Cuneiform Texts from the Folios of W. G. Lambert, Part Two
Bibliographic record
Abstract
This book publishes 323 handcopies of cuneiform tablets found in the academic papers of W. G. Lambert (1926-2011), one of the foremost Assyriologists of the twentieth century. Prepared by A. R. George and Junko Taniguchi, it completes a two-part edition of Lambert's previously unpublished handcopies. Written by Babylonian and Assyrian scribes in ancient Mesopotamia, the texts collected here are organized by genre and presented with a descriptive catalogue and indexes. The contents include omen literature, divinatory rituals, religious texts, a scribal parody of Babylonian scholarship, theological and religious texts, lexical lists, god lists, and a small group of miscellaneous texts of various genres. The tablets are mainly from the British Museum, but some come from museums in Baghdad, Berlin, Chicago, Geneva, Istanbul, Jerusalem, New Haven, Oxford, Paris, Philadelphia, Tokyo, Toronto, and Washington. In addition, there are copies of eight tablets whose current whereabouts are unknown. This third collection of Lambert's handcopies published by Eisenbrauns-following Babylonian Creation Myths and Cuneiform Texts from the Folios of W. G. Lambert, Part One-is a crucial part of the intellectual history of the field of Assyriology. In addition, many of these texts are published herein for the first time, making them a valuable and important resource for further study.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.009 |
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".