{"id":"W7161992291","doi":"10.82308/13397","title":"Application of Bayesian variable selection methods and shrinkage priors to epidemiological data","year":2023,"lang":"en","type":"dissertation","venue":"","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Prior probability; Bayesian probability; Feature selection; Frequentist inference; Missing data; Bayes' theorem; Posterior probability; Selection (genetic algorithm); Variable (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"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":[0.0460366,0.001712258,0.003152939,0.00443169,0.0009064966,0.002766713,0.003436918,0.002371137,0.003098591],"category_scores_gemma":[0.1094183,0.001630582,0.003245587,0.005357822,0.002823637,0.002837013,0.003371203,0.005802441,0.0007869052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001784676,"about_ca_system_score_gemma":0.003133583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004988961,"about_ca_topic_score_gemma":0.003764822,"domain_scores_codex":[0.9655095,0.02824995,0.001069331,0.002193843,0.002652954,0.00032433],"domain_scores_gemma":[0.9102547,0.07964239,0.00307915,0.003613474,0.003066201,0.0003440861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001307358,0.00009239896,0.005874692,0.00136603,0.001443702,0.0003118417,0.0007298503,0.2766221,0.0007787569,0.4484772,0.006310933,0.2578618],"study_design_scores_gemma":[0.0001026022,0.0001036886,0.001600955,0.0005993456,0.0001669828,0.0001573885,0.00009404518,0.4806859,0.000789439,0.5006606,0.01494032,0.00009875956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001394313,0.001426868,0.9957259,0.0004922184,0.00006516492,0.00009350864,0.0001192799,0.0001435047,0.0005393263],"genre_scores_gemma":[0.07832774,0.007067021,0.9089618,0.0006854607,0.0005887789,0.001486696,0.0008254132,0.0002247399,0.0018323],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0460366,"threshold_uncertainty_score":0.2434677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1655201101036537,"score_gpt":0.5089599152604234,"score_spread":0.3434398051567697,"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."}}