{"id":"W4221061940","doi":"10.1136/bmjgh-2021-007822","title":"Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward","year":2022,"lang":"en","type":"review","venue":"BMJ Global Health","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Royal Society; Public Health England; Department of Health and Social Care; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; Government of Canada; UK Research and Innovation; Science and Technology Facilities Council; William and Flora Hewlett Foundation; Sveriges Regering; World Health Organization","keywords":"Refugee; Human settlement; Displaced person; Public health; Pandemic; Forced migration; Political science; Public relations; Environmental planning; Management science; Geography; Infectious disease (medical specialty); Disease; Coronavirus disease 2019 (COVID-19); Medicine; Engineering","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":[0.006039281,0.001218706,0.00255185,0.003398471,0.0003411765,0.003036807,0.002312235,0.002792322,0.003312421],"category_scores_gemma":[0.01940214,0.0006041215,0.002283171,0.003858069,0.001745939,0.004308268,0.001552728,0.003628151,0.001197114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001799651,"about_ca_system_score_gemma":0.005189152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007999414,"about_ca_topic_score_gemma":0.005726841,"domain_scores_codex":[0.9979548,0.001285814,0.0002471014,0.0001417219,0.0003045168,0.00006592091],"domain_scores_gemma":[0.9836495,0.01385595,0.0007444466,0.0003643064,0.001192144,0.0001936223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007479976,0.0001207755,0.001111625,0.05863175,0.0006672224,0.0002683082,0.0006062127,0.01068169,0.000251787,0.1044339,0.04473836,0.7784135],"study_design_scores_gemma":[0.00004799959,0.0001159543,0.001495962,0.06120601,0.0005207781,0.0009854238,0.0007849784,0.004150437,0.0002860696,0.0942341,0.8360565,0.0001157575],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001548386,0.9931045,0.001816978,0.003706641,0.0003440573,0.00000962687,0.00003487301,0.00001498371,0.0008134551],"genre_scores_gemma":[0.002361895,0.994858,0.001785332,0.0003929602,0.0003399169,0.00001992621,0.00004014991,0.000007672017,0.0001942035],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.007999414,"threshold_uncertainty_score":0.03193915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5094023109968765,"score_gpt":0.5429562628990295,"score_spread":0.03355395190215305,"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."}}