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Record W2804203325 · doi:10.1097/ogx.0000000000000552

Chronic Pelvic Pain in an Interdisciplinary Setting: 1-Year Prospective Cohort

2018· article· en· W2804203325 on OpenAlexaff
Catherine Allaire, Christina Williams, Sonja Bodmer-Roy, Sean Zhu, Kristina Arion, Kristin Ambacher, Jessica Wu, Ali Yosef, Fontayne Wong, Heather Noga, Susannah Britnell, Holly Yager, Mohamed A. Bedaiwy, Arianne Albert, Sarka Lisonkova, Paul J. Yong

Bibliographic record

VenueObstetrical & Gynecological Survey · 2018
Typearticle
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsMedicinePsychosocialEtiologyPelvic painCohortProspective cohort studyPhysical therapyCohort studyGynecologyGeneral surgeryInternal medicineSurgeryPsychiatry

Abstract

fetched live from OpenAlex

(Abstracted from Am J Obstet Gynecol 2018;218:114.e1–114.e12) Chronic pelvic pain (CPP) is a common clinical problem among women. Its etiology is complex and involves an interplay of gynecologic, urologic, gastrointestinal, musculoskeletal, and psychosocial comorbidities.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.035
GPT teacher head0.363
Teacher spread0.328 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations6
Published2018
Admission routes1
Has abstractyes

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