High-performance hyperspectral imaging using virtual slit optics
Bibliographic record
Abstract
Tornado Spectral Systems (TSS) has developed High Throughput Virtual Slit (HTVS) technology that improves the performance of spectrometers by factors of several while maintaining system size. In the simplest configuration, the HTVS allows optical designers to remove the lossy slit from a spectrometer, greatly increasing throughput without a loss of resolution. This is especially useful in many standoff applications, where every photon matters. TSS has tested multiple configurations of HTVS spectral sensing and spectral imaging technology, including standoff sensing, point scan imaging, long-slit pushbroom imaging and similar configurations. The HTVS throughput-resolution advantage allows us to increase scanning speed, decrease system size, decrease aperture, decrease source intensity requirements or some combination of all four. HTVS technology expands the realm of viable spectral imaging applications. We discuss the applicability of this technology to spectral imaging and standoff sensing and present experimental results from several prototype and production spectrometers.
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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 | 0.001 |
| 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".