Benthic responses to organic enrichment under a mussel (Mytilus edulis) farm
Bibliographic record
Abstract
Bivalve culture is know to affect some interactions between the water column and the benthic environment with the organic enrichment. An in situ mesocosms experiment was used to determine the influence of mussel biodeposition on the benthic ecosystem in St. Peters Bay, Prince Edward Island, eastern Canada. Eight mussel densities (0 to 2266 mussels m-2) were placed above mesocosms to reproduce the organic enrichment from a mussel farm over 12 weeks. The experimental procedure created an accumulation of organic matter on the seafloor with increasing mussel densities. Some benthic parameters had the predicted response to organic enrichment, with the presence of anoxic sediment in sediment profile images, increased water and organic matter content, and reduced infaunal abundance and species richness. Other parameters, including redox potential, total free sulfides, and the response of the biotic index AMBI, had inconsistent responses to mussel biodeposition-related organic enrichment. Given that other studies done in other locations have observed varying results, results suggest that measurement of various parameters is important to interpret the influence of deposition from mussel farms. The conditions of the site and the study duration are also parameters to consider when evaluating the results from mesocosm studies. Results from this study also suggest that St. Peters Bay is likely impacted by biodeposition from the mussels farmed there.
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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 | 0.001 |
| 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".