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Development and Evaluation of the Arabic Index of Premature Ejaculation (AIPE)

2006· article· en· W2017166515 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Sexual Medicine · 2006
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPremature ejaculationIndex (typography)ArabicEjaculationMedicinePsychologyComputer scienceInternal medicinePhilosophyLinguisticsPsychoanalysisWorld Wide Web

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.149

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.058
GPT teacher head0.319
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it