Effect of substrate type and pellet age on the resuspension of Atlantic salmon faecal material
Bibliographic record
Abstract
The influence of substrate type and particle age on the remobilization of settled Atlantic salmonSalmo salarfaecal material was studied through a set of controlled experiments in horizontal flow flumes, simulating different bottom conditions present in fish-farming locations along the coast of Norway. There was no significant effect of pellet age on remobilization for up to 1 week old faecal material, but critical shear stresses (τc) and velocities required for resuspending faecal pellets were strongly dependent on substrate type. Smooth substrates such as mud and rock slate required lower stresses for the onset of faeces resuspension (τc%%CONV_ERR%% 0.06 Pa) than rougher surfaces such as sand (τc%%CONV_ERR%% 0.12 Pa) or fragmented rock (τc%%CONV_ERR%% 0.32 Pa), where bedforms and large fractures shield the particles from the direct influence of the drag forces. These newly determined substrate-dependent τcresuspension thresholds will contribute to the construction of more accurate numerical models that include bottom type as a parameter regulating the extent of particle spreading, in contrast to the constant-value approach that has been used to date.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".