{"id":"W2092231391","doi":"10.1108/09513550010338755","title":"Facts, myths and monsters: understanding the principles of good governance","year":2000,"lang":"en","type":"article","venue":"International Journal of Public Sector Management","topic":"Healthcare Quality and Management","field":"Health Professions","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Corporate governance; Restructuring; Excellence; Project governance; Monster; Business; Public relations; Health care; Public sector; Function (biology); Public administration; Political science; Law; Finance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002087554,0.0001088112,0.0001932533,0.0001443571,0.0001840111,0.00004694824,0.0005495552,0.00005057154,0.001429271],"category_scores_gemma":[0.00009665281,0.00007621351,0.00007814535,0.0001309163,0.00007966306,0.0003239987,0.0001754044,0.0003070527,0.00001651127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000511446,"about_ca_system_score_gemma":0.00009953867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000091396,"about_ca_topic_score_gemma":0.0001152969,"domain_scores_codex":[0.9975457,0.0003975251,0.0008505006,0.0001336769,0.0008160161,0.0002565972],"domain_scores_gemma":[0.998494,0.0003093805,0.0006909038,0.0001797326,0.0002220227,0.0001039156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001345068,0.0001633046,0.009480338,0.0003410733,0.0009852212,0.00005541596,0.005163416,0.00009763019,0.00001407355,0.8845176,0.005339476,0.09370799],"study_design_scores_gemma":[0.001917681,0.000146901,0.08935513,0.000746223,0.00006164739,0.00001763178,0.03661126,0.0002187832,0.000009376469,0.005555025,0.8651987,0.0001615823],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4650683,0.001499519,0.02642212,0.139495,0.004841979,0.001597689,0.00008264825,0.00006114459,0.3609317],"genre_scores_gemma":[0.9914609,0.001884765,0.0004002203,0.001929731,0.0002958846,0.00001120874,0.000002718137,0.00001121055,0.004003376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8789625,"threshold_uncertainty_score":0.9994836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2369769560245352,"score_gpt":0.4205139158342987,"score_spread":0.1835369598097635,"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."}}