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Record W4323356999 · doi:10.33265/polar.v42.8616

Adult survival and annual movement patterns of common snipe in Iceland

2023· article· en· W4323356999 on OpenAlexafffund
Aevar Petersen, Sverrir Thorstensen, Ib Krag Petersen, Scott W. Petrek, Kane Brides, Anna M. Calvert, Mark L. Mallory, Gregory J. Robertson, Sarah E. Gutowsky

Bibliographic record

VenuePolar Research · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsAcadia UniversityCarleton UniversityEnvironment and Climate Change Canada
FundersMitacsRoyal SocietyAcadia University
KeywordsWaderOverwinteringSubarctic climateGeographyEcologyFlywayAnnual cycleHabitatSeabirdBiologyPredation

Abstract

fetched live from OpenAlex

The common snipe (Gallinago gallinago) is a wader that breeds in subarctic regions from Iceland to Russia, and for which global populations are in decline. We studied snipe breeding in western Iceland between 1998 and 2020, locating nests and ringing birds annually. In 2019 and 2020, we deployed geolocators on nesting adults to estimate the timing of their annual migration and the location of overwintering areas. Birds moved principally between breeding locations in Iceland to wintering areas in Ireland, although some birds may winter farther north. We also found that apparent annual adult survival averaged 66%, but was higher in years with warmer, wetter winters. Given the similarity of our survival estimates to those from snipe elsewhere, we suggest that adult survival is unlikely a major contributor to declining populations, and other factors like habitat loss may be of more concern.

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)0.000
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 score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.045
GPT teacher head0.356
Teacher spread0.310 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

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