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Record W4401244517 · doi:10.1016/j.ynpai.2024.100161

The timing of the mouse hind paw incision does not influence postsurgical pain

2024· article· en· W4401244517 on OpenAlexafffund
Eleri L.F. McEachern, Maria Zilic, Susana G. Sotocinal, Nader Ghasemlou, Jeffrey S. Mogil

Bibliographic record

VenueNeurobiology of Pain · 2024
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsQueen's UniversityMcGill University
FundersCanadian Institutes of Health ResearchLouise and Alan Edwards Foundation
KeywordsHindlimbMedicineWheel runningAnesthesiaPhysical medicine and rehabilitationNeurosciencePsychologyAnatomyInternal medicine

Abstract

fetched live from OpenAlex

Chronobiological approaches have emerged as tools to study pain and inflammation. Although time-of-day effects on the expression of pain after injury have been studied, it remains unaddressed whether the timing of the injury itself can alter subsequent pain behaviors. The aim of this study was to assess postsurgical pain behaviors in a mouse hind paw incision assay in a circadian-dependent manner. Incisions were made at one of four equally spaced time points over a 24-hour period, with evoked and spontaneous pain behaviors measured using the von Frey mechanical sensitivity test, Hargreaves' radiant heat paw-withdrawal test, and the Mouse Grimace Scale. Algesiometric testing was performed in C57BL/6 mice prior to and at multiple time points after incision injury, at the same time of day, until pain resolution. No statistically significant differences were observed between groups. This study adds to the literature on circadian rhythms and their influence on pain in the pursuit of more biologically informed pre- and postoperative care.

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)0.004
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.176

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 head0.013
GPT teacher head0.257
Teacher spread0.244 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

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