Development and Evaluation of the Arabic Index of Premature Ejaculation (AIPE)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: Our report describes the construction and evaluation of the Arabic Index Premature Ejaculation (AIPE) as a diagnostic tool for premature ejaculation (PE) and presents data supporting its validity. METHODS AND MAIN OUTCOME MEASURES: Seventy-one men complaining of PE and 73 healthy subjects were asked to complete the seven-question AIPE. Diagnosis of PE was based on the criteria set by the second consultation on sexual dysfunctions. The seven items selected were based on assessment of erectile function, sexual desire, ejaculation latency, ejaculation control, patient satisfaction, partner satisfaction, and psychological distress. The AIPE was examined for sensitivity, specificity, and construct validity. RESULTS: A receiver operating characteristic curve indicated that the AIPE is an excellent diagnostic test. A cutoff score of 30 (range of scores 7-35) discriminated best (sensitivity = 0.98, specificity = 0.88). Severity of PE ranged from none (31-35) to severe (7-13). A high kappa value (0.85) indicated existence of significant agreement existed between the predicted and "true" PE classes. CONCLUSIONS: AIPE shows a potential to be a reliable aid to decrease the number of misdiagnosed cases of PE.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it