A regional ocean database for the Coastal China Sea
Bibliographic record
Abstract
Access to high-quality marine geophysical and biogeochemical in-situ data poses a challenge for model evaluation and parameter calibration of the Coastal China Sea (CCS). We describe a new regional ocean database for CCS (RODCCS) with original data from six repositories. The database covers the region of 116-135°E in longitude and 20-42°N in latitude, which embraces the Bohai Sea, the Yellow Sea, the East China Sea and a part of the Sea of Japan. About 3.9 million data points are collected and sorted according to variable types, including temperature, salinity, dissolved oxygen, silicate, nitrate, nitrite, ammonium, phosphate, Chlorophyll a, dissolved inorganic carbon, dissolved organic carbon, and particulate organic carbon. These data are quality-controlled (QCed) with six QC checks and stored in a Network Common Data Format (NetCDF) file. RODCCS includes twelve NetCDF files, each with a unified structure. The database is easily accessed and of high quality after QC checks, making it suitable for a wide range of marine modelling as well as field research for the CCS.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Dataset About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Dataset About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".