Antarctic Circumpolar Current frontal system in the South Atlantic: Monitoring using merged Argo and animal‐borne sensor data
Bibliographic record
Abstract
We describe large‐scale features of the Antarctic Circumpolar Current (ACC) in the Atlantic part of the Southern Ocean by merging Argo data and data obtained by novel animal‐borne CTD sensors. Twenty one of these CTD‐Satellite Relay Data Loggers (CTD‐SRDLs) were attached to Southern elephant seals ( Mirounga leonina ) on South Georgia. The merged data yield unified gridded hydrogaphic fields with high temporal and spatial resolution, enabling the determination of features absent in each of the data sets separately. The structure and variability of the frontal field revealed by this data set were compared with those in daily quarter‐degree, optimally interpolated sea surface temperature fields and fields of weekly gridded sea level anomaly. In general, the frontal positions derived using our data set are in agreement with previous work, especially where the pathways are constrained by topography, e.g., at the North Scotia Ridge and the South Scotia Ridge. However, with the improved temporal and spacial resolution provided by the CTD‐SRDLs, we were able to observe some novel features. All frontal positions are more variable than previously indicated across the Scotia Sea and west of the Mid‐Atlantic Ridge on seasonal time scales. The merged data set shows the temporal variability of the Southern ACC Front (SACCF) north of South Georgia and in its position east of the island, where the SACCF lies further north than has been suggested in previous work. In addition, the Subantarctic Front crosses the Mid‐Atlantic Ridge about 400 km further north when compared to previous work.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".