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Record W2329504576 · doi:10.1139/cjz-2013-0033

Marbled Murrelets (<i>Brachyramphus marmoratus</i>) foraging with gray whales (<i>Eschrichtius robustus</i>) off Vancouver Island, British Columbia

2013· article· en· W2329504576 on OpenAlexafffundvenueabout
Kate Muirhead, Christopher D. Malcolm, D.A. Duffus

Bibliographic record

VenueCanadian Journal of Zoology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsBrandon UniversityUniversity of Victoria
FundersUniversity of Victoria
KeywordsPredationForagingSeabirdBiologyFisheryMarbled meatGray (unit)Gelatinous zooplanktonEcology

Abstract

fetched live from OpenAlex

Seabirds are known to associate with marine mammals to facilitate prey capture. These occur when mammals either force prey near the surface or provide small scraps of larger prey victims. Gray whales (Eschrichtius robustus (Lilljeborg, 1861)) have been observed to provide invertebrate prey to a variety of seabird species; however, there are no published reports of Marbled Murrelets (Brachyramphus marmoratus (Gmelin, 1789)) feeding in association with gray whales. We observed Marbled Murrelets foraging within several metres of gray whales off Vancouver Island, British Columbia, feeding on epibenthic zooplankton in 2006 and 2008. Join-count statistics identified significant clustering (p = 0.1) of 258 Marbled Murrelets within 300 m of 39 feeding gray whales in June of 2006, and no association between 3 gray whales and 34 Marbled Murrelets in June and July of 2008, marking a foraging association conditional on the abundance of both gray whales and their prey, but potentially significant to Marbled Murrelet survival and fecundity.

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 score0.519
Threshold uncertainty score0.956

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.170
Teacher spread0.164 · 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

Citations1
Published2013
Admission routes4
Has abstractyes

Explore more

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