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Record W4396697101 · doi:10.1002/anie.202407862

Inside Cover: A Sensitive Technique Unravels the Kinetics of Activation and <i>Trans</i> ‐Cleavage of CRISPR‐Cas Systems (Angew. Chem. Int. Ed. 22/2024)

2024· paratext· en· W4396697101 on OpenAlex
Wei Feng, Hanyong Peng, Hongquan Zhang, Michael Weinfeld, X. Chris Le

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

VenueAngewandte Chemie International Edition · 2024
Typeparatext
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsKineticsChemistryRibonucleoproteinNucleic acidCRISPRCleavage (geology)Reaction rate constantDissociation constantINTRNAStereochemistryBiophysicsBiochemistryMaterials scienceBiologyPhysicsComputer science

Abstract

fetched live from OpenAlex

CRISPR-Cas systems are activated by the formation of a ribonucleoprotein and its binding to the target nucleic acid sequence. Both binding processes are important for the overall performance. In their Communication (e202404069) Hongquan Zhang, X. Chris Le et al. describe a new method to study the binding kinetics and report the rate constants (kon and koff) and dissociation constant (Kd) for the activation of Cas13a by its RNA target. The method can unravel and quantify the kinetics of activation and enzymatic cleavage in a dynamic system. Artwork created by Jeffrey Tao.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.007
GPT teacher head0.282
Teacher spread0.275 · 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