Bibliographic record
Abstract
Abstract Leone Caetani’s life (1869-1935) was definitely not a common one. Prince of Teano and duke of Sermoneta, he was immersed on the cream of Italian and international aristocracy of his age age of colonialism, age of adventurous travelling. On the tracks of his travels in the Middle East and in the far West, his studies and his personal writings, we tried to sketch this extraordinary figure of Orientalist on the field, of refined and renowned historian of the first period of Islam. A life through the life itself. This — we imagine — may be the right keyword to interpret his natural aptitude for extreme travels from East to West and the back to East — in the Sinai (1888-1889) and Sahara deserts (1890), in the Far West and the Rocky Mountains of Canada (1891), and back in Persia (1894) and India (1899) —, his pulsating interest for the Arabs and their origins, his craving desire to be “with boots in the mud” and “geography in his pocket”. Versed in the languages he used them to get in touch with cultures and peoples almost unknown — such as the Yazidi —, steadily convinced that only a first-hand experience could give back the exact taste of the truth. He was among the first Italians to explore the Sinai and the first Italian traveller ever in the sands of the Algerian Sahara.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".