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Record W2890223458 · doi:10.1139/facets-2018-0009

Initial indications of polycyclic aromatic hydrocarbon exposure in Saskatchewan common loons

2018· article· en· W2890223458 on OpenAlexaffvenueabout
James D. Paruk, Michael D. Chickering, John N. Mager, Steven C. Wilkie, Richard H. M. Espie

Bibliographic record

VenueFACETS · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of ReginaMinistry of the Environment, Conservation and Parks
Fundersnot available
KeywordsPolycyclic aromatic hydrocarbonFeatherTrophic levelPollutantMercury (programming language)WildlifeEnvironmental scienceEnvironmental chemistryEcologyBiologyChemistry

Abstract

fetched live from OpenAlex

Mercury (Hg) and polycyclic aromatic hydrocarbons (PAHs) are global pollutants known for their toxicity to wildlife. Because of their trophic position, common loons ( Gavia immer (Brünnich 1764)) are excellent indicators of environmental quality. In 2014 and 2015, tissue samples of ten adult common loons (plus one recapture) were obtained in Meadow Lake Provincial Park, Saskatchewan, and assessed for Hg and PAH exposure. Blood and feather levels of these contaminants are indicative of exposure during breeding and in wintering areas, respectively. Compared with an international Hg database, blood Hg levels were low (<1 μg/g). In most loons (90.5%, 10 out of 11), blood PAH concentrations were also low (<10 ng/g), but high (120 ng/g) for one individual (9.5% 1 out of 11). Feather PAH concentrations were high (95.9 ng/g and 250.6 ng/g) in two of the four loons (50%) caught in 2015. These data indicate that loons breeding in Meadow Lake Provincial Park were exposed to low levels of Hg; however, some individuals are being exposed to PAHs in both their breeding and wintering locations. The effect of these environmental pollutants on individual loon fitness is unclear, but because of their extreme toxicity in biological systems we suggest that future monitoring in the surrounding region is warranted.

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)0.000
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 score0.056
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.019
GPT teacher head0.285
Teacher spread0.266 · 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

Citations1
Published2018
Admission routes3
Has abstractyes

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