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Record W2594753311 · doi:10.4236/ape.2017.71005

Relationship between Changes in Cerebral Blood Flow with Symptoms of Acute Mountain Sickness in Men Repeatedly Exposed to Simulated High Altitude

2017· article· en· W2594753311 on OpenAlexaff
P Ondruš, Roman Alberty, T. P. Lyons, Stephen R. Muza, Vincent Échavé, J Poisson, Allen Cymerman

Bibliographic record

VenueAdvances in Physical Education · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsTranscranial DopplerCerebral blood flowMedicineEffects of high altitude on humansAltitude (triangle)Altitude sicknessAnesthesiapCO2Blood flowOxygen saturationInternal medicineCardiologyOxygenChemistry

Abstract

fetched live from OpenAlex

Objective: To study the relationship between changes in the cerebral blood flow (CBF) velocity with symptoms of acute mountain sickness (AMS) during simulated high altitude. Research Design and Methods: Mean middle arterial cerebral flow velocity (MCAv) was assessed by transcranial Doppler sonography in 8 healthy lowland male adults aged 20 - 24 yrs before and after 6 h and 48 h at simulated altitude corresponding to 4572 m. The same study was repeated three weeks later in the same subjects. End-tidal pCO2 (ETCO2) and arterial oxygen saturation (SaO2) were measured by standardized procedures. AMS symptoms were recorded using the modified environmental symptoms questionnaire after 6 h and 48 h exposure to calculate the mean score of cerebral (AMS-C) symptoms. Results: Mean MCAv significantly increased with high altitude (HA) by 4% at 6 h HA and 24% at 48 h HA (P 2 (mean ± SD 32 ± 4 mmHg; r = 0.47, P 2 (77% ± 8%; r = - 0.43, P 2 (r = - 0.55, 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 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 score0.046
Threshold uncertainty score0.493

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 head0.009
GPT teacher head0.302
Teacher spread0.293 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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