A Bibliometric Analysis of Molecular Marker Studies on Linum usitatissimum from 1998 to 2025
Bibliographic record
Abstract
Linum usitatissimum is an economically important species that is a dicotyledonous, self-pollinated, and annual herbaceous plant. L. usitatissimum provides both oil and fiber, which have a wide range of uses. The genetic variation existing within the genome is important to preserve the genetic resources and establishment of an effective breeding programmes successfully. Several molecular markers have been employed to analyse genetic characterization within the different genotypes of the species or among other plant species, including L. usitatissimum as well. Various molecular markers e.g., SSR, SCOT, RAPD, IRAP, REMAP, ISSR, and iPBS were used to understand the genetic diversity and genotyping of flax varieties, and to characterize relationships in L. usitatissimum. In the presented study, bibliometric analysis was performed to evaluate the published articles related to molecular marker studies in L. usitatissimum from 1998 to 2025 based on the WOS database. Searching the Web of Science Core Collection (WOS) by "Linum usitatissimum’’ and "molecular markers" criterias were analyzed, and the parameters include category areas, subject, country of publication, and country collaborations. According to the research results, a total of 91 published data were identified through research analysis from 1998 to 2025. Plant science, agronomy, and genetics/heredity were the top three categories. Canada and China have been the top contributors to research on molecular markers in L. usitatissimum based on WOS data. This bibliometric study evaluates the molecular marker analyses from different perspectives based on bibliometric analyses, which may be helpful to researchers working on this field and give an idea for possible projects. As a result, this study is the first bibliometric approach that aims to guide future studies by revealing molecular marker studies on flax genotypes between 1998 and 2025.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.188 | 0.244 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".