Archaeology in Miskolc during a pandemic
Bibliographic record
Abstract
In the first quarter of 2020, the situation caused by the COVID-19 pandemic, similarly to other areas, \nfundamentally shook the museum sector, including archaeology, since contacting each other, welcoming \nvisitors, negotiating with investors, working in the field together, exchanging expertise on research and \nobject processing are all important parts of our everyday work. We tried to react quickly to the situation. It \nwas clear that we needed to increase our online presence, since for an indefinite period of time this would \nremain the only way of keeping in touch with our regular guests, with our volunteers, and reaching a new \nlayer with the promotion of archaeology. In addition, we had to solve the safe conditions for working in \nthe field, since it was soon proven that investments would continue despite the pandemic situation. Below, \nwe give an insight into how the Archaeology Department of the Herman Ottó Museum in Miskolc handled \nthe situation. Not from the viewpoint of scientific breakthroughs, but from the more personal aspects of \neveryday life.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".