Factors influencing patterns in distribution, abundance and diversity of sedimentary macrofauna in deep, muddy sediments of Placentia Bay, Newfoundland and the adjacent shelf
Bibliographic record
Abstract
A nested sampling design and multivariate analyses were used to examine the community structure and spatial distribution of macrofauna on muddy substrates in Placentia Bay, Newfoundland and the adjacent shelf. The goal was to determine how macrofaunal communities are related to water column (e.g., surface productivity) and sediment characteristics (e.g., carbon and nitrogen content). Box core samples were collected at 10 sites (June & July of 1998) that were distributed from the head of the bay through the Eastern and Western Channels to the edge of the continental shelf. This is the first comprehensive study of Placentia Bay infauna and it is divided into three main components. Chapter 1 examines broad-scale patterns in community composition, diversity and abundance along an inshore/offshore gradient. Results indicate that the bay contains distinct inshore and offshore regions and benthic patterns are largely influenced by surface oceanography. Chapter 2 focuses on finer-scale patterns of distribution and abundance within the inshore region of the bay and reveals spatial patterns that were not evident in the analyses of broad-scale patterns in the previous chapter. Sediment-related factors and depth were important in explaining variation in inshore benthic patterns. Thus, contrasting the results of these two chapters suggests that different variables structure these communities at different scales. Because little biological sampling for benthos has been undertaken in this area, Chapter 3 provides a guide to the polychaetes, which are the dominant group of infauna in the study. Digital photographs of the key characteristics used to identify each species are provided to help bridge identification guides developed for other areas.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".