Optofluidic Techniques for the Manipulation of Micro Particles: Principles and Applications to Bioanalyses
Bibliographic record
Abstract
This chapter classifies optofluidic techniques into three categories, (i) fiber-based optofluidic technique; (ii) near-field optofluidic technique; and (iii) axial-type and cross-type optical chromatography. The fundamental mechanism and recent development of these optofluidic techniques are reviewed. Then, the chapter presents a novel SU-8/polydimethylsiloxane (PDMS) optofluidic chip in which an on-chip lens structure is introduced to enhance the performance of microparticle manipulation. Finally, applications of optofluidic techniques to bioanalyses are discussed. Both theoretical and experimental results have shown that the optical manipulation performance could be enhanced by the proposed on-chip lens structures, because the light beam waist radius was reduced by these lens structures. Controlled Vocabulary Terms chromatography; OBIC; symbol manipulation
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".