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Record W2074303148 · doi:10.1139/z02-158

Responses of body components to changes in the energetic demand throughout the breeding stages of rhinoceros auklets

2002· article· en· W2074303148 on OpenAlexvenueno aff
Yasuaki Niizuma, Yoko Araki, Hiroe Mori, Akinori Takahashi, Yutaka Watanuki

Bibliographic record

VenueCanadian Journal of Zoology · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersNorthwestern University
KeywordsBiologyForagingAnimal scienceIncubationEnergeticsEcologyZoologyBiochemistry

Abstract

fetched live from OpenAlex

When rearing chicks, seabirds increase their daily energy expenditures during commuting flights between foraging areas and breeding colonies, owing to the heavy food loads. At this time, parents are expected to enlarge the size of their energy-supplying organs in response to the increased energy demands but reduce their total body mass to minimize the energetic cost of flight. The changes in body components of 40 incubating and chick-rearing rhinoceros auklets (Cerorhinca monocerata) were examined. Chick-rearing auklets did not have larger energy-supplying organs and breast muscles than incubating ones. However, chick-rearing auklets had greater ash composition, but smaller lipid contents, of breast muscles than incubating ones, whereas the former had a mass of water and protein similar to the latter. Male and female auklets lost a mean of 32.6 and 32.1 g in body mass between incubation and chick-rearing stages, mainly via loss of lipid reserves, which consequently reduces flight costs by 9.9 and 9.1%, respectively. Performance of commuting flight could be improved through changes in breast muscle compositions and reductions in total body mass. Although auklets did not enlarge their energy-supplying organs, their body conditions could be maintained within the same phase between the breeding stages.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.034
GPT teacher head0.259
Teacher spread0.225 · 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

Citations26
Published2002
Admission routes1
Has abstractyes

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