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Record W2053563183 · doi:10.1002/elps.201100159

Recent advances in single‐molecule detection on micro‐ and nano‐fluidic devices

2011· review· en· W2053563183 on OpenAlex
Chang Liu, Yueyang Qu, Yong Luo, Ning Fang

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

VenueElectrophoresis · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNanotechnologyMicrofluidicsFluidicsNanofluidicsNano-Materials scienceLab-on-a-chipMicrofluidic chipEngineering

Abstract

fetched live from OpenAlex

Single-molecule detection (SMD) allows static and dynamic heterogeneities from seemingly equal molecules to be revealed in the studies of molecular structures and intra- and inter-molecular interactions. Micro- and nanometer-sized structures, including channels, chambers, droplets, etc., in microfluidic and nanofluidic devices allow diffusion-controlled reactions to be accelerated and provide high signal-to-noise ratio for optical signals. These two active research frontiers have been combined to provide unprecedented capabilities for chemical and biological studies. This review summarizes the advances of SMD performed on microfluidic and nanofluidic devices published in the past five years. The latest developments on optical SMD methods, microfluidic SMD platforms, and on-chip SMD applications are discussed herein and future development directions are also envisioned.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.644
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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 head0.015
GPT teacher head0.293
Teacher spread0.278 · 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