Carbon, Coast, and the Climate
Bibliographic record
Abstract
Abstract The Earth’s climate is strongly affected by the partitioning of carbon between its mobile reservoirs, primarily between the atmosphere and the ocean. The distribution between the reservoirs is being massively perturbed by human activities, primarily due to fossil fuel emissions, with a range of consequences, including ocean warming and acidification, sea-level rise and coastal erosion, and changes in ocean productivity. These changes directly impact valuable habitats in many coastal regions and threaten the important services the habitats provide to mankind. Among the most productive and diverse systems are coral reefs and vegetated habitats, including saltmarshes, seagrass meadows, and mangroves. Coral reefs are particularly vulnerable to ocean warming and acidification. Vegetated habitats are receiving heightened attention for their ability to sequester carbon, but they are being impacted by land-use change, sea-level rise, and climate change. Overall, coasts play an important, but poorly quantified, role in the global cycling of carbon. Carbon reservoirs on land and in the ocean are connected through the so-called land–ocean aquatic continuum, which includes rivers, estuaries, and the coastal ocean. Terrestrial carbon from soils and rocks enters this continuum via inland water networks and is subject to transformations and exchanges with the atmosphere and sediments during its journey along the aquatic continuum. The expansive permafrost regions, comprised of ground on land and in the seabed that has been frozen for many years, are of increasing concern because they store vast amounts of carbon that is being mobilized due to warming. Quantitative estimates of these transformations and exchanges are relatively uncertain, in large part because the systems are diverse and the fluxes are highly variable in space and time, making observation at the necessary spatial and temporal coverage challenging. But despite their uncertainty, existing estimates point to an important role of these systems in global carbon cycling.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".