FSR: a field portable spectral reflectometer to measure ground from NIR to LWIR
Bibliographic record
Abstract
ABB Bomem has recently designed a field-deployable reflectometer. The Full Spectrum Reflectometer (FSR) measures the diffuse reflectance of surfaces in the 0.7 μm to 13.5 μm spectral range. The spectral resolution is adjustable from 32 to 4 cm-1. The instrument is portable, battery-operated and designed for field usage in a single, lightweight and ruggedized package. In its simplest mode, the instrument is automated and can be operated by non-specialist personnel with minimal training. The FSR has a laboratory mode to measure targets brought to the instrument in a sampling cup and a field mode with automated measurement sequence. To facilitate the measurement of various ground surfaces, the instrument is packaged in a three-point mount for easy target access and stability. One of the mount is the sampling port. The instrument has its own built-in NIR and LWIR infrared sources to illuminate the ground area to be measured. The instrument includes two built-in references for calibration: a Spectralon diffuser and an Infragold diffuser. The first units were commissioned to build a spectral database of surfaces in various conditions (humidity, temperature, texture, mixing, etc.) and in the presence of interfering chemicals (oils, solvents, etc.) but the instrument can also serve other purposes such as the identification of unknown materials.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.012 |
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".