Bibliographic record
Abstract
Acute pyelonephritis should be classified clinically at the time of presentation into either uncomplicated or complicated categories. The diagnostic workup includes history, physical examination, urinalysis (including a Gram stain), and urine culture. Patients with suspected complicated pyelonephritis require the standard assessment plus blood cultures and urinary tract imaging, preferably a computed tomography (CT) scan. Patients with moderate, uncomplicated pyelonephritis can be managed as outpatients with either a fluoroquinolone (7-14 days) or trimethoprim/sulfamethoxazole (at least 14 days). Patients with severe, uncomplicated pyelonephritis can be considered for short-term hospitalization and initial administration of intravenous antibiotics. Therapy for patients with complicated pyelonephritis should include initial hospitalization, supportive therapies, administration of wide spectrum intravenous antibiotic therapy, and relief of aggravating conditions. Such maneuvers could consist of simple bladder catheterization, percutaneous nephrostomy drainage, or definitive surgery. Patients with complicated pyelonephritis require longer duration of culture-specific antibiotic dosing, careful monitoring, long-term follow-up, and possible definitive management of their underlying condition.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".