{"id":"W3166867317","doi":"10.1097/01.ccn.0000503421.75099.56","title":"Deciding if and when to retire","year":2016,"lang":"en","type":"article","venue":"Nursing Critical Care","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Smiths Detection (Canada)","funders":"","keywords":"Computer science; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004215458,0.0005784803,0.0007112517,0.0009402668,0.004088233,0.003532215,0.001049133,0.009194792,0.02085348],"category_scores_gemma":[0.03088054,0.0005361016,0.0005707146,0.000420147,0.001256938,0.004799502,0.001720767,0.01401646,0.008261051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002528819,"about_ca_system_score_gemma":0.005907582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005999243,"about_ca_topic_score_gemma":0.02762016,"domain_scores_codex":[0.9982634,0.0006736745,0.0002652036,0.000158089,0.0002997451,0.0003397715],"domain_scores_gemma":[0.9864931,0.005571299,0.0009426265,0.0001799969,0.002658997,0.004153945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000383932,0.00003393029,0.0009775969,0.0001082077,0.000007398559,0.0001159879,0.0002614351,0.00002434356,0.0001072809,0.0004967405,0.9652761,0.03255259],"study_design_scores_gemma":[0.00006976695,0.0002860999,0.009858959,0.002005729,0.00007856013,0.001254284,0.00834305,0.0002439688,0.0004715116,0.009072716,0.9681567,0.0001586657],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.001726306,0.00819599,0.0005242311,0.9188639,0.06382453,0.00007184277,0.0002098103,0.00009158952,0.006491831],"genre_scores_gemma":[0.03382437,0.03379861,0.002247109,0.8123925,0.0811541,0.0002618226,0.0005741251,0.0000645767,0.03568282],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02085348,"threshold_uncertainty_score":0.06976187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2210172885956405,"score_gpt":0.486413440609015,"score_spread":0.2653961520133744,"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."}}