Deciphering the redistribution of excess heat in the North Atlantic: time series of ocean heat content at 25N from 1850 to present
Bibliographic record
Abstract
This data set is related to the article "Deciphering the redistribution of excess heat in the North Atlantic" in Communication Earth and Environment by Marie-José Messias and Herlé Mercier. It provides time series of ocean heat content (OHC) at 25°N in the Atlantic Ocean from 1850 to 2018 in four layers (0–700m, 700–2000m, 2000–4000m, 4000m–bottom) and associated errors. The contributions of 9 source regions (Arctic Ocean, Nordic Seas, Labrador and Irminger Seas, north-eastern subpolar gyre, Mediterranean Sea, subtropical and tropical North Atlantic, subtropical and tropical South Atlantic, Sub-Antarctic Ocean and Antarctic Ocean) to the surface-to-bottom OHC at 25°N from 1850 to 2018 are also provided.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.010 | 0.009 |
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".