MétaCan
Menu
Back to cohort
Record W2134840853 · doi:10.1109/imtc.2005.1604082

Sound Localization in the Human Thorax

2006· article· en· W2134840853 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.

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.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.041
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