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Record W4387265344 · doi:10.55512/wmo546038

Ten Newly Identified Fragments of the Sanskrit <em>Saddharmapuṇḍarīka-sūtra</em> (SI 6780) in the Serindia Collection (IOM, RAS)

2023· article· en· W4387265344 on OpenAlexfundno aff
Artiom V. Mesheznikov

Bibliographic record

VenueПисьменные памятники Востока · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicIndian and Buddhist Studies
Canadian institutionsnot available
FundersUniversity of CambridgeMcMaster University
KeywordsSanskritBuddhismDharmaReincarnationLiteratureArtHistoryPhilosophyTheologyArchaeology

Abstract

fetched live from OpenAlex

The present paper deals with ten previously unpublished Sanskrit fragments that have been identified with the Buddhist text of the Mahāyāna tradition Saddharmapuṇḍarīka-sūtra, or Lotus Sūtra. These fragments have had no call numbers until recently and were found among the non-inventoried materials of the Serindia Collection (IOM, RAS), which were set aside for restoration. The fragments are written in the South Turkestan Brāhmī type of script, which was in use for recording Sanskrit texts in the Southern Serindia in the 89 centuries A.D., primarily in Khotan, one of the largest Buddhist centers in Central Asia in the 1st millennium A.D. The largest part of Sanskrit texts in the Serindia Collection is presented by the manuscripts from Khotan, which, according to contents, reflect the popularity of Mahāyāna texts in the Southern Serindia, with the Lotus Sūtra texts in Sanskrit being especially popular, numbering over 30 storage units. The fragments under study, which are currently stored in the Serindia Collection under the call number SI 6780, contain extracts from three chapters of the Lotus Sūtra: Chapter XVIII (Anumodanāpuṇyanirdeśa-parivartaḥ The Chapter Describing the Religious Merit [Obtained through] Joyful Participation [in Dharma]), Chapter XIX (Dharmabhāṇakānṛśaṃsa-parivartaḥ Benefits of a Dharma Preacher) and Chapter XX (Sadāparibhūta-parivartaḥ [Bodhisattva] Sadāparibhūta). This paper includes a description of the fragments, their transliteration and comparison with two currently known Sanskrit Lotus Sūtra versions, as well as a Russian translation, and a facsimile.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.027
GPT teacher head0.236
Teacher spread0.209 · 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

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