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Record W2901425747 · doi:10.1039/c8an01891j

Cost-effective side-illumination darkfield nanoplasmonic marker microscopy

2018· article· en· W2901425747 on OpenAlex
Mengjiao Qi, Cécile Darviot, Sergiy Patskovsky, Michel Meunier

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 · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Electron Microscopy Techniques and Applications
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMicroscopyDark field microscopyBright-field microscopyOpticsMaterials scienceNanotechnologyChemistryPhysics

Abstract

fetched live from OpenAlex

We present the development of an innovative technology for quantitative multiplexed cytology analysis based on the application of spectrally distinctive plasmonic nanoparticles (NPs) as optical probes and on cost-effective side-illumination multispectral darkfield microscopy (SIM) as the differential NP imaging method. SIM is based on lateral illumination by arrays of discrete color RGB light emitting diodes (LEDs) of spectrally adjusted plasmonic NPs and consecutive detection by the conventional CMOS color camera. We demonstrate the enhanced contrast and higher resolution of our method for individual NP detection in the liquid medium and of NP markers attached on the cell membrane in a cytology preparation by comparing it to the conventional darkfield microscopy (DFM). The proposed illumination and detection system is compatible with current clinical microscopy equipment used by pathologists and can greatly simplify the adaptation of plasmonic NPs as novel reliable and stable biological multiplexed chromatic markers for biodetection and diagnosis.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.255
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.338
Teacher spread0.329 · 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