Mitochondrial <scp>DNA</scp> phylogeography of least cisco <i><scp>C</scp>oregonus sardinella</i> in <scp>A</scp>laska
Bibliographic record
Abstract
This study presents the first detailed analysis of the mitochondrial DNA diversity of least cisco Coregonus sardinella in Alaska using a 678 bp segment of the control region (D‐loop) of the mitochondrial genome. Findings suggest that the history of C. sardinella in Alaska differs from that of other species of Coregonus present in the state and surrounding regions. The examined populations of C. sardinella are genetically diverse across Alaska. Sixty‐eight distinct mitochondrial haplotypes were identified among 305 individuals sampled from nine locations. The haplotype minimum spanning network and phylogeny showed a modest level of geographic segregation among haplotypes, suggesting high levels of on‐going or recent connectivity among distant populations. Observed ΦST values and the results of homogeneity and AMOVAs indicate incipient genetic differentiation between aggregations in three broad regional groups. Sites north of the Brooks Range formed one group, sites in the Yukon and Selawik Rivers formed a second group and sites south of the Yukon drainage formed the third group. Overall, the sequence data showed that a large proportion of mtDNA genetic variation in C. sardinella is shared across Alaska, but this variation is not homogeneously distributed across all regions and for all haplotype groups.
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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".