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Record W2114742617 · doi:10.1139/z08-065

Timing of breeding and environmental factors as determinants of reproductive performance of tree swallows

2008· article· en· W2114742617 on OpenAlexafffundvenue
Russell D. Dawson

Bibliographic record

VenueCanadian Journal of Zoology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of Northern British Columbia
FundersBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyOffspringFledgeReproductive successReproductionSeasonal breederEcologyZoologyAvian clutch sizeTemperate climateDemographyPredationPregnancyPopulation

Abstract

fetched live from OpenAlex

Decreased reproductive success among birds breeding later in the season is a common pattern in temperate environments, although the underlying mechanisms remain unresolved. The quality hypothesis suggests that high-quality individuals can begin breeding earlier in the season than poorer quality parents, and are also able to invest more in reproduction. Alternatively, the date hypothesis suggests that reduced success among late birds is due to some correlate of date, such as decreased food abundance or offspring value. To test these hypotheses, I manipulated the date that tree swallows, Tachycineta bicolor (Vieillot, 1808), raised offspring by swapping clutches among nests so that birds were raising young either earlier or later than intended, and compared reproductive performance with control nests. My results showed that fledging success was related to the date hypothesis, with later birds being less successful in raising offspring than early breeding birds. Size and mass of offspring were not explained by either hypothesis, but rather by weather conditions experienced prior to measurements being taken. My results highlight the importance of events such as periods of inclement weather that can have significant impacts on offspring quality independently of both date of breeding and parental quality.

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 score0.019
Threshold uncertainty score0.724

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)0.0010.000

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 head0.020
GPT teacher head0.213
Teacher spread0.193 · 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

Citations48
Published2008
Admission routes3
Has abstractyes

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