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Record W4409803941 · doi:10.5751/ace-02825-200115

Use of anthropogenic structures for nesting by Loggerhead Shrikes

2025· article· en· W4409803941 on OpenAlexvenueno aff
Holly M. Todaro, Emily Donahue, Alexander Harman, Courtney J. Duchardt

Bibliographic record

VenueAvian Conservation and Ecology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
FundersDirectorate for Biological SciencesArkansas State UniversityOklahoma State University
KeywordsNesting (process)EcologyGeographyFisheryBiologyEngineering

Abstract

fetched live from OpenAlex

As human activities continue to reshape ecosystems, reports of anthropogenic nest site use by birds are increasing. Although many of these reports focus on cavity nesting species using artificial nest boxes, many species also use buildings and other anthropogenic structures as nesting sites. Loggerhead Shrikes (Lanius ludovicianus) are one species for which this behavior has received limited attention in both the literature and community science databases. Here we document and compile our own observations and additional reports of shrikes using anthropogenic structures as nesting sites from a review of existing community science-based databases. Together, the six reports of nesting attempts presented here demonstrate that anthropogenic nest site use by shrikes is a repeated behavior throughout their range. Notably, the success of at least two of these anthropogenic nesting attempts suggests that these sites may offer suitable nest sites in areas where natural nesting sites are limited. Compiling information on anthropogenic nest site use by bird species may help inform the frequency, effects, and potential conservation benefits of this behavior.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.286
Teacher spread0.254 · 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 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

Citations2
Published2025
Admission routes1
Has abstractyes

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