{"id":"W4405603534","doi":"10.2196/57899","title":"Expectations and Requirements of Surgical Staff for an AI-Supported Clinical Decision Support System for Older Patients: Qualitative Study","year":2024,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bundesministerium für Bildung und Forschung","keywords":"Thematic analysis; Qualitative research; Geriatric care; Nursing; Medicine; Narrative; Psychology; Clinical decision support system; Medical education; Decision support system; Computer science; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.001057303,0.00009678285,0.0002758135,0.0001404902,0.0001010247,0.00003045255,0.00004137242,0.00006636373,0.00002098234],"category_scores_gemma":[0.0001855143,0.00008110768,0.00008296831,0.0001477391,0.0000423861,0.000198278,0.00001457106,0.00009006233,0.000004088968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007631794,"about_ca_system_score_gemma":0.0001789573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004152088,"about_ca_topic_score_gemma":0.00002089409,"domain_scores_codex":[0.9982719,0.0001110536,0.0008851335,0.0003360114,0.0002178365,0.0001780314],"domain_scores_gemma":[0.9979835,0.001113657,0.0001065777,0.0001625909,0.0004998875,0.0001338228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.001465055,0.004296003,0.09021673,0.00258031,0.0002521967,0.00001660831,0.4898776,0.000001732491,0.0000524292,0.001312123,0.008628317,0.4013009],"study_design_scores_gemma":[0.00135867,0.008363191,0.009596213,0.001158895,0.0002662389,0.000007895528,0.9706798,0.00511296,0.0006857563,0.0009193364,0.001634038,0.0002170086],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883364,0.00005749058,0.007453613,0.0003047465,0.0007021803,0.003000406,0.00003961329,0.00005771024,0.00004779747],"genre_scores_gemma":[0.9978839,0.000004270369,0.0009932554,0.00003194529,0.0002270068,0.0005781049,0.0001837925,0.00002111995,0.00007659312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4808022,"threshold_uncertainty_score":0.3307475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2787419398983305,"score_gpt":0.5939619077941287,"score_spread":0.3152199678957983,"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."}}