Biostabilization of cohesive sediment beds in a freshwater wave‐dominated environment
Bibliographic record
Abstract
An assessment of bed sediment stability was carried out over biostabilized and nonbiostabilized cohesive sediment within a laboratory wave flume. Biofilms of 5, 9, and 15 d were grown over kaolinite, and changes in bed shear stress were applied through increasing wave height. Results show that the stability of the bed was highly related to the structural integrity of the overlying and integrated biofilm. Biofilms with substantial algal growth and lifting, due to decay and gas production, were weaker than those in contact with the bed. Generally, biostabilized beds of the same age failed at similar shear stresses (although the mechanism of failure varied), and the 9‐d biofilms exhibited the greatest strength. Changes in the microbial diversity and dominant species with time, as measured with phospholipids fatty acid analysis (PLFA) and denaturing gradient gel electrophoresis (DGGE), are believed to have influenced the observed variations in bed strength. Young biofilms were dominated by bacterial species, whereas older biofilms were dominated more by algae (particularly cyanobacteria). Fungal species also played a large role in the biofilm development and structure. Laser confocal microscopy and environmental scanning electron microscopy were used to show structural differences between biofilms and changes with wave energy. Biofilm development and bio‐armoring of underlying cohesive sediments are successional processes, with new layers of biofilm integrating into the sediment beneath older decaying biofilm layers. As such, there is a continuous temporal oscillation in bed sediment stability depending on the stage of biofilm development and decay.
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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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".