Bavaria in the tenth and early eleventh centuries
Bibliographic record
Abstract
In the summer of 814 Louis the Pious had organised the Frankish subkingdoms, among which Bavaria was named for the first time. A further tradition of Carolingian Bavaria was its polyethnic structures based on Roman, German and Slav traditions, and its openness to the south and west. Among the Slav neighbours of Carolingian Bavaria the Moravians had formed the most powerful polity both in political and in ecclesiastical terms. Arnulf was evidently still a young man when he began to restore and consolidate the Bavarian regnum after his father's death in 907. Arnulf acknowledged the integrity of the east Frankish kingdom and in return was able to retain his quasi-regal rule over Bavaria; indeed, it was probably Henry's recognition which first enabled him to establish it firmly. In the second half of the tenth century there was a noticeable increase both in intellectual activity and in the use of writing in the Bavarian bishoprics.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".