An integrated hybrid interference and absorption filter for fluorescence detection in lab-on-a-chip devices
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".