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Record W2604143419 · doi:10.1039/c7cp01167a

Covering the optical spectrum through collective rare-earth doping of NaGdF<sub>4</sub> nanoparticles: 806 and 980 nm excitation routes

2017· article· en· W2604143419 on OpenAlexaff
Artiom Skripka, Riccardo Marin, Antonio Benayas, Patrizia Canton, Eva Hemmer, Fiorenzo Vetrone

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2017
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence Properties of Advanced Materials
Canadian institutionsUniversité du QuébecInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsDopingRare earthExcitationNanoparticleMaterials scienceSpectrum (functional analysis)NanotechnologyOptoelectronicsPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

) are optically excited by heating-free 806 nm light that, aside from minimizing the local thermal load, also allows to obtain a deeper sub-tissue penetration with respect to the still widely used 980 nm light. Moreover, these water-dispersed nanoplatforms offer interesting assets as triggers/probes for biomedical applications, by virtue of a plethora of emission bands (spanning the 380-1600 nm range). Our results pave the way to use these RENPs for UV/visible-triggered photodynamic therapy/drug release, while simultaneously tracking the nanoparticle biodistribution and monitoring their therapeutic action through the near-infrared signal that overlaps with biological transparency windows.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.018
GPT teacher head0.249
Teacher spread0.231 · 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

Citations38
Published2017
Admission routes1
Has abstractyes

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