A portable paper-based microfluidic platform for multiplexed electrochemical detection of human immunodeficiency virus and hepatitis C virus antibodies in serum
Bibliographic record
Abstract
This paper presents a portable paper-based microfluidic platform for multiplexed electrochemical detection of antibody markers of human immunodeficiency virus (HIV) and hepatitis C virus (HCV) in serum samples. To our best knowledge, this is the first paper-based electrochemical immunosensing platform, with multiplexing and telemedicine capabilities, for diagnosing HIV/HCV co-infection. The platform consists of an electrochemical microfluidic paper-based immunosensor array (E-μPIA) and a handheld multi-channel potentiostat, and is capable of performing enzyme-linked immunosorbent assays simultaneously on eight samples within 20 min (using a prepared E-μPIA). The multiplexing feature of the platform allows it to produce multiple measurement data for HIV and HCV markers from a single run, and its wireless communication module can transmit the results to a remote site for telemedicine. The unique integration of paper-based microfluidics and mobile instrumentation renders our platform portable, low-cost, user-friendly, and high-throughput.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".