Cold curation of pristine astromaterials: Insights from the Tagish Lake meteorite
Bibliographic record
Abstract
Abstract The curation and handling of volatile‐bearing astromaterials is of prime importance in current and future plans for sample return missions to targets containing organic compounds, ices, or other volatile components. We report on the specific curation constraints required for the preservation of the Tagish Lake meteorite, a C2 ungrouped chondrite that contains significant concentrations of organic matter, including compounds of prebiotic interest or volatile in character, and which was recovered from a frozen lake surface a few days after its fall. Here, we review the circumstances of the meteorite's handling, its complement of intrinsic and contaminant organic compounds, and an unusual reaction between some of the specimens and the Al foil in which they were enclosed. From our results, we derive the requirements for curation of the meteorite, and describe a specialized facility that enables its curation and handling. The Subzero Facility for Curation of Astromaterials consists of a purified Ar glove box enclosed within a freezer chamber, and enables investigations relevant to curation of samples at or below −10 °C. We provide several recommendations based on insights obtained from the commissioning and initial use of the facility that are relevant to collection of freshly fallen meteorites, curation of volatile‐bearing meteorites and other astromaterials, and planning and implementation of curation plans for future sample return missions to volatile‐bearing targets.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".