Bibliographic record
Abstract
Part I. Introduction: 1. Introduction to climate modeling 2. Human components of the climate system Part II. The Science: Subsystems and Processes: 3. The atmosphere 4. The ocean circulation 5. Land surface 6. Terrestrial ecosystems 7. Atmospheric chemistry 8. Marine biogeochemistry Part III. Modeling and Parameterization: 9. Climate system simulation: basic numerical and computational concepts 10. Atmospheric general circulation modeling 11. Ocean general circulation modeling 12. Sea ice models 13. Land, ice and climate 14. Biophysical models of land surface processes 15. Chemistry transport methods 16. Biogeochemical ocean models Part IV. Couplings and Interactions: 17. Global coupled models: atmosphere, ocean, sea ice 18. Tropical Pacific ENSO models: ENSO as a mode of the coupled system Part V. Sensitivity Experiments and Applications: 19. Climate variability simulated in GCMs 20. Climate-model responses to increased CO2 and other greenhouse gases 21. Modeling large climatic changes of the past 22. Changes in land use Part VI. Future Prospects: 23. Climate system modeling prospects.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.992 | 0.993 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".