Marine benthic communities and anthropogenic activities in Sept-Îles (Canada): a peaceful coexistence?
Bibliographic record
Abstract
With the development of coastal human activities comes the growing need to develop methods to describe their cumulative impacts on marine benthic communities at local geographic scales. Local assessments facilitate dialogue between multiple users of the ecosystem (industries, individuals) and allow to better understand variation among benthic communities in a given region. In this project, we aim to develop indicators of cumulative impacts to assess the environmental health of benthic ecosystems within industrialized regions in the Gulf of St. Lawrence at a small spatial scale (0.01 km2). We selected coastal regions around Sept-Îles, where numerous human activities are present at different intensities (such as international shipping, fisheries or domestic and industrial wastes). Subtidal ecosystems were sampled in 2016-2017 to characterize macro-endobenthic diversity and abiotic parameters of the sediment. We calculated impact scores for each human activity based on the distance from the source and the magnitude of its impact. We thus identified hotspots of cumulative impact and changes in the biotic and abiotic compartments along impact gradients. These results will be used for the development of indicators of cumulative stress and to understand resilience and stability of bay-scale benthic communities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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".