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Record W1868753963 · doi:10.22621/cfn.v128i3.1601

Mortality of Common Eider, <em>Somateria mollissima</em> (Linnaeus, 1758), and other water birds during two inshore oiling events in southeastern Newfoundland, 2005 and 2006

2014· article· en· W1868753963 on OpenAlexafffundvenueabout
Gregory J. Robertson, Scott G. Gilliland, Pierre C. Ryan, Johanne Dussureault, Kyran Power, Bruce Turner

Bibliographic record

VenueThe Canadian Field-Naturalist · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsGovernment of Newfoundland and Labrador
FundersGovernment of Canada
KeywordsEiderFisheryGeographyWaterfowlPopulationHarbourSubspeciesEcologyBiologyHabitatDemography

Abstract

fetched live from OpenAlex

Although the waters off Newfoundland harbour millions of wintering marine birds, chronic marine oil pollution has been repeatedly reported. Unusually high numbers (hundreds) of oiled birds were noted following two events in March 2005 and April 2006 in southeastern Newfoundland. Common Eiders (Somateria mollissima [Linnaeus, 1758]) were the main victims in the first event, with at least 1400 affected, based on retrieval of carcasses and aerial surveys. The April 2006 event affected 19 species; Common Eiders were again the most numerous with a minimum of 337 birds oiled. Among the Common Eiders affected in both events, most were the northern type, including the borealis (C. L. Brehm, 1824) subspecies and presumed intergrades between borealis and dresseri Sharpe, 1871. Coupled with the legal harvest, these oiling events may have had an effect on the wintering Common Eider population. Alcids, other sea ducks, loons and gulls were also oiled, but in low numbers (< 100); thus, their populations were not likely affected by these events.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.511
Threshold uncertainty score0.973

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.244
Teacher spread0.230 · 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

Citations4
Published2014
Admission routes4
Has abstractyes

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