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Record W1983624319 · doi:10.3171/jns.2002.97.2.0388

Functional topography of the low postcentral area

2002· article· en· W1983624319 on OpenAlexaffabout
Warren Boling, David C. Reutens, André Olivier

Bibliographic record

VenueJournal of neurosurgery · 2002
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsPostcentral gyrusTongueMedicineSensory systemMagnetic resonance imagingAnatomyRadiologyNeurosciencePathologyPsychology

Abstract

fetched live from OpenAlex

OBJECT: The goal of this study was to establish a reliable method for identification of face and tongue sensory function in the lower central area. METHODS: All positron emission tomography (PET) clinical activation studies performed over a 3-year period at the Montreal Neurological Institute and Hospital were evaluated by coregistering the PET images with three-dimensional reconstructions of magnetic resonance images obtained in the same patients. In addition to stereotactic coordinates and measurements based on distance from the sylvian fissure, gyral and sulcal landmarks were analyzed to determine their reliability in localizing the sensory areas of the tongue and lower face. The convolutional anatomy of the central area is an important guide to the identification of function. The sensory area of the tongue is recognized as a triangular region at the base of the postcentral gyrus; the sensory area of the lower face resides in the narrowed portion of the postcentral gyrus, immediately above the tongue area. CONCLUSIONS: Cortical landmarks such as the substrata of tongue and face sensory impressions are more reliable guides than stereotactic coordinates or measurements for localizing function.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.484
Threshold uncertainty score0.164

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.285
Teacher spread0.193 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations45
Published2002
Admission routes2
Has abstractyes

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