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Record W4220737961 · doi:10.1094/pdis-03-22-0475-fe

Micrografting: An Old Dog Plays New Tricks in Obligate Plant Pathogens

2022· article· en· W4220737961 on OpenAlexaff

Bibliographic record

VenuePlant Disease · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Management Techniques
Canadian institutionsUniversity of Guelph
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsObligatePathogenHuman pathogenObligate parasitePlant disease resistancePlant tissueFungal pathogen

Abstract

fetched live from OpenAlex

Micrografting, which was developed almost 50 years ago, has long been used for virus eradication, micropropagation, regeneration, rejuvenation, and graft compatibility. Recently, micrografting has been used for studies of long-distance trafficking and signaling of molecules between scions and rootstocks. The graft transmissiveness of obligate plant pathogens, such as viruses, viroids, and phytoplasmas, facilitated the use of micrografting to study biological indexing and pathogen transmission, pathogen-induced graft incompatibility, and screening for the pathogen resistance during the past 20 years. The present study provides comprehensive information on the latter subjects. Finally, prospects are proposed to direct further studies.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.216
Teacher spread0.192 · 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 designObservational
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

Citations3
Published2022
Admission routes1
Has abstractyes

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