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SUMMER FOOD HABITS OF HARLEQUIN DUCKS IN EASTERN NORTH AMERICA

2001· article· en· W2115700942 on OpenAlexaffabout
M. Robert, Louise Cloutier

Bibliographic record

VenueThe Wilson Bulletin · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsEnvironment and Climate Change Canada
FundersU.S. Fish and Wildlife Service
KeywordsPredationRange (aeronautics)BiologyLarvaTaxonAquatic insectEcologyZoology

Abstract

fetched live from OpenAlex

We collected feces of breeding Harlequin Ducks (Histrionicus histrionicus) from interior rivers of Northern Québec, Labrador and Newfoundland to document their summer food habits. We obtained 42 samples from 50 ducks. All samples contained recognizable food items, and the mean number of taxa identified per sample was 3.6 (SD = 1.6, range = 1–7). Overall, a total of 10,222 organisms from 25 taxa were identified. Nearly all (99.7%) food items were insects; the rest were mollusks and mites. Among insects, Simuliidae larvae were the most common food item, representing 87.2% of all prey counted. Other insects had low relative frequencies, the highest being Trichoptera with only 8.0%. However, in terms of frequency of occurrence, many insects were well represented: Trichoptera (83.3%), Ephemeroptera (64.3%), Diptera (61.9%), Plecoptera (33.3%), Coleoptera (11.9%), and Heteroptera (9.5%). Although Simuliidae larvae may represent the most important food taken in terms of absolute numbers, the relative importance of Trichoptera may be much higher in terms dry weight. These results are consistent with observations that Harlequin Ducks usually feed on the bed of fast stretches of rivers, and occasionally in slow-moving waters.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

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)0.0880.006

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 head0.029
GPT teacher head0.230
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

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

Citations13
Published2001
Admission routes2
Has abstractyes

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