Distribution of anthropogenic CO<sub>2</sub> in the Pacific Ocean
Bibliographic record
Abstract
This work presents an estimate of anthropogenic CO 2 in the Pacific Ocean based on measurements from the WOCE/JGOFS/OACES global CO 2 survey. These estimates used a modified version of the ΔC* technique. Modifications include a revised preformed alkalinity term, a correction for denitrification, and an evaluation of the disequilibrium terms using an optimum multiparameter analysis. The total anthropogenic CO 2 inventory over an area from 120°E to 70°W and 70°S to 65°N (excluding the South China Sea, the Yellow Sea, the Japan/East Sea, and the Sea of Okhotsk) was 44.5 ± 5 Pg C in 1994. Approximately 28 Pg C was located in the Southern Hemisphere and 16.5 Pg C was located north of the equator. The deepest penetration of anthropogenic CO 2 is found at about 50°S. The shallowest penetration is found just north of the equator. Very shallow anthropogenic CO 2 penetration is also generally observed in the high‐latitude Southern Ocean. One exception to this is found in the far southwestern Pacific where there is evidence of anthropogenic CO 2 in the northward moving bottom waters. In the North Pacific a strong zonal gradient is observed in the anthropogenic CO 2 penetration depth with the deepest penetration in the western Pacific. The Pacific has the largest total inventory in all of the southern latitudes despite the fact that it generally has the lowest average inventory when normalized to a unit area. The lack of deep and bottom water formation in the North Pacific means that the North Pacific inventories are smaller than the North Atlantic.
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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 | 0.002 |
| 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) | 0.001 | 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".