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Morphometry ofMacaca mulatta forelimb. I. Shoulder and elbow muscles and segment inertial parameters

2000· article· en· W2157884142 on OpenAlex
Ernest J. Cheng, Stephen H. Scott

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 Morphology · 2000
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsForelimbAnatomyElbowBiologyMoment of inertiaForearmAnkleFascicleMuscle architecturePhysics

Abstract

fetched live from OpenAlex

The present study examined the morphometric properties of the forelimb, including the inertial properties of the body segments and the morphometric parameters of 21 muscles spanning the shoulder and/or elbow joints of six Macaca mulatta and three M. fascicularis. Five muscle parameters are presented: optimal fascicle length (L(0)(M)), tendon slack length (L(S)(T)), physiological cross-sectional area (PCSA), pennation angle (alpha(0)), and muscle mass (m). Linear regressions indicate that muscle mass, and to a lesser extent PCSA, correlated with total body weight. Segment mass, center-of-mass, and the moment of inertia of the upper arm, forearm, and hand are also presented. Our data indicate that for some segments, radius of gyration (rho) predicts segment moment of inertia better than linear regressions based on total body weight. Key differences between the monkey and human forelimb are highlighted.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.460

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 head0.011
GPT teacher head0.219
Teacher spread0.209 · 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