MétaCan
Menu
Back to cohort
Record W1970351664 · doi:10.5539/gjhs.v2n1p160

Ramadan Fasting and Weight-Lifting Training on Vascular Volumes and Hematological Profiles in Young Male Weight-Lifters

2010· article· en· W1970351664 on OpenAlexvenueno aff
Seyed Morteza Tayebi, Parichehr Hanachi, Abbass Ghanbari–Niaki, Parvaneh Nazar Ali, Fatemeh Ghaziani

Bibliographic record

VenueGlobal Journal of Health Science · 2010
Typearticle
Languageen
FieldMedicine
TopicDietary Effects on Health
Canadian institutionsnot available
Fundersnot available
KeywordsHematocritMedicineBody weightWeight liftingPhysiologyWhite blood cellWeight lossAnimal scienceInternal medicinePhysical therapyBiologyObesity

Abstract

fetched live from OpenAlex

During the holy month of Ramadan the quality of food and eating patterns changed and drinking will be stoppedfor at least 10 to 16 hours on the basis lunar calendar. The effects of exercise and fasting solely or combined onmetabolic and hematologic responses well established. The purpose of the present study was to study the effects ofRamadan fasting with or without weight-lifting training on vascular volumes and selected hematological indices inyoung male weight-lifters. Blood samples were taken at 24h before and 24h after the last day of holy Ramadanfasting period and weight-lifting training for determination of the selected red and white blood cells compositions.The Vascular volumes (Blood, Red cells, and plasma volumes) were determined and calculated by using bothhemoglobin and hematocrit estimations before and after Ramadan fasting with or without weight-lifting training.The results indicate that red cell volume and MCHC were significantly decreased and increased in fasting group(P

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.024
GPT teacher head0.322
Teacher spread0.298 · 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

Citations40
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueGlobal Journal of Health ScienceSame topicDietary Effects on HealthFrench-language works237,207