MétaCan
Menu
Back to cohort
Record W4401726307 · doi:10.1080/15569543.2024.2393193

Contamination levels of water sources and the associated nitrate health risks to six age groups

2024· article· en· W4401726307 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueToxin Reviews · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsContaminationNitrateWater contaminationEnvironmental healthEnvironmental chemistryWater qualityEnvironmental scienceWaterborne diseasesChemistryBiologyMedicineEcology

Abstract

fetched live from OpenAlex

Advancements in health risk assessment are vital for protecting public health. This study’s objectives were to analyze the degree of nitrate contamination, the multi-route health risks to six age groups, and the potential sources of water contaminants in a Nigerian suburban area. Nitrate pollution index (NPI) results were between −1.00 and 0.06, indicating low human impact. According to the nitrate health risk analysis, infants between the ages of 6 and 12 months were more vulnerable, whereas humans between the ages of 20 and > 60 have lower risks. This may be due to the fact that infants have bodily tissues that are more vulnerable to potentially toxic contaminants. For all six age categories, the risk associated with ingestion was greater than the risk associated with dermal contact. Varimax-rotated factor analysis with five principal component extractions revealed that the sources of the water contaminants varied from geogenic processes to human-initiated activities.

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.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.896
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.285
Teacher spread0.231 · 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