{"id":"W3207418263","doi":"10.2196/34081","title":"Author’s Response to Peer Reviews of “Machine Learning–Based Prediction of COVID-19 Mortality With Limited Attributes to Expedite Patient Prognosis and Triage: Retrospective Observational Study”","year":2021,"lang":"en","type":"article","venue":"JMIRx Med","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Triage; Observational study; Coronavirus disease 2019 (COVID-19); Medicine; 2019-20 coronavirus outbreak; Computer science; Emergency medicine; Internal medicine; Virology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003049956,0.0002506709,0.0008960103,0.0003132845,0.0001050116,0.00002049831,0.00008327452,0.00009862296,0.0001329002],"category_scores_gemma":[0.05212504,0.0002087373,0.0001116187,0.001519621,0.00007427883,0.00008069491,0.0001012155,0.0002697627,0.000002284677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004683291,"about_ca_system_score_gemma":0.0008884686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002688091,"about_ca_topic_score_gemma":0.0001824607,"domain_scores_codex":[0.9958698,0.001139783,0.0008792159,0.0006468138,0.001237408,0.0002270178],"domain_scores_gemma":[0.9952636,0.001396566,0.0004452724,0.0005334697,0.001905778,0.0004553632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007064452,0.002005573,0.9358461,0.0003747187,0.0001824133,0.00005523201,0.006240362,0.0004821406,0.009753336,0.000005162983,0.03763795,0.0003525261],"study_design_scores_gemma":[0.004049037,0.005642842,0.8664485,0.0004186957,0.0003583707,0.000004473047,0.000579212,0.0004846772,0.008413883,0.000004239078,0.1134385,0.0001575192],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8562626,0.0001948019,0.0006431285,0.1389872,0.00009318868,0.00347471,0.0002653955,0.00007584482,0.000003142113],"genre_scores_gemma":[0.9896516,0.0000146028,0.002207363,0.005670445,0.00007385865,0.00104901,0.0002622821,0.00003546129,0.001035438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1333889,"threshold_uncertainty_score":0.9558593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1956045560761398,"score_gpt":0.4121727370824892,"score_spread":0.2165681810063494,"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."}}