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
Trachoma is caused by Chlamydia trachomatis. Clinical grading with the WHO simplified system can be highly repeatable provided graders are adequately trained and standardized. At the community level, rapid assessments are useful for confirming the absence of trachoma but do not determine the magnitude of the problem in communities where trachoma is present. New rapid assessment protocols incorporating techniques for obtaining representative population samples (without census preparation) may give better estimates of the prevalence of clinical trachoma. Clinical findings do not necessarily indicate the presence or absence of C. trachomatis infection, particularly as disease prevalence falls. The prevalence of ocular C. trachomatis infection (at the community level) is important because it is infection that is targeted when antibiotics are distributed in trachoma control campaigns. Methods to estimate infection prevalence are required. While culture is a sensitive test for the presence of viable organisms and nucleic acid amplification tests are sensitive and specific tools for the presence of chlamydial nucleic acids, the commercial assays presently available are all too expensive, too complex, or too unreliable for use in national programs. There is an urgent need for a rapid, reliable test for C. trachomatis to assist in measuring progress towards the elimination of trachoma.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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