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Record W4327813119 · doi:10.5281/zenodo.7746874

Iron Tonics: Tracing the Development from Classical to Iatrochemical Formulations in Ayurveda

2023· article· en· W4327813119 on OpenAlexaff
Dagmar Wujastyk

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Medicinal Plants
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTracingEpistemologyComputer sciencePhilosophyProgramming language

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.004

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.

Opus teacher head0.054
GPT teacher head0.291
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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