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
Pertussis has reemerged as a problem across the world. To better understand the nature of the resurgence, we reviewed recent epidemiologic data and we report disease trends from across the world. Published epidemiologic data from January 2000 to July 2013 were obtained via PubMed searches and open-access websites. Data on vaccine coverage and reported pertussis cases from 2000 through 2012 from the 6 World Health Organization regions were also reviewed. Findings are confounded not only by the lack of systematic and comparable observations in many areas of the world but also by the cyclic nature of pertussis with peaks occurring every 3-5 years. It appears that pertussis incidence has increased in school-age children in North America and western Europe, where acellular pertussis vaccines are used, but an increase has also occurred in some countries that use whole-cell vaccines. Worldwide, pertussis remains a serious health concern, especially for infants, who bear the greatest disease burden. Factors that may contribute to the resurgence include lack of booster immunizations, low vaccine coverage, improved diagnostic methods, and genetic changes in the organism. To better understand the epidemiology of pertussis and optimize disease control, it is important to improve surveillance worldwide, irrespective of pertussis vaccine types and schedules used in each country.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it