{"id":"W4386256390","doi":"10.32920/24050724.v1","title":"Interpreting Uncertainty in Model Predictions in Bayesian Neural Networks for COVID-19 Diagnosis","year":2023,"lang":"en","type":"preprint","venue":"","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Interpretability; Convolutional neural network; Computer science; Bayesian probability; Artificial intelligence; Coronavirus disease 2019 (COVID-19); Artificial neural network; Machine learning; Deep neural networks; Bayesian network; Visualization; Data mining; Medicine; Pathology","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":[0.003010667,0.00105951,0.0007265696,0.00109017,0.0004807736,0.002024686,0.001016703,0.001872667,0.001927406],"category_scores_gemma":[0.01867212,0.0006621978,0.0007273898,0.0005246016,0.001043139,0.00173585,0.001429332,0.002694996,0.0002796916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002354226,"about_ca_system_score_gemma":0.001179566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02468604,"about_ca_topic_score_gemma":0.01901725,"domain_scores_codex":[0.9991693,0.000361581,0.00004407084,0.0001821962,0.0001601928,0.00008258745],"domain_scores_gemma":[0.992031,0.006644437,0.000517268,0.0001918769,0.0004396899,0.0001757966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002009838,0.00003568702,0.005392432,0.00006865896,0.00005510329,0.0001875842,0.0001621563,0.9416583,0.0008845481,0.009259511,0.001575317,0.04051973],"study_design_scores_gemma":[0.000003953662,0.000007445999,0.0002984873,0.00001504305,0.000004080437,0.0000133194,0.000009166563,0.9914225,0.0002547977,0.007825784,0.0001405216,0.00000497369],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.140919,0.001380015,0.8471236,0.00486495,0.0001324144,0.00005975431,0.0007641515,0.001572315,0.003183869],"genre_scores_gemma":[0.9315138,0.0004536228,0.06455992,0.0004448031,0.0001185154,0.00006629845,0.0007547021,0.0001614711,0.00192691],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02468604,"threshold_uncertainty_score":0.04908472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07681874513635016,"score_gpt":0.379410069197914,"score_spread":0.3025913240615639,"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."}}