Bibliographic record
Abstract
Two biosensor chips, realized in standard 0.18μm CMOS, are presented with test results using biological analytes. The electrochemical biosensor, consisting of a 3×3 array of three-electrode sensing elements, occupies 1.4mm2, and can be reconfigured dynamically, via on-chip register, to perform: impedance spectroscopy, amperometric and potentiometric analysis. The design follows concepts previously published, but uses new transistor sizing and placement. Impedance spectroscopy test results are presented for the protein linker BSA; previous work is extended by presenting test results for different size on-chip aluminum-alloy electrodes offering an effective approach to detect different concentrations. The second design, the SEPTIC Detector, detects ions that flood out from a targeted bacterial cell wall when specific bacteriophages are applied. The 1.1mm2 chip is the first to confirm the efficacy of CMOS and aluminum alloy electrodes spaced to create a 0.46μm×10μm×0.9μm trench. Test results confirm identification of E. coli W3110 bacteria cells using bacteriophage λ, within 160sec.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.022 |
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".