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Record W7008829615

Comparing fatigue induced by isometric and shortening contractions in skeletal muscle

2023· other· en· W7008829615 on OpenAlexaff

Bibliographic record

VenueYork University Digital Library (York University) · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsYork University
Fundersnot available
KeywordsIsometric exerciseSkeletal muscleExtensor digitorum muscleMuscle contractionFlexor musclesMuscle fatigueSarcomere
DOInot available

Abstract

fetched live from OpenAlex

The intramuscular mechanisms causing greater fatigue-induced reduction in force during shortening compared with isometric contractions is not completely understood. The focus of this thesis was to compare fatigue in repeated shortening contractions and isometric contractions and investigate if greater force loss during repeated shortening contractions is attributed to more severe reductions in sarcoplasmic reticulum Ca2+ release. Single intact flexor digitorum brevis muscle fibres from C57Bl/6 mice were mechanically dissected and loaded with indo-1 AM fluorescent dye to assess myoplasmic free [Ca2+]. Fibres were either placed in an isometric or shortening protocol which were both stimulated at 70Hz of 600ms duration and 4 seconds rest for 50 tetani. The results of this thesis did not show that repeated shortening contractions cause greater fatigue-induced reductions in force compared with repeated isometric contractions, and there were no differences in the fatigue-induced reductions in SR Ca2+ release during the repeated contractions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.195
Teacher spread0.164 · 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 designBench or experimental
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

Citations0
Published2023
Admission routes1
Has abstractyes

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