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Record W7009016093

Conserving surface-nesting seabirds at the Prince Edward Island: The roles of research, monitoring and legislation

2003· other· en· W7009016093 on OpenAlexaboutno aff

Bibliographic record

VenueOpen University of Cape Town (University of Cape Town) · 2003
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsThreatened speciesEndangered speciesPopulationLegislationSeabirdNear-threatened speciesWetlandPopulation growth
DOInot available

Abstract

fetched live from OpenAlex

South Africa's subantarctic Prince Edward Islands support substantial proportions of the global populations of a number of surface-nesting seabirds. Populations of most of these have decreased at the islands since the 1980s and 12 of 16 species are regarded as Threatened or Near Threatened regionally or internationally. The main causes of population decreases are thought to be by-catch mortality of albatrosses and giant petrels in longline fisheries, and environmental change influencing availability of prey to penguins and the Crozet shag Phalacrocorax [atriceps] melanogenis. It is proposed that the Prince Edward Islands Special Nature Reserve be expanded to include surrounding territorial waters so as to afford additional protection for seabirds breeding there, especially those species feeding near to the islands. Consideration needs also to be given to listing species as threatened or protected in terms of planned new legislation in South Africa and then developing management plans for them, preferably linked closely with the Agreement on the Conservation of Albatrosses and Petrels and the National Plan of Action (NPOA) – Seabirds. The islands should also be nominated as a Ramsar Wetland of International Importance in recognition of their importance to seabirds, with 13 of the 16 species exceeding the 1% of the global population criterion. A combination of research, monitoring and legislation will help conserve the surface-nesting seabirds of the Prince Edward Islands into the 21st century, but only providing the effects of climate change can somehow be addressed.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.851
Threshold uncertainty score0.297

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.271
Teacher spread0.235 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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