Laboratory Transmission Spectra of Anthropogenic and Natural Terrestrial Dust and Mars Analogues
Bibliographic record
Abstract
<!--!introduction!--> Empirical laboratory spectroscopic studies of materials relevant to the Earth and Mars can provide multiple benefits to planetary exploration. We have undertaken a spectral transmission study of an extensive suite (>25 sample) of natural and anthropogenic materials present in the Earth’s atmosphere as well as of minerals known to be present or hoped-for on Mars that: (1) can be indicative of habitability; (2) may be indicative of biological processes; or are considered to be important for microorganism metabolism. Transmission spectra of these samples were acquired over the 1.5-25 micron range for different concentrations (0.3-15 wt.%) of fine-grained powders dispersed in KBr, as well as reflectance spectra over the 0.35-2.5 µm range or higher, providing a region of spectral overlap to compare transmission to reflectance absorption features. Using different concentrations of sample allows for identification of: weak and strong absorption bands; diagnostic spectral regions; as well as atmospheric windows for different dust loadings. Solar occultation measurements of the Martian atmosphere, such as those acquired by the ExoMars Trace Gas Orbiter, could be used in conjunction with these laboratory measurements to estimate atmospheric opacity. In addition, solar occultation measurements could allow for better identification of phases which are weakly expressed in surface reflectance spectra.
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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) | 0.003 | 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".