Bibliographic record
Abstract
A 22-year-old man presented with a 3-week history of increased thirst, polydipsia, and polyuria. He described consuming large volumes of water and waking up multiple times throughout the night to drink and urinate. He also endorsed symptoms of fatigue and frequent headaches. Prior to this, he had been well. There was no history of diuretic use, lithium use, or renal disease. There was no prior head trauma, cranial irradiation, or intracranial pathology. He denied consumption of nutritional or protein supplements. Clinical exam revealed a well appearing young man with normal heart rate and blood pressure. Visual fields and general neurologic exam were grossly normal.Baselines investigations revealed serum sodium ranging from 141–142 mmol/L (reference range 133–145 mmol/L), creatinine 92 umol/L (50–120 umol/L), random glucose 5.4 mmol/L (3.3–11.0 mmol/L), potassium 4.0 (3.3–5.1 mmol/L) and ionized calcium 1.25 mmol/L (1.15–1.35 mmol/L).A 24-hour urine collection was arranged, and returned a urine volume of 5.6L (normal less than 3 litres/24 hours). Further investigations revealed a serum sodium of 142 mmol/L, serum osmolality 306 mmol/kg (280–300 mmol/kg), and urine osmolality of 102 mmol/kg (50–1200 mmol/kg). AM cortisol was 372 nmol/L (200–690 nmol/L). These results demonstrated inability to concentrate the urine, despite the physiologic stimulus of hyperosmolarity. Based on this, a presumptive diagnosis of diabetes insipidus was made. The patient was instructed to drink as much as he needed to satiate his thirst, and to avoid fluid restriction. The patient was started on DDAVP intranasal spray, which provided immediate relief from his symptoms. Magnetic resonance imaging of the brain revealed an unremarkable pituitary gland with abnormal thickening of the pituitary stalk and loss of the posterior pituitary bright spot. This confirmed the diagnosis of central diabetes insipidus, presumed secondary to infiltrative disease affecting the pituitary stalk.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".