{"id":"W2804120765","doi":"10.1002/gepi.22129","title":"SimPEL: Simulation‐based power estimation for sequencing studies of low‐prevalence conditions","year":2018,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; Rare Disease Foundation; University of Calgary","keywords":"Statistical power; Leverage (statistics); Executable; Computer science; Sample size determination; Ranking (information retrieval); Genetic association; Data mining; Computational biology; Statistics; Genotype; Machine learning; Biology; Genetics; Mathematics; Gene; Single-nucleotide polymorphism","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":[0.02491081,0.001818026,0.001682938,0.002136421,0.0006127785,0.001581066,0.002869728,0.001793107,0.05123354],"category_scores_gemma":[0.09589504,0.001500918,0.002247803,0.001568576,0.001014231,0.00146559,0.002333045,0.003074076,0.004438826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009308552,"about_ca_system_score_gemma":0.002764519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002188253,"about_ca_topic_score_gemma":0.0032764,"domain_scores_codex":[0.9915197,0.006464907,0.0004424948,0.0006961368,0.0006500857,0.0002265554],"domain_scores_gemma":[0.8989496,0.09374239,0.002552685,0.002968195,0.001385701,0.000401273],"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":[0.005366449,0.0006238127,0.02737376,0.005780966,0.004173824,0.001290006,0.001721876,0.3604266,0.008031841,0.07646733,0.141945,0.3667985],"study_design_scores_gemma":[0.001759965,0.0004479828,0.003359638,0.000558094,0.0004457005,0.0004504415,0.00009843666,0.8743983,0.01008229,0.06493269,0.04334096,0.0001254892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009542233,0.0003073817,0.943092,0.0003576824,0.0001480119,0.0008205433,0.006590026,0.03629946,0.002842669],"genre_scores_gemma":[0.1087249,0.0003516909,0.8648313,0.0006192629,0.0001117409,0.008141497,0.004770682,0.009769312,0.002679509],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05123354,"threshold_uncertainty_score":0.1713932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07501922967358635,"score_gpt":0.4043770629575013,"score_spread":0.329357833283915,"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."}}