{"id":"W7132981745","doi":"","title":"Phenotyping and Latent Genetic Interaction Analysis using Quantile Regression","year":2023,"lang":"","type":"dissertation","venue":"TSpace","topic":"Cystic Fibrosis Research Advances","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Sickkids Research Institute; Hospital for Sick Children","keywords":"Quantile regression; Quantile; Genetic association; Leverage (statistics); Regression analysis; Regression; Normality; Linear model; Trait","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01148516,0.0009270236,0.001545484,0.001556698,0.0006482308,0.001739181,0.002151554,0.00109109,0.005230105],"category_scores_gemma":[0.04264792,0.0004095485,0.002373754,0.002749409,0.002146185,0.001358559,0.002349298,0.002885786,0.0008208871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001031666,"about_ca_system_score_gemma":0.001828992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01326841,"about_ca_topic_score_gemma":0.006757054,"domain_scores_codex":[0.9906645,0.006709102,0.0002416595,0.001329218,0.0007192992,0.00033628],"domain_scores_gemma":[0.9721686,0.02319873,0.001446484,0.002081709,0.000857496,0.0002469565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005116803,0.0002214445,0.119037,0.0005931182,0.001703401,0.0008382555,0.0008802571,0.2503577,0.003561419,0.285277,0.00901901,0.3279998],"study_design_scores_gemma":[0.0001159061,0.0002091581,0.02909661,0.0001328347,0.0002934346,0.0002647611,0.0002328033,0.7803023,0.001739765,0.1779279,0.009581976,0.0001026107],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02082022,0.0006722686,0.9753447,0.0005572165,0.0000652965,0.00008519121,0.0005925805,0.0005727937,0.001289705],"genre_scores_gemma":[0.627425,0.001385659,0.3633938,0.000705347,0.0001898503,0.0006271015,0.001674969,0.0005171687,0.004081175],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01326841,"threshold_uncertainty_score":0.06074005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05828844058553815,"score_gpt":0.4435583832463855,"score_spread":0.3852699426608474,"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."}}