Bibliographic record
Abstract
Imagine you have a choice. Tomorrow, you can either be dead, or you can choose a 1% chance of survival. For most of us, it's an easy decision; the odds of survival aren't good, but they are better than certain death. Now imagine that you are trying to persuade a patient not to receive cardiopulmonary resuscitation (CPR). ‘It almost certainly would not work, would only prolong the dying process,’ you explain. But CPR could work: there is perhaps a 1% chance of surviving to see another day. Why would patients choose not to receive it? However, despite most people's clear preference for continued life, the collective experience of clinicians is that CPR should not always be performed, and in many groups of patients, should only rarely be attempted. Individual physicians are required to respect this experience, while at the same time maintaining a high-quality doctor-patient relationship and providing realistic choices to seriously ill patients.
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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.017 |
| Insufficient payload (model declined to judge) | 0.051 | 0.016 |
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".