Twenty Years, Twenty Publications and could have been More: Revisiting Research Collaboration with Professor Bidyut Kanti Datta
Bibliographic record
Abstract
Professor Bidyut Kanti Datta, a renowned professor of the Department of Pharmacy, Faculty of Pharmacy, University of Dhaka, died at the age of 73 on Friday 11 September 2020 in Canada (Canadian time 7.10 am and BD time 5.10 pm), as a consequence of COVID-19 infection followed by pneumonia. This article is a brief review of his research work where the authors of this article are immensely proud to be associated with. Prof Datta published more than 60 research articles in reputed journals, and the lead author (SDS) of this article, one of his former students from the University of Dhaka, is a co-author of 20 of those publications. These 20 publications resulted from a long-standing research collaboration that spanned over two decades, especially research involving various Bangladeshi species of the genus Polygonum L. of the family, Polygonaceae, and they demonstrate the breadth and depth of research activities that Prof Datta was involved in, and his long-standing commitment to research that underpinned and enriched his teaching offerings to hundreds of students he taught in higher education sector in Bangladesh. Dhaka Univ. J. Pharm. Sci. 19(2): 97-103, 2020 (December)
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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 | 0.219 | 0.353 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.016 | 0.021 |
| Scholarly communication | 0.041 | 0.046 |
| Open science | 0.004 | 0.028 |
| Research integrity | 0.009 | 0.020 |
| Insufficient payload (model declined to judge) | 0.007 | 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".