Influence of Ohio Valley emissions on fine particle sulfate measured from aircraft over large regions of the Eastern U.S. and Canada during INTEX-NA
Bibliographic record
Abstract
Aircraft measurements of fine inorganic aerosol composition were made with a\nparticle-into-liquid sampler coupled to dual ion chromatographs (PILS-IC) as part of\nthe NASA INTEX-NA study. The sampling campaign, which lasted from 1 July to\n14 August 2004, centered over the eastern United States and Canada and showed that\nsulfate was the dominant inorganic species measured. The highest sulfate concentrations\nwere observed at altitudes below 2 km, and back trajectory analyses showed a\ndistinct difference between air masses that had or had not intercepted the Ohio River\nvalley (ORV) region. Air masses encountered below 2 km with a history over the ORV\nhad sulfate concentrations that were higher by a factor of 3.2 and total sulfur (S)\nconcentrations higher by 2.5. The study’s highest sulfate concentrations were found in\nthese air masses. The sulfur of the ORV air masses was also more processed with a mean\nsulfate to total sulfur molar ratio of 0.5 compared to 0.3 in non-ORV measurements.\nResults from a second, independent trajectory model agreed well with those from the\nprimary analysis. These ORV-influenced air masses were encountered on multiple days\nand were widely spread across the eastern United States and western Atlantic region.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".