ADABBOY: African Dust And Biomass Burning Over Yucatan
Bibliographic record
Abstract
Abstract Biomass burning (BB) emissions and African dust (AD) are often associated with poor regional air quality, particularly in the tropics. The Yucatan Peninsula is a fairly pristine site due to predominant trade winds, but occasionally BB and AD plumes severely degrade its air quality. The African Dust And Biomass Burning Over Yucatan (ADABBOY) project (January 2017–August 2018) was conducted in the Yucatan Peninsula to characterize physical and biological properties of particulate pollution at remote seaside and urban sites. The 18-month-long project quantified the large interannual variability in frequency and spatial extent of BB and AD plumes. Remote and urban sites experienced air quality degradation under the influence of these plumes, with up to 200% and 300% increases in coarse particle mass under BB and AD influence, respectively. ADABBOY is the first project to systematically characterize elemental composition of airborne particles as a function of these sources and identify bioaerosol over Yucatan. Bacteria, actinobacteria (both continental and marine), and fungi propagules vary seasonally and interannually and revealed the presence of very different species and genera associated with different sources. A novel contribution of ADABBOY was the determination of the ice-nucleating abilities of particles emitted by different sources within an undersampled region of the world. BB particles were found to be inefficient ice-nucleating particles at temperatures warmer than −20°C, whereas both AD and background marine aerosol activated ice-nucleating particles below −10°C.
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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 | 0.001 |
| 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) | 0.001 | 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".