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Record W2795916466 · doi:10.20381/ruor-18580

Persistent organic pollutants in white-tailed deer ( Odocoileus virginianus) near a magnesium smelter: Spatial distribution and human health risk assessment

2006· dissertation· en· W2795916466 on OpenAlexaboutno aff
Cecilia Tolley

Bibliographic record

VenueuO Research (University of Ottawa) · 2006
Typedissertation
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOdocoileusSmeltingPollutantHuman healthSpatial distributionWhite (mutation)Environmental scienceGeographyEnvironmental healthEcologyBiologyMedicineMetallurgyMaterials science

Abstract

fetched live from OpenAlex

A magnesium refining facility in Quebec was a known point source of persistent organic pollutants namely polychlorinated biphenyls, dioxins and furans, and hexachlorobenzene. Contaminants concentrations were measured in the fat tissue of local white-tailed deer with the assistance of the local community and hunters. Concentrations in the deer from 1999, one year before the smelter opened, were compared with deer from 2002. Results showed a significant increase in PCBs from 1999 to 2002, and total PCB concentrations showed significant decreases with distance from the smelter. Many of the mid-range PCB homologues that bioconcentrate sharply in deer showed similar relationships. Sigmacoplanar PCBs and Cytochrome P450 1A expression in liver also showed a significant inverse relationship with distance in 2002. Results of a human health risk assessment indicated that the number of deer meal portions required to exceed safe consumption levels for PCDD/Fs and coplanar PCBs increased with the distance from the smelter.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.855
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

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

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 head0.044
GPT teacher head0.362
Teacher spread0.318 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

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