Chemical compositions of solid particles present in the Greenland NEEM ice core over the last 110,000 years
Bibliographic record
Abstract
Abstract This study reports the chemical composition of particles present along Greenland's North Greenland Eemian Ice Drilling (NEEM) ice core, back to 110,000 years before present. Insoluble and soluble particles larger than 0.45 µm were extracted from the ice core by ice sublimation, and their chemical composition was analyzed using scanning electron microscope and energy dispersive X‐ray spectroscopy and micro‐Raman spectroscopy. We show that the dominant insoluble components are silicates, whereas NaCl, Na2SO4, CaSO4, and CaCO3 represent major soluble salts. For the first time, particles of CaMg(CO3)2 and Ca(NO3)2•4H2O are identified in a Greenland ice core. The chemical speciation of salts varies with past climatic conditions. Whereas the fraction of Na salts (NaCl + Na2SO4) exceeds that of Ca salts (CaSO4 + CaCO3) during the Holocene (0.6–11.7 kyr B.P.), the two fractions are similar during the Bølling‐Allerød period (12.9–14.6 kyr B.P.). During cold climate such as over the Younger Dryas (12.0–12.6 kyr B.P.) and the Last Glacial Maximum (15.0–26.9 kyr B.P.), the fraction of Ca salts exceeds that of Na salts, showing that the most abundant ion generally controls the salt budget in each period. High‐resolution analyses reveal changing particle compositions: those in Holocene ice show seasonal changes, and those in LGM ice show a difference between cloudy bands and clear layers, which again can be largely explained by the availability of ionic components in the atmospheric aerosol body of air masses reaching Greenland.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".