Summertime carbonaceous aerosols collected in the marine boundary layer of the Arctic Ocean
Bibliographic record
Abstract
The chemistry, morphology, and microscale to nanoscale structures of carbonaceous aerosols from the marine boundary layer of the Arctic Ocean were investigated by a variety of electron microscopy techniques, including scanning electron microscopy (SEM), high‐resolution transmission electron microscopy (HRTEM), and energy‐dispersive X‐ray spectroscopy (EDS). The relative levels of particles of black carbon (BC) were determined by electron paramagnetic resonance (EPR). Polycyclic aromatic hydrocarbons (PAHs) absorbed onto BC particles were extracted by the soxhlet extraction method and analyzed by gas chromatography mass spectrometry (GC‐MS). The results show that the dominant particles of BC are char particles with spherical shape, porous structure, and high sulfur content, which are typically derived from residual oil combustion on ships. The spatial distribution of BC from ship emissions was found to be concentrated around the periphery of the Arctic Ocean, suggesting relatively intensive contamination by ships in the Russian and Canadian Arctic. The abundance of PAHs on BC particles ranges from 142 to 2672 pg/m3 (mean = 702 pg/m3), which is significantly higher than values previously measured by land‐based observation. Thus we find that ship emissions are a potentially important contributor to the PAH levels at some locations in the Arctic Ocean during the summer.
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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 | 0.001 | 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".