Measurement report: Bio-physicochemistry of tropical clouds at Maïdo (Réunion, Indian Ocean): overview of results from the BIO-MAÏDO campaign
Bibliographic record
Abstract
Abstract. The BIO-MAÏDO (Bio-physicochemistry of tropical clouds at Maïdo: processes and impacts on secondary organic aerosols formation) campaign was conducted from 13 March to 4 April 2019 on the tropical island of Réunion. The main objective of the project was to improve understanding of cloud impacts on the formation of secondary organic aerosols (SOA) from biogenic volatile organic compound (BVOC) precursors in a tropical environment. Instruments were deployed at five sites: a receptor site, Maïdo Observatory (MO) at 2165 m a.s.l. and four sites along the slope of the Maïdo mountain. Observations include measurements of volatile organic compounds (VOCs) and characterization of the physical, chemical and biological (bacterial diversity and culture-based approaches) properties of aerosols and cloud water. Turbulent parameters of the boundary layer, radiative fluxes and emissions fluxes of BVOCs from the surrounding vegetation were measured to help interpret observed chemical concentrations in the different phases. Dynamical analyses showed two preferred trajectory routes for air masses arriving at MO during the daytime. Both trajectories correspond to return branches of the trade winds associated with upslope thermal breezes, where air masses likely encountered cloud processing. The highest mixing ratios of oxygenated VOCs (OVOCs) were measured above the site located in the endemic forest and the highest contribution of OVOCs to total VOCs at MO. Chemical compositions of particles during daytime showed higher concentrations of oxalic acid, a tracer of cloud processing and photochemical aging, and a more oxidized organic aerosol at MO than at other sites. Approximately 20 % of the dissolved organic compounds were analyzed. Additional analyses by ultra-high-resolution mass spectrometry will explore the complexity of the missing cloud organic matter.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".