Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the flu season under way across Europe and North America, millions will be taking flu remedies, which commonly include painkillers. The general medical advice in the UK and the US is to take painkillers such as paracetamol (acetaminophen) or aspirin. But although painkillers can make people feel better they also lower fever, which can make the virus worse. The first analysis of the effect of this on the population shows that painkillers taken at current levels to treat fevers could cause 2000 flu deaths each year in the US alone. David Earn at McMaster University in Hamilton, Canada says that some studies have shown that lowering fever may prolong viral infections and increase the amount of virus they can pass on to others. To find out what impact this might have on a flu epidemic, Earn and his colleagues turned to a 1982 study which showed that ferrets, a common animal model for human flu, produced more seasonal flu virus if their fevers were lowered either with painkillers or by having their fur shaved off.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it