Cumulative impacts of anthropogenic stressors on macrobenthic communities at a bay-scale: an experimental approach
Bibliographic record
Abstract
Human activities such as maritime transport, fishing and aquaculture create environmental stressors affecting the structure and the functioning of benthic communities. While these disturbances can act individually, they can also act synergistically and lead to changes more difficult to predict. The bay of Sept-Îles hosts a harbour receiving the most important ballast volume in North America and represents one of the most eutrophic bays in the Gulf of St. Lawrence. This project is part of the Canadian healthy oceans network (CHONe II) and attempts to identify the effect of the interaction of anthropogenic stressors on the macrobenthic invertebrate communities in the bay of Sept-Îles. In situ and laboratory manipulative experiments will be conducted to determine the influence of stressors on biological responses when taken individually, and when these stressors interact through time at different intensities. In that way, these experiments will improve our knowledge of cumulated impacts of multiple stressors on the structure of benthic communities. It will also eventually contribute to species conservation and the management of maritime resources.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".