A trophic study of a marine ecosystem off southeastern Australia using stable isotopes of carbon and nitrogen
Bibliographic record
Abstract
The stable isotopes of carbon and nitrogen were used to investigate trophic relationships of fish and invertebrates on the continental shelf of southeastern Australia. We examined 87 fish species, marine mammals, penguins, invertebrates, algal samples, suspended particulate organic matter (POM), and sediments. The main source of primary production is oceanic phytoplankton, although there is evidence of a seagrass contribution to the benthos. Marine mammals, penguins, some benthic invertebrates, and some benthic fish filled the highest trophic positions. Sources of variability in isotope results included temporal (POM, some fish) and spatial (POM, sediments) elements, bottom depth (some fish), and size (some fish). Fish had muscle δ15N values of 9.6 to 14.7 and δ13C values of 20.6 to 14.6. Cluster analysis on fish stable isotope results produced fish groups that could be interpreted with trophic and habitat information. Trophic relationships in fish, suggested by stable isotope results, were supported by stomach contents analysis. Stable isotope results may indicate more representative trophic relationships, as stomach contents analyses tend to group prey by taxon rather than by trophodynamic position. In fish and invertebrates, stable isotope results related more to functional patterns of feeding than to taxonomic relationships.
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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 | 0.000 |
| 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".