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Record W2732157208

FACTORS AFFECTING DISTRIBUTION AND DETECTION OF BOREAL CHORUS FROGS (Pseudacris maculata) AND WOOD FROGS (Rana sylvatica) AT CAPE CHURCHILL, MANITOBA

2006· article· en· W2732157208 on OpenAlexfundaboutno aff
Nicholas R Mannan, Gad Perry, David E. Andersen, Clint W. Boal

Bibliographic record

VenueUniversity of Minnesota Digital Conservancy (University of Minnesota) · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsnot available
FundersU.S. Geological SurveyParks CanadaTexas Tech University
KeywordsAmphibianEcologyCapeBorealTaigaPopulationHabitatChytridiomycosisGeographyHabitat destructionPredationBiology
DOInot available

Abstract

fetched live from OpenAlex

Amphibian populations are declining globally (Jennings and Hayes 1985, Beebee et al. 1990, Blaustein and Wake 1990). Disease, introduced predators, ultraviolet radiation, pollution, environmental change, and habitat loss and degradation have been suggested factors responsible for amphibian population declines (Jennings and Hayes 1985, Beebee et al. 1990, Laurance et al. 1996, Pounds et al. 2006). However, the relative importance of each potential factor is often unknown in specific cases. Because the processes that underlie amphibian declines are not well understood, collaborative efforts, such as the North American Amphibian Monitoring Program (NAAMP), have been developed to collect basic ecological data, and to systematically monitor amphibian population trends. Despite efforts such as the NAAMP, there are still many areas where amphibian surveys have not been conducted and little is known about local populations.

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 score0.200
Threshold uncertainty score0.402

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.160
Teacher spread0.152 · 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

Citations0
Published2006
Admission routes2
Has abstractyes

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Same venueUniversity of Minnesota Digital Conservancy (University of Minnesota)Same topicAmphibian and Reptile BiologyFrench-language works237,207