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Record W1999849306 · doi:10.1139/z07-012

The influence of buoyancy and drag on the dive behaviour of an Arctic seabird, the Thick-billed Murre

2007· article· en· W1999849306 on OpenAlexaffvenue
Kyle H. Elliott, Gail K. Davoren, Anthony J. Gaston

Bibliographic record

VenueCanadian Journal of Zoology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of ManitobaCanadian Wildlife Federation
Fundersnot available
KeywordsSeabirdNeutral buoyancyBuoyancyForagingBiologyArcticOceanographyAnimal scienceEcologyFisheryPredationGeologyMechanics

Abstract

fetched live from OpenAlex

We used time–depth recorders to investigate the behaviour of free-ranging Thick-billed Murres ( Uria lomvia L., 1758) after attaching positively (n = 9), negatively (n = 10), or neutrally (n = 9) buoyant handicaps and increasing cross-sectional area by 3% (2.8 cm 2 ; n = 8) or 6% (5.6 cm 2 ; n = 6). When buoyancy was altered or drag increased, murres reduced dive depth and duration, suggesting that murres do not manipulate dive depth to obtain neutral buoyancy during the bottom phase. Ascent rate increased as the bird surfaced and mean ascent rate increased for deeper dives, presumably reflecting steeper dive angles and greater buoyancy during deep dives. For short dives (<150 s), preceding surface pauses were better correlated with dive depth and duration than succeeding surface pauses (surface pauses were “anticipatory”), suggesting that murres control inhalation rates based on anticipated dive depth and duration. Murres reduced ascent rate near the surface, possibly to reduce the risk of decompression sickness. Neutrally buoyant recorders attached to the legs had no effect on chick feeding frequencies or adult mass loss, suggesting that this attachment method may have the least effect on the foraging behaviour of alcids.

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)0.001
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 score0.149
Threshold uncertainty score0.864

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.221
Teacher spread0.213 · 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

Citations71
Published2007
Admission routes2
Has abstractyes

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