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Record W2063370794 · doi:10.1139/z06-164

At-sea movements and habitat use of adult male Australian fur seals (Arctocephalus pusillus doriferus)

2006· article· en· W2063370794 on OpenAlexvenueno aff
Roger Kirkwood, Michael Lynch, Nick Gales, Peter Dann, Michael Sumner

Bibliographic record

VenueCanadian Journal of Zoology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsFur sealForagingBiologyFisheryRange (aeronautics)HabitatSea lionBass (fish)Ecology

Abstract

fetched live from OpenAlex

Foraging by adult male otariids, a demographic component that often interacts with commercial fisheries, are poorly known. To assess movement patterns and habitat use, nine adult male Australian fur seals ( Arctocephalus pusillus doriferus Wood Jones, 1925) from Seal Rocks, in northern Bass Strait, southeastern Australia, were tracked for periods ranging from 66 to 223 d during 1999–2001. Mean ± SD at-sea and on-land durations were 6.9 ± 2.1 d (range 2.3–10.3 d, n = 9 seals) and 2.4 ± 0.9 d (range 0.8–4.1 d), respectively. All seals foraged almost exclusively in continental shelf waters and mostly (65%–97% of time at sea) in water columns that were between 40 and 100 m deep. Six of nine seals tracked for >30 d spent 64%–98% of their time-at-sea foraging at distances <200 km from Seal Rocks, although the maximum distance achieved from the colony was 1208 km. The seals’ foraging ranges overlapped with the ranges of operation of virtually all fin-fish fisheries in southeastern Australia, but fisheries overlap was low in the most frequented foraging area of central-western Bass Strait.

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 score0.019
Threshold uncertainty score0.038

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.019
GPT teacher head0.217
Teacher spread0.198 · 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

Citations48
Published2006
Admission routes1
Has abstractyes

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