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Record W2779541338 · doi:10.1139/as-2017-0020

Cortisol levels in beluga whales (Delphinapterus leucas): Setting a benchmark for Marine Protected Area monitoring

2017· article· en· W2779541338 on OpenAlexafffundvenue
Lisa L. Loseto, Kerri Pleskach, Carie Hoover, Gregg T. Tomy, Jean‐Pierre Desforges, Thor Halldorson, Peter S. Ross

Bibliographic record

VenueArctic Science · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of ManitobaVancouver AquariumGovernment of CanadaFisheries and Oceans Canada
FundersFisheries and Oceans CanadaFisheries Joint Management Committee
KeywordsLeucasBeluga WhaleBelugaFisheryGeographyOceanographyEnvironmental scienceBiologyGeology

Abstract

fetched live from OpenAlex

Beluga whales (Delphinapterus leucas) are facing profound changes in their habitat, with impacts expected at the individual and population level. Detecting and monitoring exposure and response to environmental stressors is necessary for beluga conservation and management of human activities. Cortisol has proven as a useful tool to assess stress on wildlife. Cortisol was measured in three blubber layers and plasma in subsistence-hunted beluga whales from the summers of 2007 to 2010 using an HPLC/MS/MS. We assessed the effect of biological and biochemical factors. Cortisol ranged from undetectable to 17.8 ng/g in blubber and 2.5 to 61.2 ng/mL in plasma. Concentrations were highest in the inner blubber layer likely reflecting circulating levels. All tissues were significantly higher in 2008 for reasons that remain unclear. Cortisol levels were on par with resting levels in captive belugas. Best fit models for cortisol revealed age to be an important determinant along with length and blubber thickness. Lack of relationships with biochemical factors such as organic contaminants suggests current cortisol levels are not significantly influenced by present contaminant concentrations. Our findings support the use of middle and outer blubber tissues for an integrated measure of chronic stress that are less subject to the influence of acute stress.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.002
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 head0.058
GPT teacher head0.309
Teacher spread0.251 · 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.

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

Citations4
Published2017
Admission routes3
Has abstractyes

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