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<i>In vitro</i> selection for disease resistance in plants - an alternative to genetic engineering

2003· article· en· W4300911393 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCABI Reviews · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsUniversity of GuelphVineland Research and Innovation Centre
Fundersnot available
KeywordsBiotechnologySelection (genetic algorithm)BiologyResistance (ecology)Plant disease resistanceComputational biologyBiochemical engineeringComputer scienceGeneticsEngineeringEcologyGene

Abstract

fetched live from OpenAlex

Abstract Plant cell culture provides a unique opportunity to manipulate morphogenesis in a controlled environment, thus providing crop improvement with a powerful, complementary tool. Since the late 1970s, the process of in vitro selection has been applied to several cell culture systems to generate mutants with useful agronomic traits such as disease resistance. However, the promise of genetic engineering technology and some early failures among the in vitro selected plants stifled research in this area. Recent advances in molecular characterization of stress-related responses and the emergence of sensitive molecular analytical tools have reinvigorated research on in vitro selection. This technology is easy to use, and not encumbered by intellectual property issues and social concerns currently inhibiting development of transgenic crops. Thus it is an attractive complement to existing crop improvement strategies. The sub-cellular mechanisms that lead to altered phenotypes after in vitro selection are discussed.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
Threshold uncertainty score0.306

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 head0.015
GPT teacher head0.266
Teacher spread0.250 · 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