Low Light CMOS Contact Imager with an Integrated Poly-Acrylic Emission Filter for Fluorescence Detection
Bibliographic record
Abstract
This study presents the fabrication of a low cost poly-acrylic acid (PAA) based emission filter integrated with a low light CMOS contact imager for fluorescence detection. The process involves the use of PAA as an adhesive for the emission filter. The poly-acrylic solution was chosen due its optical transparent properties, adhesive properties, miscibility with polar protic solvents and most importantly its bio-compatibility with a biological environment. The emission filter, also known as an absorption filter, involves dissolving an absorbing specimen in a polar protic solvent and mixing it with the PAA to uniformly bond the absorbing specimen and harden the filter. The PAA is optically transparent in solid form and therefore does not contribute to the absorbance of light in the visible spectrum. Many combinations of absorbing specimen and polar protic solvents can be derived, yielding different filter characteristics in different parts of the spectrum. We report a specific combination as a first example of implementation of our technology. The filter reported has excitation in the green spectrum and emission in the red spectrum, utilizing the increased quantum efficiency of the photo sensitive sensor array. The thickness of the filter (20 μm) was chosen by calculating the desired SNR using Beer-Lambert's law for liquids, Quantum Yield of the fluorophore and the Quantum Efficiency of the sensor array. The filters promising characteristics make it suitable for low light fluorescence detection. The filter was integrated with a fully functional low noise, low light CMOS contact imager and experimental results using fluorescence polystyrene micro-spheres are presented.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".