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Record W1752164785 · doi:10.1039/c5nr06168g

Can magneto-plasmonic nanohybrids efficiently combine photothermia with magnetic hyperthermia?

2015· review· en· W1752164785 on OpenAlex
Ana Espinosa, Matthieu Bugnet, Guillaume Radtke, Sophie Neveu, Gianluigi A. Botton, Claire Wilhelm, Ali Abou‐Hassan

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

VenueNanoscale · 2015
Typereview
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsMcMaster University
FundersEuropean Research CouncilNatural Sciences and Engineering Research Council of CanadaCentre National de la Recherche Scientifique
KeywordsPhotothermal therapyMaterials scienceNanotechnologyNanomaterialsPlasmonMagnetoNanoparticleMagnetic nanoparticlesPlasmonic nanoparticlesHyperthermiaMagnetic hyperthermiaHeat generationColloidal goldCancer therapyMagnetOptoelectronicsCancerMedicine

Abstract

fetched live from OpenAlex

Multifunctional hybrid-design nanomaterials appear to be a promising route to meet the current therapeutics needs required for efficient cancer treatment. Herein, two efficient heat nano-generators were combined into a multifunctional single nanohybrid (a multi-core iron oxide nanoparticle optimized for magnetic hyperthermia, and a gold branched shell with tunable plasmonic properties in the NIR region, for photothermal therapy) which impressively enhanced heat generation, in suspension or in vivo in tumours, opening up exciting new therapeutic perspectives.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.961
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.004

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 head0.021
GPT teacher head0.257
Teacher spread0.236 · 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