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Record W1972079471 · doi:10.1364/boe.3.002500

Silica-coated super paramagnetic iron oxide nanoparticles (SPION) as biocompatible contrast agent in biomedical photoacoustics

2012· article· en· W1972079471 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiomedical Optics Express · 2012
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsNatural Resources CanadaUniversity of WaterlooUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsNanoparticleMaterials sciencePhotoacoustic imaging in biomedicinePhotoacoustic spectroscopyIron oxide nanoparticlesBiocompatible materialContrast (vision)Ex vivoIn vivoNanotechnologyBiomedical engineeringOpticsMedicine

Abstract

fetched live from OpenAlex

In this study, we report for the first time the use of silica-coated superparamagnetic iron oxide nanoparticles (SPION) as contrast agents in biomedical photoacoustic imaging. Using frequency-domain photoacoustic correlation (the photoacoustic radar), we investigated the effects of nanoparticle size, concentration and biological media (e.g. serum, sheep blood) on the photoacoustic response in turbid media. Maximum detection depth and the minimum measurable SPION concentration were determined experimentally. The nanoparticle-induced optical contrast ex vivo in dense muscular tissues (avian pectus and murine quadricept) was evaluated and the strong potential of silica-coated SPION as a possible photoacoustic contrast agents was demonstrated.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.620
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.011
GPT teacher head0.232
Teacher spread0.222 · 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