Trophic studies in a high-latitude fjord ecosystem — a comparison of stable isotope analyses (δ<sup>13</sup>C and δ<sup>15</sup>N) and trophic-level estimates from a mass-balance model
Bibliographic record
Abstract
Stable isotopes of δ13C and δ15N were used to examine food sources and trophic structure of 65 taxa, representing 19 ecological groups, in a high-latitude ecosystem. Discrimination was made between pelagic and benthic carbon sources, where feeding in most cases reflected the habitat. Trophic levels from these analyses, TLN, were compared with corresponding levels estimated by an Ecopath mass-balance model, TLE, constructed independently of the isotope data. The good correlation between the two methods (r2 = 0.72) supports the diet composition and the grouping of taxa into ecological groups in the model. However, when estimates diverged, this was often explained by the analyses of few taxa, taxa that were not the most representative for the group, or the analyses of specimens from a limited size range. Some assumed detrivores were assigned high TLN in favour of an abundant microbial community in the sediments. High TLN estimates for many invertebrate taxa, combined with relatively low TLN for fishes, suggest that parts of the benthic food web are decoupled from the classical food web.
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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) | 0.000 | 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".