Wildfire smoke transport and impact on air quality observed by a mullti-wavelength elastic-raman lidar and ceilometer in New York city
Why this work is in the frame
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Bibliographic record
Abstract
The intense wildfires from the western Canada in May 2016 injected large amount of smoke into the atmosphere. This paper presents integrated observation of the event by a lidar, ceilometer, and satellite together with models and an assessment of smoke plume impacts on local air quality in New York City (NYC) area. A dense aloft plume on May 20 and a boundary layer plume on May 25 are analyzed. The smoke mixing into planetary-boundary-layer (PBL) and strong diurnal variation of PBL-top are shown. For the 2 nd case, the ground PM2.5 measurements show a significant increase in both the urban and upwind non-urban areas of NYC. The smoke sources and transport paths are further verified by the satellite observations and HYSPLIT model data.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 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) | 0.001 | 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 it