Bibliometric Analysis of Proceedings of the Paksitan Academy of Sciences: Part B from 2016 to 2021
Bibliographic record
Abstract
Proceedings of the Pakistan Academy of Sciences: Part B (Life and Environmental Sciences) is the official flagship journal of the Pakistan Academy of Sciences. It publishes in the fields of agricultural, biological, environmental and health sciences. Scopus database is directly covering it since 2016 and till 19th April 2022, it has published 210 research documents majorly comprising of articles (n=141), book chapters (n=36), conference papers (n=26), reviews (n=6) and one (n=1) note. It also received 232 total citations. We extracted the publication data from Scopus in BibTeX format and analyzed it on R-Studio. In all publications, 313 authors from 278 institutes or universities from 14 Asian, 6 European, 2 Middle East, 1 Oceanic (Australia), 2 North American, 1 South American (Brazil) and 3 African countries have contributed. The country co-authorship network (constructed on Vosviewer) is presented in Supplemnetaty data (Figure 1). The lists of all authors (with total publications (TP), total citations (TC), publications years, h-index, g-index and m-index), all universities (with TP) and countries (with TP) are provided in supplementary data (Table 1, 2 & 3). It has achieved considerable CiteScore (0.6), SJR (0.143) and SNIP (0.347) calculated on 05th May 2022 by Scopus for the year 2021. The success could be attributed to the editorial board (which has experts from Pakistan, Australia, Canada, China, USA, Turkey, Oman, Malaysia, and Indonesia), reviewers, authors, and editorial management. The number of publications, citations and its foothold in different countries confirm that the journal’s reputation is significantly improving
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 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 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.077 | 0.135 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".