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Record W2082335563 · doi:10.1364/oe.18.023544

Nanoparticles for highly efficient multiphoton fluorescence bioimaging

2010· article· en· W2082335563 on OpenAlex
Laura Martínez Maestro, Emma Martín Rodríguez, Fiorenzo Vetrone, Rafik Naccache, Daniel Jaque, John A. Capobianco, J. Garcı́a Solé

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

VenueOptics Express · 2010
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaUniversidad Autónoma de MadridConcordia UniversityBanco Santander
KeywordsFluorescenceMaterials scienceNanoparticleQuantum dotNanotechnologyFluorescence-lifetime imaging microscopyNanorodInfraredOptoelectronicsOptics

Abstract

fetched live from OpenAlex

In this paper, we demonstrate for the first time that the new class of fluoride-based inorganic upconverting nanoparticles, NaYF4:Er3+, Yb3+, are the most efficient multiphoton excited fluorescent nanoparticles developed to date. The near-infrared-to-visible conversion efficiency of the aforementioned nanoparticles surpasses that of CdSe quantum dots and gold nanorods, which are the commercially available inorganic fluorescent nanoprobes presently used for multiphoton fluorescence bioimaging. The results presented here open new perspectives for the implementation of fluorescence tomography by multiphoton fluorescence imaging.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.437

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 head0.020
GPT teacher head0.246
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