Factors regulating the Great Calcite Belt in the Southern Ocean and its biogeochemical significance
Bibliographic record
Abstract
Abstract The Great Calcite Belt (GCB) is a region of elevated surface reflectance in the Southern Ocean (SO) covering ~16% of the global ocean and is thought to result from elevated, seasonal concentrations of coccolithophores. Here we describe field observations and experiments from two cruises that crossed the GCB in the Atlantic and Indian sectors of the SO. We confirm the presence of coccolithophores, their coccoliths, and associated optical scattering, located primarily in the region of the subtropical, Agulhas, and Subantarctic frontal regions. Coccolithophore‐rich regions were typically associated with high‐velocity frontal regions with higher seawater partial pressures of CO2 (pCO2) than the atmosphere, sufficient to reverse the direction of gas exchange to a CO2 source. There was no calcium carbonate (CaCO3) enhancement of particulate organic carbon (POC) export, but there were increased POC transfer efficiencies in high‐flux particulate inorganic carbon regions. Contemporaneous observations are synthesized with results of trace‐metal incubation experiments, 234Th‐based flux estimates, and remotely sensed observations to generate a mandala that summarizes our understanding about the factors that regulate the location of the GCB.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".