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Record W4394907717 · doi:10.1139/as-2023-0077

History of monitoring the endangered ivory gull in the Canadian Arctic

2024· article· en· W4394907717 on OpenAlexafffundvenueabout
Mark L. Mallory, H. Grant Gilchrist

Bibliographic record

VenueArctic Science · 2024
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsCarleton UniversityEnvironment and Climate Change CanadaAcadia University
FundersNorthern Contaminants ProgramNatural Sciences and Engineering Research Council of CanadaNatural Resources CanadaGovernment of NunavutAcadia University
KeywordsEndangered speciesSeabirdGeographyWildlifeIndigenousArcticRange (aeronautics)FisheryPopulationCritically endangeredThe arcticEnvironmental protectionEcologyBiologyEnvironmental healthHabitatOceanography

Abstract

fetched live from OpenAlex

The ivory gull ( Pagophila eburnea Phipps 1774) is a rare seabird found in the Canadian High Arctic. The Seymour Island Migratory Bird Sanctuary has supported the core colony for ivory gull research since the 1970s, but by the 2000s, survey work was extended across the species’ range in Nunavut, prompted by growing Indigenous concerns of population declines, which led to regular monitoring of colonies. We found marked declines in numbers of ivory gulls since the 1980s, especially in the southern part of the range, leading the Canadian Committee on the Status of Endangered Wildlife in Canada to recommend uplisting ivory gulls to Endangered under Canada’s Species At Risk Act, which the federal government did in 2009. This resulted in the development of a national Recovery Strategy that outlined research and monitoring needs. Canadian results prompted international concern and led to coordinated, international research and monitoring on this iconic Arctic species, which collectively suggested worldwide declines in the species’ numbers. Despite our efforts, the future of monitoring, and indeed of ivory gulls in Canada, remains unclear.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.081
GPT teacher head0.373
Teacher spread0.292 · 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

Citations1
Published2024
Admission routes4
Has abstractyes

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