{"id":"W4281909836","doi":"10.1016/j.socscimed.2022.115116","title":"Data flows during public health emergencies in LMICs: A people-centered mapping of data flows during the 2018 ebola epidemic in Equateur, DRC","year":2022,"lang":"en","type":"article","venue":"Social Science & Medicine","topic":"Viral Infections and Outbreaks Research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Disease surveillance; Contact tracing; Context (archaeology); Outbreak; Public health; Preparedness; Medicine; Ebola virus; Environmental health; Medical emergency; Infectious disease (medical specialty); Geography; Disease; Political science; Virology; Nursing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00114603,0.0001914395,0.0001666542,0.002476193,0.0008904066,0.001670133,0.0004688442,0.0006612902,0.002061785],"category_scores_gemma":[0.005580518,0.0001470499,0.0002616629,0.004371597,0.0004486012,0.001711428,0.002403121,0.0005441643,0.0003983889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001931779,"about_ca_system_score_gemma":0.002590466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1019606,"about_ca_topic_score_gemma":0.09481836,"domain_scores_codex":[0.9991767,0.0002743335,0.00007492148,0.000151497,0.0001216094,0.0002009145],"domain_scores_gemma":[0.9975712,0.0006313512,0.0006209011,0.0001182099,0.0007464236,0.0003119252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002655698,0.0001406169,0.924121,0.0003083512,0.0001291438,0.0006302326,0.02212852,0.002142822,0.001782128,0.003239503,0.009353053,0.03575916],"study_design_scores_gemma":[0.00001371146,0.00006654519,0.92191,0.0002865843,0.00004155706,0.0002661985,0.04196825,0.009515396,0.0009485814,0.0009697113,0.02396524,0.0000480971],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9794381,0.0002252409,0.001685534,0.002128425,0.00002706801,0.0001735975,0.01304202,0.00007180825,0.003208263],"genre_scores_gemma":[0.9875872,0.0002578549,0.003337395,0.0003597639,0.00002446991,0.0002734674,0.00675733,0.00002794571,0.001374575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1019606,"threshold_uncertainty_score":0.2027344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2350540173232593,"score_gpt":0.4185285652210106,"score_spread":0.1834745478977514,"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."}}