Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The extratropics are the cloudiest region on Earth. Changes in clouds in this region in response to warming have the potential to substantially affect global mean cloud feedback and by extension climate sensitivity. Global climate models (GCMs) predict a relatively small, but consistent positive longwave (LW) cloud feedback throughout much of the extratropics. The bulk of GCMs transition from positive subtropical shortwave (SW) cloud feedback to negative extratropical SW cloud feedback is driven by increasing cloud optical depth. However, the strength of the negative feedback in the extratropics is not agreed upon by GCMs. Recent shifts in extratropical SW cloud feedback toward more positive values in the most recent generation of GCMs have led to the emergence of several high ECS ( K) GCMs. Thus, understanding and constraining the processes that drive extratropical cloud feedback has global implications and constraint of the SW extratropical cloud feedback has garnered significant attention in the literature. In this chapter, we summarize recent literature and present the processes important for extratropical cloud feedback in the context of meteorological regimes and global climate.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.020 |
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 it