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Record W2175702605 · doi:10.2980/i1195-6860-12-4-549.1

Nest design and the abundance of parasitic<i>Protocalliphora</i>blow flies in two hole-nesting passerines

2005· article· en· W2175702605 on OpenAlexvenueno aff
Vladimír Remeš, Miloš Krist

Bibliographic record

VenueEcoscience · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsParusNest (protein structural motif)BiologyFledgeEcologyFicedulaAbundance (ecology)BroodAvian clutch sizeHabitatZoologyReproductionPredation

Abstract

fetched live from OpenAlex

:Ectoparasites dwelling in bird nests regularly reduce reproductive success and condition of breeding birds. Thus, establishing the factors that determine the abundance of ectoparasites is important for better understanding of reproductive trade-offs and life history evolution in birds. A recent hypothesis states that interspecific differences in the abundance of ectoparasites may be caused by nest composition. For example, great tits (Parus major) have nests made of mosses and fur, whereas Ficedula flycatchers have nests made of grasses, bast, and bark, and tits are more infested by nest-dwelling ectoparasites than flycatchers. We swapped nests between pairs of great tits and collared flycatchers (F. albicollis) during egg-laying or early incubation and counted parasitic Protocalliphora blow flies at the end of breeding to test this hypothesis experimentally. We controlled statistically for habitat (oak versus spruce forest), brood size, season, year, and mean nestling weight before fledging. We found a significant effect of bird species (tit > flycatcher), habitat (oak > spruce), and year. There was no effect of nest type. Consequently, the hypothesis ascribing the different abundance of ectoparasites in great tits and collared flycatchers to different nest composition was not supported by our study.

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 score0.014
Threshold uncertainty score0.551

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 studies0.0000.001
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 head0.014
GPT teacher head0.269
Teacher spread0.255 · 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

Citations25
Published2005
Admission routes1
Has abstractyes

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