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Record W2159571336 · doi:10.1016/s1090-3801(02)00056-3

The significance of A‐δ and C fibres for the perception of synthetic heat

2003· article· en· W2159571336 on OpenAlexfundno aff
H. Fruhstorfer, Eva‐Liz Harju, Ulf Lindblom

Bibliographic record

VenueEuropean Journal of Pain · 2003
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsnot available
FundersVårdalstiftelsenMcGill University
KeywordsPerceptionChemistryPsychologyNeuroscience

Abstract

fetched live from OpenAlex

Synthetic heat is a perception of strong, but not painful, heat arising when skin is stimulated by an alternating pattern of adjacent cold and warmth. This study examines the contribution of different classes of nerve fibres to this perception. In 40 subjects changes in synthetic heat and thermal perceptions were studied during a 30-min ischaemic nerve block in one reaction time, and one threshold determination task. Synthetic heat stimuli were described as hot or warm, but not as painful, and were preceded by a transient cold. Reaction times for synthetic heat stimuli did not differ from those for cold stimuli. Thresholds for synthetic heat and thermal stimuli were similar. During A fibre nerve block the perception of synthetic heat lost the cold component whereas the frequency of hot and warm descriptors did not change. The perception of cold stimuli changed, such that pure cold was replaced by dysaesthetic descriptors. Reaction times and thresholds for thermal and synthetic heat stimuli increased equally during the nerve block. It is concluded that the perception of synthetic heat most likely arises from the fusion of signals dependent on unmyelinated low threshold cold and warm receptors. It is not dependent on A-delta cold fibres, and a contribution of nociceptors is quite unlikely. The possibility of a psychological contribution at the perceptual level is discussed.

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)0.003
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score0.239

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
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 head0.098
GPT teacher head0.261
Teacher spread0.163 · 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

Citations44
Published2003
Admission routes1
Has abstractyes

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