Changes in North American extremes derived from daily weather data
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- Insufficient payload (model declined to judge)
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: ObservationalConsensus signal: Observational
- Genre
- Candidate signal: EmpiricalConsensus signal: Empirical
- Teacher disagreement score
- 0.058
- Threshold uncertainty score
- 1.000
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.232 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
Detailed homogeneity assessments of daily weather observing station data from Canada, the United States, and Mexico enabled analysis of changes in North American extremes starting in 1950. The approach used a number of indices derived from the daily data, primarily based on the number of days per year that temperature or precipitation observations were above or below percentile thresholds. Station level indices were gridded to produce North American area‐averaged time series. The results indicated that the increase in the number of days exceeding the 90th percentile is about the same magnitude as the decrease in the number of days below the 10th percentile. Analysis of extremes farther out on the tails of the distribution (e.g., 95th and 97.5th percentiles) reveals changes very similar to the 90th and 10th percentiles. Annual extreme lowest temperatures are warming faster than annual extreme highest temperatures when the index assessed is the actual temperature, but cold and hot extremes are changing about the same when examined on a normalized basis. On the basis of several measures, heavy precipitation has been increasing over the last half century, and the average amount of precipitation falling on days with precipitation has also been increasing. These observed changes since the late 1960s, decrease in cold extremes, increases in warm extremes, and increases in heavy precipitation, are consistent with a warming planet.
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.
The record
- Venue
- Journal of Geophysical Research Atmospheres
- Topic
- Climate variability and models
- Field
- Environmental Science
- Canadian institutions
- Environment and Climate Change Canada
- Funders
- not available
- Keywords
- PercentileEnvironmental sciencePrecipitationClimatologyHomogeneity (statistics)Atmospheric sciencesMeteorologyGeographyStatisticsGeologyMathematics
- Has abstract in OpenAlex
- yes