A bibliometric analysis of Serials Review from 1991 to 2020
Bibliographic record
Abstract
The study's objectives were to identify the document type, publishing trends, authorship patterns of research, most prolific authors, countries and keywords, top citied articles, and country collaboration of published articles in Serials Review (SR) through bibliometric measures from 1991-2020. The data was retrieved from the Scopus database and analyzed through VOSviewer, Microsoft excel, and Biblioshiny. The result found that most of the studies were published in the form of empirical (1785) with total citation (4998) during 1991-2020. Publications were increased from 2002 to 2004, but after 2014 the publications ratio decreased. A single authorship pattern was shown by most of the publications. Blythe, K published 70 publications from 1991-2020, while Collins had 194 citations against only 30 publications. The article titled “The access/impact problem and the green and gold roads to open access” having 223 citations. The countries’ collaboration was shown that the USA and Canada were having 20 research collaborations during 1991-20. Academic libraries, open access, and electronic resources were the most used keywords by the authors. It can be beneficial for readers to understand highly cited journals, the most prolific authors and the bibliographic coupling of institutions. It is also helpful for and editorial team of SR for further developments.
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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 arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.008 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.107 | 0.144 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".