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Record W2262375083 · doi:10.1642/auk-15-176.1

Diet reconstruction using next-generation sequencing increases the known ecosystem usage by a shorebird

2016· article· en· W2262375083 on OpenAlexafffundabout
Travis G. Gerwing, Jin‐Hong Kim, Diana J. Hamilton, Myriam A. Barbeau, Jason A. Addison

Bibliographic record

VenueThe Auk · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsMount Allison UniversityUniversity of New Brunswick
FundersNature Conservancy of CanadaNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsCalidrisBayBiologyPredationEcologyHabitatIntertidal zoneSandpiperGeneralist and specialist speciesMarine ecosystemFisheryEcosystemFreshwater ecosystemGeography

Abstract

fetched live from OpenAlex

Molecular scatology and next-generation sequencing identified previously unknown linkages among ecosystems in the diet of Semipalmated Sandpipers (Calidris pusilla) in the Bay of Fundy, Canada. During their annual migratory stopover, the birds consumed a wider range of prey items than previously reported, which suggests that they are not selecting for the amphipod Corophium volutator and are acting as generalist foragers. Our analysis identified several novel prey items—arachnids, crabs, bivalves, several terrestrial and freshwater insect species, ctenophores, cnidarians, and fish (likely eggs or juveniles)—indicating that Semipalmated Sandpipers consume prey from marine, freshwater, and terrestrial ecosystems. Connections between Semipalmated Sandpipers and freshwater and terrestrial ecosystems were previously unknown in the Bay of Fundy. Current conservation efforts for this species are focused on beach and intertidal habitats; however, we may also need to consider the surrounding freshwater and terrestrial habitat.

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)0.001
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 score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.092
GPT teacher head0.249
Teacher spread0.158 · 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

Citations75
Published2016
Admission routes3
Has abstractyes

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