A technique for continuous detection of drill liquid in ice cores
Bibliographic record
Abstract
Abstract When drilling ice cores deeper than ∼100 m, drill liquid is required to maintain ice-core quality and to limit borehole closure. Due to high-pressure air bubbles in the ice, the ice core can crack during drilling and core retrieval, typically at 600–1200 m depth in Greenland. Ice from this ‘brittle zone’ can be contaminated by drill liquid as it seeps through cracks into the core. Continuous flow analysis (CFA) systems are routinely used to analyse ice for chemical impurities, so the detection of drill liquid is important for validating accurate measurements and avoiding potential instrument damage. An optical detector was constructed to identify drill liquid in CFA tubing by ultraviolet absorption spectroscopy at a wavelength of 290 nm. The set-up was successfully field-tested in the frame of the NEEM ice-core drilling project in Greenland. A total of 27 cases of drill liquid contamination were identified during the analysis of 175 m of brittle zone ice. The analyses most strongly affected by drill liquid contamination include insoluble dust particles, electrolytic conductivity, ammonium, hydrogen peroxide and sulphate. This method may also be applied to other types of drill liquid used at other drill sites.
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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 | 0.001 | 0.001 |
| 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".