MétaCan
Menu
← Back to cohort
Record W3158569307 · doi:10.1139/cjz-2020-0254

Long-term stability in the volume of Atlantic Puffin (<i>Fratercula arctica</i>) eggs in the western North Atlantic

2021· article· en· W3158569307 on OpenAlexafffundvenue
Kyle J. Lefort, Heather L. Major, Alexander L. Bond, Antony W. Diamond, Ian L. Jones, William A. Montevecchi, Jennifer F. Provencher, Gregory J. Robertson

Bibliographic record

VenueCanadian Journal of Zoology · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsMemorial University of NewfoundlandEnvironment and Climate Change CanadaUniversity of SaskatchewanUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaCrown-Indigenous Relations and Northern Affairs CanadaEnvironment and Climate Change Canada
KeywordsBiologyOceanographyAbundance (ecology)FisheryEcologyGeology

Abstract

fetched live from OpenAlex

In the eastern North Atlantic, declines in the volume of Atlantic Puffin (Fratercula arctica (Linnaeus, 1758)) eggs have been associated with shifts in the marine ecosystem, such as changes in the abundance of forage fishes and increasing sea-surface temperatures. In the western North Atlantic, where similar shifts in oceanographic conditions and changes in the abundance of forage fishes have presumably occurred, trends in the volume of Atlantic Puffin eggs remain unknown. In this study, we investigate Atlantic Puffin egg volume in the western North Atlantic. We compiled 140 years (1877–2016) of egg volume measurements (n = 1805) and used general additive mixed-effects models to investigate temporal trends and regional variation. Our findings indicate that Atlantic Puffin egg volume differs regionally but has remained unchanged temporally in the western North Atlantic since at least the 1980s.

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)0.001
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 score0.909
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.020
GPT teacher head0.243
Teacher spread0.223 · 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

Citations2
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Zoology→Same topicMarine and fisheries research→French-language works237,207→