MétaCan
Menu
Back to cohort
Record W2170022595 · doi:10.1139/z06-095

Diving behaviour of Cuvier’s (<i>Ziphius cavirostris</i>) and Blainville’s (<i>Mesoplodon densirostris</i>) beaked whales in Hawai‘i

2006· article· en· W2170022595 on OpenAlexvenueno aff
Robin W. Baird, Daniel L. Webster, Daniel J. McSweeney, Allan D. Ligon, Gregory S. Schorr, Jay Barlow

Bibliographic record

VenueCanadian Journal of Zoology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersNational Marine Fisheries Service
KeywordsBeaked whaleBiologyFisheryOceanographyZoologyWhaleGeology

Abstract

fetched live from OpenAlex

Beaked whales (family Ziphiidae) are thought to be among the longest and deepest diving mammals, and some species appear to be prone to mass-strand in response to high-intensity sonar. We studied diving behaviour of Cuvier’s ( Ziphius cavirostris G. Cuvier, 1823) and Blainville’s ( Mesoplodon densirostris (Blainville, 1817)) beaked whales in Hawaiian waters using suction-cup-attached time–depth recorders. Six whales, two Cuvier’s and four Blainville’s, were tagged and 41 h of dive data were collected. While Cuvier’s beaked whales were found in significantly deeper water depths (median depth = 2079 m) than Blainville’s beaked whales (median depth = 922 m), several aspects of diving were similar between the two species: (i) both regularly dove for 48–68 min to depths greater than 800 m (maximum 1408 m for Blainville’s and 1450 m for Cuvier’s); (ii) ascent rates for long/deep dives were substantially slower than descent rates, while for shorter dives there were no consistent differences; and (iii) both spent prolonged periods of time (66–155 min) in the upper 50 m of the water column. Based on time intervals between dives for the Cuvier’s beaked whales, such long dives were likely aerobic, but both species appeared to prepare for long dives by spending extended periods of time near the surface.

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 score0.589
Threshold uncertainty score0.760

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 studies0.0000.001
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 head0.008
GPT teacher head0.194
Teacher spread0.186 · 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

Citations165
Published2006
Admission routes1
Has abstractyes

Explore more

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