{"id":"W4412580484","doi":"10.2196/79713","title":"Cross-Silo Federated Learning for Predicting Successful Mechanical Ventilation Weaning: A Study Across Five ICU Databases (Preprint)","year":2025,"lang":"en","type":"preprint","venue":"JMIR Medical Informatics","topic":"Respiratory Support and Mechanisms","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Silo; Information silo; Mechanical ventilation; Weaning; Database; Computer science; Medicine; Engineering; World Wide Web; Anesthesia; Mechanical engineering; 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":[],"consensus_categories":[],"category_scores_codex":[0.01655723,0.0006405056,0.0009398024,0.001495334,0.0004892775,0.001455439,0.001479891,0.0008992438,0.0004599059],"category_scores_gemma":[0.02385084,0.0002587649,0.001449721,0.001591874,0.0005518019,0.001635203,0.001279691,0.000834341,0.0001758378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001162321,"about_ca_system_score_gemma":0.001138583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009009992,"about_ca_topic_score_gemma":0.004791734,"domain_scores_codex":[0.9924201,0.003563905,0.001023582,0.001784972,0.0008863683,0.0003210636],"domain_scores_gemma":[0.9787567,0.01256444,0.001788348,0.00323255,0.00291722,0.0007407655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005099665,0.004304021,0.7788367,0.0009290804,0.002783444,0.0005816654,0.0005936592,0.05444855,0.001692508,0.0008443965,0.005883774,0.1440026],"study_design_scores_gemma":[0.0008561471,0.006086253,0.4291829,0.0003904781,0.002254301,0.001319253,0.002283142,0.5428275,0.007902225,0.00162866,0.00512372,0.0001454535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919198,0.001096388,0.004844212,0.0002507025,0.00004688424,0.0001354929,0.001305998,0.0001387482,0.0002618367],"genre_scores_gemma":[0.9892454,0.0002746824,0.005931601,0.0001098003,0.00004429848,0.00009752514,0.004163909,0.00001368439,0.0001190856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01655723,"threshold_uncertainty_score":0.08756405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04481235708421125,"score_gpt":0.3991641830525706,"score_spread":0.3543518259683593,"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."}}