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Record W4391475644 · doi:10.5962/p.364030

Diet of wintering Bald Eagles, Haliaeetus leucocephalus, in New Brunswick

2000· article· en· W4391475644 on OpenAlexvenueaboutno aff
Rudolph F. Stocek

Bibliographic record

VenueThe Canadian Field-Naturalist · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsBald eagleGeographyZoologyFisheryBiology

Abstract

fetched live from OpenAlex

Stocek, Rudolph F. 2000.Diet of wintering Bald Eagles, Haliaeetus leucocephalus, in New Brunswick.Canadian Field-Naturalist 114 (4): 605-611.The diet of wintering Bald Eagles (Haliaeetus leucocephalus) in New Brunswick was determined from 949 feeding observations, 1992-1999.White-tailed Deer (Odocoileus virginianus) accounted for 43% of the total occurrences, offal 30%, birds 16%, other mammals 8%, fish 3% and invertebrates < 1%.Thirty-five percent of the prey items were of aquatic origin.There were considerable dietary differences between inland and coastal feeding eagles.Avian prey (seabirds and waterfowl) were of greater importance to the coastal birds.Salmon offal consumption at aquaculture sites along the coast was significant.Over 70% of the dietary items taken by immature eagles were scavenged deer and offal.Some of the prey items consumed showed a marked seasonal variation.Almost 60% of all feeding occurrences in February and March involved deer.Both birds and fish decreased in importance from late fall to early spring.Immature eagles were found more commonly in mixed feeding groups than as solitary foragers.The risk of environmental contaminant exposure is likely greater for coastal wintering eagles that feed more heavily on aquatic organisms than for inland wintering birds.

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 score0.304
Threshold uncertainty score0.612

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.206
Teacher spread0.197 · 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

Citations5
Published2000
Admission routes2
Has abstractyes

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