Representativeness and seasonality of major ion records derived from NEEM firn cores
Bibliographic record
Abstract
Abstract. The seasonal and annual representativeness of ionic aerosol proxies (among others, calcium, sodium, ammonium and nitrate) in various firn cores in the vicinity of the NEEM drill site in northwest Greenland have been assessed. Seasonal representativeness is very high as one core explains more than 60% of the variability within the area. The inter-annual representativeness, however, can be substantially lower (depending on the species) making replicate coring indispensable to derive the atmospheric variability of aerosol species. A single core at the NEEM site records only 30% of the inter-annual atmospheric variability in some species, while five replicate cores are already needed to cover approximately 70% of the inter-annual atmospheric variability in all species. The spatial representativeness is very high within 60 cm, rapidly decorrelates within 10 m but does not diminish further within 3 km. We attribute this to wind reworking of the snow pack leading to sastrugi formation. Due to the high resolution and seasonal representativeness of the records we can derive accurate seasonalities of the measured species for modern (AD 1990–2010) times as well as for pre-industrial (AD 1623–1750) times. Sodium and calcium show similar seasonality (peaking in February and March respectively) for modern and pre-industrial times, whereas ammonium and nitrate are influenced by anthropogenic activities. Nitrate and ammonium both peak in May during modern times, whereas during pre-industrial times ammonium peaked during July–August and nitrate during June–July.
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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 | 0.000 | 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 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".