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Record W2086531350 · doi:10.1039/b819080a

An integrated hybrid interference and absorption filter for fluorescence detection in lab-on-a-chip devices

2009· article· en· W2086531350 on OpenAlex

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

VenueLab on a Chip · 2009
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMaterials scienceMicroelectronicsOptoelectronicsInterference filterFilter (signal processing)AttenuationOptical filterAutofluorescenceAbsorption (acoustics)MicrofluidicsChipMicrofabricationFluorescenceOpticsNanotechnologyComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

We present a hybrid optical filter design that combines interference and absorbing components for enhanced fluorescence detection in miniaturized highly-integrated lab-on-a-chip devices. The filter is designed in such a way that the advantages of each technology are used to offset the disadvantages of the other. The filter is fabricated with microfabrication compatible processes and materials for monolithic integration with microelectronics and microfluidics devices. The particular embodiment of the filter described herein is designed to discriminate fluorescence emission at 650 nm from excitation at 532 nm. The 9-layer interference filter component is fabricated with alternating TiO(2) and SiO(2) thin-film layers and has an attenuation of -12.6 dB at 532 nm and -0.76 dB at 650 nm. The absorbing filter component is fabricated using a dyed photopolymer (KMPR + Orasol Red) having an attenuation of -32.6 dB at 532 nm and -1.28 dB at 650 nm. The total rejection ratio of the hybrid filter is 43 dB. The filter exhibits very low autofluorescence and performs equally well at off-axis incidence angles.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.531

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 head0.013
GPT teacher head0.236
Teacher spread0.224 · 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