Atoms and Alchemy: Chymistry and the Experimental Origins of the Scientific Revolution
Bibliographic record
Abstract
Since the Enlightenment, alchemy has been viewed as a sort of antiscience, disparaged by many historians as a form of lunacy that impeded the development of rational chemistry. But, in Atoms and Alchemy, William R. Newman - a historian widely credited for reviving recent interest in alchemy - exposes the speciousness of these views and challenges widely held beliefs about the origins of the Scientific Revolution. Tracing the alchemical roots of Robert Boyle's famous mechanical philosophy, Newman shows that alchemy contributed to the mechanization of nature, a movement that lay at the very heart of scientific discovery. Boyle and his predecessors - figures like the mysterious medieval Geber or the Lutheran professor Daniel Sennert - provided convincing experimental proof that matter is made up of enduring particles at the microlevel. At the same time, Newman argues that alchemists created the operational criterion of an atomic element as the last point of analysis, thereby contributing a key feature to the development of later chemistry. Atoms and Alchemy thus provokes a refreshing debate about the origins of modern science and will be welcomed - and deliberated - by all who are interested in the development of scientific theory and practice.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".