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Record W4404706683 · doi:10.1249/jes.0000000000000352

Task-Dependent Mechanisms Underlying Prolonged Low-Frequency Force Depression

2024· review· en· W4404706683 on OpenAlexaff
Andrew J. Richards, Daiki Watanabe, Takashi Yamada, Håkan Westerblad, Arthur J. Cheng

Bibliographic record

VenueExercise and Sport Sciences Reviews · 2024
Typereview
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsYork University
Fundersnot available
KeywordsPhysical medicine and rehabilitationDepression (economics)Excitation–contraction couplingMuscle contractionMedicineNeuroscienceCardiologyPsychologyInternal medicineSkeletal muscle

Abstract

fetched live from OpenAlex

Prolonged low-frequency force depression (PLFFD) is an intramuscular phenomenon involving the slow recovery of submaximal muscle strength following strenuous exercise. We hypothesize that the contribution of impaired excitation-contraction coupling processes to PLFFD is task dependent, and that they will be different between metabolically and mechanically demanding exercises. We also discuss evidence of the effectiveness of interventions to mitigate PLFFD.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.074
GPT teacher head0.370
Teacher spread0.296 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations10
Published2024
Admission routes1
Has abstractyes

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