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Record W3216887772 · doi:10.1002/2688-8319.12108

Vital rate estimates for the common eider <i>Somateria mollissima</i> , a data‐rich exemplar of the seaduck tribe

2021· article· en· W3216887772 on OpenAlexafffund
Alex Nicol‐Harper, Kevin A. Wood, Antony W. Diamond, Heather L. Major, Aevar Petersen, Grigori Tertitski, C. Patrick Doncaster, Thomas H. G. Ezard, Geoff M. Hilton

Bibliographic record

VenueEcological Solutions and Evidence · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of FrederictonUniversity of New Brunswick
FundersNatural Environment Research CouncilNatural Sciences and Engineering Research Council of CanadaEnvironment and Climate Change CanadaBritish Ornithologists' Union
KeywordsEiderFledgeAvian clutch sizePopulationBiologyEcologyDemographyGeographyHatchingReproduction

Abstract

fetched live from OpenAlex

Abstract This database collates vital rate estimates for the common eider ( Somateria mollissima ), providing a complete demographic parameterization for this slow life‐history species. Monitored across its circumpolar range, the common eider represents a data‐rich exemplar species for the less‐studied seaducks, many of which are under threat. The database contains estimates of the following vital rates: first‐year survival; second‐year survival; adult annual survival; first breeding (both age‐specific recruitment probability, and breeding propensity across potential recruitment ages); breeding propensity of established female breeders; clutch size; hatching success; and fledging success. These estimates are drawn from 134 studies, across the scientific and grey literature, including three previously inaccessible datasets on clutch size that were contributed in response to a call for data through the IUCN Species Survival Commission's Duck Specialist Group. Although clutch size has been much studied, the contributed datasets have enhanced coverage of studies reported in non‐English languages, which were otherwise only represented when cited in English‐language publications. Breeding propensity has been little studied, perhaps because adult females are often assumed to attempt breeding every year; we obtained a mean breeding propensity of 0.72. Our synthesis highlights the following gaps in data availability: juvenile and male survival; population change; and studies from Russia (at least accessible in English). The database is intended to serve population modellers and scientists involved in the policy and practice of seaduck conservation and management.

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)0.008
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: none
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.002

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 head0.083
GPT teacher head0.309
Teacher spread0.225 · 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
Published2021
Admission routes2
Has abstractyes

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