Characterization of epibenthic community structure in the Beaufort Sea area
Bibliographic record
Abstract
The Canadian Arctic is facing new issues with increased marine traffic, exploration and exploitation of resources. Knowledge of the environment is needed to address these issues. Fisheries and Oceans Canada conducted a survey during summers 2012 to 2014 in the Canadian Beaufort Sea and the Amundsen Gulf. The “BREA-MFP” Beaufort Regional Environmental Assessment-Marine Fish Project” objective was to improve knowledge of the composition of fish communities and their habitats in offshore waters of the Beaufort Sea and the Amundsen Gulf. As an important part of the fish habitat and diet, the epibenthos was sampled to characterize and improve the knowledge of epibenthic community structure (diversity and abundance) in these areas. The benthos is ideal as an ecological indicator index because organisms are sessile, highly diverse, and long-lived. Moreover, environmental factors such as organic matter content, benthic Chla, and sediment grain size are known to influence the benthic community composition. Collected data are used to establish baselines for epibenthic diversity, abundances, and community compositions, and for comparisons among regions (Beaufort Sea, Amundsen Gulf) and gradients (nearshore-offshore depth, East-West). Furthermore, the study highlighted new occurrences of species for the area indicating additional studies are needed to assess benthic biodiversity in this area.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 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".