Bibliographic record
Abstract
The fundamental mechanisms that explain high subpolar North Atlantic (SPNA) decadal predictability within a particular modeling framework are described. The focus is on the Community Earth System Model (CESM), run in both a historical forced-ocean configuration as well as in a fully coupled configuration initialized from the former. The initialized prediction experiments comprise the CESM Decadal Prediction Large Ensemble (CESM-DPLE)—a 40-member set of retrospective hindcasts documented in Yeager et al. (Bull Am Meteorol Soc 99:1867–1886. https://doi.org/10.1175/bams-d-17-0098.1 , 2018). Heat budget analysis confirms the driving role of advective heat convergence in skillful prediction of SPNA upper ocean heat content out to decadal lead times. The key ocean dynamics are topographically-coupled overturning/gyre fluctuations that are geographically centered over the mid-Atlantic ridge (MAR). Long-lasting predictive skill for ocean heat transport can be related to predictable barotropic gyre and sigma-coordinate AMOC circulations, but depth-coordinate AMOC is far less predictable except in the deepest layers. The foundation of ocean memory (and circulation predictive skill) in CESM-DPLE is Labrador Sea Water thickness, which propagates predictably through interior pathways towards the MAR where large anomalies accumulate and persist. Abyssal thickness anomalies drive predictable decadal changes in the gyre circulation, including changes in sea level gradient and near surface flow, that account for the high predictability of SPNA upper ocean heat content.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".