Viability and stress state of bacteria associated with primary production or zooplankton-derived suspended particulate matter in summer along a transect in Baffin Bay (Arctic Ocean)
Bibliographic record
Abstract
In the framework of the GreenEdge Project (whose the general objective is to understand the dynamic of the phytoplankton spring bloom in Arctic Ocean), lipid composition and viability and stress state of bacteria were monitored in sea ice and suspended particulate matter (SPM) samples collected in 2016 along a transect from sea ice to open water in Baffin Bay (Arctic Ocean). Lipid analyses confirmed the dominance of diatoms in the bottommost layer of ice and suggested (i) the presence of a strong proportion of micro-zooplankton in SPM samples collected at the western ice covered St 403 and St 409 and (ii) a high proportion of macro-zooplankton (copepods) in SPM samples collected at the eastern ice covered St 413 and open water St 418. The use of the propidium monoazide (PMA) method allowed to show a high bacterial mortality in sea ice and in SPM material collected in shallower waters at St 409 and St 418. This mortality was attributed to the release of bactericidal free fatty acids by sympagic diatoms under the effect of light stress. A strong cis-trans isomerization of bacterial MUFAs was observed in the deeper SPM samples collected at the St 403 and St 409. It was attributed to the ingestion of bacteria stressed by salinity in brine channels of ice by sympagic bacterivorous microzooplankton (ciliates) incorporating trans fatty acids of their preys before to be released in the water column during melting. The high trans/cis ratios also observed in SPM samples collected in the shallower waters at St 413 and St 418 suggest the presence of positively or neutrally buoyant extracellular polymeric substances (EPS)-rich particles retained in sea ice and discharged (with bacteria stressed by salinity) in seawater after the initial release of algal biomass. Such EPS particles, which are generally considered as ideal vectors for bacterial horizontal distribution in the Arctic, appeared to contain a high proportion of dead and non-growing bacteria.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".