A sample preparation guide for clay‐rich carbonaceous chondrites
Bibliographic record
Abstract
Abstract The matrix of the C2‐ungrouped Tarda meteorite contains abundant smectite minerals that swell and crumble when exposed to polar liquids, causing the sample to rapidly slake. This phenomenon presents a serious challenge when polishing the meteorite, as common polishing liquids used on carbonaceous chondrites, such as water, ethanol, ethylene glycol, and isopropyl alcohol, are polar and will cause the sample to swell, making it unsuitable for some analyses. Hexane and mineral oil are nonpolar liquids that were found to not induce swelling on highly expansive montmorillonite‐clay analog material and were effectively integrated into a polishing procedure for Tarda. Here, we detail a procedure for mounting, cutting, and polishing the Tarda meteorite to prepare a surface that is suitable for a variety of sensitive techniques, such as electron microprobe analysis. This work offers a practical methodology for the preparation of other clay‐rich samples, which may include the recently returned Ryugu and Bennu 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.064 | 0.042 |
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".