{"id":"W4400098873","doi":"10.1038/s41746-024-01166-w","title":"A multi-center study on the adaptability of a shared foundation model for electronic health records","year":2024,"lang":"en","type":"article","venue":"npj Digital Medicine","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Adaptability; Computer science; Modular design; Artificial intelligence; Machine learning; Foundation (evidence); Robustness (evolution); Scalability; Medical record; Usability; Task (project management); Medicine; Human–computer interaction; Engineering; Database","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":[0.01026941,0.0006162117,0.0004710266,0.0004725289,0.0005804169,0.0008623304,0.001344837,0.0007399741,0.001184677],"category_scores_gemma":[0.02823594,0.0003602149,0.000911596,0.0004501883,0.0006056859,0.001723379,0.001484899,0.001677302,0.0004133675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00103929,"about_ca_system_score_gemma":0.00067401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005992304,"about_ca_topic_score_gemma":0.006587622,"domain_scores_codex":[0.9966408,0.001889115,0.0001962544,0.0008413872,0.0002742559,0.0001582707],"domain_scores_gemma":[0.9784821,0.01168949,0.001352377,0.004973174,0.0023845,0.001118364],"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":[0.004949589,0.005333163,0.5471893,0.0002722941,0.001102814,0.0006161535,0.002740862,0.1990003,0.01309592,0.001002073,0.006643554,0.218054],"study_design_scores_gemma":[0.0003797795,0.006059132,0.2686901,0.00007218728,0.0004850829,0.0005360529,0.002006317,0.6986458,0.0167991,0.002142121,0.004037538,0.0001468256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948097,0.00006459085,0.004313787,0.0001779977,0.00002307059,0.00006448585,0.0001578194,0.0001057728,0.0002827529],"genre_scores_gemma":[0.9951503,0.00002774777,0.003707957,0.00009587018,0.00002528122,0.00005965257,0.0006290051,0.00002869516,0.0002756038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01026941,"threshold_uncertainty_score":0.0543105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09029825835760427,"score_gpt":0.3822316847891663,"score_spread":0.2919334264315621,"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."}}