MétaCan
Menu
Back to cohort
Record W2096784265 · doi:10.1007/s00300-011-1064-4

Inter-breeding movements of little auks Alle alle reveal a key post-breeding staging area in the Greenland Sea

2011· article· en· W2096784265 on OpenAlexaboutno aff
Anders Mosbech, Kasper Lambert Johansen, Nikolaj I. Bech, Peter Lyngs, Ann M. A. Harding, Carsten Egevang, Richard A. Phillips, Jérôme Fort

Bibliographic record

VenuePolar Biology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersInstitut Polaire Français Paul Emile VictorBritish Antarctic SurveyNatural Environment Research CouncilSight Research UKNational Science Foundation
KeywordsSeabirdBiologySeasonal breederEcologyPredationPeriod (music)EcosystemMarine ecosystemCharadriiformesFishery

Abstract

fetched live from OpenAlex

Seabirds are important components in marine ecosystems. However, knowledge of their ecology and spatial distribution during the non-breeding season is poor. More investigations during this critical period are required urgently, as marine environments are expected to be profoundly affected by climate change and human activities, with both direct and indirect consequences for marine top predators. Here, we studied the distribution of little auks (Alle alle), one of the most abundant seabird species worldwide. We found that after the breeding season, birds from East Greenland quickly travelled north-east to stay for several weeks within a restricted area in the Greenland Sea. Activity patterns indicated that flying behaviour was much reduced during this period, suggesting that this is the primary moulting region for little auks. Birds then performed a southerly migration to overwinter off Newfoundland. These preliminary results provide important information for the conservation of this species and emphasise the need for further studies at a larger spatial scale.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.037
GPT teacher head0.251
Teacher spread0.214 · 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

Citations37
Published2011
Admission routes1
Has abstractyes

Explore more

Same venuePolar BiologySame topicAvian ecology and behaviorFrench-language works237,207