MétaCan
Menu
Back to cohort
Record W2751924847 · doi:10.1086/693387

Divorce in an Island Bird Population: Causes, Consequences, and Lack of Inheritance

2017· article· en· W2751924847 on OpenAlexaboutno aff
Nathaniel T. Wheelwright, Céline Teplitsky

Bibliographic record

VenueThe American Naturalist · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
FundersAgence Nationale de la Recherche
KeywordsDemographyFledgeTraitBiologyReproductive successPopulationMatingInheritance (genetic algorithm)Sexual selectionMate choiceSeasonal breederMating systemEcologyGenetics

Abstract

fetched live from OpenAlex

Divorce (mate switching) is widely considered an adaptive strategy that female birds use to improve their reproductive success. However, in few species are the causes and consequences of divorce well understood, and the genetic basis and inheritance of divorce have never been explored. In Savannah sparrows (Passerculus sandwichensis) breeding on Kent Island, New Brunswick, Canada, 47.0% of pairs in which both partners survived to the following breeding season ended in divorce. Secondary females, which received less parental assistance than primary females, tended to divorce when breeding success was low or when paired with small males. Unlike young females or widows, older females improved their fledging success after divorce. Young males (but not older males) suffered lower reproductive success following a divorce. However, neither the lifetime number of divorces nor whether an individual had ever divorced affected the fitness of females or males, which suggests little or no selection for the trait. We found moderate repeatability for divorce in females (although not in males) but no additive genetic variance or evidence of maternal or paternal effects. Divorce in Savannah sparrows appears to be a nonheritable flexible behavior whose expression and consequences depend on an individual's sex, mating status, size, and age.

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 score0.200
Threshold uncertainty score0.974

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)0.0000.000

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 head0.088
GPT teacher head0.300
Teacher spread0.212 · 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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueThe American NaturalistSame topicPlant and animal studiesFrench-language works237,207