A Scientometric Assessment of Indo-US Collaboration Pattern in Leishmaniasis Research during 2012–2016
Bibliographic record
Abstract
This study examines the pattern of growth and collaboration in leishmaniasis research for the year 2012–2016 as indicated by papers indexed in Science Citation Index-Expanded. The study found that Brazil is world's most prolific producer of leishmaniasis research and has the second lowest international collaboration rate among the countries. USA was the top partner for India, showing 68 co-affiliated papers with India. Salton's measures clearly indicate that India's strongest mutual collaborative partner is Belgium (0.124) and then USA (0.084). On USA's side, Salton's measure for Brazil was highest (0.157). Out of 68 paper, 59% were bilateral (involving only India and USA) and 29 multilateral (involving other countries also with India and USA. A highly significant difference observed in CPP for domestic Indian papers (listing India-affiliated researchers only) was 6.0 and for domestic USA papers 9.34. For papers listing both Indian and USA authors (international or multilateral China-Canada collaborations) the CPP was 138.44. Thus, collaboration with USA dramatically increases the average citation rate for India-based researchers. Prolific institution, journal and author were discussed for Indo-US collaborated papers.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.039 | 0.086 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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, 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".