Bibliographic record
Abstract
The Aṣṭādaśa Purāṇas (the eighteen major Purāṇas) were essentially religious and cultural documents, some of them preserved mathematical concepts within their cosmology, astronomy, ritualism, architecture and chronology. This work discusses the mathematics in Purāṇic literature, with an emphasis on large numbers, place value (in positional number systems), units of measure including a section on time and introductory level geometry. The Purāṇas use cosmological time scales that are readily understandable to laypersons, unlike new units of time, such as microseconds. The ideas of space are evident in the representations (images) of altars, temples, mandalas and celestial spaces and those of number/ratio in ritual operations that would have been implicit evocations or calculations. Astronomical mathematics: planetary motions and time cyclesAstronomical mathematics, such as the study of planetary motion through time and comprising cycles, also demonstrates the intertwining of celestial reason with mathematical thought. Through exploring correspondences with these mathematical items, the paper makes a case for the Purāṇas to work not just as theological and mythological texts but also vehicles of scientific and mathematical learning in early India. This kind of interdisciplinary study highlights that the Purāṇic literature contributed to the early Indian mathematical tradition and intellectual history.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| 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".