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Record W1579788178 · doi:10.1364/ol.35.000700

Photothermal optical coherence tomography in ex vivo human breast tissues using gold nanoshells

2010· article· en· W1579788178 on OpenAlexfundno aff
Chao Zhou, Tsung-Han Tsai, Desmond C. Adler, Hsiang‐Chieh Lee, David Cohen, Amy E. Mondelblatt, Yihong Wang, James L. Connolly, James G. Fujimoto

Bibliographic record

VenueOptics Letters · 2010
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsnot available
FundersAir Force Office of Scientific ResearchNational Cancer InstituteNatural Sciences and Engineering Research Council of CanadaConsortia for Improving Medicine with Innovation and Technology
KeywordsNanoshellPhotothermal therapyOptical coherence tomographyMaterials scienceEx vivoOpticsScatteringExcitationPreclinical imagingBiomedical engineeringModulation (music)In vivoPlasmonOptoelectronicsNanotechnologyMedicinePhysics

Abstract

fetched live from OpenAlex

We demonstrate photothermal optical coherence tomography (OCT) imaging in highly scattering human breast tissue ex vivo. A 120 kHz axial scan rate, swept-source phase-sensitive OCT system at 1300 nm was used to detect phase changes induced by 830 nm photothermal excitation of gold nanoshells. Localized phase modulation was observed 300-600 microm deep in scattering tissue using an excitation power of only 22 mW at modulation frequencies up to 20 kHz. This technique enables integrated structural and molecular-targeted imaging for cancer markers using nanoshells.

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.236
Teacher spread0.226 · 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 teacher head, not a consensus.

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

Citations5
Published2010
Admission routes1
Has abstractyes

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