Heating of carbonaceous materials: Insights into the effects of thermal metamorphism on spectral properties of carbonaceous chondrites and asteroids
Bibliographic record
Abstract
Abstract Carbonaceous chondrites (CCs) are important materials for understanding the early evolution of the solar system and delivery of organic material to the early Earth. Spectral analysis of CCs can establish the relationship between them and their possible parent asteroids, which helps to determine the surface composition of the asteroid. In this paper, the 0.3–26 μm reflectance spectra of a series of coals ranging from lignite to anthracite (Earth analogs of organic matter contained in CCs), a coal heated to various durations and temperatures, and reflectance spectra of CM2 meteorites were analyzed in conjunction with compositional information to derive spectral–compositional relationships. All types of coals have strong aromatic absorptions (3.28 and 5–6.5 μm) and aliphatic “triplet” absorptions (3.38, 3.41, and 3.48 μm). In contrast, CM2 meteorites have obvious aliphatic absorptions and lack aromatic absorptions. The reason is the weak absorption coefficients of aromatic materials and the overlap with strong OH/H2O absorption. Absorptions in the coal spectra are strongly related to elemental H/C ratio. When the H/C ratio is >0.55, the absorption intensity of an aliphatic increases linearly with the increase of H/C. For heated coal, increasing heating time above 1 h at 450 °C causes the disappearance of the aliphatic “triplet” absorptions. Similarly, heating Murchison meteorite to 400 °C for 1 week causes all the organic absorptions to disappear. This implies that in remote sensing detections, only asteroids (e.g., with CM and CI carbonaceous chondrites compositions) that experienced low thermal metamorphism (<400 °C) are suitable as potential targets for detecting organic compounds using features in the 3–4 µm region.
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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 | 0.000 |
| 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) | 0.001 | 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".