Phylogenetic Estimation of Community Composition and Novel Eukaryotic Lineages in Base Mine Lake: An Oil Sands Tailings Reclamation Site in Northern Alberta
Bibliographic record
Abstract
Reclamation of anthropogenically impacted environments is a critical issue worldwide. In the oil sands extraction industry of Alberta, reclamation of mining-impacted areas, especially areas affected by tailings waste, is an important aspect of the mining life cycle. A reclamation technique currently under study is water-capping, where tailings are capped by water to create an end-pit lake (EPL). Base Mine Lake (BML) is the first full-scale end-pit lake in the Alberta oil sands region. In this study, we sequenced eukaryotic 18S rRNA genes recovered from 92 samples of Base Mine Lake water in a comprehensive sampling programme covering the ice-free period of 2015. The 565 operational taxonomic units (OTUs) generated revealed a dynamic and diverse community including abundant Microsporidia, Ciliata and Cercozoa, though 41% of OTUs were not classifiable below the phylum level by comparison to 18S rRNA databases. Phylogenetic analysis of five heterotrophic phyla (Cercozoa, Fungi, Ciliata, Amoebozoa and Excavata) revealed substantial novel diversity, with many clusters of OTUs that were more similar to each other than to any reference sequence. All of these groups are entirely or mostly heterotrophic, as a relatively small number of definitively photosynthetic clades were amplified from the BML samples.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".