Availability and Accessibility of Research Outputs in NARS: A case study with IARI
Bibliographic record
Abstract
This article focuses on the trends in publication, authorship pattern, availability, and accessibility of articles during 2008–2010 from the Indian Agricultural Research Institute (IARI), a constituent of the National Agricultural Research System in India. The data reveal that during the period of study, researchers from IARI produced 1,833 publications, most of which were jointly authored, and that the most preferred journal for publication by researchers is the Indian Journal of Agricultural Sciences, which is now an Open Access journal. While publications from IARI are available to subscribers of the Consortium for e-Resources in Agriculture (CeRA), public availability to IARI publications is very meager. Hence, in order to make their research output more accessible and available to a wider audience, IARI researchers should deposit their work in IARI’s Open Access repository Eprints@IARI. However, making such a deposit requires an Open Access policy, which IARI is yet to adopt.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.228 | 0.088 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.029 | 0.093 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".