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Record W2138262381 · doi:10.5253/078.100.0203

The Diet of an Endemic Subspecies of the Eurasian Spoonbill<i>Platalea leucorodia balsaci,</i>Breeding at the Banc d'Arguin, Mauritania

2012· article· en· W2138262381 on OpenAlexaff
Jan Veen, Otto Overdijk, Thor Veen

Bibliographic record

VenueArdea · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant and Fungal Species Descriptions
Canadian institutionsUniversity of British Columbia
FundersAdessium Foundation
KeywordsSubspeciesBiologyForagingPopulationZoologyEcologyShrimpFisheryDemography

Abstract

fetched live from OpenAlex

In the period 1998–2010 the endemic subspecies of the Eurasian Spoonbill Platalea leucorodia balsaci breeding in Mauritania has decreased in numbers considerably. The causes for this decline are unknown. This study aimed to investigate the diet of the species. We analysed faecal material collected in the breeding colonies in 8 different years. The results show that Mauritanian Spoonbills almost exclusively eat shrimp (59.7%) and small fish (35.4%), the latter being dominated by Gobiidae (20.8%), Soleidae (4.8%) and Mugilidae (2.8%). Another 10 fish families were represented in small proportions. Shrimp were quantified on the basis of (parts of) mandibles present in the samples. All prey items eaten by the Spoonbills were extremely small. Diet composition of adult birds and chicks appeared to be similar. There was great variation in diet composition of adults between years, but there was no trend in any of the major diet components over the study period. This indicates that the decline of the Spoonbill population is not correlated with changes in food composition. Our diet study has been of a qualitative nature. Considering the dramatic population decline we plea for a more detailed ecological study of the species, including a quantitative approach of food intake and foraging conditions.

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 score0.013
Threshold uncertainty score0.026

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 studies0.0000.000
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 head0.014
GPT teacher head0.217
Teacher spread0.203 · 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

Citations17
Published2012
Admission routes1
Has abstractyes

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