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Record W2080155430 · doi:10.1159/000086823

Development of a New Model to Investigate the Fetal Nociceptive Pathways

2005· article· en· W2080155430 on OpenAlexaff
V. Debarge, Sophie Bresson, Sophie Jaillard, F. Elbaz, Yvon Riou, S. Dalmas, Philippe Deruelle, Anne Sophie Ducloy, F Puech, Laurent Storme

Bibliographic record

VenueFetal Diagnosis and Therapy · 2005
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsPediatric Oncology Group
Fundersnot available
KeywordsNociceptionMedicineStimulationNoxious stimulusReflexSufentanilAnesthesiaSural nerveBiceps femoris muscleFetusStimulus (psychology)BicepsInternal medicineAnatomyPregnancyPsychologyBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of the study was to develop an experimental model to investigate the fetal nociceptive pathways and fetal analgesia. METHODS: We tested the electromyographic (EMG) response from the biceps femoris to electrical stimulation of the sural nerve in chronically-prepared fetal lambs with and without sufentanil. RESULTS: An EMG response could be recorded 140 ms after the electrical stimulation above a threshold of current's intensity. The response presents the characteristics of a nociceptive flexion reflex. The reflex magnitude increased with the stimulus intensity. Sufentanil decreased the response. Bradycardia was noted 10 s after the stimulation and was not observed after sufentanilinfusion. Catecholamine concentrations were not altered by the stimulation. CONCLUSION: Our study shows that a nociceptive flexion reflex can be recorded in the ovine fetus. We suggest that this reflex can be used as a new tool to study the ontogenesis of the nociceptive pathways and the effects of analgesic drugs during fetal life.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.080
GPT teacher head0.296
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), 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

Citations14
Published2005
Admission routes1
Has abstractyes

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