{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003464594,0.0002147005,0.0006592857,0.0001220659,0.00005705652,0.00001901795,0.0003389124,0.0003481578,0.0001904699],"category_scores_gemma":[0.01875871,0.000168936,0.00003034569,0.0004364682,0.00002428644,0.00004303934,0.0001311574,0.0002549063,0.00001158328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002213267,"about_ca_system_score_gemma":0.00005630652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002933399,"about_ca_topic_score_gemma":0.00009994514,"domain_scores_codex":[0.9978539,0.0004942651,0.0006650389,0.0006178319,0.0001630185,0.0002059952],"domain_scores_gemma":[0.9936472,0.005219887,0.0002780973,0.0005966882,0.0001430554,0.0001150835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003470536,0.00004463529,0.0001564605,0.0006178907,0.00004657689,3.540315e-7,0.0001499566,0.000002245191,0.00377918,0.8248897,0.00232236,0.1679559],"study_design_scores_gemma":[0.00009358206,0.0001352212,0.006253072,0.0001280226,0.0001665251,0.00000239104,0.0003300201,0.04633066,0.001629915,0.9434291,0.001213932,0.0002876326],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000925685,0.00001853682,0.9912632,0.0000363179,0.0001491975,0.0005779558,0.00007547227,0.0001191922,0.00683452],"genre_scores_gemma":[0.0006641999,0.00002631193,0.9953969,0.0000449875,0.00005648872,0.00009422632,0.0004679088,0.00003558891,0.003213356],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1676683,"threshold_uncertainty_score":0.9895067,"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."}}