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Record W2522510617 · doi:10.1503/cjs.012016

A review of the literature and discussion: establishing a consensus for the definition of post-mastectomy pain syndrome to provide a standardized clinical and research approach

2016· review· en· W2522510617 on OpenAlexaffvenue
Murial Brackstone

Bibliographic record

VenueCanadian Journal of Surgery · 2016
Typereview
Languageen
FieldMedicine
TopicNerve Injury and Rehabilitation
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineBreast cancerMastectomyNeuropathic painPain syndromeGeneral surgeryBreast surgerySurgeryPhysical therapyCancerAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

SUMMARY: Chronic pain presents a management challenge for physicians and patients alike, and post-mastectomy pain is no exception. In this issue, Waltho and Rockwell present a review of post-mastectomy pain syndrome (PMPS) and propose a standard definition that should allow future studies to be comparable. The proposed definition of "post-breast surgery pain syndrome" includes pain after any type of breast surgery that is of at least moderate intensity and comprises neuropathic qualities, that is present in the ipsilateral breast/chest/arm, that lasts longer than 6 months and is present at least half the time. Further work is needed to clarify whether this pain syndrome is in fact driven by neuralgia resulting from the axillary dissection component of breast cancer surgery.

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)0.004
metaresearch head score (Gemma)0.010
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: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0020.001
Research integrity0.0030.003
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 head0.153
GPT teacher head0.402
Teacher spread0.249 · 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
GenreReview

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

Citations18
Published2016
Admission routes2
Has abstractyes

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