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Record W3139694760 · doi:10.1093/chemse/bjab018

Olfactory–Trigeminal Interactions in Patients with Parkinson’s Disease

2021· review· en· W3139694760 on OpenAlexafffund
Cécilia Tremblay, Johannes Frasnelli

Bibliographic record

VenueChemical Senses · 2021
Typereview
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsHôpital du Sacré-Cœur de MontréalUniversité du Québec à Trois-Rivières
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchParkinson Canada
KeywordsNeuroscienceOlfactory systemDiseaseParkinson's diseaseOlfactionModalitiesPsychologyMedicinePathology

Abstract

fetched live from OpenAlex

Olfactory dysfunction (OD) is a highly frequent early non-motor symptom of Parkinson's disease (PD). An important step to potentially use OD for the development of early diagnostic tools of PD is to differentiate PD-related OD from other forms of non-parkinsonian OD (NPOD: postviral, sinunasal, post-traumatic, and idiopathic OD). Measuring non-olfactory chemosensory modalities, especially the trigeminal system, may allow to characterize a PD-specific olfactory profile. We here review the literature on PD-specific chemosensory alteration patterns compared with NPOD. Specifically, we focused on the impact of PD on the trigeminal system and particularly on the interaction between olfactory and trigeminal systems. As this interaction is seemingly affected in a disease-specific manner, we propose a model of interaction between both chemosensory systems that is distinct for PD-related OD and NPOD. These patterns of chemosensory impairment still need to be confirmed in prodromal PD; nevertheless, appropriate chemosensory tests may eventually help to develop diagnostic tools to identify individuals at risks for PD.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-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 score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.189
GPT teacher head0.321
Teacher spread0.132 · 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

Citations13
Published2021
Admission routes2
Has abstractyes

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