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
Hotel prices continued to gain ground during the recent quarter, regaining losses incurred during the pandemic. Prices in all regions are reverting to their long-term average, with hotels in the Pacific and South Atlantic regions rising above their standardized average. Hotels in both gateway and non-gateway cities continue to exhibit positive performance, although hotels in the gateway cities have posted greater gains. For both large and small hotels, transaction volume increased both quarter over quarter and year over year. Our moving average trendlines indicate that large hotels are priced to buy, while small hotels represent an opportunistic buy at best. Large hotels reached a new statistical high based on our standardized unexpected price (SUP) performance metric. Mortgage financing volume rose, given that financing costs were lower this quarter. Among factors that have contributed to this situation are the facts that the relative risk premium remained stationary this quarter and that the hotel delinquency rate has continued to decline. Our economic value added (EVA) and our shareholder value added (SVA) are positive, indicating that hotel investment based on operating performance is currently financially feasible. Looking toward the next quarter, our leading indicators of hotel price performance indicate that positive price momentum should continue to exist for both large and small hotels.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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