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Record W2794934685 · doi:10.1002/ajpa.23469

The thermoregulatory function of the human hand: How do palm and digit proportions affect heat loss?

2018· article· en· W2794934685 on OpenAlexaff
Stephanie Payne, Alison Macintosh, Jay T. Stock

Bibliographic record

VenueAmerican Journal of Physical Anthropology · 2018
Typearticle
Languageen
FieldMedicine
TopicInfrared Thermography in Medicine
Canadian institutionsWestern University
FundersUniversity of Cambridge
KeywordsNumerical digitSkin temperatureBody surface areaMathematicsMedicineBiomedical engineeringSurgeryArithmetic

Abstract

fetched live from OpenAlex

OBJECTIVES: The current study assessed whether ecogeographical patterns seen in hand proportions correlate with heat loss directly. Using a brief severe cold immersion experiment on the hand, the influence of hand and digit dimensions on heat loss was evaluated. MATERIALS AND METHODS: A sample of 113 living individuals were tested. Two-dimensional and three-dimensional scanning techniques were used to assess hand and digit dimensions. Thermal imaging analysis was used to quantify heat loss during a 3-min ice-water immersion of the hands. RESULTS: When body size was accounted for, hand width and digit length relative to total hand length were significant predictors of heat loss from the hand. DISCUSSION: The current study provides empirical evidence to support the link between thermodynamic principles relating to surface area-to-volume ratio, and ecogeographical patterns associated with temperature.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.982

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 studies0.0000.020
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 head0.007
GPT teacher head0.289
Teacher spread0.282 · 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.

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

Citations10
Published2018
Admission routes1
Has abstractyes

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