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Record W2037947254 · doi:10.1080/0899022021000009143

Differences in the sensations of warmth on the anterior torso of normal and spinal-cord transected individuals

2002· article· en· W2037947254 on OpenAlexaff
Robert W. Dykes, Fatima Saddiki-Traki, Nicole Tremblay, F. Boureau, X. Morel-Fatio

Bibliographic record

VenueSomatosensory & Motor Research · 2002
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsTorsoSpinal cordSensationMedicineCordAudiologyAbdomenSpinal cord injurySensory thresholdAnatomyPsychologySurgeryNeuroscience

Abstract

fetched live from OpenAlex

The threshold to warming was measured at 10 sites on the anterior torso between the umbilicus and the clavicle of normal and spinal-cord transected individuals. In normal individuals, thresholds were higher on the thorax than on the abdomen. Men had higher and more variable thresholds than women. Magnitude estimations of supra-threshold stimuli showed that men offer verbal estimates of warmth that are about half of the size of the estimates given by women to the same stimuli. The psychometric function shows that in women, the sensation of warmth grows more rapidly than in men after starting from a higher initial value. After spinal-cord injury, thresholds for detection of warming were elevated. This effect was most noticeable within 8 cm of the anesthetic zone, but farther away, thresholds were still elevated but uniform as a function of distance, being about 30% higher than in normal individuals. After spinal-cord injury, the psychometric functions show that small stimuli elicit relatively large sensations and that these sensations grow more slowly with increasing skin temperatures than for normal individuals. Thus, for small warm stimuli spinal-cord-injured patients (both men and women) have a response similar to normal women but the slope of the psychometric function is flat, being similar to the slope observed for normal men.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.213
GPT teacher head0.375
Teacher spread0.162 · 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 designBench or experimental
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

Citations6
Published2002
Admission routes1
Has abstractyes

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