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Record W7058141381

Muscle Oxygenation of the Paretic and Nonparetic Legs Measured During Arterial Occlusion and Exercise in Chronic Stroke

2021· dissertation· W7058141381 on OpenAlexfundno aff

Bibliographic record

VenueTSpace · 2021
Typedissertation
Language
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsOxygenationSkeletal muscleChronic strokeLeg muscleStroke (engine)Oxygen saturation
DOInot available

Abstract

fetched live from OpenAlex

Oxygen delivery and demand are reduced in the paretic leg post-stroke, reflecting decreases of vascular function and reductions of muscle quantity and quality. It is unknown how muscle oxygenation is altered post-stroke and how it relates to functional ambulation. Skeletal muscle O2 saturation (SMO2) of the paretic and nonparetic legs of eleven post-stroke individuals were monitored with two near-infrared spectroscopy (NIRS) devices during rest, arterial occlusion, submaximal exercise and six-minute walk test (6MWT). Oxygen consumption (p=0.03) and microvascular responsiveness (p=0.04) were reduced in the paretic compared to the nonparetic leg. The exercise deoxygenation slope in the paretic leg was significantly steeper than the non-paretic leg (p=0.047) indicating a greater oxygen mismatch at the onset of exercise. Average 6MWT SMO2 of each leg was not significantly correlated with 6MWT distance. These impairments in the paretic leg may require strategies like prolonged warmups, resistance, or single leg training to improve muscle oxygenation.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.010
GPT teacher head0.276
Teacher spread0.266 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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