“Palatia” in Septimania: signs of Al-Andalus territorial organisation at the north of the Pyrenees
Bibliographic record
Abstract
Presence of Andalusian State in Septimania has been traditionally neglected, with few exceptions, by historiography. In this text, we try to offer a view of the territorial organisation of the Andalusian State at the north of the Pyrenees by means of a line of research, contrasted in Catalunya Vella, that identifies the toponyms derived from palatium with a primitive network of settlements built during the Islamic conquest. The study of documentary and toponymic sources reveals that these toponyms show the guidelines of a logical spread, always concentrated in southern Septimania. La presència de l’estat andalusí en terres septimanes ha estat, salvant comptades ocasions, tradicionalment negligida per la historiografia. En aquest text, tot aplicant una línia de recerca contrastada a Catalunya Vella que identifica els topònims derivats de palatium amb una primerenca xarxa d’establiments creats a partir de la conquesta islàmica, pretenem donar una primera visió de quin fou l’abast de l’organització territorial d’aquest estat al nord dels Pirineus. L’estudi de les fonts documentals i de la toponímia conservada ens permet veure com aquests topònims mostren unes pautes de dispersió coherents, alhora que es concentren sense excepcions a la meitat meridional de la Septimània.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".