{"id":"W4385256550","doi":"10.20944/preprints202307.1701.v1","title":"Health Diplomacy as a Tool to build resilient health systems in Conflict Settings – A Case of Sudan","year":2023,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Health and Conflict Studies","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Diplomacy; Health care; Harmony (color); Political science; International Health Regulations; Health policy; International health; Politics; Global health; Sustainable development; Leverage (statistics); Economic growth; Business; Public relations; Development economics; Medicine; Economics; Law; Coronavirus disease 2019 (COVID-19)","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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008948322,0.0008365192,0.00295173,0.001007723,0.001108819,0.0000168351,0.000914635,0.0007263727,0.0001764412],"category_scores_gemma":[0.003247615,0.0008601219,0.0002932542,0.0009251211,0.0001256479,0.00007721734,0.00506296,0.00377585,0.00330429],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00222322,"about_ca_system_score_gemma":0.007822822,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2157657,"about_ca_topic_score_gemma":0.005254787,"domain_scores_codex":[0.9866748,0.002706115,0.004887389,0.002192041,0.0008758877,0.002663701],"domain_scores_gemma":[0.9914812,0.00121599,0.00254247,0.002759184,0.0006058373,0.001395351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006861779,0.0005359771,0.6711195,0.04540295,0.0003166992,0.0007723379,0.2588679,0.0009994186,0.0001016159,0.004006288,0.01530539,0.001885751],"study_design_scores_gemma":[0.002641846,0.0004817073,0.451969,0.02039117,0.00004064633,0.0001234926,0.0263017,0.000230443,0.00005419563,0.0004149741,0.4960584,0.001292395],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.898223,0.001834456,0.00004996553,0.08108236,0.002460124,0.01265061,0.0005212564,0.0005993182,0.002578863],"genre_scores_gemma":[0.9632523,0.001980206,0.0001401929,0.02190631,0.0005670567,0.005682098,0.0001087873,0.0002134417,0.006149614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.480753,"threshold_uncertainty_score":0.9993849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2625929700323125,"score_gpt":0.52328624463689,"score_spread":0.2606932746045775,"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."}}