Bibliographic record
Abstract
The regional MOM5 domain contain the Atlantic Ocean between 100°W and 20°E bounded north and south by 65°N and 20°S, respectively. The regional MOM5 will have a fully eddy-resolving horizontal resolution of 0.1° in the GOM region from 10°N to 30°N and from 100°W to 70°W, decreasing linearly to 0.25° in the rest of the model domain. The regional MOM5 has 25 vertical z-coordinates, and is driven by the surface forcing fields obtained from CMIP5 dataset under the historical, RCP4.5, and RCP8.5 scenarios. The initial and boundary conditions are obtained from CMIP5. The ocean boundaries at 65°N and 20°S will be treated as closed, but are outfitted with about 5° of buffer zones in which the temperature and salinity will be linearly relaxed toward the corresponding fields obtained CMIP5 dataset. The sea surface salinity (SSS) of the model are also relaxed toward CMIP5 dataset. Two additional buffer zones will be located in the northwestern corner over the Labrador Sea, and in the Gulf of Cadiz (representing the Mediterranean Sea). The restoring time scale for the northern and southern boundaries will vary linearly from 25 days at the inner edge to 5 days at the walls. The timescale for the Labrador Sea region will be 25 days and, for the Mediterranean Sea, 365 days. The MOM4 model simulations are initialized from CMIP5 model simulations and are continuously run from 1900 to 2100. The available variables include temperature, salinity, sea surface height, current vectors, etc.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".