SAMSON: Spectral Absorption-fluorescence Microscopy System for ON-site-imaging of algae
Bibliographic record
Abstract
This paper presents SAMSON, a Spectral Absorption-fluorescenceMicroscopy System for ON-site-imaging of algae within a watersample. Designed to be portable and low-cost for on-site use,the optical sub-system of SAMSON consists of a mixture of low-cost optics and electronics, designed specifically to capture bothfluorescent and absorption responses from a water sample. Thegraphical user interface (GUI) sub-system of SAMSON was de-signed to enable flexible visualisation of algae in the water samplein real-time, with the ability to perform fine-grained exposure con-trol and illumination wavelength selection. We demonstrate SAM-SON’s capabilities by equipping the system with two fluorescentillumination sources and seven absorption illumination sources toenable the capture of multispectral data from six different algaespecies (three from the Cyanophyta phylum (blue-green algae) andthree from the Chlorophyta phylum (green algae)). The key benefitof SAMSON is the ability to perform rapid acquisition of fluores-cence and absorption data at different wavelengths and magnifica-tion levels, thus opening the door for machine learning methods toautomatically identify and enumerate different algae in water sam-ples using this rich wealth of data.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".