Distribution and export of particulate organic carbon in East Antarctic coastal polynyas
Bibliographic record
Abstract
Polynyas represent regions of enhanced primary production due to the low, or absent, sea-ice cover coupled with the proximity of nutrient sources. However, studies throughout the Southern Ocean suggest elevated primary production does not necessarily result in increased carbon export. Three coastal polynyas in East Antarctica and an off-shelf region were visited during the austral summer of 2016/2017 to examine the vertical distribution of particulate organic carbon (POC). Carbon export was also examined using thorium-234 (234Th) as a proxy at two of the polynyas. Our results show that concentrations and integrated POC stocks were higher within the polynyas compared to the off-shelf sites. Within the polynyas, vertical POC concentrations were higher in the Mertz and Ninnis polynyas compared to the Dalton polynya. Similarly, higher carbon export was measured in the diatom-dominated Mertz polynya, where large particles (53 μm) represented a significant fraction of the particulate 234Th and POC, compared to the small flagellate-dominated Dalton polynya, where almost all the particulate 234Th and POC were found in the smaller size fraction (1 - 53 μm). The POC to Chlorophyll-a ratios suggests that organic matter below the mixed layer in the polynyas consisted largely of fresh phytoplankton at this time of the year. In combination with a parallel study on phytoplankton production at these sites, we find that increased primary production at these polynyas does lead to greater concentrations and export of POC and a higher POC export efficiency.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".