Innovative treatment by bioremediation of contaminated sediments from the Venice Lagoon, Italy: the Arsenale Vecchio case study.
Bibliographic record
Abstract
Bonardi, M.; Ravagnan, G.; Stirling, J.A.R.; Morucchio, C. and De Sanctis, S., 2007. Innovative treatment by bioremediation of contaminated sediments from the Venice Lagoon, Italy: the Arsenale Vecchio case study. Journal of Coastal Research, SI 50 (Proceedings of the 9th International Coastal Symposium), 895 – 899. Gold Coast, Australia, ISSN 0749.0208 Sediments in industrialized and/or urbanized coastal shallow waters have reached an alarming and harmful level of contamination that requires the development of new cost effective technologies. We report on the in situ forced aeration experiment in the Arsenale shipyard dock basin of the Venice Lagoon, Italy. This study follows the promising results obtained by similar experiment carried out in the Industrial Harbor of Marghera, where sediment reworking and mixing are strong. The study site of the Arsenale shipyard was chosen in order to test a new forced aeration system aimed at oxygenating the surficial sediments with a minimum of reworking and mixing. The aeration technique, chosen for the oxygenation of the highly polluted bottom sediments, is unique due to its innovative use of a system of porous pipes laid on the bottom sediments, therefore it is non intrusive and does not obstruct harbor activities. Forced aeration consists in the introduction of a great quantitative of oxygen at the surficial sediment-water column interface with the aim of stimulating aerobic bacterial communities to create an adapt environment for the biodegradation of organic and inorganic pollutants. The general reduction of organic pollutants and heavy metals in the surficial sediments resulted in the documented return of small fish to the area as an indication of a less polluted environment. The experiment has indicated that tangential forced aeration could represent a non intrusive and cost effective way for reducing organic and heavy metal pollutants in coastal environments where other techniques may not be environmentally and/or economically feasible.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".