Contrasting Ice Algae and Snow‐Dependent Irradiance Relationships Between First‐Year and Multiyear Sea Ice
Bibliographic record
Abstract
Abstract During the 2018 Multidisciplinary Arctic Program‐Last Ice in the Lincoln Sea, we sampled 45 multiyear ice (MYI) and 34 first‐year ice (FYI) cores, combined with snow depth, ice thickness, and transmittance surveys from adjacent level FYI and undeformed MYI. FYI sites show a decoupling between bottom‐ice chlorophyll a (chl a) and snow depth; however, MYI showed a significant correlation between ice‐algal chl a biomass and snow depth. Topographic control of the snow cover resulted in greater spatiotemporal variability of the snow over the level FYI, and consequently transmittance, compared to MYI with an undulating surface. The coupled patterns of snow depth, transmittance, and chl a indicate that MYI provides an environment with more stable light conditions for ice algal growth. The importance of sea ice surface topography for ice algal habitat underpins the potential ecological changes associated with projected increased ice dynamics and deformation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".