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Record W4249582138 · doi:10.21611/qirt.2010.136

Dual-Mode Photoacoustic Phased-Array Imager for Biomedical Applications

2010· article· en· W4249582138 on OpenAlexaff
S. Telenkov, A. Mandelis

Bibliographic record

VenueProceedings of the 2010 International Conference on Quantitative InfraRed Thermography · 2010
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDual modePhased arrayPhotoacoustic imaging in biomedicineDual (grammatical number)Computer sciencePhased-array opticsMode (computer interface)OptoelectronicsMaterials scienceOpticsElectronic engineeringPhysicsEngineeringTelecommunications

Abstract

fetched live from OpenAlex

Conventional pulse-echo ultrasound is routinely used in medical practice for diagnostic imaging.Despite its obvious success, traditional ultrasound has low-contrast when the targeted tissues lack echogenic features.Pulsed laser photoacoustics was developed as a hybrid technology taking advantage of high-contrast optical methods and high-resolution ultrasound.We present a novel photoacoustic imager that utilizes a conventional ultrasonic phasedarray sensor for rapid scanning of the targeted tissues and features dual-mode operation: traditional pulsed timedomain and frequency-domain photoacoustic method with chirped optical excitation (the photoacoustic radar or sonar).Typical characteristics of the imager and potential for biomedical applications will be discussed.

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)0.001
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.019
GPT teacher head0.286
Teacher spread0.267 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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