Decadal variability of Labrador Sea Water formation 
Bibliographic record
Abstract
Transient tracer observations from GLODAPv2 and more recent data are used tocompute transit time distributions (TTDs) for Labrador Sea Water. These TTDs are then integratedbasin wide over the subpolar, subtropical and tropical Atlantic. This allows to infer ventilation,export and formation rates of LSW. We further devide the LSW density range into an upper (ULSW) and adeeper part (DLSW). The results reflect the known variability of LSW formation, with high formation ratesof DLSW in the 1990s and after 2015, and periods with increased ULSW formation in between.Astonishingly, the DLSW formation rate is always significantly larger than zero,even in years without direct DLSW ventilation.We also compare the formation rates derived from the TTDs with those calculated from CFC/SF6 inventories. This shows, that the formation rates inferred from tracer inventoriesdepend more strongly on the integration regions (subpolar North Atlantic onlyor including subtropics (and tropics)) than the TTD derived formation rates.
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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 | 0.000 |
| 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".