Oxygen Therapy: A Scientometric Mapping of Indian Publications
Bibliographic record
Abstract
The present study has been carried out to find out the research performance in the field of Oxygen Therapy in India during 1991-2021 as indexed in the Web of Science database. A total 1648 research publications have been found in the Web of Science during 31 years period of 1991-2021 and were downloaded for analyze with the help of Histcite, VosViewer and Biblioshiny. The study also provide comparative performance of different Scientometric parameters including total research productivity, yearly research output, authorship pattern, International collaboration, Institution wise concentration, Source wise distribution of publications, Subject wise publications, most prolific authors and highly Cited papers etc. The most collaborated countries are: United States with 177 (14699 Citations), Saudi Arabia with 54 (3235 Citations), UK with 52 (9432 Citations), Australia with 49 (8418 Citations), Canada with 46 (8666 Citations). The most productive Institutions are: Indian Institute of Science Bangalore with 106 publications and registered 3018 Citations followed by Indian Institute of Technology with 84 and registered 1815 Citations, All India Institute of Medical Science with 72 (3372 Citations), Bhabha Atom Res Centre with 41 (549 Citations), Postgrad Institute of Med Education & Research with 36(927 Citations). The most preferred journals were: RSC ADVANCES topped the list with 32 (496 Citations) articles followed by DALTON TRANSACTIONS with 25 (885 Citations) articles, MATERIALS SCIENCE & ENGINEERING C-MATERIALS FOR BIOLOGICAL APPLICATIONS with 21 (564 Citations) articles, JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY B-BIOLOGY with 20 (309 Citations) articles. The average number of publications published per year was 29.79 the highest number of papers 217, 166, 152 were published in 2020, 2019, 2018. Authorship and collaboration trend was towards multi-authored papers (1648) from 8575 authors. The collaboration Index is 5.19.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.085 | 0.115 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".