Executive summary: The International Consultation on incontinence 2008—committee on: “Dynamic Testing”; for Urinary or fecal incontinence. Part 3: Anorectal physiology studies
Bibliographic record
Abstract
AIMS: The members of 'The International Consultation on Incontinence 2008 (Paris) Committee on Dynamic Testing' provide an executive summary of the chapter 'Dynamic Testing' that discusses testing methods for patients with signs and or symptoms of incontinence. Testing of patients with signs and or symptoms of urinary as well as testing of patients with fecal incontinence is discussed. METHODS: Evidence based and consensus committee report. RESULTS: The chapter 'Dynamic Testing' is a continuation of previous Consultation-reports added with a new systematic literature search and expert discussion. Conclusions, based on the published evidence and recommendations, based on the integration of evidence with expert experience and discussion are provided separately, for transparency. CONCLUSION: This third part of a series of three articles summarizes the recommendations given in the paragraph: 'Anorectal physiology studies' with regard to fecal incontinence (whether or not in combination with urinary incontinence) and includes only the most recent and relevant literature references.
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 | 0.019 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.052 | 0.031 |
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".