Bibliographic record
Abstract
Abstract. The drastic decline of Arctic sea ice due to global warming and polar amplification of environmental changes in the Arctic basin profoundly alter primary production with consequences for polar ecosystems and the carbon cycle. In this study, we use highly branched isoprenoids (HBIs), brassicasterol, dinosterol and terrestrial biomarkers (n-alkanes and campesterol) in surface sediments to assess sympagic and pelagic algal production with changing sea ice conditions along a latitudinal transect from the Bering Sea to the high latitudes of the western Arctic Ocean. Suspended particulate matter (SPM) was also collected in surface waters at several stations of the Chukchi basin to provide snapshots of phytoplankton communities under various sea ice conditions for comparison with underlying surface sediments. Our results show that sympagic production (IP25 and HBI-II) increased northward between 62° N and 73° N, with maximum values at the sea ice edge in the Marginal Ice Zone (MIZ) between 70° N and 73° N in southeastern Chukchi Sea and along the coast of Alaska. They were consistently low at northern high latitudes (>73° N) under perennial sea ice and in the Ice-Free Zone (IFZ) of the Bering Sea. Enhanced pelagic sterols and HBI-III occurred in the IFZ across the Bering Sea and in southeastern Chukchi Sea up to 70° N–73° N in the MIZ conditions that marks a shift of sympagic over pelagic production. In surface water SPM, pelagic sterols display similar patterns as Chl a, increasing southwards with higher amounts found in the Chukchi shelf pointing out the dominance of diatom production. Higher cholesterol values were found in the mid-Chukchi Sea shelf where phytosterols were also abundant. This compound prevailed over phytosterols in sediments, compared to SPM, reflecting efficient consumption of algal material in the water column by herbivorous zooplankton.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.012 | 0.007 |
| Insufficient payload (model declined to judge) | 0.336 | 0.284 |
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".