Bibliographic record
Abstract
In a storm event, a first flush (FF) phenomenon occurs when most of the pollution load is transported in the initial part of the event discharged volume. The objectives of the study were to consider its severity for a number of pollutants as well as to recognize rainfall–runoff characteristics that influence it. The study was conducted in a semi-arid region of a mixed residential and commercial urban catchment in Iran. Ten major rainfall events were monitored for total solids (TS), total suspended solids (TSS), chemical oxygen demand (COD), total nitrogen (TN), Zn, and Pb. Total suspended solids and COD were usually above the permitted discharge. Power and polynomial functions fit well to the normalized curve of the distribution of pollutant load with volume. Discharge loads of TN, Pb, and Zn were approximately uniform. There was a relatively weak FF for TS, TSS, and COD. No correlation between FF load of TS and COD and rainfall–runoff characteristics was observed, but the amount of the FF load of TSS increases when the intensity and duration of a rainfall event increase. Key words: first flush, urban runoff quality, pollution load distribution, event mean concentration, urban stormwater runoff.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".