Bibliographic record
Abstract
This volume offers a very useful commentary, mostly solid but not ground-breaking, on a once neglected Septuagintal book. After a list of more than 30 major manuscripts (Greek, Latin, Hebrew, Aramaic, and Syriac), plus a map of the Assyrian empire in the eight century bce, the volume begins with a 30-page introduction, covering topics such as textual witnesses, canonicity, original language (probably Aramaic), date of origin (third or second century bce), place of composition (uncertain), plot, historical setting, themes (e.g. kinship), Ancient Near Eastern parallels (the Assyrian story of Ahiqar and the Egyptian tale of Khons), Greek dialect, and modern commentaries. Thereafter the volume provides the Greek text of Tobit from Codex Sinaiticus with an English translation on each facing page. The main part of the volume (the next 120 pages) consists of commentary on the Sinaiticus text, dealing with both linguistic and theological matters. Near the end of the volume Littman presents the shorter Greek text of Tobit from Codex Vaticanus, again with an English translation on each facing page, but without a separate commentary. The volume ends with a bibliography, plus indexes of topics and biblical references.
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 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 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.103 | 0.035 |
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".