Covid-19 Therapy and Treatment: A Scientometric Study of Indian Publications
Bibliographic record
Abstract
The paper examines 2539 Indian publications on Covid-19 Therapy and Treatment, as covered in Scopus database during 2019-May 2021. The top 10 most productive countries individually contributed global share of 33136, with USA accounting for the highest publication share with 8538, followed by China with 4558, Italy with 3707, United Kingdom with 3184, India with 2539, Spain with 1625, Germany with 1563, France with 1539, Canada. with 1353 and Iran with 1212 Publications. India is ranked at 5th position in global Covid-19 Therapy and Treatment research output. USA topped the list with 309 share in India’s international collaborative papers, followed by U.K. 161, Saudi Arabia 108, Australia 83, Italy 79 and China70, etc. The most productive Institutions are: All India Institute of Medical Sciences, New Delhi with 173 Publications, followed by Postgraduate Institute of Medical Education &Research, Chandigarh with 141, Datta Meghe Institute of Medical Sciences Deemed to be University with 71, Manipal Academy of Higher Education with 59. It is noted that 118 Institutions with more than 10 Publications, 5 Institutions with more than 50 Publications. The most preferred journals are: Journal Of Biomolecular Structure And Dynamics scored with 67 Publications, followed by Diabetes And Metabolic Syndrome Clinical Research And Reviews with 56, International Journal Of Current Research And Review with 42. The most leading authors are: Dhama, K. from Indian Veterinary Research Institute, Bareilly, India with 38 Publications followed by Tiwari, R. from College of Veterinary Science India, Tirupati, India with 23, Malik, Y.S. from Indian Veterinary Research Institute, Bareilly, India with 16, Javaid M from Jamia Millia Islamia, New Delhi, India, and Medhi, B. from Postgraduate Institute of Medical Education &Research, Chandigarh, Chandigarh, India, and Vaishya, R. Indraprastha Apollo Hospitals, New Delhi, India with 15 respectively. Major portion of these publications appeared in foreign journals of repute, as reflected by their impact factors and Citescores. The study also indicates that Indian scientists have huge international collaboration in this field Indian literature output peaked at about the same time as that of the world output. © 2021. All Rights Reserved.
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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 | 0.008 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.098 | 0.202 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| 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".