Improvement of Sediment-Water Quality by Resuspension
Bibliographic record
Abstract
Heavy eutrophication was found in a canal located in the central part of Fukuyama City, Japan due to a high organic content (30 percent loss on ignition). As a result, hydrogen sulfide production often occurred, mostly from spring to autumn. Therefore, Fukuyama City decided to investigate the possibility of cleaning up the bottom of the canal using a resuspension technique. The pilot test was evaluated for an area of 3000 m2. The amount of wet resuspended solids removed from the bottom of the water column was about 11 tonnes. The ORP of the surface sediments was initially -150 mV but increased to above +70 mV after redeposition. In comparison to the original sediments, quantitative analyses showed that full scale implementation would enable the removal of about 10 % of the resuspended solids, and reduce COD by 95 %, T-P by 50 %, T-N by 100 % and sulfide by 75 % for redeposited sediments.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".