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Record W2920807198 · doi:10.1017/qua.2018.140

Pacific walrus diet across 4000 years of changing sea ice conditions

2019· article· en· W2920807198 on OpenAlexaff
Casey T. Clark, Lara Horstmann, Anne de Vernal, Anne M. Jensen, Nicole Misarti

Bibliographic record

VenueQuaternary Research · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsSea iceTrophic levelOceanographyArctic ice packArcticGeologyClimate changePhysical geographyGeographyPaleontology

Abstract

fetched live from OpenAlex

Abstract Declining sea ice is expected to change the Arctic's physical and biological systems in ways that are difficult to predict. This study used stable isotope compositions (δ 13 C and δ 15 N) of archaeological, historic, and modern Pacific walrus ( Odobenus rosmarus divergens ) bone collagen to investigate the impacts of changing sea ice conditions on walrus diet during the last ~4000 yr. An index of past sea ice conditions was generated using dinocyst-based reconstructions from three locations in the northeastern Chukchi Sea. Archaeological walrus samples were assigned to intervals of high and low sea ice, and δ 13 C and δ 15 N were compared across ice states. Mean δ 13 C and δ 15 N values were similar for archaeological walruses from intervals of high and low sea ice; however, variability among walruses was greater during low-ice intervals, possibly indicating decreased availability of preferred prey. Overall, sea ice conditions were not a primary driver of changes in walrus diet. The diet of modern walruses was not consistent with archaeological low sea ice intervals. Rather, the low average trophic position of modern walruses (primarily driven by males), with little variability among individuals, suggests that trophic changes to this Arctic ecosystem are still underway or are unprecedented in the last ~4000 yr.

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)0.000
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 score0.070
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.008

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 head0.060
GPT teacher head0.367
Teacher spread0.308 · 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

Citations32
Published2019
Admission routes1
Has abstractyes

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