Efficient Carbon Recycling at the Central‐Northern Lesser Antilles Arc: Implications to Deep Carbon Recycling in Global Subduction Zones
Bibliographic record
Abstract
Abstract Carbon recycling efficiency of arc (CREA) is an important parameter to assess the recycling of slab carbon into Earth's deep interior. Although previous studies observed variable degrees of recycled slab carbon at global arcs, the CREA value of any individual subduction zone has not been obtained due to the loose constraints on carbon budget in altered oceanic crust (AOC). Here, through estimates of carbon input by both sediments and AOC at DSDP Site 543 and recycled carbon output from major volcanoes in the Central‐Northern Lesser Antilles, we show an extremely efficient carbon recycling case, with the CREA value reaching 100±27%. Nearly complete slab carbon release at sub‐arc depth implies little carbon has been lost in the forearc region or subducted into the deep mantle in this subduction zone. Our results highlight strongly variable CREA on a global scale, which must be considered in the modeling of global deep carbon cycle.
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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 | 0.001 |
| 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".