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Experimental dissociation of the effects of diet, age and breeding experience on primary reproductive effort in zebra finches <i>Taeniopygia guttata</i>

2003· article· en· W2129717574 on OpenAlexafffund
Tony D. Williams, Julian K. Christians

Bibliographic record

VenueJournal of Avian Biology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaSimon Fraser UniversityRoyal Society
KeywordsTaeniopygiaBiologyAvian clutch sizeReproductive successZoologyZebra finchReproductionAnimal scienceEcologyDemographyPopulation

Abstract

fetched live from OpenAlex

Reproductive performance varies with age in a wide range of organisms, and increasingly such patterns are interpreted in terms of state‐dependent models. We sought to characterise ‘state’ with regards to age‐related variation in clutch size, egg mass and timing of breeding in captive zebra finches Taeniopygia guttata , focusing on the roles of diet quality, age and breeding experience. Females on a high‐quality diet laid larger clutches of larger eggs than did females on a low‐quality diet. The effect of age on reproductive performance was examined by comparing females breeding (i.e. paired) for the first time at either 3‐ and/or 6‐months of age. Clutch size increased with age but on the low‐quality diet only, not on the high‐quality diet. Furthermore, clutch size decreased between 3‐ and 6‐months of age in birds bred first on the high‐quality diet and then on the low‐quality diet. Age did not affect egg mass but older birds had shorter laying intervals. Reproductive performance did not differ between females breeding at 6‐months of age for the first or second time: the effects of age were not due to ‘training’ effects or experience specific to breeding (e.g. undergoing the physiological process of egg formation). In conclusion, nutritional condition (diet) emerged as a central component of state that could strongly influence, and even reverse, any age‐dependent increase in primary reproductive performance.

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 score0.126
Threshold uncertainty score0.237

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)0.0000.000

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 head0.243
Teacher spread0.235 · 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

Citations22
Published2003
Admission routes2
Has abstractyes

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