Alternative integrations for microfluidic cytometry
Bibliographic record
Abstract
Two possible system integration approaches for portable real time cytometry in microfluidic applications are discussed. An ocular mounted linear CMOS image sensor configured for real time detection of particles being transported in microfluidic channels is first described. This system delivers cytometry functionality utilizing standard microfluidic chips and conventional optics. While this approach affords a certain ease of integration, one significant drawback is the singular field of view onto the microfluidic substrate and the reliance on conventional microscopy. However, the microscopy resolution makes possible a simple device capable of determining precise position, size and trajectory information on a per particle basis. A second architecture comprises flip-chip integration of a custom CMOS active pixel sensor aboard a custom microfluidic glass substrate. At the expense of optical resolution, the near field sensor topology obviates the need for conventional microscopy, affords simultaneous multi-channel sensing and takes strides towards cost effective micro total analysis system (uTAS) deployment. The two platforms share a common microcontroller for processing, control and display as well as a unified host-side application programming interface; an approach which will enable side-by-side comparison of the two hardware architectures in real time. The common user interface, a platform independent .NET application, deploys to both desktop and compact framework pocket PC platforms.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".