{"id":"W4289519099","doi":"10.2196/36427","title":"Uncertainty Estimation in Medical Image Classification: Systematic Review","year":2022,"lang":"en","type":"review","venue":"JMIR Medical Informatics","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Estimation; Artificial intelligence; Data mining; Data science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.01169093,0.001436244,0.004228924,0.009064588,0.000495492,0.002428154,0.002019321,0.001931147,0.003395155],"category_scores_gemma":[0.07236048,0.0007567439,0.004208384,0.006233187,0.001270029,0.002579019,0.001470476,0.00141896,0.0005266514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002033719,"about_ca_system_score_gemma":0.0073933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003602225,"about_ca_topic_score_gemma":0.006324866,"domain_scores_codex":[0.9928886,0.002594898,0.001945638,0.0006670593,0.001775084,0.000128716],"domain_scores_gemma":[0.9240721,0.06439188,0.005649789,0.0009992872,0.00461066,0.0002762097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001570944,0.00003014958,0.0006325031,0.5760247,0.003727152,0.00007837565,0.0001508594,0.0007722235,0.000189915,0.001434803,0.006486258,0.410316],"study_design_scores_gemma":[0.000125268,0.0003795305,0.003165803,0.8470064,0.0220326,0.0008308258,0.0002588887,0.0009669827,0.00075249,0.004356515,0.1200232,0.0001013616],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001245116,0.998662,0.0005237771,0.0003204134,0.00008828739,0.00004410222,0.00004903433,0.000007147348,0.0001808155],"genre_scores_gemma":[0.004015246,0.9940726,0.001144684,0.0003495739,0.0001632598,0.0001156366,0.00006601973,0.000006400484,0.00006650004],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01169093,"threshold_uncertainty_score":0.06182826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04360340881777357,"score_gpt":0.384361274943199,"score_spread":0.3407578661254254,"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."}}