The Evaluation of Salinity Measurements from PALACE Floats
Bibliographic record
Abstract
Seven PALACE (Profiling Autonomous Lagrangian Circulation Explorer) floats were deployed in October 1996 in the Irminger Basin of the Atlantic Ocean as a U.K. contribution to the World Ocean Circulation Experiment. Of these floats, four were fitted with a conductivity–temperature–depth package. The floats were ballasted to drift at a depth of about 1500 m, above the Labrador Sea Water (LSW) cold and fresh extreme, and programmed to surface every 14 days. The floats made a profile during each ascent to the surface. The authors present a method to evaluate the performance of the conductivity sensors and to calibrate the float salinity data. Since the LSW appears to be relatively stable over a timescale of ∼1–2 months and a length scale of ∼50–100 km, the authors were able to make direct comparisons between the first year of float data and accurate ship-based measurements and, therefore, were able to correct for errors of the conductivity sensors. A correction was applied in all cases. The conductivity sensors were all stable within, or very close to, the manufacturer's specification, with a maximum drift for salinity of (0.0009 ± 0.0004) month−1.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".