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Record W3104658373 · doi:10.3389/fchem.2020.580033

A Perspective on Application of Carbon Quantum Dots in Luminescence Immunoassays

2020· article· en· W3104658373 on OpenAlexafffund
Mahdi Hesari, Zhifeng Ding

Bibliographic record

VenueFrontiers in Chemistry · 2020
Typearticle
Languageen
FieldMaterials Science
TopicCarbon and Quantum Dots Applications
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationOntario Innovation Trust
KeywordsQuantum dotNanotechnologyNanomaterialsLuminescenceCarbon nanotubeBiocompatibilityMaterials scienceCarbon fibersCadmium telluride photovoltaicsCarbon quantum dotsOptoelectronicsComposite number

Abstract

fetched live from OpenAlex

Quantum dots (QDs) have been established in our daily life, for instance, in display screens and light-harvesting technologies, mainly owing to their peculiar opto-electronic features. However, toxicity of inorganic QDs, such as CdSe, CdTe, and perovskites, limits their applications in biological environments for medical diagnosis and bio-imaging purposes. A new generation of QDs called carbon quantum dots (CQDs) have been progressing rapidly over the past few years. CQDs have become as popular as other carbon-based nanomaterials such as carbon nanotubes (CNTs), due to their ease of preparation, ultra-small size, biocompatibility, and bright luminescence.

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)0.004
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.004
Scholarly communication0.0030.006
Open science0.0030.001
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.0110.004

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 head0.009
GPT teacher head0.242
Teacher spread0.233 · 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 designNot applicable
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

Citations12
Published2020
Admission routes2
Has abstractyes

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