Global Asthma Research with Special Reference to India: A Scientometric Assessment of Publication Output during 2007-16
Bibliographic record
Abstract
The paper examines 2094 Indian publications on asthma research, as covered in Scopus database during 2007-16, registering an annual average growth rate of 12.14%, global share of 2.72%, qualitative citation impact averaged to 10.857citations per paper and international collaborative publication share of 13.51%.The top 12 most productive countries individually contributed global share from 2.72% to31.27%, with largest global publication share coming from USA (31.27%), followed by U.K. (10.45%), Germany (5.60%), Canada (5.44%), etc. Together, the 12 most productive countries accounted for 83.80% share of global publication output during 2007-16.Medicine, among subjects, accounted for the highest publications share (61.32%), followed by pharmacology, toxicology & pharmaceutics (35.05%) biochemistry, genetics & molecular biology (20.25%), immunology & microbiology (7.78%), agricultural & biological sciences (3.44%) and chemistry (2.88%) and during 2007-16.Among different type of asthma, allergic asthma contributed the highest number of publications, followed by bronchial asthma, atopic asthma, occupational asthma and seasonal asthma, etc. during 2007-16.The top 15most productive organizations and authors together contributed 33.48% and 19.96% respectively as their share of global publication output and 43.88% and 36.93%respectively as their share of global citation output during 2007-16.Among 2059 journal papers, the top 15 journals contributed 25.89% share to the Indian journal output during 2007-16.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.063 | 0.172 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".