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Record W2127832049

Repair of obstetric perineal lacerations.

2003· article· en· W2127832049 on OpenAlexaff
Lawrence Leeman, Maridee Spearman, Rebecca G. Rogers

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsMedicineEpisiotomyFecal incontinenceAnal sphincterSurgeryUrinary incontinencePerineumIncidence (geometry)External anal sphincterForcepsSphincterVaginal deliveryForceps deliveryRectumPregnancyAnal canal
DOInot available

Abstract

fetched live from OpenAlex

Family physicians who deliver babies must frequently repair perineal lacerations after episiotomy or spontaneous obstetric tears. Effective repair requires a knowledge of perineal anatomy and surgical technique. Perineal lacerations are classified according to their depth. Sequelae of obstetric lacerations include chronic perineal pain, dyspareunia, urinary incontinence, and fecal incontinence. With lacerations involving the anal sphincter complex, particular attention must be given to anatomy and surgical technique because of the high incidence of poor functional outcomes after repair. An overlapping technique to repair the external anal sphincter, rather than the traditional end-to-end technique, is being investigated to determine if it might decrease the incidence of anal incontinence. Minimizing the use of episiotomy and forceps deliveries can decrease the occurrence of severe perineal lacerations.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.022
GPT teacher head0.239
Teacher spread0.217 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations37
Published2003
Admission routes1
Has abstractyes

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