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Record W2154186608 · doi:10.1656/045.019.0408

Aerial Surveys of the Labrador Coast, 2006: Observations of Marine Bird Distribution and Abundance During the Breeding Season

2012· article· en· W2154186608 on OpenAlexaffabout
Keith G. Chaulk

Bibliographic record

VenueNortheastern Naturalist · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsEiderAbundance (ecology)GeographyEcologyShoreCharadriiformesTernFisherySeasonal breederDistribution (mathematics)FlockBiology

Abstract

fetched live from OpenAlex

Very few large-scale studies of breeding marine birds have been conducted in Labrador. To address this information deficit, we conducted near-shore aerial surveys of the Labrador coastline between 6–11 and 21–26 June 2006. Our primary species of interest was Somateria mollissima (Common Eider), for which we counted only adult males. In total, we identified 8 species and 5 species categories (alcid colony, mixed tern and gull colony, etc). In total, we counted 40,700 birds, of which Common Eiders were the most widely distributed species, accounting for 88% of all flock/colony observations. Melanitta perspicillata (Surf Scoter) was the second most abundant species, but had a limited distribution, while Cepphus grylle (Black Guillemot) was the third most abundant species observed, but showed the second widest regional distribution. This information is valuable to resource managers and ecosystem researchers.

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 score0.099
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

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

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 head0.017
GPT teacher head0.205
Teacher spread0.187 · 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

Citations1
Published2012
Admission routes2
Has abstractyes

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