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Record W4224245863 · doi:10.1111/ppa.13565

Shoot tip cryotherapy for plant pathogen eradication

2022· article· en· W4224245863 on OpenAlexaff
Min‐Rui Wang, Wen‐Lu Bi, Jean Carlos Bettoni, Dong Zhang, Gayle M. Volk, Qiao‐Chun Wang

Bibliographic record

VenuePlant Pathology · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCryotherapyBiologyShootPathogenAgronomyMicrobiologySurgeryMedicine

Abstract

fetched live from OpenAlex

Abstract Diseases caused by plant pathogens such as viruses, viroids and phytoplasmas cause huge economic losses of agricultural production and limit the safe movement of plant materials across borders. The use of pathogen‐free planting materials provides a strategy for efficient management of these diseases and facilitates the global exchange of genetic resources. Shoot tip cryotherapy is a novel biotechnology method that uses cryogenic procedures to eradicate plant pathogens from the diseased plants. Combining thermotherapy or chemotherapy with shoot tip cryotherapy has further enhanced pathogen eradication efficiency. This review provides updated and comprehensive information on shoot tip cryotherapy and the combination of thermotherapy or chemotherapy with shoot tip cryotherapy for pathogen eradication. Prospects are proposed for future 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.956
Threshold uncertainty score0.467

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 studies0.0010.000
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 head0.053
GPT teacher head0.258
Teacher spread0.205 · 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 designNot applicable
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

Citations37
Published2022
Admission routes1
Has abstractyes

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