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Record W1987203653 · doi:10.1097/jom.0b013e318206b112

The Genetics of Altitude Tolerance

2011· review· en· W1987203653 on OpenAlexafffund
Martin J. MacInnis, Pei Wang, Michael S. Koehle, Jim L. Rupert

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsAltitude (triangle)BiologyGenetic predispositionGeneticsGenotypeEffects of high altitude on humansEnvironmental healthAltitude sicknessGeneEcologyMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Acute mountain sickness (AMS) has become a significant environmental health issue as improvements in transportation, "environmental tourism," and resource development lure more people to the highlands. Whether there is a genetic contribution to AMS susceptibility is a central question in high-altitude medicine. This article provides a systematic review of the evidence supporting such an innate predisposition. METHODS: Scientific literature databases were screened using the terms "acute mountain sickness/AMS" and "altitude illness" combined with the terms "DNA," "gene," "genetic," or "polymorphism." RESULTS: Sixteen genes from a variety of pathways have been tested for association with AMS and variants in eight showed positive associations suggesting that AMS is an environmentally mediated polygenic disorder. CONCLUSIONS: The data suggest that genotype contributes to capacity to rapidly and efficiently acclimatize to altitude; nevertheless, the mechanisms by which this occurs have yet to be elucidated.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.039
GPT teacher head0.314
Teacher spread0.275 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations30
Published2011
Admission routes2
Has abstractyes

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