Review: simple questions and clinical tests are moderately useful for diagnosing urinary incontinenceCommentary
Bibliographic record
Abstract
J M Holroyd-Leduc Dr J M Holroyd-Leduc, Foothills Medical Centre, Calgary, Alberta, Canada; jayna.holroyd-leduc@calgaryhealthregion.ca How accurate are simple clinical procedures and tests for diagnosing urinary incontinence (UI) in adults? Studies selected evaluated clinical diagnosis of stress or urge UI in adults and used a reference standard of diagnosis by an expert (urologist or urogynaecologist) and/or urodynamic studies in all patients. Outcomes were summary positive (+LR) and negative (−LR) likelihood ratios. Medline and EMBASE/Excerpta Medica (to Jul 2007), and reference lists were searched for cohort and case–control studies published in English. 40 studies (age range 16–98 y, >99% women) met the selection criteria. Simple questions such as “Do you lose urine during sudden physical exertion, lifting, coughing, or sneezing?” and “Do you experience such a strong and sudden urge to void that you leak before …
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".