Bibliographic record
Abstract
While reading the Hebrew Bible, it is possible for modern readers to misunderstand the original Hebrew meanings of the English translations. Common words such as ‘heart’, ‘mind’, ‘soul’ (נפש) and ‘spirit’ (רוח) are often misinterpreted to have English connotations that were not used in the Hebrew Bible. For instance, the biblical Hebrew words (לבב ,לב and לבח), frequently translated as ‘heart’ had connotations that could be argued to correspond more accurately to the English definition of the word ‘mind.’ Conversely, the biblical Hebrew word (לב or לב), generally interpreted as ‘mind,’ is perhaps better understood in relation to the modern understanding of the heart as one's emotional centre. Also, as opposed to the non-physical modern notion of an immortal ‘soul’, biblical authors and their intended audiences understood it in relation to the physical. Furthermore, ‘spirit’ meant the energy and character of oneself and had divine connotations as associated with the breath or divine essence of YHWH. Therefore, in order to appropriately understand the Hebrew Bible, the fallibility of translation must be recognized.
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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.682 | 0.626 |
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".