Bibliographic record
Abstract
Dear Readers, The Journal of Interdisciplinary Sciences (JIS) wishes to announce the series publication of Volume 7, Issue 2 (November 2023). This issue include papers from interdisciplinary sciences from various discipline. Since the founding of the journal in 2017 until 2023, the academic journey have become very interesting in terms of academic collaboration, knowledge sharing and intellect transformations. Our next issue will be published in May 2024 we invite researchers, managers, leaders, scientists, students and others for paper submission. The call for paper submission is also announced in the journal’s announcement portal http://journalofinterdisciplinarysciences.com/announcement/ The Journal of Interdisciplinary Sciences (JIS) is an online open access journal, which offers free submissions, free publication and open access to download its published research paper from the journal’s website http://journalofinterdisciplinarysciences.com/ It is recommended that all author(s) submitting their manuscript to JIS are advised to read the author guidelines from the journal website http://journalofinterdisciplinarysciences.com/submit-your-papers/authors-guidelines/ 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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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; a candidate call from one teacher head, 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".