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Record W2166443650 · doi:10.14430/arctic734

Status of Marine Birds of the Southeastern Beaufort Sea

2002· article· en· W2166443650 on OpenAlexaffvenueabout
D. Lynne Dickson, H. Grant Gilchrist

Bibliographic record

VenueARCTIC · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsCanadian Forest Service
Fundersnot available
KeywordsEiderBeaufort scaleFisheryWaterfowlArcticPelagic zoneBeaufort seaGeographyOceanographyLarusEcologyBiologyHabitatFish <Actinopterygii>HerringGeology

Abstract

fetched live from OpenAlex

This summary and update of information on the marine birds of the southeastern Beaufort Sea is intended to support discussions on how to improve management of marine resources in the Canadian Beaufort Sea region. Perhaps the most outstanding use of the Beaufort Sea by marine birds is the staging during spring migration by hundreds of thousands of eiders and long-tailed ducks in the early open water off Cape Bathurst and Banks Island. During midsummer, tens of thousands of long-tailed ducks, scoters, scaup, and mergansers moult in the sheltered bays and behind barrier beaches and spits. Although several species of geese, ducks, loons, gulls, and terns nest on islands and in wetlands along the Beaufort Sea coast, this region has relatively few nesting seabirds compared to eastern Arctic Canada and the Bering Sea. Two possible reasons for this are a shortage of cliffs suitable for nesting and a lack of pelagic fish. The five most common sea duck species that occur in the region, long-tailed duck, king eider, common eider, surf scoter, and white-winged scoter, have all declined in numbers since the mid-1970s. Western Arctic brant populations have also declined, although their status within the Beaufort Sea region is unclear. Brant and king eider are the only marine bird species harvested there in substantial numbers. Other threats to Beaufort Sea marine bird populations include oil spills, global warming, coastal development, and contaminants. Certain threats can be managed at a local level since they are a result of local economic development, but others, such as global warming or loss of critical wintering areas, stem from environmental problems outside the region. Solving these issues will require mutual understanding and commitment on the part of numerous countries.

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)0.001
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 score0.536
Threshold uncertainty score0.934

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.032
GPT teacher head0.195
Teacher spread0.164 · 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

Citations68
Published2002
Admission routes3
Has abstractyes

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