{"id":"W4312075446","doi":"10.1136/bmjopen-2022-064137","title":"Anti-corruption in global health systems: using key informant interviews to explore anti-corruption, accountability and transparency in international health organisations","year":2022,"lang":"en","type":"article","venue":"BMJ Open","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; Connaught Fund","keywords":"Transparency (behavior); Accountability; Language change; Thematic analysis; Snowball sampling; Public relations; Political science; Strengths and weaknesses; Medicine; Public administration; Qualitative research; Sociology; Psychology; Law; Social science; Social psychology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005466391,0.0001273025,0.0003858902,0.0002113701,0.0005445745,0.0002868444,0.0005303101,0.00003860522,0.0005589622],"category_scores_gemma":[0.0000696144,0.0001482372,0.00002914957,0.0005960228,0.0000396241,0.0007875545,0.0004479801,0.0001480683,0.00002548502],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004627602,"about_ca_system_score_gemma":0.002070454,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07504362,"about_ca_topic_score_gemma":0.06710932,"domain_scores_codex":[0.9974283,0.0004730358,0.001036978,0.0003571793,0.0003507479,0.0003537366],"domain_scores_gemma":[0.9992439,0.00002388512,0.0003087017,0.0001911239,0.00005423106,0.0001781583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007605055,0.0002592848,0.659681,0.00009880211,0.00001135239,0.00000233416,0.2789537,0.005394372,0.00000483653,0.00255676,0.0004782609,0.05248325],"study_design_scores_gemma":[0.001190246,0.00009114468,0.6914194,0.0002963314,0.000002376408,0.0000176574,0.221734,0.003964581,2.873769e-7,0.0001592218,0.08078662,0.0003381527],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778309,0.00006433904,0.001020484,0.01224923,0.001567841,0.005426643,0.00008871799,0.00003243322,0.001719343],"genre_scores_gemma":[0.9967954,0.0001637458,0.0004667853,0.001764012,0.0000589281,0.0005843415,0.00007531911,0.000007839731,0.00008367062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08030836,"threshold_uncertainty_score":0.9991934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2481665327909096,"score_gpt":0.479835231483428,"score_spread":0.2316686986925185,"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."}}