{"id":"W2625420570","doi":"10.1093/ije/dyx076","title":"Health and Demographic Surveillance System (HDSS) in Matlab, Bangladesh","year":2017,"lang":"en","type":"article","venue":"International Journal of Epidemiology","topic":"Immune responses and vaccinations","field":"Immunology and Microbiology","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Global Affairs Canada; Department for International Development; Department for International Development, UK Government; Golfers Against Cancer; Styrelsen för Internationellt Utvecklingssamarbete","keywords":"Medicine; Public health; Child mortality; Cholera; Environmental health; Population; Psychological intervention; Fertility; Epidemiology; Government (linguistics); Pediatrics; 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":[0.001164836,0.0005833285,0.0004558459,0.001542881,0.0004280207,0.0005879502,0.0005947825,0.0002366287,0.01199708],"category_scores_gemma":[0.002258545,0.000336741,0.0001714373,0.002568786,0.00029968,0.0003763326,0.0007355448,0.0004316967,0.004678644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002086308,"about_ca_system_score_gemma":0.004629615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07536185,"about_ca_topic_score_gemma":0.05725344,"domain_scores_codex":[0.9992852,0.0002238648,0.0001492634,0.0001320574,0.0001456434,0.00006397191],"domain_scores_gemma":[0.9976756,0.0003450839,0.0005094039,0.0002555052,0.0009970549,0.0002173837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001465247,0.0002014714,0.5494224,0.001655702,0.0002209519,0.0006711232,0.001652109,0.003213122,0.006361512,0.005588828,0.2208181,0.2087295],"study_design_scores_gemma":[0.00031071,0.0004897699,0.6507131,0.000382125,0.0001285133,0.0006982838,0.001465299,0.004114063,0.00503966,0.001043763,0.3355049,0.0001098149],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1138359,0.001047496,0.008244131,0.001409438,0.0001352249,0.003176694,0.8071614,0.001739877,0.06324985],"genre_scores_gemma":[0.4873911,0.002522528,0.03430085,0.0007620106,0.00008646874,0.008225447,0.411137,0.000187034,0.05538763],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07536185,"threshold_uncertainty_score":0.1498464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03337465719337206,"score_gpt":0.3486325544536673,"score_spread":0.3152578972602952,"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."}}