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Record W4210764491 · doi:10.1080/09603123.2022.2031912

Self-reported symptoms of ocular allergy and its comorbid factors among residents living near a landfill site in Ghana

2022· article· en· W4210764491 on OpenAlexaff
Prince Peprah, Michael Agyemang Kwarteng, Kofi Asiedu, Williams Agyemang‐Duah, Anthony Kwame Morgan, Akwasi Adjei Gyimah

Bibliographic record

VenueInternational Journal of Environmental Health Research · 2022
Typearticle
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineAllergyEnvironmental healthMultivariate analysisInternal medicineImmunology

Abstract

fetched live from OpenAlex

Residents close to landfill sites may be exposed to long-term emitted toxic compounds that may have effects on their eyes. The aim of this study was to determine the prevalence of symptomatic ocular allergy and its comorbid factors among residents living near a landfill site in Ghana. An exploratory cross-sectional design involving 400 inhabitants living around a landfill site was employed. The prevalence of symptomatic ocular allergy was 59.3%. In a bivariate analysis, comorbid conditions including respiratory disease, coughing, flu, cholera, skin disease, diarrhoea, and hypertension predicted symptomatic ocular allergy. However, only cholera remained a significant predictor of symptomatic ocular allergy in the multivariate analysis. Symptomatic ocular allergy was high among inhabitants around the landfill site in Ghana. While proper design and management of landfills in Ghana is crucial, further longitudinal and clinical studies are required to clinically establish the link between landfill and ocular allergy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.357
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2022
Admission routes1
Has abstractyes

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