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Record W2143073730 · doi:10.1093/beheco/arr202

Brood parasites may use gape size constraints to exploit provisioning rules of smaller hosts: an experimental test of mechanisms of food allocation

2011· article· en· W2143073730 on OpenAlexaff
Karen L. Wiebe, Tore Slagsvold

Bibliographic record

VenueBehavioral Ecology · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBiologyExploitBroodProvisioningTest (biology)EcologyComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

We investigated whether a mechanism of gape size limitation could increase the competitive ability of a large brood parasite in a brood of smaller host nestlings. The gape size of hatchling birds may limit the size of prey they can swallow and hence parents should bring larger more profitable prey as their nestlings grow. The relatively large gape of a brood parasite in a brood of smaller hosts may 1) increase provisioning rate to the brood, 2) allow the parasite to swallow large prey, or 3) cause parents to start bringing larger prey at an earlier nestling stage. We added 1 large same-aged great tit Parus major nestling to broods of smaller blue tits Cyanistes caeruleus to simulate a naive brood parasite system and filmed them when 2–3 days old. The cue of a single large nestling did not cause parents to increase provisioning rates nor to change the species of prey, but prey items were larger than in control broods. Large prey were “tested” more often than small prey, that is offered and then removed from the gapes of small nestlings, and 17% of the prey that the great tit nestling received had been previously offered to a blue tit. Our results revealed that prey size brought by parents could further increase the competitive ability of brood parasites.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.487

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)0.0000.000

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 head0.139
GPT teacher head0.279
Teacher spread0.140 · 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 designBench or experimental
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

Citations7
Published2011
Admission routes1
Has abstractyes

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