{"id":"W4408127938","doi":"10.2196/71098","title":"Authors’ Response to Peer Reviews of “Predicting Escalation of Care for Childhood Pneumonia Using Machine Learning: Retrospective Analysis and Model Development”","year":2025,"lang":"en","type":"article","venue":"JMIRx Med","topic":"Pneumonia and Respiratory Infections","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Pneumonia; Medicine; Computer science; Internal medicine","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02821325,0.001138233,0.002834919,0.002401725,0.004022792,0.006316744,0.002850987,0.01419786,0.04783905],"category_scores_gemma":[0.3512523,0.001203071,0.002790458,0.001788704,0.002238924,0.002216926,0.003593662,0.01401111,0.03445721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004136156,"about_ca_system_score_gemma":0.01264482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007699982,"about_ca_topic_score_gemma":0.01251517,"domain_scores_codex":[0.9630529,0.009231563,0.007245819,0.002449104,0.01596803,0.002052625],"domain_scores_gemma":[0.6447697,0.06906196,0.01542461,0.009130957,0.252701,0.008911811],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007180864,0.00001112841,0.0003264733,0.0001701864,0.00002886511,0.00008887664,0.00004321075,0.0000396624,0.00006473502,0.0001560644,0.9952631,0.00373594],"study_design_scores_gemma":[0.0001335628,0.00004044697,0.002070054,0.0008424367,0.00007915826,0.0003133589,0.0003969463,0.0007492623,0.0004574188,0.0009075504,0.9939291,0.00008064903],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0004881197,0.001444022,0.0008916434,0.5362261,0.4566146,0.000160097,0.001484825,0.0003011022,0.002389534],"genre_scores_gemma":[0.01169884,0.003663368,0.00338564,0.6049342,0.3256698,0.0008805831,0.00209288,0.0006826276,0.0469921],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9717867,"threshold_uncertainty_score":0.1600376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02038921620244906,"score_gpt":0.3363499094185438,"score_spread":0.3159606932160947,"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."}}