Ontogenetic shifts in morphology and resource use of cisco <i>Coregonus artedi</i>
Bibliographic record
Abstract
Two previously described lacustrine cisco Coregonus spp. morphs [i.e. a small (<300 mm fork length, L(F)), low-gillraker (≤44) morph and a large (≥300 mm L(F) ), high-gillraker (≥45) morph] from Great Slave Lake, NT, Canada, were found to be synonymous with cisco Coregonus artedi. Geometric body shape did not differ between the two size classes nor could they be differentiated by 24 size-corrected linear measurements, indicating that the two groups had similar phenotypes. Strong, positive correlations between all linear characters and geometric centroid size (a composite variable of fish body length, mass and age) suggested that body morphology changed with age as fish grew. Total gillraker number (N(GR)) increased with L(F) according to: N(GR) = 36.3 + 0.034L(F). Differences in gillraker number and phenotype with age and size were explained by shifts in habitat and trophic resource use. Relative abundance within 0-30, 30-60, 60-90 and >90 m depth strata differed between size classes suggesting that morphology changed when fish shifted their habitat as they grew older. Large C. artedi had lower δ(13)C and slightly higher δ(15)N, indicating greater reliance on pelagic prey resources (i.e. more or larger zooplankton, such as Mysis spp.), compared to small C. artedi, which relied slightly more on benthic prey. Gillraker shape and number have always been used as key diagnostic characters in coregonine taxonomy; based on the findings presented here, ontogenetic shifts should be accounted for in resulting classifications.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".