{"id":"W2053334023","doi":"10.1016/j.nepr.2010.02.003","title":"Using the Situated Clinical Decision-Making framework to guide analysis of nurses’ clinical decision-making","year":2010,"lang":"en","type":"article","venue":"Nurse Education in Practice","topic":"Simulation-Based Education in Healthcare","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Situated; Clinical decision making; Medical decision making; Medicine; Psychology; Management science; Intensive care medicine; Family medicine; Computer science; Engineering; Artificial intelligence","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007096814,0.0002785857,0.0008480121,0.001211717,0.0002707771,0.00009287991,0.0004954768,0.0006164458,0.001102673],"category_scores_gemma":[0.1431549,0.0002386733,0.0003905975,0.004928871,0.0002258855,0.000439945,0.00005826995,0.002056335,0.00009703303],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003937856,"about_ca_system_score_gemma":0.006075202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003514027,"about_ca_topic_score_gemma":0.0002009529,"domain_scores_codex":[0.9934098,0.0009746493,0.003329926,0.0008505603,0.001022598,0.0004124516],"domain_scores_gemma":[0.8879979,0.1018674,0.002228324,0.002870688,0.004507785,0.0005279554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009048159,0.001755221,0.8084041,0.0000155007,0.0003241286,0.000004439397,0.00387452,0.004096343,0.0000168444,0.001643863,0.003605338,0.1753549],"study_design_scores_gemma":[0.0005373396,0.0001542626,0.927165,0.001548476,0.002896003,0.00004959316,0.03235681,0.02014692,0.000007465359,0.00258393,0.01225227,0.0003019616],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9454736,0.0001309778,0.02656243,0.008580692,0.01636898,0.001162412,0.000008129898,0.00005950465,0.001653263],"genre_scores_gemma":[0.7108909,0.00001990731,0.2816382,0.006027483,0.001273508,0.00004275293,0.0000160673,0.00003979672,0.00005135651],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2550757,"threshold_uncertainty_score":0.9998105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07343266855051508,"score_gpt":0.5861288208021831,"score_spread":0.512696152251668,"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."}}