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Record W4385390253 · doi:10.37908/mkutbd.1234256

A bibliometric analysis of global publications on flax (Linum usitatissimum L.) disease during 2001-2021

2023· article· en· W4385390253 on OpenAlexaboutno aff
Sıtora Karimova, Erkin Kholmuradov, Mukhiddin Juliev, Farangiz Boytorayeva, Hamro Nuraliyev

Bibliographic record

VenueMustafa Kemal Üniversitesi Tarım Bilimleri Dergisi · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsnot available
Fundersnot available
KeywordsLinumScopusBibliometricsWeb of scienceLibrary scienceMEDLINEComputer sciencePolitical scienceBiologyBotany

Abstract

fetched live from OpenAlex

Researchers around the world have published articles on flax (Linum usitatissimum L.) and its diseases. However, there is no bibliometric analysis of flax and its diseases in the Scopus database. The purpose of this work is to analyze the scientific results in the field of flax and its diseases and follow its evolution worldwide based on the data collected from the Scopus database. In the article, global scientific publications related to flax and its diseases were analyzed by a bibliometrician. In this study, a total of 243 articles published during 2001-2021 years were evaluated. The results show that the number of articles in the database has increased year by year, with Canada, Australia and the United States occupying the core positions, accounting for 64.6% of the total published articles worldwide. P.N. Dodds is the author with the most published articles. This paper summarizes several possible research ideas and the systematic bibliometric analysis will help research groups and researchers to understand global research trends in flax and its diseases and to focus future research. Also, results obtained in this systematic review of flax-related articles by using statistical and visual bibliometric analysis can provide important and detailed information to scientists involved in research on it.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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 categoriesBibliometrics, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.194
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.239
Teacher spread0.214 · 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

Labeled directly by 2 models reading the full record.

Bibliometrics

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

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