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Record W2318157802 · doi:10.1021/nn202490m

NIR-to-NIR Two-Photon Excited CaF<sub>2</sub>:Tm<sup>3+</sup>,Yb<sup>3+</sup> Nanoparticles: Multifunctional Nanoprobes for Highly Penetrating Fluorescence Bio-Imaging

2011· article· en· W2318157802 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

VenueACS Nano · 2011
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence Properties of Advanced Materials
Canadian institutionsConcordia UniversityInstitut National de la Recherche Scientifique
FundersDepartment of Health and Social CareNational Institute for Health and Care Research
KeywordsFluorescenceNanoparticleMaterials scienceExcited statePenetration depthYtterbiumFluorescence-lifetime imaging microscopyPhotonPenetration (warfare)IonAnalytical Chemistry (journal)NanotechnologyOptoelectronicsOpticsChemistryAtomic physicsDopingPhysics

Abstract

fetched live from OpenAlex

In this study, we report on the remarkable two-photon excited fluorescence efficiency in the "biological window" of CaF(2):Tm(3+),Yb(3+) nanoparticles. On the basis of the strong Tm(3+) ion emission (at around 800 nm), tissue penetration depths as large as 2 mm have been demonstrated, which are more than 4 times those achievable based on the visible emissions in comparable CaF(2):Er(3+),Yb(3+) nanoparticles. The outstanding penetration depth, together with the fluorescence thermal sensitivity demonstrated here, makes CaF(2):Tm(3+),Yb(3+) nanoparticles ideal candidates as multifunctional nanoprobes for high contrast and highly penetrating in vivo fluorescence imaging applications.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.023
GPT teacher head0.241
Teacher spread0.217 · 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