Utility of Condition Indices as Predictors of Lipid Content in Slimy Sculpin (Cottus cognatus)
Bibliographic record
Abstract
Slimy sculpin (Cottus cognatus) are increasingly being used as indicator species. This has primarily entailed measuring their condition, the assumption being that condition can be used as a surrogate for lipid content. While there is evidence to suggest this assumption is applicable to some fish, it has yet to be validated for C. cognatus. Further, there are several means by which one may calculate condition, the most commonly employed of which are indirect measurements of lipid content (namely, Fulton’s K, somatic K (Ks), and Le Cren’s relative condition factor (Kn)). We compared the ability of each of these morphometric indices to predict whole-body lipid content in C. cognatus. There was a moderate degree of evidence that Fulton’s K, Ks, and Kn are reliable predictors (Ks and Kn in particular). Of the latter we recommend Kn be used because, unlike Ks, it does not require that fish be killed. And while Fulton’s K did not perform quite as well, we consider it a sufficient substitute if the data necessary to calculate Kn are unavailable.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".