{"id":"W4281385920","doi":"10.1371/journal.pone.0268093","title":"Seroprevalence of SARS-CoV-2 infection and associated factors among Bangladeshi slum and non-slum dwellers in pre-COVID-19 vaccination era: October 2020 to February 2021","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Foreign, Commonwealth and Development Office; International Centre for Diarrhoeal Disease Research, Bangladesh; Global Affairs Canada; United Nations Population Fund","keywords":"Slum; Seroprevalence; Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Vaccination; Virology; Medicine; Geography; Environmental health; Outbreak; Immunology; Antibody; Serology; Population; Infectious disease (medical specialty)","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":[0.0002538822,0.0002532042,0.0001561933,0.0004675673,0.0003388579,0.0003920733,0.0001790959,0.0002632637,0.001656728],"category_scores_gemma":[0.0005840862,0.0002283338,0.0001621101,0.0005438065,0.0002693122,0.000366537,0.0003416277,0.0002747736,0.0003734811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004386528,"about_ca_system_score_gemma":0.0002638071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01518878,"about_ca_topic_score_gemma":0.02665182,"domain_scores_codex":[0.9998616,0.00002852074,0.00001953738,0.00002977641,0.00002496116,0.00003559313],"domain_scores_gemma":[0.999592,0.00003784425,0.00017712,0.000012742,0.00006012483,0.0001202019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002994264,0.00001625439,0.9991854,0.000006103072,0.000005131711,0.00005264161,0.0001619451,0.000009948033,0.0001595987,0.000004575072,0.00007334076,0.0002951078],"study_design_scores_gemma":[0.000001825084,0.00005538271,0.9990885,0.000005012023,0.000002545159,0.00009669396,0.0006066718,0.00002601716,0.00002089774,0.000003932073,0.00009076507,0.000001738267],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991645,0.00005756402,0.00001012321,0.00002971396,0.000002185389,0.000005107143,0.0004058683,0.000001174926,0.0003238018],"genre_scores_gemma":[0.9991651,0.00007796181,0.00002079702,0.00002440867,0.000002835088,0.000009892411,0.0004122233,5.053776e-7,0.0002863943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01518878,"threshold_uncertainty_score":0.03020078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1599261079521531,"score_gpt":0.3590726136394196,"score_spread":0.1991465056872666,"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."}}