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Anti-CRISPRs: Protein Inhibitors of CRISPR-Cas Systems

2020· review· en· W3011435240 on OpenAlex

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

VenueAnnual Review of Biochemistry · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversity of Toronto
FundersNational Institute of General Medical SciencesCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsCRISPRBiologyComputational biologyGenomeGenome editingPalindromeMobile genetic elementsArchaeaGeneticsCRISPR interferenceTrans-activating crRNAGene

Abstract

fetched live from OpenAlex

(CRISPR-associated) genes are found frequently in bacteria and archaea, serving to defend against invading foreign DNA, such as viral genomes. CRISPR-Cas systems provide a uniquely powerful defense because they can adapt to newly encountered genomes. The adaptive ability of these systems has been exploited, leading to their development as highly effective tools for genome editing. The widespread use of CRISPR-Cas systems has driven a need for methods to control their activity. This review focuses on anti-CRISPRs (Acrs), proteins produced by viruses and other mobile genetic elements that can potently inhibit CRISPR-Cas systems. Discovered in 2013, there are now 54 distinct families of these proteins described, and the functional mechanisms of more than a dozen have been characterized in molecular detail. The investigation of Acrs is leading to a variety of practical applications and is providing exciting new insight into the biology of CRISPR-Cas systems.

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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.715
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.342
Teacher spread0.331 · 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