{"id":"W2892721734","doi":"10.1016/j.jtbi.2018.09.029","title":"Allelic frequency estimation in presence of uncertain priors","year":2018,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"","keywords":"Prior probability; Hyperparameter; Bayes' theorem; Estimator; Mathematics; Statistics; Bayes estimator; Bayes factor; Computer science; Bayesian probability; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.01825887,0.0007374195,0.002346444,0.002334597,0.0009149187,0.003845467,0.004200592,0.003055367,0.001606945],"category_scores_gemma":[0.08759473,0.002259468,0.001464346,0.002206821,0.002812371,0.00597299,0.00350354,0.003308235,0.0003896512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001244879,"about_ca_system_score_gemma":0.001124904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004309651,"about_ca_topic_score_gemma":0.003810627,"domain_scores_codex":[0.9934475,0.003961297,0.0003287175,0.001297682,0.0006911224,0.0002736057],"domain_scores_gemma":[0.8815402,0.1109509,0.002446529,0.003086137,0.001448854,0.0005273551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003780619,0.000111755,0.0113386,0.0002350246,0.0004282036,0.0004138777,0.0005766064,0.7082293,0.002127909,0.1952155,0.001112025,0.07983318],"study_design_scores_gemma":[0.00002502771,0.00001349971,0.0008628946,0.00001824784,0.0000424084,0.0001283698,0.00002557201,0.8606728,0.0004800911,0.1373013,0.0004000206,0.00002972511],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0290807,0.0003506762,0.9695728,0.0004216184,0.00002467088,0.00001375296,0.00006603378,0.0000863302,0.0003834646],"genre_scores_gemma":[0.6548018,0.0007510349,0.3403903,0.000336817,0.0003111503,0.0001403041,0.0005069752,0.0001577206,0.002603921],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01825887,"threshold_uncertainty_score":0.09656328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01440423069238195,"score_gpt":0.3196798136324079,"score_spread":0.305275582940026,"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."}}