Bibliographic record
Abstract
Research presented in this paper is primarily based upon two manuscripts from the Kongōji 金剛寺 manuscript set of the Buddhist canon: (1) Zhenyuan xinding Shijiao mulu 貞元新定釋教 錄 [Buddhist Catalogue Newly Revised during the Zhenyuan-era [785-805; T no.2157; henceforth Zhenyuan lu and abbreviated as Z.) no.0502-007(a&b)-008 and (2) Z no.1181-001.The first manuscript is a late-Heian period copy of what appears to be a Naraera manuscript of the apocryphal Shoulengyan jing 首楞嚴經 [Skt.*Śūraṃgama-sūtra; Book of the Hero's March], T no.945.The second manuscript is a Kamakura-era copy of a Nara period manuscript of the Xu gujin yijing tuji 續古今譯經圖紀 [Supplement to the Portraits and Records of Translated Scriptures, Past and Present, T no.2152], which is an account of nineteen translators compiled by Zhisheng 智昇 (active 700-740), in 730.Both of our earliest accounts of the composition of the Shoulengyan jing, the Kaiyuan shijiao lu 開元釋教錄 [Catalogue of Buddhist Texts Made during the Kaiyuan-era (713-741)] and Xu gujin yijing tuji agree that Huaidi 懷迪 and an anonymous 'Indian monk', rather than *Pāramiti, compiled the Shoulengyan jing.Yet almost all later sources in China and modern secondary studies of this important scripture ascribe the *Śūraṃgama-sūtra to *Pāramiti in error.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.006 |
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".