Data for atmospheric transport of North African dust-bearing supermicron freshwater diatoms to South America: implications for iron transport to the equatorial North Atlantic Ocean
Bibliographic record
Abstract
The equatorial North Atlantic Ocean (NAO) is a nutrient-limited ecosystem that relies on the deposition of long-range transported iron (Fe)-containing aerosols to stimulate primary productivity. Using microscopy, we characterized supermicron and super-coarse mode African aerosols transported to the western NAO in boreal winter/spring. We detected three particle types including African dust, primary biological aerosol particles, and freshwater diatoms (FDs). FDs contained 4% Fe by weight due to surficial dust inclusions that may be susceptible to chemical processing and dissolution. FDs were typically larger than dust particles and comprised 38% of particles between 10 and 18 μm in diameter. The low density, high surface-area-to-volume ratio, and large aspect ratios of FD particles suggest a mechanism by which they can be carried great distances aloft. These same properties likely increase the residence time of FDs in surface waters thereby increasing the time for Fe dissolution and their potential impact on marine biogeochemical cycles. This data is associated with the article: Barkley, A.E., Olson, N.E., Prospero, J.M., Gatineau, A., Panechou, K., Maynard, N.G., China, S., Ault, A.P. & Gaston, C.J. (2021). Atmospheric transport of North African dust-bearing supermicron freshwater diatoms to South America: implications for iron transport to the equatorial North Atlantic Ocean. Accepted to Geophysical Research Letters (GRL).
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 | 0.000 | 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) | 0.001 | 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".