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GROWTH AND DEVELOPMENT OF PREFLEDGING CANADA GEESE AND LESSER SNOW GEESE: ECOLOGICAL ADAPTATION OR PHYSIOLOGICAL CONSTRAINT?

2002· article· en· W2174695589 on OpenAlexafffundabout
Shannon S. Badzinski, C. Davison Ankney, James O. Leafloor, Kenneth F. Abraham

Bibliographic record

VenueThe Auk · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsCochraneMinistry of Natural Resources and ForestryWestern University
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Fish and Wildlife ServiceMinistry of Natural Resources
KeywordsBrantaBiologyAnatidaeEcologyGooseSnowWaterfowlArcticBroodAdaptation (eye)FledgeZoologyHabitatGeographyHatching

Abstract

fetched live from OpenAlex

Neonate, gosling, and adult Canada Geese (Branta canadensis interior) and Lesser Snow Geese (Chen caerulescens caerulescens) were collected to evaluate if growth rates and developmental patterns differed interspecifically and to determine if such differences were better explained by physiology of the growth process or by ecological conditions historically experienced by those two species. Patterns of growth and development of Canada and Lesser Snow goose goslings were similar to those reported for other Arctic geese, but differences in relative growth rates and developmental patterns of external structures, digestive organs, and skeletal muscles were observed between these two species. As compared to Canada Geese, body parts associated with locomotion and acquisition or processing of food generally increased at relatively faster rates and were more developed relative to adult size in Lesser Snow Geese. Relative rates of increase for carcass protein and body mass in these two species did not support a physiological constraint on growth. Rates and patterns of growth and development were better explained as adaptations to ecological factors, such as growing season and nesting or brood rearing conditions, historically experienced by these two species.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.985
Threshold uncertainty score0.987

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)0.0010.000

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 head0.076
GPT teacher head0.227
Teacher spread0.151 · 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

Citations10
Published2002
Admission routes3
Has abstractyes

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