Thermal infrared reflectance and emission spectroscopy of quartzofeldspathic glasses
Bibliographic record
Abstract
This investigation seeks to better understand the thermal infrared (TIR) spectral characteristics of naturally‐occurring amorphous materials through laboratory synthesis and analysis of glasses. Because spectra of glass phases differ markedly from their mineral counterparts, examination of glasses is important to accurately determine the composition of amorphous surface materials using remote sensing datasets. Quantitatively characterizing TIR (5–25 μ m) spectral changes that accompany structural changes between glasses and mineral crystals provides the means to understand natural glasses on Earth and Mars. A suite of glasses with compositions analogous to common terrestrial volcanic glasses was created and analyzed using TIR reflectance and emission techniques. Documented spectral characteristics provide a basis for comparison with TIR spectra of other amorphous materials (glasses, clays, etc.). Our results provide the means to better detect and characterize glasses associated with terrestrial volcanoes, as well as contribute toward understanding the nature of amorphous silicates detected on Mars.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 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".