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
Since the mid-twentieth century, warming in mountain regions has outpaced the global rate, with important regional implications for snowpacks and the ski industry. Recent climate litigation by communities in the State of Colorado signals the need to assess how observed changes in climate may have damaged the ski industry. This study presents a novel application of the SkiSim2.0 ski operations model at 226 ski areas across 4 US regional ski markets to assess what the ski industry could have looked like if post-1970s anthropogenic climate change had not occurred. Relative to 1960–1979, modelled average ski seasons (with snowmaking) in the 2000–2019 period have shortened between 5.5 and 7.1 days. National direct economic losses associated with lost skier visits and increased snowmaking costs are estimated at US$252 million annually. For the 2050s, regional ski seasons are projected to shorten between 14–33 days (low emissions) and 27–62 days (high emissions). The associated national direct economic losses range from US$657 to 1352 million annually. Climate change is an evolving business reality for the US ski industry. The economic damage already done is clear and the extent of future damages is dependent on the success of Paris Climate Agreement.
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) | 0.001 | 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