SCHMID, Alois, WEIGAND, Katharina, Die Herrscher Bayerns. 25 historische Portraits von Tassilo III. bis Ludwig III.
Bibliographic record
Abstract
Après les empereurs allemands (1519-1918) en 1990 et les souverains français (1498-1870) en 1994 (voir BullMHFA, 30/31, 1995, p. 254), le grand éditeur munichois se tourne désormais vers ses propres terres en consacrant cet ouvrage aux dynastes bavarois du VIe s. à 1918. La Bavière est en effet pratiquement le seul « duché originel » du royaume franc a avoir perduré sans grand changement et sans division irréductible jusqu’à aujourd’hui (voir les cartes en fin de volume), forgeant ainsi une v...
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.012 |
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; both teacher heads 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".