Bibliographic record
Abstract
Foreword Volume 4 of the new series of Aestimatio is now complete. Though the move to a print-when-ready model of publication took longer than we anticipated, we are finding that it works well for us and will, we trust, benefit our readers and authors also. As we close this volume and start work on the next, we find it a good time to reiterate the journal’s aim and to clarify some of the ways in which we want to pursue it going forward. When we established Aestimatio (new series), we stated our focus as the history of science from antiquity to the early modern period. We still recognize that the appropriate geo-cultural scope of science in the Old World before the modern era encompasses cultures in Eurasia and Africa. This chronological and geo-cultural scope allows Aestimatio to publish research situated in sources from Arabic, Byzantine, Syriac, and Slavic cultures. We are pleased that scholars in the sciences of these languages and cultures see a home for their work in our journal. As an example, volume 4 includes the publication of Florentina Badalanova Geller’s “Galen’s Nachlass in Slavonic Intellectual Landscapes: Knowledge Transmission in the Byzantine” [https://jps.library.utoronto.ca/index.php/aestimatio/article/view/44904] and volume 5 will include a focus section entitled “Diagrams in Medieval Europe: Magic, Science and Ritual” edited by Sophie Page and Richard Kieckhefer. We continue to promote work that seeks to place science in its Babylonian, Egyptian, Greek, and Latin cultural contexts, but want now to encourage submissions of research on the Syriac, Aramaic, Byzantine, and Old Church Slavonic as well as Arabic materials that all contribute to our knowledge of the sciences in late antique and medieval contexts. In pursuit of this goal, Chessie and I have invited and are delighted to welcome Anne-Laurence Caudano (University of Winnipeg) to our editorial staff. Anne-Laurence is a highly esteemed medievalist with a special interest in the history of Byzantine science. With her expertise and input, the journal stays true to its original and continuing commitment to the study of the sciences in the ancient Near Eastern and Mediterranean worlds and their later legacy in Byzantium, Western and Eastern Europe. Alan C. Bowen and Francesca Rochbergbowen@IRCPS.orgfrochberg@gmail.com How to cite: Bowen, A. C. and F. Rochberg, “From the Editors”. Aestimatio: Sources and Studies in the History 0f Science (2024) 5: vii–viii
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.413 | 0.374 |
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".