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Record W2137486029 · doi:10.1525/cond.2008.8563

MIGRATORY CONNECTIVITY AND RATE OF POPULATION DECLINE IN A VULNERABLE SONGBIRD

2008· article· en· W2137486029 on OpenAlexaff
Jason Jones, D. Ryan Norris, M. Katherine Girvan, Jennifer J. Barg, Kurt Kyser, Raleigh J. Robertson

Bibliographic record

VenueOrnithological Applications · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsQueen's UniversityUniversity of Guelph
Fundersnot available
KeywordsSongbirdWarblerEcologyPopulationGeographyBreedSeasonal breederBiologyNest (protein structural motif)FeatherHabitatDemography

Abstract

fetched live from OpenAlex

It has been hypothesized that populations that are strongly connected between two periods of the year (i.e., individuals that breed in similar locations and also spend the nonbreeding season in similar locations) will be most vulnerable to population perturbations. Using stable-hydrogen isotopes in feathers and data from the North American Breeding Bird Survey, we examined this hypothesis for a vulnerable songbird, the Cerulean Warbler (Dendroica cerulea). Cerulean Warblers exhibit a parallel migration system, whereby western breeding populations are generally connected to southwestern wintering sites and eastern breeding populations are generally connected to northeastern wintering sites. As predicted, breeding populations that exhibited the strongest degree of migratory connectivity with a specific wintering region were also those populations that experienced the most severe declines over the past 40 years. Our results suggest that the strength of migratory connectivity should be an important factor when making resource-allocation decisions for the management and conservation of migratory 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 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)0.002
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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.257
Teacher spread0.236 · 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

Citations37
Published2008
Admission routes1
Has abstractyes

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