Soluble chromophores in marine snow, seawater, sea ice and frost flowers near Barrow, Alaska
Bibliographic record
Abstract
We measured light absorption in 42 marine snow, sea ice, seawater, brine, and frost flower samples collected during the OASIS field campaign between February 27 and April 15, 2009. Samples represented multiple sites between landfast ice and open pack ice in coastal areas approximately 5 km west of Barrow, Alaska. The chromophores that are most commonly measured in snow, H2O2, NO3−, and NO2−, on average account for less than 1% of sunlight absorption in our samples. Instead, light absorption is dominated by unidentified “residual” species, likely organic compounds. Light absorption coefficients for the frost flowers on first‐year sea ice are, on average, 40 times larger than values for terrestrial snow samples at Barrow, suggesting very large rates of photochemical reactions in frost flowers. For our marine samples the calculated rates of sunlight absorption and OH production from known chromophores are (0.1–1.4) × 1014 (photons cm−3 s−1) and (5–70) × 10−12 (mol L−1 s−1), respectively. Our residual spectra are similar to spectra of marine chromophoric dissolved organic matter (CDOM), suggesting that CDOM is the dominant chromophore in our samples. Based on our light absorption measurements we estimate dissolved organic carbon (DOC) concentrations in Barrow seawater and frost flowers as approximately 130 and 360 μM C, respectively. We expect that CDOM is a major source of OH in our marine samples, and it is likely to have other significant photochemistry as well.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".