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Record W3125115458 · doi:10.18433/jpps31434

ADVANCES OF NON-IRON METAL NANOPARTICLES IN BIOMEDICINE

2021· review· en· W3125115458 on OpenAlexvenueno aff
Anroop B. Nair, Mohamed A. Morsy, Pottathil Shinu, Sabna Kotta, Mithra Chandrasekaran, Abu Tahir

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2021
Typereview
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsnot available
Fundersnot available
KeywordsBiomedicineNanotechnologyPhotothermal therapyNanoparticleDrug deliveryMaterials scienceBioinformaticsBiology

Abstract

fetched live from OpenAlex

Metal nanoparticles (MNPs) comprise of nanoparticles originating from metallic elements with additional properties inherent to metal ions. MNPs found applications in various field such as electronics, optics, mechanics, physics etc. There are many reviews on iron MNPs for biomedical application. Hence, in this review, we focus on non-iron MNPs and their vivid biomedical applications. Here, we review the applications of non-iron MNPs in biomedicine such as drug delivery, gene delivery, anticancer activity, antimicrobial activity, tissue engineering, bioimaging, and photodynamic, and photothermal therapies.

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 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)0.005
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.728
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.098
GPT teacher head0.449
Teacher spread0.352 · 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 teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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

Citations18
Published2021
Admission routes1
Has abstractyes

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