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Record W4391502606 · doi:10.5962/p.353872

Heavy metal concentrations in Arctic Foxes, Alopex lagopus, in the Prudhoe Bay Oil Field, Alaska

2003· article· en· W4391502606 on OpenAlexvenueaboutno aff
Warren B. Ballard, Matthew A. Cronin, Martin D. Robards, William A. Stubblefield

Bibliographic record

VenueThe Canadian Field-Naturalist · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
FundersTexas Tech University
KeywordsLagopusBayArcticBeaufort seaOil fieldThe arcticOceanographyEnvironmental scienceGeographyBiologyGeology

Abstract

fetched live from OpenAlex

Heavy metal concentrations in Arctic Foxes, Alopex lagopus, in the Prudhoe Bay Oil Field, Alaska.Canadian Field-Naturalist 117(1): 119-121.Liver and kidney tissue samples from 30 Arctic Foxes (Alopex lagopus) collected in the Prudhoe Bay Oil field in Alaska during 1994 were analyzed for barium, cadmium, chromium, mercury, nickel, selenium, and vanadium.Mean concentrations for all metais were higher in kidney than liver tissues.Mean liver concentrations (ug/g dry weight) for females and male foxes, respectively, were 0.12 and 0.09 for barium, 0.48 and 0.57 for cadmium, 1.03 and 1.04 for chromium, 1.10 and 0.54 for mercury, 0.17 and undetectable for nickel, 3.00 and 2.69 for selenium, and 0.05 and 0.06 for vanadium.Heavy metal concentrations in Arctic Fox liver and kidney tissues were low compared to non-industrial areas in Canada and the Norwegian Arctic.Arctic foxes in the Prudhoe Bay oil field have relatively low concentrations of heavy metals, although most (25 of 30) of the foxes analyzed were juveniles and concentrations may differ in adults.

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 score0.183
Threshold uncertainty score0.363

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 studies0.0010.000
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 head0.018
GPT teacher head0.247
Teacher spread0.229 · 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

Citations5
Published2003
Admission routes2
Has abstractyes

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