Factors influencing carbon, nitrogen, and phosphorus content of fish from a Lake Superior coastal wetland
Bibliographic record
Abstract
The narrow fish nutrient ranges (C, 42.8-48.4%; N, 9.6-12.7%; P, 1.91-2.74%) in this study suggest that overall mean values are adequate for quantifying movement of C, N, or P as part of fish-mediated nutrient transport. We measured C, N, and P in 20 species of Lake Superior coastal wetland fish to better understand variability in fish elemental content caused by differences in species, habitat, season, life stage, or size. Fish were sampled within Bark Bay slough and at its inlet/outlet to Bark Bay, Lake Superior, from May to November 1995. Elemental content averaged across all fish (n = 192) was 45.1% for C, 11.3% for N, and 2.45% for P. We did find significant differences (p [Formula: see text] 0.05) among nine tested species. However, less than one third of the analyses were significant for effects of location or date of capture or fish length on fish nutrient content and nutrient ratios. Regressions of N:P ratios against growth rate indices and, separately, fineness ratios were significant, suggesting that growth rate and body shape are important factors driving N:P ratios in fish.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".