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Record W2134840853 · doi:10.1109/imtc.2005.1604082

Sound Localization in the Human Thorax

2006· article· en· W2134840853 on OpenAlexaff
A.M. McKee, Rafik Goubran

Bibliographic record

Venue2005 IEEE Instrumentationand Measurement Technology Conference Proceedings · 2006
Typearticle
Languageen
FieldMedicine
TopicPhonocardiography and Auscultation Techniques
Canadian institutionsCarleton University
Fundersnot available
KeywordsThorax (insect anatomy)Sound (geography)Computer scienceAcousticsAnatomyPhysicsMedicine

Abstract

fetched live from OpenAlex

This paper compares two methods of source localization in the human thorax using a multisensor stethoscope. The multisensor stethoscope measurement technique consists of several stethoscope chest pieces simultaneously recording and storing audio data for computer-aided analysis. Localization method A finds the source location by measuring the relative power at different points in the field and identifying the location of maximum power. Localization method B finds the source by solving a system of equations based on the difference in time of arrival of signals at different microphones and the measured microphone positions. To illustrate this concept, a circular array of microphones equally spaced in one plane is assumed to be in a free-field homogeneous medium. Simulations, conducted in Matlab, as well as verification results are presented. Two in vitro verification models were constructed, and preliminary trials were done on a human test subject

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.041
GPT teacher head0.289
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 designBench or experimental
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

Citations13
Published2006
Admission routes1
Has abstractyes

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