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Record W2278610738 · doi:10.1093/icb/icv099

Conservation Physiology and Conservation Pathogens: White-Nose Syndrome and Integrative Biology for Host–Pathogen Systems

2015· review· en· W2278610738 on OpenAlexafffund
Craig K. R. Willis

Bibliographic record

VenueIntegrative and Comparative Biology · 2015
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsUniversity of Winnipeg
FundersSociety for Integrative and Comparative Biology (SICB)University of Winnipeg
KeywordsConservation biologyBiologyEcologyConservation sciencePopulationEcosystemMedicine

Abstract

fetched live from OpenAlex

Conservation physiology aims to apply an understanding of physiological mechanisms to management of imperiled species, populations, or ecosystems. One challenge for physiologists hoping to apply their expertise to conservation is connecting the mechanisms we study, often in the laboratory, with the vital rates of populations in the wild. There is growing appreciation that infectious pathogens can threaten populations and species, and represent an important issue for conservation. Conservation physiology has much to offer in terms of addressing the threat posed to some host species by infectious pathogens. At the same time, the well-developed theoretical framework of disease ecology could provide a model to help advance the application of physiology to a range of other conservation issues. Here, I use white-nose syndrome (WNS) in hibernating North American bats as an example of a conservation problem for which integrative physiological research has been a critical part of research and management. The response to WNS highlights the importance of a well-developed theoretical framework for the application of conservation physiology to a particular threat. I review what is known about physiological mechanisms associated with mortality from WNS and emphasize the value of combining a strong theoretical background with integrative physiological studies in order to connect physiological mechanisms with population processes and thereby maximize the potential benefits of conservation physiology.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.158
GPT teacher head0.344
Teacher spread0.186 · 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 teacher head, not a consensus.

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

Citations25
Published2015
Admission routes2
Has abstractyes

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