Bibliographic record
Abstract
Climate change simulations made with coupled global climate models typically show a marked hemispheric asymmetry with more warming in the northern high latitudes than in the south. This asymmetry is ascribed to heat uptake by the ocean at high southern latitudes. A recent version of the CCCma climate model exhibits a much more symmetric warming, compared to an earlier version, and agrees somewhat better with observed 20th century trends. This is associated with an improved parameterization of ocean mixing which results in a decrease in heat penetration into the Southern Ocean, in accord with earlier ocean‐only and simple coupled model investigations. The global average warming and the net penetration of heat into the global ocean (and hence its thermal expansion) are essentially unchanged. Observed trends in sea‐ice extent over the past two decades exhibit hemispheric asymmetry with a statistically significant decrease in northern but not in southern ice cover. Both model versions are consistent with these observations implying that observed ice extent is not yet an indicator of asymmetry in future global warming. Taken together, these results suggest that southern hemisphere climate warming at a rate comparable to that in the northern hemisphere should be considered a realistic possiblity.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".