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Bats and their resistance to deadly viruses - a review

2014· review· en· W1983062917 on OpenAlexaff
Amrita Banerjee, Sonu Subudhi, Cynthia Tamandjou

Bibliographic record

VenueIndian Journal of Comparative Microbiology Immunology and Infectious Diseases · 2014
Typereview
Languageen
FieldImmunology and Microbiology
TopicRabies epidemiology and control
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsResistance (ecology)VirologyBiologyEnvironmental ethicsEcologyPhilosophy

Abstract

fetched live from OpenAlex

Bats are the only mammals capable of flight and play an important role in the ecosystem. Bats have been the source of several deadly viruses such as Ebola, Henipavirus and SARS, which have caused lethal infections in other mammals. Besides rabies, none of the other viruses seem to produce any symptoms in bats. This has led to numerous investigations on the bat immune system. Understanding the immune response produced by bats to suppress the replication of these viruses could be helpful in extrapolating the knowledge to human immune responses to these viruses. It could also help in designing drugs and therapies to control the viral infection in humans. This review intends to put together the current researches that are being carried out in the field of bat immunology along with ideas and comments brought about.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.026
GPT teacher head0.316
Teacher spread0.289 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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