Case 2: Weight lost… and found
Bibliographic record
Abstract
A 17-year-old female was evaluated in the emergency department for syncope following a 10 kg weight loss over three months. The weight loss began after a trip to Europe. It was associated with burning postprandial epigastric pain and significantly decreased oral intake. Gaviscon (Prestige Brands Inc, USA), prescribed by her community gastroenterologist, had no effect. She denied any associated nausea, vomiting, changes in bowel movements, fevers, rigours, joint problems or skin complaints. Of note, she was amenorrheic for two months before presentation. Before the onset of symptoms, the patient enjoyed playing competitive soccer and was described as a high-achieving grade 12 student. On examination, her heart rate was 39 beats/min, blood pressure was 78/50 mmHg, weight was 44 kg (<5th percentile for age), height was 165 cm (50th to 75th percentile for age) and body mass index was 16.2 kg/m2 (<5th percentile for age). Examination of the skin, nails and teeth, and cardiac and respiratory systems were unremarkable. Abdominal examination revealed diffuse pain to deep palpation. She had a normal complete blood count, electrolyte levels and electrocardiogram. The patient was admitted to an eating disorders unit for medical stabilization, weight restoration and diagnostic work-up.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".