Supplementary material to "A numerical model study of the main factors contributing to hypoxia and its sub-seasonal to interannual variability off the Changjiang Estuary"
Bibliographic record
Abstract
Model-data comparisons of temperature and salinityThe model reproduces remotely sensed spatial and temporal SST patterns (from the NOAA AVHRR sensor; https://www.nodc.noaa.gov/SatelliteData/ghrsst/)very well with monthly correlation coefficients of 0.89 and above (Figure S1).Simulated surface salinity also shows similar spatial and seasonal pattern as available in situ data (Figure S2) with a correlation coefficient of 0.84.Both the model and observations indicate that the CDW is confined to the coast south of the estuary in early spring (March 2011) and autumn (October 2013) and extends eastward and northeastward in summer.Some interannual variations occur, e.g., the CDW extends northward and eastward in June 2012 while it mainly spreads southeastward in June 2013.At the bottom, freshwater is confined to the coast with high-salinity water coming from the open ocean (Figure S3).The correlation coefficient between simulated and observed bottom salinity is 0.87.Simulated bottom temperature shows significant seasonal variations consistent with the observations (Figure S4) with a correlation coefficient of 0.88.Higher temperature in south and east regions in March indicates the commencement of Kuroshio intrusion onto shelves.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.309 | 0.019 |
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".