Bibliographic record
Abstract
t is clear from the paper by Tamarkina and colleagues 1 that as we know more about the pathophysiology of vesicoureteral reflux (VUR) in children, we know less on how to manage these patients.The pendulum is swinging toward pre-emptively treating patients with VUR, though we know that this entity is a benign condition and may not need any surgical or medical intervention.The authors raise many concerns in the treatment of VUR, the least being antibiotic prophylaxis; of note, after using the different medical approaches over past decades, flags are now being raised about the possible complications associated with antibiotics.Furthermore, we are not yet sure of the longterm outcome of deflux in the patients that we have already treated (e.g., local inflammatory changes or persistent resolution of reflux).A critical question may arise when treating patients with VUR pre-emptively: what are we going to do for patients in whom this "incidental anesthetic" approach fails?Are we going to bring them back to the operating room, or are we going to keep them on antibiotics and just watch them?Although there is a role for deflux in the treatment armamentarium of VUR management, it is clear that the "inci-
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".