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Record W2065671920 · doi:10.1139/h00-022

Estrogen and Gender Effects on Muscle Damage, Inflammation, and Oxidative Stress

2000· review· en· W2065671920 on OpenAlex

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

VenueCanadian Journal of Applied Physiology · 2000
Typereview
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsEstrogenOxidative stressInternal medicineEndocrinologyMuscle damageSkeletal muscleCreatine kinaseInflammationAntioxidantVitamin CMedicineBiologyBiochemistry

Abstract

fetched live from OpenAlex

Information suggests that there may be gender-based differences in skeletal muscle responses to damaging exercise. Evidence demonstrates that estrogen has strong antioxidant properties and may be an important factor in maintaining postexercise membrane stability and limiting creatine kinase (CK) leakage from damaged muscle in female animals. Research demonstrates effects of estrogen and possible gender differences in other morphological and biochemical indices of postexercise muscle damage and leukocyte invasion. Nevertheless, there are conflicting findings suggesting that in some in vivo exercise models, estrogen administration has limited ability to affect exercise-induced oxidative stress and muscle damage and may cause loss of tissue vitamin C. Gender differences appear to exist in tissue levels of other important antioxidants such as vitamin E and glutathione. More research is needed to fully define the potential for estrogen to influence postexercise muscle damage and the inflammatory response and to determine the mechanisms by which it may operate.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.301
Teacher spread0.270 · 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