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Record W2105598102 · doi:10.1002/mus.1090

Comparison of interpolation and central activation ratios as measures of muscle inactivation

2001· article· en· W2105598102 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

VenueMuscle & Nerve · 2001
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsTetanusLinear regressionMathematicsContraction (grammar)StimulationChemistryAnesthesiaMedicineInternal medicineStatistics

Abstract

fetched live from OpenAlex

The objective of this study was to investigate different methods of estimating muscle inactivation, derived from single and multiple voluntary contractions. Ten subjects performed maximal and submaximal leg extensor contractions to determine an interpolation (IT) or central activation ratio (CAR). A superimposed evoked force was compared with the force output of either a voluntary (CAR) or resting evoked contraction (IT ratio), or the ratios were inserted into regression equations (linear, polynomial, exponential). Linear-regression estimates of CAR using doublets and tetanus provided physiologically inaccurate values. Whereas IT ratios using doublets (IT-doublet) and tetanus (IT-tetanus) had a significant difference in only one interaction, IT-tetanus and CAR using a tetanus (CAR-tetanus) estimates provided the most extensive correlation within and between measures. Thus, tetanic stimulation superimposed upon single maximal or multiple contractions seems to provide the most valid measure of muscle inactivation when using the interpolated-twitch technique.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.800
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.031
GPT teacher head0.265
Teacher spread0.234 · 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