Composition of aerosol in airborne particulate matter and snow at Alert, Canada 2014-2015
Bibliographic record
Abstract
Carbonaceous aerosols are a major component of fine airborne particulate matter (PM) and play a complex role in the climate system, via their role in light scattering and absorption, cloud nucleation, and the melting of ice- and snow-covered surfaces, and in air pollution and human health. They are removed from the atmosphere via aging and dry and wet deposition. Over the course of one year, we simultaneously analyzed the composition of carbonaceous aerosol in both PM and snow collected at the Dr. Neil Trivett Global Atmosphere Watch Observatory at Alert, Canada. To understand the seasonal variation in the EC (elemental carbon) and OC (organic carbon) burden, we quantified the amount of total carbon (TC) and fraction of light-scattering organic carbon (OC) and light-absorbing elemental carbon (EC) with a Sunset OC/EC analyzer using the EnCan-Total-900 (ECT9) protocol. In addition, we measured the stable carbon value and radiocarbon content of the EC fraction to apportion it into contributions from fossil fuel combustion (gaseous, liquid, and solid fuels such as natural gas, coal, and diesel) and biomass burning (wildfires and biofuel combustion).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".