MétaCan
Menu
Back to cohort
Record W3016455112

Calibration of an Ultrasound Tomography System for Medical Imaging with 2D Contrast-Source Inversion

2013· article· en· W3016455112 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMspace (University of Manitoba) · 2013
Typearticle
Languageen
FieldEngineering
TopicFlow Measurement and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTomographyContrast (vision)CalibrationInversion (geology)Medical imagingUltrasoundMedical physicsRadiologyComputer scienceMedicineNuclear medicineGeologyComputer visionPhysicsSeismology
DOInot available

Abstract

fetched live from OpenAlex

This dissertation describes two possible methods for the calibration of an ultrasound tomography system developed at University of Manitoba's Electromagnetic Imaging Laboratory for imaging with the contrast-source inversion algorithm. The calibration techniques are adapted from existing procedures employed for microwave tomography. A theoretical model of these calibration principles is developed in order to provide a rationale for the effectiveness of the proposed procedures. The applicability of such an imaging algorithm and calibration methods in the context of ultrasound are discussed. Also presented are 2D and 3D finite-difference time-domain update equations for the simulation of acoustic wave propagation in inhomogeneous media. Details regarding the application of an absorbing boundary-condition, point-source modelling and the treatment of penetrable objects are included in this document.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.815

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 head0.006
GPT teacher head0.154
Teacher spread0.149 · 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