A kiskorú árvákról való gondoskodás az Eszterházy uradalom Győr vármegyei falvaiban a 19. század második negyedében
Bibliographic record
Abstract
Using the example of three settlements in Győr County, Gyömöre, Szerecseny, andMénfő, this study shows how minor orphans were cared for in the Eszterházyfamily's Pápa-Ugod-Devecser estate in the second quarter of the 19th century. Itbriefly discusses the most important characteristics of the document collections,then follows the fate of 53 orphans from 19 families in Gyömöre and 57 orphans from25 families in Szerecseny over a period of about two decades. Among other things, itexamines who the guardians were, who dealt with the affairs of the orphans, and howlong their assets remained in the orphan fund. Through the fate of Mihály Salamon'sfive orphans, it also attempts to show how a picture of a family can be pieced togetherfrom the remaining documents.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".