Bibliographic record
Abstract
A previously healthy, 2-year-old boy presented to the emergency department with 3 days of fever, cough, four episodes of post-tussive emesis with streaks of blood, two loose bowel movements and decreased urine output. The parents had noticed increased work of breathing for 12 hours. On physical examination, he was ill-looking and irritable, calming in his mother’s arms. Heart rate was 170/minute, respiratory rate 56/minute and oxygen saturation 86%. Capillary refill was 2–3 seconds, there was increased work of breathing (intercostal retractions, tracheal tug, nasal flaring), and occasional bilateral crackles with no wheezing. The child was stabilized, receiving high flow oxygen, a bolus of 20 mL/kg of IV normal saline and one dose of 100 mg/kg of ceftriaxone. Blood work was as shown (Table 1). A portable chest radiograph was ordered (Figure 1). ... He was admitted to the paediatric intensive care unit for 24 hours, receiving respiratory support with continuous positive airway pressure and a blood transfusion of red packed cells. Blood cultures and viral swabs were negative. He was discharged home after 3 days of clinical observation. He was prescribed iron supplements and his family was asked to follow up with his paediatrician with the diagnosis of viral pneumonia and iron deficiency anaemia.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".