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NESTING SUCCESS OF FOREST BIRDS IN SOUTHEAST ALASKA AND ADJACENT CANADA

2000· article· en· W2127528799 on OpenAlexaboutno aff
Mary F. Willson, Scott M. Gende

Bibliographic record

VenueOrnithological Applications · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsNest (protein structural motif)PredationEcologyWarblerBiologyVegetation (pathology)GeographyHabitat

Abstract

fetched live from OpenAlex

Predation caused 78% of nest failures in coastal forests of southeast Alaska and interior forests of adjacent Canada. Nest success tended to be better in coastal than interior forests. Mayfield daily nest survival from predation on open-cup nests was higher in egg than nestling phase for most species. Species building large (thrush-sized) nests had lower Mayfield daily survival from predation than species building smaller (warbler-sized) nests, but there was no difference in daily survival (total and from predation only) among species nesting in different vegetation strata. Nesting success differed little with nest cover or nest site diversity for most species. Total nest success within species was only sometimes higher in commonly used nest sites than in less frequently used sites. Nest survival from predation did not generally decrease with increasing nest density within guilds of species with similar nests or with nest-site similarity. We emphasize the likelihood of varied outcomes of natural selection on nest-site selection in differing circumstances.

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 score0.118
Threshold uncertainty score0.237

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 communication0.0000.000
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 head0.010
GPT teacher head0.223
Teacher spread0.212 · 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

Citations45
Published2000
Admission routes1
Has abstractyes

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