Where and how long ago was water in the western North Atlantic ventilated? Maximum entropy inversions of bottle data from WOCE line A20
Bibliographic record
Abstract
A maximum entropy (ME) method is used to deconvolve tracer data for the joint distribution of locations and times since last ventilation. The deconvolutions utilize World Ocean Circulation Experiment line A20 repeat hydrography for CFC‐11, potential temperature, salinity, oxygen, and phosphate, as well as Global Ocean Data Analysis Project (GLODAP) radiocarbon data, combined with surface boundary conditions derived from the atmospheric history of CFC‐11 and the World Ocean Atlas 2005 and GLODAP databases. Because of the limited number of available tracers the deconvolutions are highly underdetermined, leading to large entropic uncertainties, which are quantified using the information entropy of relative to a prior distribution. Additional uncertainties resulting from data sparsity are estimated using a Monte Carlo approach and found to be of secondary importance. The ME deconvolutions objectively identify key water mass formation regions and quantify the local fraction of water of age τ or older last ventilated in each region. Ideal mean age and radiocarbon age are also estimated but found to have large entropic uncertainties that can be attributed to uncertainties in the partitioning of a given water parcel according to where it was last ventilated. Labrador/Irminger seawater (L water) is determined to be mostly less than ∼40 a old in the vicinity of the deep western boundary current (DWBC) at the northern end of A20 but several decades older where the DWBC recrosses the section further south, pointing to the importance of mixing via a multitude of eddy‐diffusive paths. Overflow water lies primarily below L water with young waters (τ ≲ 40 a) at middepth in the northern part of A20 and waters as old as ∼600 a below ∼3500 m.
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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 | 0.000 | 0.000 |
| 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".