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Record W4378640280 · doi:10.1111/joor.13523

Fifty years of development of neuroscientific insights into oro‐facial pain and its control

2023· review· en· W4378640280 on OpenAlexaff
Barry J. Sessle

Bibliographic record

VenueJournal of Oral Rehabilitation · 2023
Typereview
Languageen
FieldHealth Professions
TopicTemporomandibular Joint Disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyOrofacial painSwallowingCognitionNeuroscienceMedicineCognitive psychologyPhysical therapyDentistry

Abstract

fetched live from OpenAlex

When the Journal of Oral Rehabilitation was established in 1973, there was very limited understanding of the mechanisms underlying neurally based functions, including those unique to the face, mouth and jaws (e.g. dental pain, taste, chewing, swallowing and salivation). Since that time, technological and other advances have led to new insights into the structure, connectivity and function of cranial nerves and areas of the central nervous system (CNS) involved in oro-facial functions and disorders or related functions (e.g. cognition, emotion, stress, consciousness, sleep, learning and memory). This review focuses on the advances in understanding of the neural basis of oro-facial pain and its control over the past five decades. The review first briefly considers how oro-facial pain conditions are now classified, diagnosed and managed. It then outlines novel insights that have been gained over this period through neuroscience research into the neural basis of these oro-facial pain conditions and the clinical relevance to these insights to the diagnosis and management of these conditions. The review also identifies promising research directions and gaps in knowledge that still need to be addressed to improve the understanding, diagnosis and management of oro-facial pain conditions.

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)0.005
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation 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 score0.974
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
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 head0.082
GPT teacher head0.435
Teacher spread0.353 · 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.

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

Citations11
Published2023
Admission routes1
Has abstractyes

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