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Record W1979597346 · doi:10.1111/mms.12178

Threshold foraging by gray whales in response to fine scale variations in mysid density

2014· article· en· W1979597346 on OpenAlexaff
Laura Feyrer, David A. Duffus

Bibliographic record

VenueMarine Mammal Science · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsForagingBaleenPredationWhaleCetaceaEcologyFisheryBiologyHumpback whalePopulation densityPopulation

Abstract

fetched live from OpenAlex

Abstract The gray whale ( Eschrichtius robustus ) is a coastal species whose nearshore summer foraging grounds off the coast of British Columbia offer an opportunity to study the fine scale foraging response of baleen whales. We explore the relationship between prey density and gray whale foraging starting with regional scale (10 km) assessments of whale density (per square kilometer) and foraging effort as a response to regional mysid density (per cubic meter), between 2006 and 2007. In addition we measure prey density at a local scale (100 m), while following foraging whales during focal surveys. We found regional mysid density had a significant positive relationship with both gray whale density and foraging effort. We identify a threshold response to regional mysid density for both whale density and foraging effort. In 2008 the lowest average local prey density measured beside a foraging whale was 2,300 mysids/m 3 . This level was maintained even when regional prey density was found to be substantially lower. Similar to other baleen whales, the foraging behavior of gray whales suggests a threshold response to prey density and a complex appreciation of prey availability across fine scales.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.116
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.233
Teacher spread0.223 · 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

Citations22
Published2014
Admission routes1
Has abstractyes

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