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Record W2586444887 · doi:10.1071/ma17008

Virus discovery in bats

2017· article· en· W2586444887 on OpenAlex
Rebecca I. Johnson, Ina Smith

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMicrobiology Australia · 2017
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsCarbon Engineering (Canada)
Fundersnot available
KeywordsBiologyVirologyVirus classificationZoologyHost (biology)VirusEvolutionary biologyEcologyGeneticsGenome

Abstract

fetched live from OpenAlex

(Uploaded by Plazi for the Bat Literature Project) Comprising approximately 20% of known mammalian species, bats are abundant throughout the world1. In recent years, bats have been shown to be the reservoir host for many highly pathogenic viruses, leading to increased attempts to identify other zoonotic bat-borne viruses. These efforts have led to the discovery of over 200 viruses in bats and many more viral nucleic acid sequences from 27 different viral families2,3 (Table 1). Over half of the world's recently emerged infectious diseases originated in wildlife15, with the genetic diversity of viruses greater in bats than in any other animal16. As humans continue to encroach on the habitat of bats, the risk of spillover of potentially zoonotic viruses is also continuing to increase. Therefore, the surveillance of bats and discovery of novel pathogens is necessary to prepare for these spillover events17.

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.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.066
GPT teacher head0.367
Teacher spread0.301 · 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