A novel dual-path high-throughput acousto-optic tunable filter imaging spectropolarimeter
Bibliographic record
Abstract
It is highly demanding to identify healthy and non-healthy species in a heterogeneous environment such as human tissues. In such a case, one identifier, such as a spectral fingerprint, might be inadequate. Therefore, additional identification is required, for instance, a polarisation measurement. In view of that, the development of a spectropolarimeter that captures two cross-polarised arrays of spectral images is a key requirement. To meet this requirement, an imager optical setup has been designed to provide spatial, spectral and polarisation preference information for species that exist in a heterogeneous environment, such as in medical tissue samples. The spectral and polarisation information is obtained employing an acousto-optic tunable filter and a polarising beam splitter, respectively. The optical imager is designed to operate in the visible-near infrared range (450–850 nm) with a spectral resolution of 3 nm. The spectropolarimeter design along with optical characterisation results are reported.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".