Integrated optical microfluidic lab-on-a-chip
Bibliographic record
Abstract
Bio-security for health monitoring and diagnosis are the needs of the hour, for rapid detection of biological and chemical species. This calls for a necessity to develop a cost effective miniaturized and portable biosensor device for in-situ biomedical applications and Point-of-Care Testing (POCT). While portability of the biosensor is required for in-situ medical detections, miniaturization is essential for handling smaller sample volumes and high throughput. Thus, the above mentioned concerns cannot be addressed unless a fully integrated biosensor system is developed. In this work, an integrated opto microfluidic based Lab-on-a-chip device is proposed for carrying out fluorescence based biodetection. The input and output fibers were integrated with the microfluidic channel so as to make a robust setup. Fluorescence detection was carried out using Alexafluor 647 tagged antibody particles and the output was measured with a Spectrometer-on-Chip, integrated with the device. The experimental results prove that the proposed device is highly suitable for Lab-on-a-Chip applications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".