Neuro-Urology: Call for Universal, Resource-Independent Guidance
Bibliographic record
Abstract
Neurogenic lower urinary tract dysfunction (NLUTD), the abnormal function of the lower urinary tract in the context of neurological pathology, has been the subject of multiple efforts worldwide for the development of clinical practice guidelines. These guidelines are based on the same body of evidence, and are therefore subject to the same gaps. For example, sexual and bowel dysfunction in the context of NLUTD, optimal renal function assessment in those who are non-ambulatory or with low muscle mass, optimal upper tract surveillance timing, and modification of diagnostic and treatment modalities for low-resource nations and communities are inadequately addressed. In addition, many aspects of the conclusions and final recommendations of the guidelines are similar. This duplicative work represents a large expenditure of time and effort, which we believe could be focused instead on evidence gaps. Here, we call for a global unified approach to create a single, resource-independent, comprehensive guidance on NLUTD, neurogenic sexual, and neurogenic bowel dysfunction. Targeted research addressing the evidence gaps should be called for and pursued. This will allow for focus to shift to filling the gaps in the evidence for future guidelines.
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 | 0.054 | 0.132 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.023 | 0.036 |
| Insufficient payload (model declined to judge) | 0.019 | 0.009 |
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".