Snowball versus slushball Earth: Dynamic versus nondynamic sea ice?
Bibliographic record
Abstract
Modeling studies of the Neoproterozoic snowball Earth offer two variations for snowball conditions, the original “hard” snowball Earth where the ocean is completely covered by sea ice, and an alternate slushball Earth or “soft” snowball, where there is an equatorial oasis of open water. We use the University of Victoria Earth System Climate Model to show that the soft snowball result is only possible when dynamics are excluded from the sea ice component of the model. Using a purely thermodynamic sea ice component the soft snowball condition is stable, whereas with a dynamic and thermodynamic sea ice component it is not. As the behavior of dynamic sea ice largely depends on wind stress, we compare simulations using two different wind fields: a zonally averaged present‐day wind field and a wind field derived by a general circulation model, the Fast Ocean Atmosphere Model, using Neoproterozoic conditions. Another consequence of using dynamic sea ice is that the sea ice does not become sufficiently thick to flow under its own weight when there is open water; this suggests that sea glacier dynamics are not important for snowball inception.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".