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Record W4236951701 · doi:10.1093/auk/117.4.892

Egg Rejection by Cowbird Hosts in Grasslands

2000· article· en· W4236951701 on OpenAlexaff
Brian D. Peer, Scott K. Robinson, James R. Herkert

Bibliographic record

VenueThe Auk · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCowbirdSparrowParasitismBiologyBrood parasiteHost (biology)GrasslandEcologyZoology

Abstract

fetched live from OpenAlex

Abstract We tested Field Sparrows (Spizella pusilla), Vesper Sparrows (Pooecetes gramineus), Lark Sparrows (Chondestes grammacus), Grasshopper Sparrows (Ammodramus savannarum), Dickcissels (Spiza americana), Eastern Meadowlarks (Sturnella magna), and Western Meadowlarks (S. neglecta) to determine whether the low level (<10%) of observed parasitism by Brown-headed Cowbirds (Molothrus ater) on these grassland hosts is a result of egg rejection. Western Meadowlarks rejected 78% of artificial and real cowbird eggs, Eastern Meadowlarks rejected 36% of artificial cowbird eggs, and Dickcissels rejected 11% of artificial cowbird eggs. None of the other hosts regularly rejected cowbird eggs. Thus, egg rejection may account for some, but not all, of the low level of observed parasitism on grassland hosts in the Midwest. Meadowlarks were also tested with nonmimetic eggs, and the remaining hosts were tested with undersized mimetic and nonmimetic eggs when possible. All hosts, with the exception of the Field Sparrow, demonstrated some level of rejection of the nonmimetic eggs. These results suggest that some grassland hosts, which apparently have been in contact with cowbirds the longest, have evolved some form of rejection behavior that might have selected for mimetic eggs in cowbirds. The intermediate levels of rejection by both species of meadowlarks also may indicate that rejection is increasing in these populations.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.998

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)0.0110.003

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 head0.005
GPT teacher head0.215
Teacher spread0.209 · 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 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

Citations27
Published2000
Admission routes1
Has abstractyes

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