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Record W4211259883 · doi:10.5860/choice.192841

Ranaviruses: lethal pathogens of ectothermic vertebrates

2015· article· en· W4211259883 on OpenAlexfundno aff

Bibliographic record

VenueChoice Reviews Online · 2015
Typearticle
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsnot available
FundersMedical Center, University of RochesterOffice of Research and Engagement, University of Tennessee, KnoxvilleState Key Laboratory of Freshwater Ecology and BiotechnologyU.S. Department of Homeland SecurityWashington State UniversityNational Natural Science Foundation of ChinaLife Sciences Research FoundationNational Key Research and Development Program of ChinaUniversity of RochesterNatural Sciences and Engineering Research Council of CanadaU.S. Department of AgricultureCalifornia State University San MarcosNational Institutes of HealthNational Science Foundation
KeywordsEctothermBiologyRanavirusZoologyEcologyAmphibian

Abstract

fetched live from OpenAlex

The first book of its kind, this work discusses the global extent of ranaviruses, principles of ranavirus ecology and evolution.�The research included�provides guidance on designing ranavirus surveillance studies to determine risk. Ranaviruses are are double-stranded DNA viruses that cause hemorrhagic disease in amphibians, reptiles, and fish. Ranaviruses have caused mass die-offs of ectothermic vertebrates in wild and captive populations around the globe. Ranaviruses: Lethal Pathogens of Ectothermic Vertebrates serves an urgent need to assemble the contemporary information on ranaviruses, and provide guidance on how to assess�this threat in 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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0190.014

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 head0.150
GPT teacher head0.394
Teacher spread0.245 · 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
GenreReview

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

Citations113
Published2015
Admission routes1
Has abstractyes

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