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Record W2556304477 · doi:10.1139/apnm-2016-0435

Comparison of immunohematological profile between endurance- and power-oriented elite athletes

2016· article· en· W2556304477 on OpenAlexvenueno aff
José P. Morgado, Catarina N. Matias, Cristina P. Monteiro, Francisco Alves, Joana F. Reis, Diana A. Santos, Analiza M. Silva, Fátima Martins, Maria Teresa Seixas, Petronila Rocha‐Pereira, Luís B. Sardinha, Maria José Laires

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2016
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsnot available
Fundersnot available
KeywordsHematocritAthletesMedicineElite athletesHemoglobinPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

There is general perception that elite athletes are highly susceptible to changes in immunohematological profile. The objective of this study was to compare immunohematological parameters of elite athletes of different aerobic and muscular strength sports and analyze changes over 2 months. Sixteen judoists and 14 swimmers were evaluated 2 months before (M1) and immediately prior to competition (M2). Hemogram and lymphocytes subpopulations were assessed with automatic counter and flow cytometry, respectively. Judoists had higher neutrophils and lower monocytes and eosinophils percentages than swimmers at M1 and M2. At M2 judoists had lower red blood cells (RBC), hemoglobin, and hematocrit than swimmers. At M2 judoists' hematocrit and CD16 decreased while swimmers' hemoglobin and hematocrit increased. In conclusion, neither sports characteristics nor intense training seem to displace the athletes' immunohematological profile out of the clinical range, despite the possibility of occurrence of microlesions that may stimulate production of leukocytes and reduction of RBC in judoists.

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 score0.001
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 head0.312
Teacher spread0.288 · 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

Citations14
Published2016
Admission routes1
Has abstractyes

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