Optofluidic Device Based Microflow Cytometers for Particle/Cell Detection: A Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Optofluidic devices combining micro-optical and microfluidic components bring a host of new advantages to conventional microfluidic devices. Aspects, such as optical beam shaping, can be integrated on-chip and provide high-sensitivity and built-in optical alignment. Optofluidic microflow cytometers have been demonstrated in applications, such as point-of-care diagnostics, cellular immunophenotyping, rare cell analysis, genomics and analytical chemistry. Flow control, light guiding and collecting, data collection and data analysis are the four main techniques attributed to the performance of the optofluidic microflow cytometer. Each of the four areas is discussed in detail to show the basic principles and recent developments. 3D microfabrication techniques are discussed in their use to make these novel microfluidic devices, and the integration of the whole system takes advantage of the miniaturization of each sub-system. The combination of these different techniques is a spur to the development of microflow cytometers, and results show the performance of many types of microflow cytometers developed recently.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it