A CMOS-Microfluidic Chemiluminescence Contact Imaging Microsystem
Bibliographic record
Abstract
A hybrid CMOS-microfluidic microsystem for chemiluminescence and electrochemiluminescence-based biochemical sensing is presented. The microsystem integrates a two-layer soft polymer microfluidic network and a CMOS imager fabricated in a standard 0.35-$\mu$m technology. The CMOS imager consists of a 64$\,\times\,$128-pixel array interdigitated with a 32$\,\times\,$64 electrolessly plated nickel–gold microelectrode array. A two-transistor reset path technique attenuates the subthreshold leakage current of the reset transistor which constitutes a significant portion of the dark current. An active reset technique, in-pixel flicker noise cancellation, and pixel binning contribute to noise reduction. The imager achieves a low dark current of 3.6 nA/cm$^{2}$for photodiode reset voltages as high as 2.3 V, noise of 110$\mu$Vrms with maximum time of photon integration of 90 s, and a dynamic range of 67.8 dB. The CMOS-microfluidic microsystem is validated in on-chip chemiluminescence and electrochemiluminescence detection of luminol.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".