Bibliographic record
Abstract
This research paper aims to scrutinize the image of Spain in the light of the travelogue of Dr. Husain Mounis, in which he portraits the biographical aspects of Spain. It is all about beautiful landscapes, historical buildings, grand mosques, beautiful cities, culture, customs, and traditions of the people in a very unique and fascinating manner. Travelogue is an important part of literature in any of the world languages. All the nations are fond of Traveling and Journey since ancient times. The journey has gained special importance in Islamic literature and many scholars have been known to be adventurous travelers in different periods of time. Dr. Hussain Mounis is also one of them. He looks at the situation anywhere from a different perspective, making his travel journey different from the other and portraits the beautiful Picture of Andulas. This paper consists of a preface, two chapters and a conclusion. In the introduction, an importance of travelogue has been given. In the 1st chapter gives brief introduction of Dr. Hussain Mounis and his contributions in the field of Arabic language. The 2nd chapter explains the portrait of Andulas.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.983 | 0.982 |
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".