MétaCan
Menu
Back to cohort
Record W613388500 · doi:10.1007/s10646-015-1506-9

Mercury and cortisol in Western Hudson Bay polar bear hair

2015· article· en· W613388500 on OpenAlexaff
Thea Bechshøft, Andrew E. Derocher, Evan S. Richardson, Patrick Mislan, Nicholas J. Lunn, Christian Sonne, Runé Dietz, David M. Janz, Vincent L. St. Louis

Bibliographic record

VenueEcotoxicology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of SaskatchewanAlberta Environment and Protected AreasUniversity of Alberta
Fundersnot available
KeywordsMercury (programming language)BayEndocrine systemEcotoxicologyUrsus maritimusBiologyEndocrinologyInternal medicineChemistryPhysiologyEcologyMedicineHormoneOceanographyGeologyArctic

Abstract

fetched live from OpenAlex

Non-invasive methods of assessing animal health and life history are becoming increasingly popular in wildlife research; hair samples from polar bears (Ursus maritimus), are being used to study an ever broader range of anthropogenic and endocrine compounds. A number of contaminants are known to disrupt endocrine function in polar bears. However, the relationship between mercury and cortisol remains unknown, although mercury is an endocrine disruptor in other species. Here, we examine the relationship between concentrations of cortisol and total mercury (THg) analyzed in guard hair from 378 polar bears (184 females, 194 males) sampled in Western Hudson Bay, 2004-2012. The difference in mean cortisol concentration between female (0.8 ± 0.6 pg/mg) and male (0.7 ± 0.5 pg/mg) polar bears bordered on significance (p = 0.054). However, mean mercury concentration was significantly greater (p = 0.009) in females (4.7 ± 1.4 μg/g) than males (4.3 ± 1.2 μg/g). Hair cortisol in males was significantly influenced by mercury, age, and fatness, as well as interactions between mercury and year, mercury and fatness, and year and fatness (all: p < 0.03) (multiple regression analysis, whole model: r(2) = 0.14, F(7,185) = 4.43, p = 0.0001). Fatness was the only significant variable in the multiple regression analysis for females (r(2) = 0.06, F(1,182) = 13.0, p = 0.0004). In conclusion, a significant, but complex, relationship was found between mercury and cortisol concentrations in hair from male, but not female, polar bears.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score1.000

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.024
GPT teacher head0.258
Teacher spread0.233 · 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; both teacher heads agree on what is shown here.

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

Citations44
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueEcotoxicologySame topicMarine animal studies overviewFrench-language works237,207