Morphological divergence and origin of sympatric populations of European whitefish (<i>Coregonus lavaretus</i>L.) in Lake Femund, Norway
Bibliographic record
Abstract
Combining morphological and genetic analysis, we compared patterns of diversification within and between morphs among sympatric European whitefish (Coregonus lavaretus L.) populations in Lake Femund, Norway. Seven external populations, from potential colonization routes into Lake Femund were included. We found that deep-, shallow-, river- and bay spawning populations are distinct morphs in Lake Femund. Within morphs, populations range from being similar genetically (Fst=0-0.005) among deep-spawning populations to being highly differentiated (Fst=0.153) between bay-spawning populations. Between morphs, genetic differences ranged from a low (Fst=0.008-0.022) between deep- and shallow-spawning populations to high difference (Fst=0.125-0.143) between shallow- and bay-spawning populations. A higher proportion of molecular variance was seen among (3.9%) than within morphs (2.8%). The adaptive gene combinations behind the four morphs seem to have originated within the lake, although the lake could have been colonized from more than one source population.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".