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Record W2337364160 · doi:10.1039/c6an00129g

Paper-based biodetection using luminescent nanoparticles

2016· review· en· W2337364160 on OpenAlex
Qiang Ju, M. Omair Noor, Ulrich J. Krull

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.

Bibliographic record

VenueThe Analyst · 2016
Typereview
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBioanalysisNanotechnologyNanoparticleLuminescenceOptical sensingLuminescent MeasurementsMaterials scienceChemistryOptoelectronics

Abstract

fetched live from OpenAlex

Point-of-care and in-field technologies for rapid, sensitive and selective detection of molecular biomarkers have attracted much interest. Rugged bioassay technology capable of fast detection of markers for pathogens and genetic diseases would in particular impact the quality of health care in the developing world, but would also make possible more extensive screening in developed countries to tackle problems such as those associated with water and food quality, and tracking of infectious organisms in hospitals and clinics. Literature trends indicate an increasing interest in the use of nanomaterials, and in particular luminescent nanoparticles, for assay development. These materials may offer attributes for development of assays and sensors that could achieve improvements in analytical figures of merit, and provide practical advantages in sensitivity and stability. There is opportunity for cost-efficiency and technical simplicity by implementation of luminescent nanomaterials as the basis for transduction technology, when combined with the use of paper substrates, and the ubiquitous availability of cell phone cameras and associated infrastructure for optical detection and transmission of results. Luminescent nanoparticles have been described for a broad range of bioanalytical targets including small molecules, oligonucleotides, peptides, proteins, saccharides and whole cells (e.g., cancer diagnostics). The luminescent nanomaterials that are described herein for paper-based bioassays include metal nanoparticles, quantum dots and lanthanide-doped nanocrystals. These nanomaterials often have broad and strong absorption and narrow emission bands that improve opportunity for multiplexed analysis, and can be designed to provide emission at wavelengths that are efficiently processed by conventional digital cameras. Luminescent nanoparticles can be embedded in paper substrates that are designed to direct fluid flow, and the resulting combination of technologies can offer competitive analytical performance at relatively low cost.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.046
GPT teacher head0.283
Teacher spread0.237 · 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