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Record W2092681135 · doi:10.1139/h08-151

Impact of wall filter selection on the detection of vasomotor changes in the brachial artery: a pilot study

2009· article· en· W2092681135 on OpenAlexaffvenue
Michel J. Johnson, J. Kevin Shoemaker

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2009
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsNipissing UniversityWestern University
Fundersnot available
KeywordsBrachial arteryBlood flowFilter (signal processing)VasomotorBiomedical engineeringForearmMedicineBlood pressureDiastoleUltrasoundCardiologyMaterials scienceInternal medicineSurgeryRadiologyComputer science

Abstract

fetched live from OpenAlex

During Doppler ultrasound assessment of blood flow, a wall filter is used to reduce or eliminate high-amplitude, low-velocity signals from the vessel wall and the surrounding tissue. This study investigated the impact of a range of wall filters (22 Hz, 75 Hz, 128 Hz, and 252 Hz) on the accuracy of forearm blood flow monitoring during the sympathoexcitatory application of lower body negative pressure, when peripheral blood flow may decrease substantially. The 252 Hz filter eliminated diastolic flow in 4 of 10 participants. In the remaining participants, the 252 Hz filter minimized the sensitivity of the pulsatility index. The interpretation of physiological responses could ultimately be compromised by using filters beyond 128 Hz.

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)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.269
Teacher spread0.248 · 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 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

Citations0
Published2009
Admission routes2
Has abstractyes

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