Iron Tonics: Tracing the Development from Classical to Iatrochemical Formulations in Ayurveda
Bibliographic record
Abstract
Around the eleventh century CE, Sanskrit medical texts began to record profound changes in the methods used for drug manufacture. New substances, especially metallic and non-metallic minerals, were added to the ayurvedic pharmacopoeia or were given new prominence. More significantly, however, new ways of processing raw materials were introduced that were thought to make them fit for medical use. Most of the new, but also many of the traditional substances were now put through a series of complicated, multi-stage processes before they were used as components of compound medicines. In this article, I will use the example of recipes for iron-based medicines, which describe the processing of iron and other substances to trace the evolution of these changes and to query whether the changes in drug production flow from earlier developments, or whether they represent a more fundamental shift in the theory and practice of medicine. I also consider whether the introduction of new substances and the new methods of drug production can be related to notions concerning the potency of substances and formulations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".