MétaCan
Menu
Back to cohort
Record W4404621486 · doi:10.70251/hyjr2348.246165

Effect of Myrosinase Enzyme Encoding Gene Knockout on the Bitter Taste of Broccoli: A CRISPR-Cas9 Experimental Proposal

2024· article· en· W4404621486 on OpenAlexaff

Bibliographic record

VenueAmerican journal of student research. · 2024
Typearticle
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsAurora College
Fundersnot available
KeywordsMyrosinaseCRISPRBitter tasteTasteGeneEnzymeBiologyGeneticsBiochemistryBotanyGlucosinolate

Abstract

fetched live from OpenAlex

Many people perceive bitterness when consuming broccoli. Glucosinolates and their degraded products are the main contributors to the bitter taste. Production and hydrolysis of glucosinolates require c gene using CRISPR-Cas9 will reduce broccoli’s bitter taste. This study also hypothesized that knocking out the myrosinase encoding gene will reduce bitterness in broccoli. The research involves designing a plasmid to deliver the CRISPR-Cas9 system to target and disrupt broccoli’s myrosinase enzyme encoding gene. Successful completion of this proposal could lead to the development of a broccoli variety that is more palatable to a broader population, potentially increasing its consumption and associated health benefits.

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)0.003
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.424
Teacher spread0.377 · 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 designBench or experimental
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

Explore more

Same venueAmerican journal of student research.Same topicBiochemical Analysis and Sensing TechniquesFrench-language works237,207