Bibliographic record
Abstract
Abstract Climatology is the interdisciplinary study of the earth system that encompasses the atmosphere, hydrosphere, cryosphere, lithosphere, biosphere, and anthrosphere. Modern climatology includes not only these components but also importantly their interactions involving detailed global observing systems and complex computer‐based numerical models. The state of the climate system at any time is determined by the forcings acting upon it and the complex and interlocking internal feedbacks that these forcings prompt. Because of these feedback processes, the climate system does not respond to forcings, including human‐induced ones, in a smooth and gradual way and the response can be rapid and sometimes discontinuous. Climate models, with which we hope to predict future climates, must be able to capture such apparent discontinuities that have been observed in paleoclimatic records. To meet these requirements, modern climate models are composed of multiple interacting modules, which attempts to mimic components of the earth system, so that complicated feedbacks and synergisms in the climate system can be simulated faithfully. Human activities and associated needs, such as food and energy and water resources, are becoming increasingly dependent on, and even an integral part of, the climate system. With increasing evidence of the effects of human activities on the climate system, international bodies were established to coordinate scientific assessments of human influence on climate and to recommend appropriate mitigation and adaptation measures for policy makers.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.256 | 0.150 |
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".