Bibliographic record
Abstract
Abdul Sattar Dalvi enjoys a remarkable position in Urdu language and literature, research and criticism and in translation and linguistics. He devoted all his life to teach in different universities of the world. He is admired due to his intellectual and literary abilities not only in India but in Pakistan also. His literary master piece “Do Zubanain Do Adab (Urdu Hindi kay Tanazur Main)” is a part of the syllabus of Ph.D. Urdu in various universities of Pakistan. Progressive movement produced many sincere, able, intellectual and honest literary personalities e.g., poets, fiction and prose writers and critics. A prominent name among them was Ali Sardar Jafri. Abdul Sattar Dalvi was well aware of the status of his multifaceted personality, understanding his position and status he saved various articles, written an him, from the hands of the time. In this research work he has presented the articles of eminent writers on the personality, poetry and prose of Ali Sardar Jafri as evidence. This research article is an analysis of Abdul Sattar Dalvi’s work on Ali Sardar Jafri.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.985 | 0.989 |
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; the direct Gemma label and the distilled Codex classifier 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".