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Record W2017321465 · doi:10.1642/auk-14-51.1

Northern Flickers increase provisioning rates to raise more but poorer quality offspring when given experimentally enlarged broods

2014· article· en· W2017321465 on OpenAlexafffund
Annessa B. Musgrove, Karen L. Wiebe

Bibliographic record

VenueThe Auk · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBroodBiologyOffspringAvian clutch sizePaternal careZoologyEcologyPopulationFacultativeParental investmentDemographyAnimal scienceReproduction

Abstract

fetched live from OpenAlex

Brood enlargement experiments have been conducted in several species of birds to investigate how parents of both sexes adjust their investment in the current breeding attempt. We studied parental feeding effort in the Northern Flicker (Colaptes auratus), a species with partially reversed sex roles where males invest more in parental care than females and in which there is facultative polyandry and no extra-pair young. By experimentally manipulating brood sizes to be either larger or smaller by about 40%, we tested the flexibility of provisioning responses by each sex and whether the upper limit to provisioning corresponded to the maximum clutch size in the population. Both male and female parents increased feeding rates to enlarged broods, but per-nestling provisioning declined so that they fledged lighter nestlings with shorter wings. Mortality in reduced broods was lower than in control broods, but there was no difference in the incidence of mortality between control and enlarged broods. Parents with enlarged broods raised lighter fledglings than control parents with the same brood size suggesting clutch size is individually optimized. We conclude that, although flickers were able to raise extra offspring, brood size may be individually optimized if the smaller mass and wing length of offspring lead to lower recruitment.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.286
Teacher spread0.270 · 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; both teacher heads agree on what is shown here.

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

Citations18
Published2014
Admission routes2
Has abstractyes

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