Aerosol Measurements at Utqiagvik, Alaska, from 2022 to 2027 for Sustaining The Utqiagvik Aerosol Record of Decades (STUARD)
Bibliographic record
Abstract
### Access Dataset can be accessed and downloaded from the 'ADC' directory via: [http://arcticdata.io/data/10.18739/A2X63B701](http://arcticdata.io/data/10.18739/A2X63B701) ### Overview The Arctic is warming faster than any other place on Earth, with sea ice declining rapidly and sources of sea spray and biogenic aerosol emissions changing by consequence. Utqiagvik is at the forefront of this change, abutting one of the largest areas of sea ice loss. This change will have far-reaching impacts to both the environment and the community. Because this change has happened largely in the last decade, now is an important time to both document that change and to continue a data record that will allow for a characterization of the New Arctic, as climate is already altering the Arctic landscape forever. The longest and most complete record of aerosol properties in the American Arctic is that of Utqiagvik, making this unique location serve as a regional record of changes in atmospheric aerosol properties. This dataset will extend the baseline measurements of this Arctic aerosol record, including and continuing the 15-year record of submicron inorganic components (Quinn et al., 2009; Quinn et al., 2002), re-instituting the 2-year record of organic components collected a decade ago (Frossard et al., 2011; Shaw et al., 2010), enhancing the chemical analysis with sulfur isotopes to improve interpretation of emission sources (Kunasek et al., 2010; Thiemens & Lin, 2019), continuing particle number size distribution measurements (Freud et al., 2017), and re-starting cloud condensation nuclei measurements (Schmale, Henning, et al., 2018).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.010 |
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".