Bibliographic record
Abstract
APF Command and Staff College is established to enhance the professionalism of mid-level officers of Armed Police Force, Nepal. The college is imparting empirical knowledge blending it with the practical aspects, so that officers will be able to cope with the emerging non-traditional security paradigms and other security concerns. Apart from its designed syllabus, College is also conducting seminars, conferences and workshops as part and parcel in cooperation and collaboration to Tribhuvan University and other academic institutions. College has published this noble journal to reflect its conceptual, theoretical and empirical research. The research has been confined to ethos of security, development and peace spectrum. It encompasses articles from scholars, researchers and practitioners aligning it with contemporary issues and security related dynamics of modern era. Professors, academics, researchers, policy makers and students may seize learning opportunity and will highly be benefited from the articles included in the journal. The editorial board reserves the right to edit, moderate or reject the article submitted. The articles included in this journal are mostly research based. Views expressed in the articles are purely personal and academic opinion of the authors and are not necessarily endorsed by APF Command and Staff College and editorial board.
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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.102 | 0.080 |
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".