MétaCan
Menu
Back to cohort
Record W2156366490 · doi:10.1139/z03-208

Separation of foraging habitat among breeding sites of a colonial marine predator, the northern fur seal (<i>Callorhinus ursinus</i>)

2004· article· en· W2156366490 on OpenAlexvenueno aff
Bruce W. Robson, Michael E. Goebel, Jason D. Baker, Rolf R. Ream, Thomas R. Loughlin, Robert C. Francis, George A. Antonelis, Daniel P. Costa

Bibliographic record

VenueCanadian Journal of Zoology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsForagingFur sealBiologyForageHabitatPredationEcologyPredatorSeasonal breederFisheryGeography

Abstract

fetched live from OpenAlex

This study examines whether lactating northern fur seals (Callorhinus ursinus) from different breeding sites on the Pribilof Islands in the eastern Bering Sea forage in separate areas. Satellite transmitters were attached to 97 northern fur seal females from nine breeding areas for 119 complete foraging trips during the 1995 and 1996 breeding seasons. Females from St. Paul and St. George islands tended to travel in different directions relative to their breeding site in both years of the study. St. Paul Island females dispersed in all directions except to the southeast, where St. George Island females foraged. Habitat separation was also observed among breeding areas on northeastern and southwestern St. Paul Island and to a lesser degree on northern and southern St. George Island. Although foraging direction led to geographical separation among sites, the maximum distance traveled and the duration of foraging trips did not differ significantly among islands in either year. The results of this study document that lactating fur seals from the same site share a common foraging area and that females from different breeding sites tend to forage in separate areas and hydrographic domains.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.843
Threshold uncertainty score0.916

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 science0.0000.000
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 head0.011
GPT teacher head0.223
Teacher spread0.211 · 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

Citations114
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of ZoologySame topicMarine animal studies overviewFrench-language works237,207