Bibliographic record
Abstract
Este artículo trata sobre la conquista de Libia y Túnez por Saladino (Salah al-Din) y los Ayyubíes en las décadas de 1170 y 1180. En primer lugar se presenta una reconstrucción de las campanas dirigidas por los mamelucos ayyubíes Sharaf al-Din Qaraqush e Ibn Qaratikin en Libia y de la guerra entre los almohades y los Ayyubíes en Ifriqiya (Túnez) basada en fuentes primarias relevantes. A continuación se estudia en qué medida Saladino fue el responsable de estas expediciones militares y, finalmente, se discute el motivo de dichas expediciones. Se llega a la conclusión de que Saladino y sus emires invadieron el Magreb con el fin de controlar los puntos septentrionales de los ejes oriental y central de las rutas comerciales que cruzaban el Sahara y con esto lograr tener acceso al oro de África Occidental que pasaba a lo largo de estas rutas. Esto ocurrió en un momento en que había una gran escasez de metales preciosos en Egipto y Saladino necesitaba efectivo para pagar sus guerras con los cruzados en Palestina.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".