Bibliographic record
Abstract
1. AAIW is defined by the low salinity tongue, and spiciness is defined by salinity anomaly along isopycnal surfaces, so that one can use salinity or spiciness to trace AAIW. Here we use WOA18 data downloaded from https://www.nodc.noaa.gov/OC5/woa18/woa18data.html, and the results are shown in Figure 2, one can trace AAIW with different tracers, including the absolute salinity (panel a), the spiciness (panel b), the distance from the origin (defined by the temperature and salinity at 30oS and 50 m below the sea surface) (panel c), and the spicity (panel d).2. As observed in Schmitt (1981), density ratio was 1.89 and 1.95 for the South and North Center Water stations. Using World Ocean Circulation Experiment (WOCE) database (https://cchdo.ucsd.edu/), we find two stations: (17.4oS, 30.8oW) in Section A17 and (24.5oN, 36.7oW) in Section A05-2, nearest to those in Schmitt (1981), to calculate the density ratio.3. In the Arctic Ocean, we used temperature and salinity data acquired with Ice-Tethered Profiler (ITP), downloaded from https://www.whoi.edu/page.do?pid=28866. With the vertical resolution of 0.25 m, the data enables us to examine the small-scale structures, i.e. diffusive convection staircases. The ITP4 station is located at (79.0oN, 142.5oW) in the Canada Basin, where a stack of staircases exists in the upper layer of a water mass, called as Antarctic Water (Figure 3(a)) (Padman and Dillon, 1987).
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.526 | 0.657 |
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".