Effects of aqueous alteration on primordial noble gases and presolar SiC in the carbonaceous chondrite Tagish Lake
Bibliographic record
Abstract
Abstract Effects of aqueous alteration on primordial noble gas carriers were investigated by analyzing noble gases and determining presolar SiC abundances in insoluble organic matter (IOM) from four Tagish Lake meteorite (C2‐ung.) samples that experienced different degrees of aqueous alteration. The samples contained a mixture of primordial noble gases from phase Q and presolar nanodiamonds (HL, P3), SiC (Ne‐E[H]), and graphite (Ne‐E[L]). The second most altered sample (11i) had a ~2–3 times higher Ne‐E concentration than the other samples. The presolar SiC abundances in the samples were determined from NanoSIMS ion images and 11i had a SiC abundance twice that of the other samples. The heterogeneous distribution of SiC grains could be inherited from heterogeneous accretion or parent body alteration could have redistributed SiC grains. Closed system step etching (CSSE) was used to study noble gases in HNO3‐susceptible phases in the most and least altered samples. All Ne‐E carried by presolar SiC grains in the most altered sample was released during CSSE, while only a fraction of the Ne‐E was released from the least altered sample. This increased susceptibility to HNO3 likely represents a step toward degassing. Presolar graphite appears to have been partially degassed during aqueous alteration. Differences in the 4He/36Ar and 20Ne/36Ar ratios in gases released during CSSE could be due to gas release from presolar nanodiamonds, with more He and Ne being released in the more aqueously altered sample. Aqueous alteration changes the properties of presolar grains so that they react similar to phase Q in the laboratory, thereby altering the perceived composition of Q.
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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 | 0.000 | 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) | 0.001 | 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".