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Record W1912658888 · doi:10.1139/cjz-2012-0213

High-tide flight by wintering Dunlins (<i>Calidris alpina</i>): a weather-dependent trade-off between energy loss and predation risk

2012· article· en· W1912658888 on OpenAlexaffvenueabout
Dick Dekker

Bibliographic record

VenueCanadian Journal of Zoology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsTC Scientific (Canada)
Fundersnot available
KeywordsCalidrisBayBiologyPredationCharadriiformesArcticOceanographyEcology

Abstract

fetched live from OpenAlex

Migratory shorebirds wintering or staging on ocean coasts collect at high tide on roosting sites that remain above the flood line. However, some species of Calidris sandpipers spend the high-tide interval in flight over the ocean. In the winters of 2006–2012, the characteristics of high-tide flight by Dunlins (Calidris alpina (L., 1758)) were studied at Boundary Bay, British Columbia, Canada. At wind speeds of 1–6 m/s, flocks of Dunlins remained airborne over the ocean for up to 4 h at altitudes of >30 m. If winds were >10 m/s, the Dunlins coursed low over the waves. Ambient temperature was a significant determinant in the occurrence and duration of high-tide flight. In October and November, the Dunlins spent just as much time in flight before as after high tide, but in January, flight duration was 43% shorter after high tide than before high tide. The mean January temperatures were significantly lower than in October and November. The Dunlins were hunted by Peregrine Falcons (Falco peregrinus Tunstall, 1771), which captured 81 prey in 494 attacks. The maximum kill rate of 0.28 captures per hour of observation was recorded in the second hour after high tide, which suggests that predation risk is greatest for Dunlins that return early from high-tide flight.

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 score0.015
Threshold uncertainty score0.029

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 communication0.0010.000
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 head0.006
GPT teacher head0.200
Teacher spread0.193 · 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

Citations4
Published2012
Admission routes3
Has abstractyes

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