Bibliographic record
Abstract
The article complements an earlier publication on the organization of the hussars for the 1683 Vienna campaign. According to the findings of that article, the final size of the crown lance cavalry was determined before May 19th, so before the date on which the subsidies of Emperor Leopold I for the new levies in the Crown Army were paid. Out of the 26 banners, 24 participated in the Battle of Vienna and the Battle of Párkány, which in the third billing quarter of 1683 (1 August – 31 October) comprised 3045 horses. It was ultimately ruled out that the hussar rota of the Brańsk starost Stefan Branicki fought at Vienna and Párkány, and it was confirmed that the banner of the Pomeranian voivode Władysław Denhoff took part in these battles. In 1683, the crown hussars reached their highest number in the second half of the 17th century, and almost all their banners (excluding two) took part in the decisive battles of the Vienna and Hungarian campaigns
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.030 | 0.017 |
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".