Contamination analysis of Arctic ice samples as planetary field analogs and implications for future life-detection missions to Europa and Enceladus
Bibliographic record
Abstract
Missions to detect extraterrestrial life are being designed to visit Europa and Enceladus in the next decades. The contact between the mission payload and the habitable subsurface of these satellites involves significant risk of forward contamination. The standardization of protocols to decontaminate ice cores from planetary field analogs of icy moons, and monitor the contamination in downstream analysis, has a direct application for developing clean approaches crucial to life detection missions in these satellites. Here we developed a comprehensive protocol that can be used to monitor and minimize the contamination of Arctic ice cores in processing and downstream analysis. We physically removed the exterior layers of ice cores to minimize bioburden from sampling. To monitor contamination, we constructed artificial controls and applied culture-dependent and culture-independent techniques such as 16S rRNA amplicon sequencing. We identified 13 bacterial contaminants, including a radioresistant species. This protocol decreases the contamination risk, provides quantitative and qualitative information about contamination agents, and allows validation of the results obtained. This study highlights the importance of decreasing and evaluating prokaryotic contamination in the processing of polar ice cores, including in their use as analogs of Europa and Enceladus.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".