A Compact Field-portable Computational Multispectral Microscope using Integrated Raspberry Pi
Bibliographic record
Abstract
In this paper, we present a compact field-portable computationalmultispectral microscopy system powered by an integrated RaspberryPi computer. The optical components of the low-cost, compactmicroscopy system consists of a cemented achromatic doubletlens place on top of a Raspberry Pi camera module, used tocapture magnified broadband microscopy imaging acquisitions atthree broadband channels in the visible spectrum based on theBayer pattern color filter array. The captured broadband microscopyacquisitions are then processed by a numerical spectral demultiplexer,which demultiplexes the magnified broadband acquisitionsto generate a set of narrowband microscopy images. A Helianthusstem was imaged using the proposed computational multispectralmicroscopy system, and demonstrated to be able to produce narrowbandmicroscopy images at 16 different wavelengths with a singleacquisition without the need for wavelength scanning, whichmakes it well-suited for fast microscopy imaging applications suchas the study of transient phenomenona.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".