A CMOS Amperometric System for Multi-Neurotransmitter Detection
Bibliographic record
Abstract
In vivo multi-target and selective concentration monitoring of neurotransmitters can help to unravel the brain chemical complex signaling interplay. This paper presents a dedicated integrated potentiostat transducer circuit and its selective electrode interface. A custom 2-electrode time-based potentiostat circuit was fabricated with 0.13 μm CMOS technology and provides a wide dynamic input current range of 20 pA to 600 nA with 56 μ W, for a minimum sampling frequency of 1.25 kHz. A multi-working electrode chip is functionalized with carbon nanotubes (CNT)-based chemical coatings that offer high sensitivity and selectivity towards electroactive dopamine and non-electroactive glutamate. The prototype was experimentally tested with different concentrations levels of both neurotransmitter types, and results were similar to measurements with a commercially available potentiostat. This paper validates the functionality of the proposed biosensor, and demonstrates its potential for the selective detection of a large number of neurochemicals.
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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 | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".