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Record W2040341764 · doi:10.1080/02640410600908050

Quantifying delayed-onset muscle soreness: A comparison of unidimensional and multidimensional instrumentation

2006· article· en· W2040341764 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Sports Sciences · 2006
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsnot available
Fundersnot available
KeywordsDelayed onset muscle sorenessInstrumentation (computer programming)Physical medicine and rehabilitationMedicinePhysical therapyPsychologyComputer scienceMuscle damageInternal medicine

Abstract

fetched live from OpenAlex

Unidimensional pain instrumentation, whereby participants simply rate the intensity of their pain on one evaluative level, has been the most common method of assessing delayed-onset muscle soreness (DOMS). However, pain has been shown to be a multidimensional phenomenon including sensory, affective, and evaluative aspects. The aims of this study were two-fold: (1) to compare the DOMS pain responses derived from a multidimensional instrument (i.e. the McGill Pain Questionnaire--MPQ) with those using a unidimensional measure (i.e. a visual analogue scale), and (2) to identify the MPQ descriptors most commonly used to characterize DOMS among a sample of 14 male (mean age = 24.7 years, s = 4.4) and 9 female participants (mean age = 24.6 years, s = 3.5). Although the results demonstrated no significant differences between the pain ratings of the two instruments (mean values of the pain rating indices had a Spearman rank correlation coefficient of r = 1.00), suggesting no significant advantage to be gained in using the MPQ, a clearer description of DOMS emerged. The most frequently selected DOMS descriptors were "tight" (95% of participants chose this descriptor at least once), "sore" (86%), "tender" (86%), "annoying" (86%), and "pulling" (68%). These findings may be of use to researchers and sports medicine professionals in their deliberations about which instrumentation to use in quantifying DOMS and in distinguishing such pain from other, potentially more serious, musculoskeletal damage.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score0.177

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.058
GPT teacher head0.362
Teacher spread0.304 · 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