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Record W4405751418 · doi:10.1016/j.xplc.2024.101232

RNA modifications in plant biotic interactions

2024· review· en· W4405751418 on OpenAlexaff
Linhao Ge, Mingxuan Jia, Delphine M. Pott, Hao He, Hongying Shan, Rosa Lozano‐Durán, Aiming Wang, Xueping Zhou, Fangfang Li

Bibliographic record

VenuePlant Communications · 2024
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsAgriculture and Agri-Food Canada
FundersNational Key Research and Development Program of China Stem Cell and Translational ResearchNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsBiotic stressRNABiologyComputational biologyGeneticsAbiotic stressGene

Abstract

fetched live from OpenAlex

A modification and its diverse roles in plant biotic interactions, including plant-virus, plant-bacterium, plant-fungus, and plant-insect relationships. Furthermore, we highlight new technological developments driving research progress in this field and outline key challenges that remain to be addressed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.288
GPT teacher head0.371
Teacher spread0.083 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations25
Published2024
Admission routes1
Has abstractyes

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