Concentrations and properties of ice nucleating substances in exudates from Antarctic sea-ice diatoms
Bibliographic record
Abstract
The ocean contains ice nucleating substances (INSs), some of which can be emitted to the atmosphere where they can influence the formation and properties of clouds. A possible source of INSs in the ocean is exudates from sea-ice diatoms. Here we examine the concentrations and properties of INSs in supernatant samples from dense sea-ice diatom communities collected from Ross Sea and McMurdo Sound in the Antarctic. The median freezing temperatures of the samples ranged from approximately -17 to -22 °C. Based on our results and a comparison with results reported in the literature, the ice nucleating ability of exudates from sea-ice diatoms is likely not drastically different from the ice nucleating ability of exudates from temperate diatoms. The number of INSs per mass of DOC for the supernatant samples were lower than those reported previously for the sea surface microlayer and bulk sea water collected in the Arctic and Atlantic. The INSs in the supernatant sample collected from Ross Sea were not sensitive to temperatures up to 100 °C, were larger than 300 kDa, and were different from ice shaping and recrystallization inhibiting molecules present in the same sample. Possible candidates for these INSs include polysaccharide containing nanogels. The INSs in the supernatant sample collected from McMurdo Sound were sensitive to temperatures of 80 and 100 °C and were larger than 1000 kDa. Possible candidates for these INSs include protein containing nanogels.
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 | 0.001 |
| Science and technology studies | 0.000 | 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".