Bendable Electro-chemical Lactate Sensor Printed with Silver Nano-particles
Bibliographic record
Abstract
Here we report a flexible amperometric lactate biosensor using silver nanoparticle based conductive electrode. Mechanically bendable cross-serpentine-shaped silver electrode is generated on flexible substrate for the mechanical durability such as bending. The biosensor is designed and fabricated by modifying silver electrode with lactate oxidase immobilized by bovine serum albumin. The in-sensor pseudo Ag/AgCl reference electrode is fabricated by chloridization of silver electrode, which evinced its long-term potential stability against a standard commercial Ag/AgCl reference electrode. The amperometric response of the sensor shows linear dependence with lactate concentration of 1~25 mM/L. Anionic selectivity is achieved by using drop-casted Nafion coated on silver electrode against anionic interferences such as ascorbate. This non-invasive electrochemical lactate sensor also demonstrates excellent resiliency against mechanical deformation and temperature fluctuation which leads the possibility of using it on human epidermis for continuous measurement of lactate from sweat. Near field communication based wireless data transmission is demonstrated to reflect a practical approach of the sensor to measure lactate concentration portably using human perspiration.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".