A User-Centered Approach in the Development of a Label-Free Impedimetric Chemiresistor for H <sub>2</sub> O <sub>2</sub>
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide A strong focus on laboratory optimization in new sensing technology often delays and sometimes prevents successful real-world implementation. Accordingly, we present a proof-of-concept impedimetric chemiresistor (ICR) for a noninvasive, point-of-care device that combines the development of a novel electrochemical sensing modality with a user-centered approach. The ICR features a two-electrode design fabricated by using a low-cost, scalable roll-to-roll (R2R) flexographic printing technique and a zeolitic imidazolate framework-8 (ZIF-8) chemiresistive channel. Here, we demonstrated the ICR’s response to hydrogen peroxide (H 2 O 2 ) as an initial step toward a noninvasive hypoglycemia diagnostic tool. The ICR exhibits a linear impedance response to H 2 O 2, with a limit-of-detection of 3.7 mM, a dynamic range of 4–60 mM, and preliminary validation in human saliva. Early user feedback guided device design and highlighted how incorporating usability throughout development supports the successful transition from a lab prototype to a real-world healthcare technology.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".