Hurricanes Pauline and Nora rainwater chemical composition
Bibliographic record
Abstract
Rainwater from hurricanes Pauline and Nora was sampled for chemical analysis at the Pacific Coast of Mexico. Rainwater sampling under extreme conditions presents a unique opportunity to study oceanic rain chemical composition. An excess sulphate ((SO24)xs) as low as 0% was measured near the centre of hurricane Pauline in Huatulco Bays. Another remarkable result was obtained in another rainwater sample of Pauline rain bands with a total SO24 concentration below the detection limit. Also, Na+ and Cl concentrations were extremely low (0.02 and 0.025 mg L1, respectively). The explanation of these results is also presented. Some light rains were also collected in Tapachula while Pauline was severely affecting Huatulco Bays. Only rainwater samples from hurricane Nora outer rain bands were sampled in Manzanillo, where it was interesting to evaluate the profound impact that a single power plant had on the chemical composition of hurricane Nora rains. Excess sulphate did not correlate with Mg2+ in Huatulco Bays and Manzanillo. However, it correlated with Mg2+ in Tapachula, even though this town is located 27 km from the coast. A further oxidation of organic sulphur containing compounds combined with a simultaneous transport of sea spray inland is proposed to explain this correlation.
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".