Vertical structure of archaeal communities and the distribution of ammonia monooxygenase A gene variants in two meromictic High Arctic lakes
Bibliographic record
Abstract
The distribution of archaeal amoA and 16S rRNA genes was evaluated in two marine-derived, meromictic lakes in the Canadian High Arctic: Lake A and Lake C1 on the northern coast of Ellesmere Island. The amoA gene was recorded in both lakes, with highest copy numbers in the oxycline. Sequence analysis showed that amoA from the two lakes shared 94% similarity, indicating at least two phylogenetically distinct clusters. Clone libraries of archaeal 16S rRNA genes from Lake A revealed strong vertical differences in archaeal community diversity and composition down the water column. The oxic layer was dominated by one group of Euryarchaeota affiliated to the Lake Dagow Sediment (LDS) cluster. This group was absent from the oxycline, which had an extremely low archaeal diversity of two phylotypes. Both belonged to the Crenarchaeota Marine Group I (MGI), the marine group that has been linked to archaeal amoA; however, there was a low ratio of amoA to MGI copy numbers, suggesting that many MGI Archaea did not carry the amoA gene. The anoxic zone contained representatives of the RC-V (Rice Cluster-V) and LDS clusters of Euryarchaeota. These results show the strong vertical differentiation of archaeal communities in polar meromictic lakes, and they suggest archaeal nitrification within the oxycline of these highly stratified waters.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".