Bibliographic record
Abstract
Floods are considered to be the most common natural disaster which causes more destructive effects than other natural disasters including loss of human life, property and infrastructure damage, as well as a negative impact on social and economic development. Besides these consequences, floods also affect water quality. The aim of this paper is to present water quality impairment caused by the floods in Serbia in May 2014. The parameters of water quality were measured 13 times in 2014 (12 ordinary monthly measurements and one extraordinary measurement during the flood) in hydrological stations Ostruznica and Sabac (on the river Sava) and Badovinci (on the river Drina). The Canadian Water Quality Index (CWQI) was used for water quality assessment. This method calculates the overall water quality and the water quality for specific conditions and purposes including: drinking, aquatic habitats, recreation, irrigation, and livestock. Water quality decline was recorded in all the stations in overall water quality as well as for specific uses. Turbidity and heavy metals values were tens of times higher than normal ranges. The most drastic example was Al with the values which were thousand(s) of times higher than the objective.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".