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Record W4206670787 · doi:10.1038/s41598-022-04965-x

Experimental inoculation trial to determine the effects of temperature and humidity on White-nose Syndrome in hibernating bats

2022· article· en· W4206670787 on OpenAlexafffund
Winifred F. Frick, Emily Johnson, Tina L. Cheng, Julia S. Lankton, Robin W. Warne, Jason Dallas, Katy L. Parise, Jeffrey T. Foster, Justin G. Boyles, Liam P. McGuire

Bibliographic record

VenueScientific Reports · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsUniversity of Waterloo
FundersU.S. Geological SurveyTrent UniversityNational Fish and Wildlife FoundationTexas Tech UniversityBat Conservation International
KeywordsHibernation (computing)BiologyMicroclimateHumidityPathogenWildlife diseasePopulationDiseaseWildlifeInoculationZoologyEcologyImmunologyMedicineGeographyInternal medicine

Abstract

fetched live from OpenAlex

Disease results from interactions among the host, pathogen, and environment. Inoculation trials can quantify interactions among these players and explain aspects of disease ecology to inform management in variable and dynamic natural environments. White-nose Syndrome, a disease caused by the fungal pathogen, Pseudogymnoascus destructans (Pd), has caused severe population declines of several bat species in North America. We conducted the first experimental infection trial on the tri-colored bat, Perimyotis subflavus, to test the effect of temperature and humidity on disease severity. We also tested the effects of temperature and humidity on fungal growth and persistence on substrates. Unexpectedly, only 37% (35/95) of bats experimentally inoculated with Pd at the start of the experiment showed any infection response or disease symptoms after 83 days of captive hibernation. There was no evidence that temperature or humidity influenced infection response. Temperature had a strong effect on fungal growth on media plates, but the influence of humidity was more variable and uncertain. Designing laboratory studies to maximize research outcomes would be beneficial given the high costs of such efforts and potential for unexpected outcomes. Understanding the influence of microclimates on host-pathogen interactions remains an important consideration for managing wildlife diseases, particularly in variable environments.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.837
Threshold uncertainty score0.515

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.238
Teacher spread0.221 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations46
Published2022
Admission routes2
Has abstractyes

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