Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it