Bibliographic record
Abstract
Dear Readers, Journal of interdisciplinary Sciences (JIS) is now completing its eight years of publication journey. However, this year in September, we were hit by the heavy rainfall causing the consequences of excessive flooding, which apparently also flooded the JIS office destroying every document and equipment’s. But we were determined to offer our continuous services to the authors and the readers around the world who depended on us for their publication which encouraged ourselves to meet the publication date of November 2nd, publishing its volume 8, issue 2. In this Volume 8, issue 2, JIS is only publishing few papers from interdisciplinary sciences. We will now start working with the next volume for the year 2025 and we hope we can continue to serve the educational and scientific community. We look for your support and expect to receive your submission. Thank you Let us join and collaborate together to ENRICH the BEAUTIFUL MINDS TOWARDS INTELLIGENT MINDS Mani Man Singh Rajbhandari. Ph.D. Founder and Editor-in-Chief Journal of Interdisciplinary Sciences (JIS) www.journalofinterdisciplinarysciences.com
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 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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.188 | 0.131 |
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".