SalishSeaCast hourly surface along-axis wind velocity, temperature and nitrate summary 2015-2019
Bibliographic record
Abstract
Aggregated hourly surface along-axis wind velocity, temperature and nitrate results for 2015-2019 from the SalishSeaCast hourly hindcast archive (https://salishsea.eos.ubc.ca/erddap/). This file is a companion asset to the following publication: B. Moore-Maley and S. E. Allen: Wind-driven upwelling and surface nutrient delivery in a semi-enclosed coastal sea, Ocean Sci., 2022. SalishSeaCast is a NEMO 3.6 configuration for the Salish Sea (https://salishsea-meopar-docs.readthedocs.io/). Along-axis wind velocity and wind stress are calculated from the Environment and Climate Change Canada HRDPS model (https://weather.gc.ca/grib/grib2_HRDPS_HR_e.html). This file has a companion software repository, which includes scripts to recreate the file (https://github.com/SalishSeaCast/SoG_upwelling_EOF_paper).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.044 |
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".