Bibliographic record
Abstract
#### Summary points Anaphylaxis is an alarming medical emergency,1 2 3 not only for the patient or caregiver, but also sometimes for the healthcare professionals involved. Although it is thought of as uncommon, the lifetime prevalence is estimated at 0.05-2%,4 5 and the rate of occurrence is increasing. Hospital admissions, although uncommon, are also increasing, as are admissions to critical care units.6 7 Many anaphylaxis episodes now occur in community settings.8 Accurate community based population estimates are difficult to obtain because of underdiagnosis, under-reporting, and miscoding, as well as use of different anaphylaxis definitions and different methods of case ascertainment in the populations studied.5 Although death from anaphylaxis seems to be uncommon, it is under-reported.9 In this article, we draw on evidence from randomised controlled trials, quasi-experimental and other observational studies, and systematic reviews. We also reference key evidence based international and national anaphylaxis guidelines and their updates.1 2 10 11 #### Sources and selection criteria We based this review on Medline and …
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".