Use of Stress Signals of Their Attached Bacteria to Monitor Sympagic Algae Preservation in Canadian Arctic Sediments
Bibliographic record
Abstract
Based on the strong aggregation of sympagic (ice-associated) algae and the high mortality or inactivity of bacteria attached to them, it was previously hypothesized that sympagic algae should be significant contributors to the export of carbon to Arctic sediments. In the present work, the lipid content of 30 sediment samples collected in the Canadian Arctic was investigated to test this hypothesis. The detection of high proportions of trans vaccenic fatty acid (resulting from cis-trans isomerase (CTI) activity of bacteria under hypersaline conditions) and 10S-hydroxyhexadec-8(trans)-enoic acid (resulting from 10S-DOX bacterial detoxification activity in the presence of deleterious free palmitoleic acid) confirmed: (i) the strong contribution of sympagic material to some Arctic sediments, and (ii) the impaired physiological status of its associated bacterial communities. Unlike terrestrial material, sympagic algae that had escaped zooplanktonic grazing appeared relatively preserved from biotic degradation in Arctic sediments. The expected reduction in sea ice cover resulting from global warming should cause a shift in the relative contributions of ice-associated vs. pelagic algae to the seafloor, and thus to a strong modification of the carbon cycle.
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) | 0.001 | 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".