{"id":"W4389913144","doi":"10.1136/ebnurs-2023-103783","title":"Engaging nurses in developing generative artificial intelligence-based technologies can enhance their work motivation, engagement and satisfaction","year":2023,"lang":"en","type":"article","venue":"Evidence-Based Nursing","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Health Services; Mount Royal University","funders":"","keywords":"Generative grammar; Work (physics); Work engagement; Psychology; Knowledge management; Job satisfaction; Computer science; Applied psychology; Engineering; Artificial intelligence; Social psychology; Mechanical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001343591,0.0002460313,0.0002959966,0.000812342,0.0004935469,0.00009296487,0.00009629808,0.0001640568,0.00002063736],"category_scores_gemma":[0.002526625,0.000233995,0.00005010327,0.002097468,0.0002695169,0.0002726935,0.00001805754,0.0004983757,0.00001860759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009036253,"about_ca_system_score_gemma":0.0007585618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003586691,"about_ca_topic_score_gemma":0.0002404464,"domain_scores_codex":[0.997689,0.0003250179,0.0006516844,0.0005369954,0.0003114007,0.0004859109],"domain_scores_gemma":[0.9976096,0.001620675,0.0001719799,0.0002786335,0.000241013,0.00007807735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001379212,0.00005272577,0.1212654,0.0001203719,0.000008905268,0.000009239448,0.007666386,0.003046504,0.003682611,0.0005305776,0.0001201029,0.8633593],"study_design_scores_gemma":[0.0000552184,0.0002926179,0.1104585,0.01338622,0.00003876862,0.000003923848,0.05381081,0.01711486,0.7911628,0.01308239,0.0001355085,0.0004583846],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8872103,0.0007781325,0.04386833,0.06581037,0.001081254,0.0008071888,0.000002304795,0.0004255123,0.00001658837],"genre_scores_gemma":[0.993883,0.0003521566,0.004745266,0.0005683035,0.0002052486,0.0001687496,0.00003073322,0.000027332,0.00001922532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8629009,"threshold_uncertainty_score":0.9542038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2894587343944577,"score_gpt":0.4336333897904117,"score_spread":0.144174655395954,"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."}}