Too much of a good thing: management of diabetic ketoacidosis in adults.
Bibliographic record
Abstract
A healthy 19-year-old man presents to your emergency department complaining of weakness and lethargy for the past 2 weeks. He sleeps 10 hours a day, yet remains tired. His appetite has been poor and he constantly feels thirsty. He voids frequently with no dysuria or hematuria. For the past 24 hours, he has been experiencing moderately severe and diffuse abdominal pain; he vomited 4 times in the past 2 hours. He has lost 10 kg over the past 2 weeks. He denies other symptoms or using drugs or medications, and he drinks alcohol only socially. His personal and family medical histories are not relevant. An examination reveals blood pressure of 115/60 mm Hg, heart rate of 135 beats per minute, temperature of 36.9°C, respiration rate of 24 breaths per minute, and oxygen saturation of 100% on room air. The patient is alert and appears uncomfortable, retching repeatedly. The mucosae are dry and the abdomen soft but diffusely tender, with normal bowel sounds and no peritoneal signs. There is no costovertebral angle tenderness. Findings from the remainder of the examination are noncontributory. A bedside glucometer displays “High-High-High.” Laboratory investigations reveal a white blood cell count of 14.2 × 109/L, a hemoglobin level of 143 g/L, a platelet count of 365 × 109/L, a sodium level of 133 mmol/L, a potassium level of 2.9 mmol/L, a chloride level of 103 mmol/L, a blood urea nitrogen level of 17 mmol/L, a creatinine level of 144 μmol/L, a glucose level of 29.7 mmol/L, an arterial pH of 7.10, a Pco(2) of 23 mm Hg, a Po(2) of 95 mm Hg, a bicarbonate level of 11 mmol/L, and an oxygen saturation of 95%. Urinalysis results are positive for high levels of ketones and glucose. How would you approach this patient?
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".