MétaCan
Menu
Back to cohort
Record W2788980870 · doi:10.1089/dna.2018.4153

Targeted Elimination of Peroxisomes During Viral Infection: Lessons from HIV and Other Viruses

2018· review· en· W2788980870 on OpenAlex
Cheung Pang Wong, Zaikun Xu, Christopher Power, Tom C. Hobman

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueDNA and Cell Biology · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchAlberta InnovatesCanada Research Chairs
KeywordsBiologyPeroxisomeBiogenesisMitochondrionViral replicationVirologyImmune systemCell biologyOrganelleSignal transductionVirusImmunologyReceptorGeneticsGene

Abstract

fetched live from OpenAlex

Peroxisomes are membrane-bound organelles that are best known for their roles in lipid metabolism. Mounting evidence indicates that they are also important nodes for antiviral signaling. While research over the past few decades has revealed effective viral strategies to block antiviral signalling pathways from the plasma membrane, mitochondria and/or the nucleus, until recently, very little was known about how viruses interfere with peroxisome-based antiviral signaling. In this essay, we review how viruses use a variety of strategies to interfere with peroxisome biogenesis, a phenomenon that has implications for evasion of the host immune system as well as pathogenesis.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.662
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.024
GPT teacher head0.302
Teacher spread0.278 · 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