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Record W2134049250 · doi:10.1002/elps.201500355

Light emitting diode, photodiode‐based fluorescence detection system for DNA analysis with microchip electrophoresis

2015· article· en· W2134049250 on OpenAlexaff
Gordon H. Hall, D. Moira Glerum, C. Backhouse

Bibliographic record

VenueElectrophoresis · 2015
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhotodiodeElectrophoresisFluorescenceCapillary electrophoresisDNA sequencerChromatographyMaterials scienceAnalytical Chemistry (journal)DNAChemistryOptoelectronicsOpticsDNA sequencing

Abstract

fetched live from OpenAlex

Electrophoretic separation of fluorescently end-labeled DNA after a PCR serves as a gold standard in genetic diagnostics. Because of their size and cost, instruments for this type of analysis have had limited market uptake, particularly for point-of-care applications. This might be changed through a higher level of system integration and lower instrument costs that can be realized through the use of LEDs for excitation and photodiodes for detection--if they provide sufficient sensitivity. Here, we demonstrate an optimized microchip electrophoresis instrument using polymeric fluidic chips with fluorescence detection of end-labeled DNA with a LOD of 0.15 nM of Alexa Fluor 532. This represents orders of magnitude improvement over previously reported instruments of this type. We demonstrate the system with an electrophoretic separation of two PCR products and their respective primers. We believe that this is the first LED-induced fluorescence microchip electrophoresis system with photodiode-based detection that could be used for standard applications of PCR and electrophoresis.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.191
Teacher spread0.184 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations15
Published2015
Admission routes1
Has abstractyes

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