{"id":"W4408415869","doi":"10.2196/63216","title":"Large Language Model–Based Critical Care Big Data Deployment and Extraction: Descriptive Analysis","year":2025,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Software deployment; SQL; Database; User interface; Data extraction; Cloud computing; Interface (matter); Software engineering; Operating system; MEDLINE","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":[0.004748076,0.0009868479,0.0003945025,0.001786909,0.0007177445,0.002831963,0.001935281,0.000460713,0.003374101],"category_scores_gemma":[0.01859795,0.0007600424,0.001400674,0.001305398,0.0009150046,0.003646018,0.002830176,0.001606536,0.001655028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001741033,"about_ca_system_score_gemma":0.004173164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007218473,"about_ca_topic_score_gemma":0.0114195,"domain_scores_codex":[0.9968337,0.0009957342,0.0003540771,0.0006587986,0.0009974941,0.0001601003],"domain_scores_gemma":[0.9902366,0.004925595,0.0006549927,0.002148549,0.001710579,0.0003235927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001784318,0.00110511,0.07189864,0.001822142,0.0004383355,0.002701997,0.006183624,0.1267177,0.04411836,0.1019555,0.1376344,0.5036398],"study_design_scores_gemma":[0.0001824567,0.0002369649,0.007561311,0.0002795494,0.0001107056,0.0007123915,0.001276271,0.8009065,0.06020905,0.05636954,0.07198204,0.0001731716],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07635018,0.0003463088,0.8453146,0.002404043,0.0001399554,0.0009381323,0.008630742,0.05943298,0.006443128],"genre_scores_gemma":[0.2741268,0.0003231066,0.6958773,0.0007199349,0.00005642726,0.000883176,0.02070787,0.004642155,0.002663265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007218473,"threshold_uncertainty_score":0.02511054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1502516311148447,"score_gpt":0.4542273811311704,"score_spread":0.3039757500163257,"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."}}