Bibliographic record
Abstract
It has been shown that microbial communities are active at temperatures close to freezing (0-1˚C) in subglacial systems. These microorganisms are an integral part of the biogeochemical cycles that take place in subglacial environments and it has been argued that they may play a significant role in global biogeochemical cycles on glacial-interglacial timescales. Previous research at Robertson Glacier, Canada has shown that its subglacial sediments harbor diverse assemblages of potential nitrifying and nitrate reducing organisms. My research project has focused on an aspect of the aerobic portion of the nitrogen cycle in subglacial systems. I set up enrichment cultures for nitrite oxidizers at 4˚C, close in situ subglacial temperatures, using subglacial sediments from Roberson Glacier. Conversion of the added nitrite to nitrate in the biotic experiments and no change in the unamended control experiments demonstrated microbial nitrite oxidation. Multiple transfers of the enrichment culture were then undertaken to try and obtain a pure culture. The activity, through nitrite oxidation and cell biomass of these latter 4oC enrichments was measured, and showed activity but without significant increases in biomass. Ongoing work is focused on determining the identity of the nitrite oxidizing organism or organisms in the enrichments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".