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Record W2102395448 · doi:10.1139/z05-184

Distribution of boreal toad populations in relation to estimated UV-B dose in Glacier National Park, Montana, USA

2006· article· en· W2102395448 on OpenAlexvenueno aff
Blake R. Hossack, Stephen A. Diamond, Paul Stephen Corn

Bibliographic record

VenueCanadian Journal of Zoology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsnot available
Fundersnot available
KeywordsNational parkSnowpackBorealBiologyGlacierToadSnowElevation (ballistics)EcologyPhysical geographyGeography

Abstract

fetched live from OpenAlex

A recent increase in ultraviolet B radiation is one hypothesis advanced to explain suspected or documented declines of the boreal toad (Bufo boreas Baird and Girard, 1852) across much of the western USA, where some experiments have shown ambient UV-B can reduce embryo survival. We examined B. boreas occupancy relative to daily UV-B dose at 172 potential breeding sites in Glacier National Park, Montana, to assess whether UV-B limits the distribution of toads. Dose estimates were based on ground-level UV-B data and the effects of elevation, local topographic and vegetative features, and attenuation in the water column. We also examined temporal trends in surface UV-B and spring snowpack to determine whether populations are likely to have experienced increased UV-B exposure in recent decades. We found no support for the hypothesis that UV-B limits the distribution of populations in the park, even when we analyzed high-elevation ponds separately. Instead, toads were more likely to breed in water bodies with higher estimated UV-B doses. The lack of a detectable trend in surface UV-B since 1979, combined with earlier snow melt in the region and increasing forest density at high elevations, suggests B. boreas embryos and larvae likely have not experienced increased UV-B.

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 score0.057
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.021
GPT teacher head0.253
Teacher spread0.232 · 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

Citations13
Published2006
Admission routes1
Has abstractyes

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