{"id":"W4399836078","doi":"10.2196/55321","title":"Perspectives on Artificial Intelligence in Nursing in Asia","year":2024,"lang":"en","type":"article","venue":"Asian/Pacific Island Nursing Journal","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transformative learning; Health care; China; Perspective (graphical); Interpretation (philosophy); Computer science; Psychology; Artificial intelligence; Knowledge management; Nursing; Data science; Medicine; Political science; Pedagogy","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":[0.0008136324,0.0002145646,0.0003108665,0.001158339,0.0001716385,0.0002194383,0.0001059466,0.0001898769,0.0002393082],"category_scores_gemma":[0.0002058332,0.0001900268,0.0001225931,0.0009727242,0.0001973626,0.0002405432,0.000003836638,0.001387752,0.0001621072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001472681,"about_ca_system_score_gemma":0.000530964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000307148,"about_ca_topic_score_gemma":0.00004179412,"domain_scores_codex":[0.997763,0.0001412873,0.0007420314,0.0004189103,0.0003735401,0.0005611688],"domain_scores_gemma":[0.9992768,0.0001568811,0.00007625866,0.0001986945,0.0001027672,0.0001886558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004700394,0.0006950659,0.001423991,0.00003990819,0.00001204925,0.0004134059,0.1025206,0.00007427199,0.0003276654,0.012629,0.001391539,0.8800025],"study_design_scores_gemma":[0.000147522,0.001845621,0.01340697,0.03096276,0.00009297604,0.003892347,0.6834628,0.0178997,0.006696395,0.2397185,0.001197943,0.0006764453],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7478631,0.009073246,0.01420122,0.08293788,0.008853531,0.0008490814,0.000006745152,0.0001552832,0.1360599],"genre_scores_gemma":[0.9971042,0.0004456971,0.0006346125,0.00004338368,0.00149979,0.000007636223,0.000005841183,0.00003455194,0.0002242951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.879326,"threshold_uncertainty_score":0.7749067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0701916850010137,"score_gpt":0.4250265135627872,"score_spread":0.3548348285617735,"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."}}