Bibliographic record
Abstract
The future of the past – this was the philosophical point of view used by Helmi Uprus decades ago in interpreting manorial architecture, when the first summaries were compiled on the inventories of manors.1 The survival and preservation of cultural heritage involve topics which occasionally become clear only after a certain period of time, in hindsight, and where the future can sometimes be quite contradictory because of radical changes in society. By the mid-1970s, the temporal distance had become sufficient to tackle the topic of manors as cultural memory in real time and place, i.e. it was possible to seek out values that had been neglected for some reason and thus forgotten. Various painful aspects related to manors had lost their edge and manor houses had become a topic of architectural history. By the last quarter of the 20th century, about three generations had passed since manorial life ended2. During that time, emotions had cooled and ownership relations had changed. Manors now seemed like a distant romantic world, where our ancestors were busy as well, although mostly in the role of coachmen and cooks. World War I and the subsequent revolutions disrupted the continuity of manorial life, both politically and economically, and caused chaos in the way of life. The newly established Republic of Estonia and the
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".