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Record W3031067498 · doi:10.31542/muse.v4i1.1854

Environmental Injuries: Hyperthermia and Hypothermia

2020· article· en· W3031067498 on OpenAlexaffvenue
Amanda McDonald, Rebekah Stubbs, Prince Lartey, Shaeleigh Kokot

Bibliographic record

VenueMacEwan University Student eJournal · 2020
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsMacEwan University
Fundersnot available
KeywordsHypothermiaHyperthermiaCore temperatureMedicineCore (optical fiber)Heat illnessIntensive care medicineAnesthesiaPsychologyMedical emergencyEngineeringInternal medicineGeography

Abstract

fetched live from OpenAlex

Environmental injuries are an important type of sport injury to study as they can occur year-round, through a variety of activities, and occur to a broad range of athletic populations. Hyperthermia (a core body temperature above 38.5°C) and hypothermia (a core body temperature below 35°C) are two common environmental injuries that can be life threatening. This research paper examines the mechanisms of how and why these injuries occur and the effect they have on the body. This paper also outlines preventative measures to take, including identifying internal and external predisposing risk factors, as well as ways to treat hyperthermia and hypothermia to return an athlete back to play.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.018
GPT teacher head0.232
Teacher spread0.214 · 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
GenreOther

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

Citations7
Published2020
Admission routes2
Has abstractyes

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