Microbial biodiversity of high Arctic wetland cryosolic soils and development of phylogenetic microarrays for polar applications
Bibliographic record
Abstract
This thesis consisted of two studies: the microbial biodiversity of Arctic wetland cryosol and the testing of two phylogenetic microarrays using environmental samples from the Canadian high Arctic. The first involved culture-independent and dependent analyses which assessed the diversity and structure of cryosol microorganisms. Active layer communities were distinct from permafrost communities in DGGE profiles, 16S rRNA gene clone libraries for Bacteria and Archaea and total cell enumerations and viable cell counts. Findings suggest novel aspects of Arctic wetland permafrost soil compared to previously studies. Comparisons to other Arctic permafrost and more temperate wetland 16S rRNA gene clones demonstrated the existence of common features of cold-adapted communities and Arctic wetlands. The second study was to compare characterizations from two phylogenetic microarrays (PGMAs) against 6 previously constructed clone libraries from high Arctic sites. A general environmental PGMA (GE.10) and a PGMA specifically for cyro-environments (Cryo-PGMA) were tested. The combined data, or "dual-PGMA", had moderate coverage of the taxa identified in clone libraries (51%) and detected corresponding genera at a relatively low rate (26%). The dual-PGMA demonstrated capability of reproducing broad phylogenetic community structures identified in clone libraries and contributed additional taxonomic detail not found there. The dual-PGMA had comparable sensitivity to other PGMA platforms and detected taxa occupying 0.6% of the total clone library. Principle coordinate analysis grouped communities from similar geographical and physical environments. The dual-PGMA demonstrated a capacity for profiling patterned differences in microbial communities while providing general approximations of taxonomic structure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".