MétaCan
Menu
Back to cohort
Record W2077824744 · doi:10.2980/21-2-3653

Nest site characteristics and breeding success of the red-backed shrike (<i>Lanius collurio</i>) in agricultural landscape in eastern Poland: Advantage of nesting close to buildings

2014· article· en· W2077824744 on OpenAlexvenueno aff
Artur Goławski, Cezary Mitrus

Bibliographic record

VenueEcoscience · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsShrikeNesting (process)GeographyNest (protein structural motif)AgricultureEcologyBird nestHabitatBiologyPredationEngineeringArchaeology

Abstract

fetched live from OpenAlex

One of the most important factors influencing breeding success in many bird species is predation. Nest site choice is one way of lowering the probability of such losses. In an agricultural landscape of eastern Poland, we examined the relationship between red-backed shrike (Lanius collurio) nest site characteristics, i.e., height above ground, concealment, and occurrence of thorns, and the risk of nest predation. We also considered the relationship with distance to potential predators, i.e., corvid nests, and the distance to buildings. Our results showed that only 1 environmental factor significantly influenced breeding success. Birds nesting closer to buildings achieved higher breeding success than those more distant from buildings. A positive correlation between date of first egg laying and distance from the nest to the buildings was also found. These results indicate that areas with human activities and buildings can created habitats that improve breeding success for some species. On the other hand, the growth of such habitats also contributes to decreasing availability of semi-natural areas for breeding and foraging for these species.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.005
GPT teacher head0.214
Teacher spread0.208 · 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

Citations10
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueEcoscienceSame topicAvian ecology and behaviorFrench-language works237,207