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Record W2795146597 · doi:10.1089/ham.2017.0164

The 2018 Lake Louise Acute Mountain Sickness Score

2018· article· en· W2795146597 on OpenAlexaffabout
Robert C. Roach, Peter H. Hackett, O Oelz, Peter Bärtsch, Andrew M. Luks, Martin J. MacInnis, J. Kenneth Baillie, Eric Achatz, Edi Albert, J. Andrews, James D. Anholm, Mohammad Zahid Ashraf, Paul S. Auerbach, Buddha Basnyat, Beth A. Beidleman, Remco R. Berendsen, Marc Moritz Berger, Konrad E. Bloch, Hermann Brugger, Annalisa Cogo, Ricardo Gonzalez Costa, Andrew F. Cumpstey, Allen Cymerman, Tadej Debevec, Catriona Duncan, David J. Dubowitz, Angela Fago, Michaël Furian, Matt Gaidica, Prosenjit Ganguli, Michael P. W. Grocott, Debra Hammer, David P. Hall, David Hillebrandt, Matthias P. Hilty, Gigugu Himashree, Benjamin Honigman, Ned Gilbert-Kawai, Bengt Kayser, Linda E. Keyes, Michael S. Koehle, Samantha Kohli, Arlena Kuenzel, Benjamin D. Levine, Mona Lichtblau, Jamie Macdonald, Monika Brodmann Maeder, Marco Maggiorini, Daniel Martín, Shigeru Masuyama, John McCall, Scott McIntosh, Grégoire P. Millet, Fernando A. Moraga, Craig A. Mounsey, Stephen R. Muza, Samuel J. Oliver, Qadar Pasha, Ryan F. Paterson, Lara Phillips, Aurélien Pichon, Philipp A. Pickerodt, Matiram Pun, Manjari Rain, Drummond Rennie, Ri‐Li Ge, Steven Roy, Samuel Vergès, Tatiana Batalha Cunha dos Santos, Robert B. Schoene, Otto D. Schoch, Talant Sooronbaev, Craig D. Steinback, Mike Stembridge, Glenn M. Stewart, Tsering Stobdan, Giacomo Strapazzon, Andrew W. Subudhi, Erik R. Swenson, A. A. Roger Thompson, Martha C. Tissot van Patot, Rosie Twomey, Silvia Ulrich, Nicolas Voituron, Dale R. Wagner, Shih-hao Wang, John B. West, Matt Wilkes, Gabriel Willmann, Michael Yaron, Ken Zafren

Bibliographic record

VenueHigh Altitude Medicine & Biology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsMcMaster University
FundersNational Institute for Health and Care ResearchWellcome Trust
KeywordsMountaineeringMedicineGeographyArchaeology

Abstract

fetched live from OpenAlex

Roach, Robert C., Peter H. Hackett, Oswald Oelz, Peter Bärtsch, Andrew M. Luks, Martin J. MacInnis, J. Kenneth Baillie, and The Lake Louise AMS Score Consensus Committee. The 2018 Lake Louise Acute Mountain Sickness Score. High Alt Med Biol 19:1-4, 2018.- The Lake Louise Acute Mountain Sickness (AMS) scoring system has been a useful research tool since first published in 1991. Recent studies have shown that disturbed sleep at altitude, one of the five symptoms scored for AMS, is more likely due to altitude hypoxia per se, and is not closely related to AMS. To address this issue, and also to evaluate the Lake Louise AMS score in light of decades of experience, experts in high altitude research undertook to revise the score. We here present an international consensus statement resulting from online discussions and meetings at the International Society of Mountain Medicine World Congress in Bolzano, Italy, in May 2014 and at the International Hypoxia Symposium in Lake Louise, Canada, in February 2015. The consensus group has revised the score to eliminate disturbed sleep as a questionnaire item, and has updated instructions for use of the score.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.003

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 head0.012
GPT teacher head0.280
Teacher spread0.267 · 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 designTheoretical or conceptual
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

Citations566
Published2018
Admission routes2
Has abstractyes

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