Bibliographic record
Abstract
To the Editor: We thank Dr. Zorowitz for his thoughtful explication of the differences between the three major streams of Judaism, and we agree for the most part with him. Space restraints did not allow us to go into much detail with respect to any of the three religions described in our work. As such, we directed the interested reader to appropriate references. That being said, we stand by our contention that overall doctrinal differences within Judaism relevant to care of the elderly are on the whole narrower than between those found in various other faiths. (For example, see the varieties of Christianity (e.g., Protestant, Roman Catholic, Greek Orthodox, Russian Orthodox)). The differences within Judaism are primarily of degree and not of substance, although quantitative changes can in the end affect qualitative ones. We certainly agree with Dr. Zorowitz that one should make no assumption about how a patient or family member will react simply according to his or her stated religious preference. It is only one of many variables but one about which there has not been much discussion in the geriatric medical literature to date.
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 | 0.005 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.029 | 0.042 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".