Nanoparticle and microorganism detection with a side-micron-orifice-based resistive pulse sensor
Bibliographic record
Abstract
This paper presents the detection of nanoparticles and microorganisms using a recently developed side-orifice-based resistive pulse sensor (SO-RPS). By decreasing the channel height of the detection section of the SO-RPS, the detection sensitivity was increased and an average signal to noise ratio (S/N) of about 3 was achieved for 100 nm polystyrene particles. It was also found that spherical particles generate symmetrical signals. Algae with irregular shapes generate signals with more complex patterns. A scatter plot of signal magnitude versus signal width was proven to be reliable for differentiating bacteria from the nanoparticles and two types of algae. The side orifice for detecting heterogeneous nanoparticles and microorganisms is advantageous to avoid orifice clogging and the large flow resistance.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".