MétaCan
Menu
Back to cohort
Record W2405577680 · doi:10.1055/s-2003-44637

Tensile Strength of Healing Peripheral Nerves

2003· article· en· W2405577680 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Reconstructive Microsurgery · 2003
Typearticle
Languageen
FieldMedicine
TopicNerve Injury and Rehabilitation
Canadian institutionsWestern University
FundersAmerican Association for Hand Surgery
KeywordsMedicineSciatic nerveUltimate tensile strengthPeripheralPeripheral nerveSurgeryNerve injuryAnatomyInternal medicine

Abstract

fetched live from OpenAlex

Although the time required for a nerve to gain sufficient strength to withstand normal physiologic forces of joint motion is unknown, typically nerve repairs are protected up to 3 weeks postoperatively. The authors investigated the mechanical strength of a nerve repair as a function of time. Fifty adult Sprague-Dawley rats underwent sciatic nerve division and repair, and were sacrificed in groups of 10 at 0, 1, 2, 4, and 8 weeks. Repaired nerves were then mechanically loaded at 5 mm/min to failure. Gapping across the repair site was captured on high-resolution video. The contralateral sciatic nerve served as a control. A significant increase in tensile strength was gained between 0 and 1 week and between 2 and 4 weeks. Healing nerves achieved 63 percent of the strength of the control by 8 weeks. Controls showed no gain in strength over the testing period. Gapping occurred at lower forces at all time increments. From 0 to 1 week, a significant increase in load necessary to produce gapping was found, which did not increase significantly again until 8 weeks. These results may have implications for postoperative rehabilitation protocols in patients with nerve injuries.

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.

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)0.001
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 score0.294
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.015
GPT teacher head0.272
Teacher spread0.257 · 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