Ion Channel Biosensors—Part II: Dynamic Modeling, Analysis, and Statistical Signal Processing
Why this work is in the frame
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Bibliographic record
Abstract
This paper deals with the dynamic modeling, analysis, and statistical signal processing of the ion channel switch biosensor. The electrical dynamics are described by a second-order linear system. The chemical kinetics of the biosensor response to analyte concentration in the reaction-rate-limited regime are modeled by a two-timescale nonlinear system of differential equations. Also, the analyte concentration in the mass-transport-influenced regime is modeled by a partial differential equation subject to a mixture of Neumann and Dirichlet boundary conditions. By using the theory of singular perturbation, we analyze the model so as to predict the performance of the biosensor in transient and steady-state regimes. Finally, we outline the use of statistical signal processing algorithms that exploit the biosensor dynamics to classify analyte concentration.
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.
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 | 0.000 |
| 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 it