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Record W1993185734 · doi:10.1109/iembs.2010.5626054

Understanding complex muscles in the rat hindlimb: Activations and actions

2010· article· en· W1993185734 on OpenAlexaff
Matthew C. Tresch, David A. Klein, Sang Hoon Yeo, Cody Lendon Mullens, Thomas G. Sandercock, Dinesh K. Pai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Neurological Disorders and Stroke
KeywordsHindlimbBicepsBiceps femoris muscleNeuroscienceComputer scienceAnatomyPhysical medicine and rehabilitationBiologyMedicine

Abstract

fetched live from OpenAlex

We present research examining the function of complex muscles in the rat hindlimb. Two related sets of experiments are described. In the first, we examine the degree of specificity in spinal pattern generators, assessing whether the pattern generators at birth are capable of differentially activating intramuscular subdivisions in the complex hindlimb muscle biceps femoris. In the second, we describe a novel approach for creating a musculoskeletal model to capture the mechanical actions of individual muscles and evaluate its ability to capture the action of both simple and complex muscles in the rat hindlimb.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.124
GPT teacher head0.266
Teacher spread0.142 · 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 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

Citations2
Published2010
Admission routes1
Has abstractyes

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