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Record W4400880468 · doi:10.1021/cen-10222-scicon6

Breaking up the CRISPR conga line

2024· article· en· W4400880468 on OpenAlexaboutno aff
Sarah Braner

Bibliographic record

VenueC&EN Global Enterprise · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsCRISPRLine (geometry)BiologyGeneticsMathematicsGene

Abstract

fetched live from OpenAlex

A team of researchers led by Alan Davidson at the University of Toronto have discovered a small protein that can disassemble a stable bacterial CRISPR-Cas7 complex without using an apparent energy source ( Nature 2024, DOI: 10.1038 /s41586-024-07642-3 ). The protein, dubbed AcrIF25, comes from a bacteriophage, and the CRISPR-Cas7 complex it attacks comes from the bacterium Pseudomonas aeruginosa . Joseph Bondy-Denomy of the University of California, San Francisco, says that just as bacteria evolved CRISPR as a way to combat bacteriophages, phages developed ways to thwart CRISPR. This race for survival plays out very quickly because bacteria and phages change faster than most eukaryotes do. “If you wanted to figure out new ways that have evolved in nature for one thing to inhibit another thing, looking at the CRISPR and anti-CRISPR arms race is a great place to look for that sort of mechanistic novelty, and that’s exactly what

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.668
Threshold uncertainty score0.426

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 head0.005
GPT teacher head0.319
Teacher spread0.314 · 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 designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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