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Record W4281614476 · doi:10.3390/agronomy12061283

Cucurbitaceous Vegetables’ Gummy Stem Blight Research

2022· article· en· W4281614476 on OpenAlexaff
Qing Luo, Guo‐Fei Tan, Yiqiao Ma, Ping-Hong Meng, Jian Zhang

Bibliographic record

VenueAgronomy · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvances in Cucurbitaceae Research
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsBiologyBlightResistance (ecology)CropPlant disease resistanceHorticultureBiotechnologyAgronomyGene

Abstract

fetched live from OpenAlex

Cucurbits are an important vegetable crop of the gourd family. Unfortunately, gummy stem blight (GSB) causes a major fungal disease on Cucurbitaceous vegetable crops. It is also known as black root when affecting fruits, and it is found all over the world. GSB is caused by the fungal pathogen Didymella bryoniae. Research efforts have investigated the different developmental stages and various parts of Cucurbits affected with this disease. In the present paper, we have completed a systematic review for the disease’s symptomatic, pathogenic microbes, resistance resources, resistance inheritance regularity, molecular biology and genomic study of resistance gene and control method, etc., on Cucurbits. This review provides the background and rationale for future studies aiming to address the issues existing in gummy stem blight research and development.

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)0.001
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score0.687

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.002
Research integrity0.0000.001
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 head0.052
GPT teacher head0.356
Teacher spread0.304 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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