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Record W4378071961 · doi:10.3389/fpain.2023.1150749

Preclinical orofacial pain assays and measures and chronic primary orofacial pain research: where we are and where we need to go

2023· review· en· W4378071961 on OpenAlexaff
Shirin Sadighparvar, Faez Saleh Al‐Hamed, Reza Sharif‐Naeini, Carolina B. Meloto

Bibliographic record

VenueFrontiers in Pain Research · 2023
Typereview
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsOrofacial painEtiologyMedicinePathophysiologyChronic painChronic fatigue syndromeBurning mouth syndromePhysical therapyBioinformaticsDermatologyPathology

Abstract

fetched live from OpenAlex

Chronic primary orofacial pain (OFP) conditions such as painful temporomandibular disorders (pTMDs; i.e., myofascial pain and arthralgia), idiopathic trigeminal neuralgia (TN), and burning mouth syndrome (BMS) are seemingly idiopathic, but evidence support complex and multifactorial etiology and pathophysiology. Important fragments of this complex array of factors have been identified over the years largely with the help of preclinical studies. However, findings have yet to translate into better pain care for chronic OFP patients. The need to develop preclinical assays that better simulate the etiology, pathophysiology, and clinical symptoms of OFP patients and to assess OFP measures consistent with their clinical symptoms is a challenge that needs to be overcome to support this translation process. In this review, we describe rodent assays and OFP pain measures that can be used in support of chronic primary OFP research, in specific pTMDs, TN, and BMS. We discuss their suitability and limitations considering the current knowledge of the etiology and pathophysiology of these conditions and suggest possible future directions. Our goal is to foster the development of innovative animal models with greater translatability and potential to lead to better care for patients living with chronic primary OFP.

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)0.094
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.704
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0940.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.005
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 head0.294
GPT teacher head0.464
Teacher spread0.170 · 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; both teacher heads agree on what is shown here.

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

Citations15
Published2023
Admission routes1
Has abstractyes

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