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Record W4391303960 · doi:10.1139/as-2023-0032

Monitoring colonial cliff-nesting seabirds in the Canadian Arctic: The Coats Island field station

2024· article· en· W4391303960 on OpenAlexaffvenueabout
Allison Patterson, Anthony J. Gaston, Alyssa Eby, Marianne Gousy‐Leblanc, Jennifer F. Provencher, Birgit M. Braune, J. Mark Hipfner, H. Grant Gilchrist, Josiah Nakoolak, Kerry J. Woo, Kyle H. Elliott

Bibliographic record

VenueArctic Science · 2024
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of WindsorUniversity of OttawaQueen's UniversityMcGill UniversityCarleton UniversityEnvironment and Climate Change Canada
Fundersnot available
KeywordsCliffNesting (process)GeographyFisheryColonialismArcticThe arcticField (mathematics)OceanographyArchaeologyBiologyGeologyEngineering

Abstract

fetched live from OpenAlex

The Coats Island field station in northern Hudson Bay, Canada, was established by the Canadian Wildlife Service in 1984 to monitor the thick-billed murre ( Uria lomvia, akpa, [Formula: see text]) population in the context of harvest management and federal responsibilities under the Migratory Birds Convention Act. The long-term monitoring program has continued annually for 34 of the last 39 years, making it the most frequently monitored seabird colony in the Canadian Arctic. In the 1990s, the focus of efforts at the site shifted from population monitoring and harvest management to long-term monitoring of murres as an indicator of environmental change. In addition to informing harvest management of murres in Canada, long-term monitoring and research at Coats Island have helped to establish thick-billed murres as an indicator species for Arctic seabirds, identified major shifts in the marine prey communities of Hudson Bay, enabled the assessment of international agreements on reducing contaminants in Arctic wildlife, and improved the understanding of the effects of climate change on Arctic marine birds. Coats Island has developed into an essential research site for all aspects of murre ecology and served as a training site for new generations of Arctic ecologists.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.065
GPT teacher head0.421
Teacher spread0.355 · 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.

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

Citations10
Published2024
Admission routes3
Has abstractyes

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