Ocean Model Canada Basin Profiles and Water Mass properties
Bibliographic record
Abstract
The archive contains basin averaged data, transect data, and pointwise data covering the near surface thermal maximum and the pacific water properties for 34 CMIP6 models, ORAS5, and several GFDL models of diffferent resolutions. See the corresponding publication for more information: Fajber, R., Planat, N., & Rosenblum E.: Do CMIP6 models have Pacific Water Heat Signatures in the Canada Basin? Journal of Geophysical Research: Oceans. Submitted. File Listing: --Pointwise property data These are the NSTM and the Pacific Water properties for each individual profile from the individual models. *_1970_2014.nc: NSTM and PacWater Properties for the corresponding model or dataset. --Transect Data This is data that is interpolated for each model to be along 70N 170W to 78N 126W Sec*.npy : Transects through the Canada Basin for the GFDL model suite transect*.nc: transects for the CESM2, EC-Earth, and oras5 datasets. --Basin Averaged Data This is data that is averaged over the rectangle with southwest corner 72N 150W, and northeast corner 80N 125W for each cmip6 model and the ORAS5 data. basin_averaged/m*.nc: basin averaged data
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.013 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.049 | 0.037 |
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".