A 5-month-old boy with bloody stools
Bibliographic record
Abstract
A 5-month-old previously healthy boy presented with bloody, loose green stools for 2 days. He was mostly breastfed with occasional dairy protein formula supplementation. His mother consumed an unrestricted diet. There was no history of vomiting, cellulitis, joint swelling, or eczema. The child was born at term by vaginal delivery. His birth weight was 3.77 kg (80th %) and height was 51 cm (60th %). He received antibiotics for presumed sepsis after prolonged maternal rupture of membranes. His parents were nonconsanguineous and of European background. His grandmother had irritable bowel syndrome. He appeared well, active, and not toxic. His weight was 6.5 kg (20th %) and height was 65 cm (50th %). His temperature was 37.5°C, heart rate was 120/minute, and blood pressure was 88 mmHg systolic. His perfusion and hydration were good. Abdominal, skin, mucous membrane, and perineal examinations were normal. Investigations showed a leukocytosis of 20.3 × 109/L (reference 5.0 to 15.0 × 109/L) and normal haemoglobin, albumin, and platelet counts. His stool smear demonstrated red and white blood cells. Stool culture, electron microscopy for virus, and abdominal radiograph and ultrasound were unremarkable.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".