Argo-based anthropogenic carbon concentration and inventory in the Labrador and Irminger Seas over 2011-202
Bibliographic record
Abstract
The ocean is a net sink for a quater of the carbon dioxide emitted to the atmosphere by human industrial activities and land-use change (Cant). The North Atlantic Ocean encompasses the highest ocean storage capacity of Cant per unit area. In particular, the Labrador and Irminger Seas are two basins storing a high amount of Cant due to the deep convection activity taking place there. The temporal evolution of Cant concentration in these two basins and their Cant inventories in the 0-1800 depth layer are estimated over the period 2011-2021. The Cant values are estimated from Argo floats equipped with oxygen sensors, predictive neural networks (ESPER_NN and CONTENT) and a carbon-based back-calculation method (φCOT method). On average, Cant inventories are similar in the two basins and amount to 75.3 and 75.6 mol/m2 in the Irminger and Labrador seas, respectively. Over the study period, Cant inventories increase in the two basins at a storage rate of 1.01±0.14 mol/m2/yr in the Irminger Sea and 0.94±0.2 mol/m2/yr in the Labrador Sea. The processes involved in Cant evolution in the two basins are then investigated.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".