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Record W6969276273 · doi:10.5683/sp2/wg5hej

Data from: Offspring fitness varies with parental extra-pair status in song sparrows, Melospiza melodia

2021· dataset· en· W6969276273 on OpenAlexaff

Bibliographic record

VenueBorealis · 2021
Typedataset
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOffspringHatchlingReproductionMaternal effectSelection (genetic algorithm)Reproductive success

Abstract

fetched live from OpenAlex

AbstractNumerous studies have tested for indirect selection on female extra-pair reproduction (EPR) by quantifying whether extra-pair young (EPY) are fitter than their within-pair young (WPY) maternal half-siblings. In contrast, the hypothesis that offspring of EPY and WPY (rather than the EPY and WPY themselves) differ in fitness has not been tested, even though inter-generational effects of parental extra-pair status on offspring fitness could alter the magnitude and direction of indirect selection on EPR. We tested whether offspring of EPY song sparrows, Melospiza melodia, were more likely to recruit or produce hatched or recruited offspring over their lifetimes than offspring of WPY. Hatchlings with one or two EPY parents were more likely to recruit and produce hatched offspring than hatchlings with two WPY parents. Furthermore, these relationships differed between maternal versus paternal extra-pair status. Hatchlings with EPY fathers were more likely to recruit and produce offspring than hatchlings with WPY fathers. In contrast, hatchlings with EPY mothers were as likely to recruit as hatchlings with WPY mothers and tended to be less likely to produce recruited offspring. Depending on the causal genetic and environmental mechanisms, such conflicting inter-generational relationships between parental extra-pair status and offspring fitness could substantially influence the evolutionary dynamics of EPR.

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: Observational
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.052
GPT teacher head0.321
Teacher spread0.269 · 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
GenreDataset

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

Citations0
Published2021
Admission routes1
Has abstractyes

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