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Record W6910870369 · doi:10.5061/dryad.cz8w9gj35

Egg covering in great tits and effects on pied flycatchers

2021· dataset· en· W6910870369 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsNest (protein structural motif)Nest boxWoodlandNesting (process)Laying

Abstract

fetched live from OpenAlex

This dataset contains data from experiments carried out in a woodland area and described in the paper: “T. Slagsvold, and Wiebe, K. L. (2021) “Egg covering in cavity nesting birds may prevent nest usurpation by other species.” https://doi.org/10.1007/s00265-021-03045-w The experiments investigated a new hypothesis, namely that the cavity nesting birds, like titmice, cover their eggs when they leave the nest during the egg laying period to prevent usurpation of the cavity by other birds. We provided nest boxes in a woodland area and filmed great tit (Parus major)nests during the egg-laying period to study the behavior of the female. Then we presented prospecting male pied flycatchers (Ficedula hypoleuca) with a dyad of nest boxes, to study whether they hesitated to enter a box when the tit eggs were covered or not, depending on the size and depth of the box. Main results of the experiments were that (1) during the egg-laying period, the female great tit spent bouts of highly variable length outside the nest box, from a few minutes to more than an hour. Therefore, when visiting a nest cavity, prospecting birds would have difficulty predicting whether an aggressive tit owner would soon return. (2) The pied flycatchers hesitated longer to enter a nest box with no visible tit eggs than a box with exposed eggs. (3) This was most evident for nest boxes with dark versus light interior paint, supporting the idea that better interior illumination makes prospecting birds more confident about entering an unfamiliar cavity.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0040.000

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 head0.034
GPT teacher head0.321
Teacher spread0.288 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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