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Record W2023429586 · doi:10.1111/plb.12230

A landscape of hairy and twisted: hunting for new trichome mutants in the <scp>S</scp>askatoon <i><scp>A</scp>rabidopsis</i> T‐<scp>DNA</scp> population

2014· article· en· W2023429586 on OpenAlexaff
Ali Taheri, Peng Gao, Min Yu, De-Jun Cui, Sharon Regan, Isobel A. P. Parkin, Margaret Y. Gruber

Bibliographic record

VenuePlant Biology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsFort Saskatchewan Community HospitalPlant Biotechnology InstituteQueen's UniversityAgriculture and Agri-Food Canada
Fundersnot available
KeywordsTrichomeBiologyMutantGeneGeneticsPhenotypePopulationFunction (biology)AlleleBotany

Abstract

fetched live from OpenAlex

A total of 88 new Arabidopsis lines with trichome variation were recovered by screening 49,200 single-seed descent T3 lines from the SK activation-tagged population and from a new 20,000-line T-DNA insertion population (called pAG). Trichome variant lines were classified into 12 distinct phenotype categories. Single or multiple T-DNA insertion sites were identified for 89% of these mutant lines. Alleles of the well-known trichome genes TRY, GL2 and TTG1 were recovered with atypical phenotype variation not reported previously. Moreover, atypical gene expression profiles were documented for two additional mutants specifying TRY and GL2 disruptions. In remaining mutants, ten lines were disrupted in genes coding for proteins not implicated in trichome development, five were disrupted in hypothetical proteins and 11 were disrupted in proteins with unknown function. The collection represents new opportunities for the plant biology community to define trichome development more precisely and to refine the function of individual trichome genes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.243
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2014
Admission routes1
Has abstractyes

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