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Record W1976377522 · doi:10.1675/063.033.0107

Foraging Behavior of Non-Breeding Semipalmated Plovers

2010· article· en· W1976377522 on OpenAlexaff
Melissa Rose, Erica Nol

Bibliographic record

VenueWaterbirds · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsMinistry of Natural Resources and Forestry
Fundersnot available
KeywordsForagingCharadriusPloverPredationSalt marshEcologyHabitatBiomass (ecology)BiologyEnvironmental science

Abstract

fetched live from OpenAlex

Time activity budgets, foraging habitat quality and behavior of Semipalmated Plovers (Charadrius semipalmatus) were examined during three non-breeding seasons in a large estuarine system in southeastern Georgia, USA. Among the foraging sites available to shorebirds at each tidal stage, non-breeding plovers tracked those with the greatest biomass and density of invertebrate prey. Prey biomass differed according to tidal conditions but was strongly predicted by the salinity, organic content and particle sizes of the sediments. Foraging rates (pecks/ min) and densities (birds/ha) of plovers were both predicted by invertebrate density and biomass. Foraging rates correlated significantly with the rate of defecations, indicating that peck rates were related to intake rates. Foraging rates reached an asymptote of 25 pecks per minute, suggesting an upper limit to the rate of capture unconstrained by digestive bottlenecks. While available, nearly all plovers foraged when on mudflat habitats, while about 33% foraged on salt marsh habitats and 12% foraged on beaches. There was no effect of density of foraging birds on their rate of foraging at mudflats, suggesting that birds were not experiencing intra-specific competition at this productive site.

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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.237
Teacher spread0.228 · 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

Citations31
Published2010
Admission routes1
Has abstractyes

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