Hyperspectral Cathodoluminescence Imaging and Analysis Extending from Ultraviolet to Near Infrared
Bibliographic record
Abstract
The measurement of near-infrared (NIR) cathodoluminescence (CL) with sufficient sensitivity to allow full spectral mapping has been investigated through the application of optimized grating spectrometers that allow the ultraviolet (UV), visible, and NIR CL spectra to be measured simultaneously. Two optical spectrometers have been integrated into an electron microprobe, allowing simultaneous collection of hyperspectral CL (UV-NIR), characteristic X-rays, and electron signals. Combined hyperspectral CL spectra collected from two natural apatite (Ca5[PO4]3[OH,F]) samples from Wilberforce (Ontario, Canada) and Durango (Mexico) were qualitatively analyzed to identify the emission centers and then deconvoluted pixel-by-pixel using least-squares fitting to produce a series of ion-resolved CL intensity maps. Preliminary investigation of apatite has shown strong NIR emissions associated primarily with the rare-earth element Nd. Details of growth and alteration were revealed in the NIR that were not discernable with electron-induced X-ray mapping. Intense emission centers from Nd3+ and Sm3+ were observed in the spectra from both apatites, along with minor emissions from other 3+ rare-earth elements. Quantitative electron probe microanalysis was performed on points within the mapped area of the Durango apatite to produce a calibration line relating cathodoluminescent intensity of the fitted peak centered at 1,073 nm (1.156 eV) to the Nd concentration.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".