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Processes that influence timing of breeding, nesting distribution, and nest success in avian taxa

2022· dataset· en· W6906659352 on OpenAlexaff

Bibliographic record

VenueECCC Data Catalogue · 2022
Typedataset
Languageen
Field
Topic
Canadian institutionsGovernment of QuebecEnvironment and Climate Change CanadaGovernment of Canada
Fundersnot available
KeywordsNest (protein structural motif)BreedNesting (process)Reproductive successRange (aeronautics)PopulationArcticTaxonReproduction

Abstract

fetched live from OpenAlex

Although the extent to which large-scale environmental change will affect birds that breed in arctic areas will vary among species, reduced reproductive success and population declines have been observed in long-distance migrants and species whose reproduction depends on non-climatic cues. However, the proximate cues that birds use to determine timing of breeding and have not been examined across a broad taxonomic scale and remain poorly quantified for many species. Similarly, factors influencing the distribution and survival of nests are limited for many species, particularly those that breed in northern locations. This program evaluates the processes that influence timing of breeding, nesting distribution, and nest success across a range of taxa, thus improving predictions of how avian populations will respond to changing environmental conditions across their ranges.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.093
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.014

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 head0.055
GPT teacher head0.304
Teacher spread0.248 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2022
Admission routes1
Has abstractyes

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Same venueECCC Data CatalogueFrench-language works237,207