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
Climatological observations are available for Fairbanks, Interior Alaska, for up to 100 years. This is a unique data set for Alaska, insofar as it is of relatively high quality and without major breaks. Applying the best linear fit, we conclude that the mean annual temperature rose from -3.6°C to -2.2°C over the century, an increase of 1.4°C (compared to 0.8°C worldwide). This comparison clearly demonstrates the well-known amplification or temperature change for the polar regions. The observed temperature increase is neither uniform over the time period nor uniform throughout the course of a year. The winter, spring, and summer seasons showed a temperature increase, while autumn showed a slight decrease in temperature. For many activities, the frequencies of extremes are more important than the average values. For example, the frequency of very low temperatures (below -40°C, or -40°F) has decreased substantially, while the frequency of very high temperatures (above 26.7°C, or 80°F) increased only slightly. Finally, the length of the growing season increased substantially (by 45%) as a result of an earlier start in spring and a later first frost in autumn. Precipitation decreased for Fairbanks. This is a somewhat counter-intuitive result, as warmer air can hold more water vapor. The date of the establishment of the permanent snow cover in autumn showed little change; however, the melting of the snow cover now occurs earlier in the spring, a finding in agreement with the seasonal temperature trends. The records for wind, atmospheric pressure, humidity, and cloudiness are shorter, more broken, or of lower quality. The observed increase in cloudiness and the decreasing trend for atmospheric pressure in winter are related to more advection and warmer temperatures during this season.
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 | 0.000 |
| 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) | 0.002 | 0.000 |
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