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Record W2107786077 · doi:10.2144/05385rr01

Improved T-DNA vector for Tagging Plant Promoters via High-Throughput Luciferase Screening

2005· article· en· W2107786077 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBioTechniques · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsnot available
FundersVector InstituteVlaams Instituut voor Biotechnologie
KeywordsLuciferaseGeneReporter geneDNABiologyPromoterMolecular biologyPlasmidRecombinant DNAExpression vectorGeneticsGene expressionGenomeComputational biologyTransfection

Abstract

fetched live from OpenAlex

Transferred DNA (T-DNA) tagging is a powerful tool for tagging and in planta characterization of plant genes on a genome-wide scale. An improved promoter tagging vector is described here, which contains the codon-optimized luciferase (luc+) reporter gene 31 bp from the right border of the T-DNA. Compared to the wild-type luciferase gene, this construct provides significantly increased reporter gene expression and a 40 times higher tagging frequency. The utility of the construct is demonstrated in banana, a tropical monocot species, by screening embryogenic cell colonies and regenerated plants with an ultrasensitive charged-coupled device (CCD) camera. The improved vector resulted in a luciferase activation frequency of 2.5% in 19,000 cell colonies screened. Detailed molecular analysis of flanking DNA sequences in a tagged line revealed insertion of the luciferase tag in a novel gene with near-constitutive expression.

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 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: none
Teacher disagreement score0.632
Threshold uncertainty score0.560

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 head0.012
GPT teacher head0.247
Teacher spread0.235 · 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