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Record W4319034920 · doi:10.3389/fpain.2023.1111559

Contribution of microvascular dysfunction to chronic pain

2023· review· en· W4319034920 on OpenAlexafffund
Terence J. Coderre

Bibliographic record

VenueFrontiers in Pain Research · 2023
Typereview
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchLouise and Alan Edwards Foundation
KeywordsFibromyalgiaChronic painMedicineMicrocirculationComplex regional pain syndromePathologyPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

There is growing evidence that microvascular dysfunction is a pathology accompanying various injuries and conditions that produce chronic pain and may represent a significant contributing factor. Dysfunction that occurs within each component of the microvasculature, including arterioles, capillaries and venules impacts the health of surrounding tissue and produces pathology that can both initiate pain and influence pain sensitivity. This mini review will discuss evidence for a critical role of microvascular dysfunction or injury in pathologies that contribute to chronic pain conditions such as complex regional pain syndrome (CRPS) and fibromyalgia.

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 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)0.032
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.819
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0320.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.092
GPT teacher head0.405
Teacher spread0.313 · 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 teacher head, not a consensus.

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

Citations16
Published2023
Admission routes2
Has abstractyes

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