Bibliographic record
Abstract
A previously well nine-year-old girl was transferred to her local tertiary paediatric centre after 15 days of fever and lymphadenopathy. Her symptoms started with fever and headache, resulting in several visits to her family doctor and eventually a prescription for cefprozil. Despite antibiotic therapy, the fever persisted, with increasing malaise and the development of ‘lumps’ on the left side of her neck. She was brought to her local emergency room on day 9 of her illness. Assessment in the emergency room noted the above symptoms plus a complaint of myalgias, particularly when her temperature was at its highest. She also described persistent ‘backache’ localized to her spine. The review of her systems noted the absence of rashes, gastrointestinal symptoms, weight loss, anorexia or other constitutional symptoms. The patient's medical history was unremarkable, noting only attention-deficit hyperactivity disorder treated with methylphenidate. She had no known allergies, and her immunizations were up to date. The patient lived at home with her parents, step-sister and pet cat. All members of her family were well, with no contributory medical history, and none of whom had similar symptoms. She had not travelled outside of eastern Canada, where she was born, nor had tuberculosis or other sick contacts.
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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".