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Record W6940226010 · doi:10.6084/m9.figshare.c.6492695

Supplementary material from "Early-life sibling conflict in Canada jays has lifetime fitness consequences"

2023· other· en· W6940226010 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2023
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsSiblingInclusive fitnessDominance (genetics)Reproductive successCompetition (biology)Biological dispersal

Abstract

fetched live from OpenAlex

While delaying natal dispersal can provide short-term benefits for juveniles, lifetime fitness consequences are rarely assessed. Furthermore, competition for limited positions on a natal territory could impose an indirect fitness cost on the winner if the outcome has negative effects on its siblings. We use radio-tracking and 58 years of nesting data in Ontario, Canada to examine the lifetime fitness consequences of sibling expulsion in the Canada jay (<i>Perisoreus canadensis</i>). Six weeks after fledging, intra-brood dominance struggles result in one ‘Dominant Juvenile’ (DJ) remaining on the natal territory after expelling its subordinate siblings (Ejectees (EJs)). Despite an older age-at-first-reproduction, DJs produced more recruits over their lifetime and had higher first-year survival than EJs, leading to substantially higher direct fitness. Even though DJs incurred an indirect fitness cost by expelling their siblings and there was no evidence that their presence on the natal territory increased their parents' reproductive output the following year, they still had substantially higher inclusive fitness than EJs. Our results demonstrate how early-life sibling conflict can have lifetime consequences and that such fitness differences in Canada jays are driven by the enhanced first-year survival of DJs pursuant to the early-summer expulsion of their sibling competitors.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.970
Threshold uncertainty score0.997

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)0.9740.004

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 head0.044
GPT teacher head0.224
Teacher spread0.181 · 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 designNot applicable
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

Citations1
Published2023
Admission routes1
Has abstractyes

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