Tibetan inscriptions : proceedings of a panel held at the Twelfth Seminar of the International Association for Tibetan Studies, Vancouver 2010
Bibliographic record
Abstract
Inscriptions are a rather neglected field within Tibetan Studies, because they are often located in places that are not easily accessible for both geographical and political reasons. It is thus especially welcome that two of the contributions to this volume deal with inscriptions documented on recent field trips to Tibet: Benjamin Wood discusses an inscription in Zha lu that relates an enigmatic conflict in the history of the monastery, and Kurt Tropper looks into an epigraphic cycle on the life of the Buddha in Tsaparang. Moreover, Nathan Hill provides a new interpretation of the beginning of the famous Rkong po inscription, and Kunsang Namgyal Lama surveys the various kinds of texts found on tsha tshas. An extra level of reflection is added to the volume by Cristina Scherrer-Schaub's methodological considerations on the classification and interpretation of inscriptions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".