Hellenistic Astronomy: The Science in Its Contexts edited by Alan C. Bowen and Francesca Rochberg
Bibliographic record
Abstract
One of the daunting challenges involved in reviewing a 750-page standard tome on a subject like astronomy is being able to evaluate all aspects of the volume, covering technical data as well as any possible impact of subject matter on other disciplines. The editors, mindful of their readership consisting of both “insiders” and “outsiders”, have taken decisive steps towards making Hellenistic astronomy accessible and comprehensible, with an appropriate balance between complex graphs and arithmetic equations and more general topics, as well as a glossary of technical terminology. The present reviewer, an unrepentant “outsider”, will attempt to focus on some key issues involving the connections between Babylonian and Greek astronomy in the period in question, as well as the impact of astronomy as a whole. Reviewed by: M. J. Geller, Published Online (2021-08-31)Copyright © 2021 by M. J. GellerThis open access publication is distributed under a Creative Commons Attribution-NonCommercial-NoDerivatives License (CC BY-NC-ND) Article PDF Link: https://jps.library.utoronto.ca/index.php/aestimatio/article/view/37730/28731 Corresponding Author: M. J. Geller,University College LondonE-Mail: mark.geller@fu-berlin.de
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".