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Record W4390537008 · doi:10.62115/rbfp.2023.3(3)45-54

Manobra do Ligamento Largo reduz dor e outros sintomas da dismenorreia primaria

2023· article· en· W4390537008 on OpenAlexaboutno aff
Aline Aparecida Mufatto, Alana Tamisa Leonel

Bibliographic record

VenueRevista Brasileira de Fisioterapia Pelvica · 2023
Typearticle
Languageen
FieldMedicine
TopicMenstrual Health and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical therapyPopulationLigamentMcGill Pain QuestionnaireSurgeryVisual analogue scale

Abstract

fetched live from OpenAlex

Background: Primary dysmenorrhea corresponds to menstrual pain that affects 50% of women, making many unable to perform their ADLs. Aims: To evaluate the effects of an intrapelvic myofascial release maneuver for the perovarian region (Broad Ligament Maneuver), in reducing the symptoms of primary dysminorrhea. Method: Uncontrolled clinical trial with volunteers who answered questionnaires to classify pain level (VAS and McGill) and to screen premenstrual symptoms (PSST). Results: All participants showed positive results in all variables, both in reducing the level of pain and in other premenstrual symptoms. Conclusion: The Broad Ligament Maneuver is efficient in reducing symptoms associated with primary dysmenorrhea, reducing patients' pain in more than 70%, and by that constituting a promising non-drug alternative for half of the world's population who suffer from this problem.

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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.028
GPT teacher head0.333
Teacher spread0.305 · 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 designNon-randomized trial
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

Citations0
Published2023
Admission routes1
Has abstractyes

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