167,0.0004504166,0.8392504,0.0005326623,0.00003473429,0.0001564271,0.0003502527,0.0001879257,0.00102045],"genre_scores_gemma":[0.7816607,0.0004037737,0.2145592,0.0003366836,0.00007871746,0.0007457598,0.0007562294,0.000117465,0.001341524],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04384074,"threshold_uncertainty_score":0.2318547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05375349937890683,"score_gpt":0.3422809946349025,"score_spread":0.2885274952559957,"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."}}