The Archimedes Palimpsest
Bibliographic record
Abstract
Introduction: the Archimedes Palimpsest project William Noel Part I. The Manuscripts: Part II. History: 1. The making of the Euchologion Abigail Quandt 2. The strange and eventful history of the Archimedes Palimpsest John Lowden 3. Itinera Archimedea: on Heiberg in Constantinople and Archimedes in Copenhagen Erik Petersen Part III. Conservation: 4. Conserving the Archimedes Palimpsest Abigail Quandt Part IV. The Digital Palimpsest: 5. Imaging and image-processing techniques William A. Christens-Barry, Roger L. Easton, Jr and Keith T. Knox 6. Imaging with x-ray fluorescence Uwe Bergmann 7. The Palimpsest data set Doug Emery, Alex Lee and Michael Toth Part V. The Texts: 8. The Palimpsest in context Natalie Tchernetska and Nigel Wilson 9. The place of Codex C in Archimedes scholarship Reviel Netz Appendix: concordance of foliations.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.045 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".