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Record W2061625262 · doi:10.1055/s-0030-1254123

Blood Testing in Sport: Hematological Profiling

2010· article· en· W2061625262 on OpenAlexaff
H. Kuipers, Sanda Dubravčić-Šimunjak, Jane Moran, David Mitchell, Joel Shobe, Hiroya Sakai, Ruben Ambartsumov

Bibliographic record

VenueInternational Journal of Sports Medicine · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHemoglobinAltitude (triangle)MedicineEffects of high altitude on humansInternal medicineAnimal scienceBiologyAnatomyMathematics

Abstract

fetched live from OpenAlex

Hemoglobin concentration and percent reticulocytes (%retics) were analyzed in blood samples taken pre-competition, post-competition, and during out of competition testing in elite speed skaters. Percent reticulocytes during screening was not different from the values obtained post-race, and no significant gender difference was found. Mean hemoglobin concentration both in males and females was slightly higher at 1 425 m altitude compared to <750 m altitude (0.23 g/dl increase in males and 0.48 g/dl increase in females; p<0.05 and p<0.01, respectively). Mean %retics at 1 425 m altitude is higher (0.24% in males and 0.27% in females, respectively, p<0.01) compared to blood sampled <750 m altitude. The distribution of percent reticulocytes shows 11 out of 11 500 samples with %reticulocytes below 0.4%. From the 171 samples with a values >2.4% in 52 skaters at least two consecutive samples yielded a percent reticulocytes above 2.4%. In 50 individuals with generally normal values but at least in two consecutive samples values above 2.4% the pattern required additional testing. In conclusion, percent reticulocytes are a robust hematological parameter, including acute exercise.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score0.231

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.013
GPT teacher head0.284
Teacher spread0.271 · 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 teacher head, 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

Citations5
Published2010
Admission routes1
Has abstractyes

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