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Record W2929956849 · doi:10.1111/micc.12546

The reliability of cutaneous low‐frequency oscillations in young healthy males

2019· article· en· W2929956849 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMicrocirculation · 2019
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsBrock University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsMedicineLaser Doppler velocimetryReliability (semiconductor)WaveletSpectral analysisNuclear medicineAnimal scienceBlood flowCardiologyPhysicsBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Spectral analyses of laser-Doppler flowmetry measures enable a simple and non-invasive method to investigate mechanisms regulating skin blood flow. We assessed within-day and day-to-day variability of cutaneous spectral analyses. METHODS: Eleven young, healthy males were tested twice in three identical sessions, with 19 to 24 days between visits, for a total of six tests. Wavelet data were analyzed at rest, in response to local skin heating to 42 and 44°C, and during 5-minutes PORH. We did this for six frequency bands commonly associated with physiological functions. To assess reliability, we calculated CV and ICC scores. RESULTS: At rest, mean CV for the wavelet data ranged from 21% to 24% and ICC scores ranged from 0.67 to 0.91. During local heating, mean CV scores ranged from 17% to 22% and mean ICC scores ranged from 0.71 to 0.95. For peak PORH, CV ranged from 14% to 23% and the ICC range was 0.88 to 0.97. For the area under the curve of the PORH, CV range was 12% to 21% and ICC range was 0.81 to 0.92. CONCLUSIONS: These analyses indicate good-to-excellent reliability of the wavelet data in healthy young males.

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.

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 score0.481
Threshold uncertainty score0.179

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 head0.013
GPT teacher head0.281
Teacher spread0.268 · 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