An electrochemical Lab-on-a-CD system for parallel whole blood analysis
Bibliographic record
Abstract
Lab-on-a-CD, as a main branch of Lab-on-a-chip technology, has led to several very successful commercial products. Most of these existing Lab-on-a-CD systems present complex system designs and thus are relatively expensive. In this work, we have developed a simple but robust Lab-on-a-CD system for parallel whole blood analyses. This Lab-on-a-CD system incorporates electrochemical bioanalysis and a simple blood sample separation mechanism into the centrifugal platform, and thus reduces the system's complexity. To demonstrate the applicability, the system was applied to perform basic metabolic panel tests, for example, the concentrations of glucose, lactate and uric acids of whole blood samples. Using only 16 μL of whole blood, within a few minutes, the Lab-on-a-CD system could produce results that agreed in general with the data by a conventional system. Therefore, this proof-of-concept Lab-on-a-CD system has demonstrated the potential to become a robust and simple-to-use device for parallel blood analyses.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".