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Record W2993654080 · doi:10.1676/1559-4491-131.4.789

Video recordings of Brown-headed ( <i>Molothrus ater</i> ) and Shiny ( <i>M. bonariensis</i> ) cowbirds reveal oviposition from an elevated position: Implications for host–parasite coevolution

2019· article· en· W2993654080 on OpenAlexaff
Kevin Ellison, Vanina D. Fiorini, Rosalyn Gloag, Spencer G. Sealy

Bibliographic record

VenueThe Wilson Journal of Ornithology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCowbirdBrood parasiteNest (protein structural motif)BiologyEggshellZoologyHost (biology)EcologyParasitism

Abstract

fetched live from OpenAlex

Molothrine cowbirds are obligate brood parasites that lay eggs within 5–10 s in the minutes before sunrise. Robust analysis of their position at laying has therefore only been made possible with the development of high-resolution and low-light video recording technologies. From video recordings, we observed the moment of oviposition clearly in 8 and 31 instances of egg laying by Brown-headed (Molothrus ater) and Shiny (M. bonariensis) cowbirds, respectively. Both species laid from an elevated position such that their eggs dropped into nests from an estimated height of 4–8 cm. We propose this elevated laying position has selected for high eggshell strength in cowbirds, because stronger eggshells would be less likely to be damaged during egg laying. Stronger eggshells might also damage other eggs when dropped into the nest, thereby further reducing nestling competition from nest mates and drive selection for cowbird eggshell strength. A role for laying position in the evolution of cowbird egg strength is not mutually exclusive of the view that thickly shelled eggs have evolved as a defense to egg rejection by hosts and/or egg puncture behavior of cowbirds.

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)0.001
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 score0.472
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.263
Teacher spread0.251 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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