Electrochemical Sensing of DNA with Porous Silicon Layers
Bibliographic record
Abstract
The nanostructure known as porous silicon is an excellent material for sensing applications. Due to its large internal surface, it is capable of adsorbing an enormous amount of different compounds. The average porous size can be easily adjusted to allow the pene- tration of molecular compounds with different sizes. In this work we show a sensing application for porous silicon. We have fabricated a biosensor from DNA. The biosensor is an electrochemical device that transduces the hybridization of DNA into a chemical oxidation of guanine by , the reduced form of which is then detected electrochemically. The anodic peak current of was linearly related to the target DNA sequence in the range 0.5×10 -10 - 500×10 -10 M with a detection limit of 0.5×10 -10 M. In addition the ruthenium bipyridine indicator was able to selectively discriminate against different DNA sequences; a necessary property for sensing applications. + 2 3 ) (bpy Ru + 2 3 ) (bpy Ru
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".