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
Abstract Retail ‐ General (MIC: 5.2 SIC: 5331 NAIC: 452990) Wal‐Mart Stores operated 1,353 discount department stores, 1,713 Supercenters, 551 Sam's Clubs and 85 Neighborhood Markets in the U.S. as of Jan 31 2005. Co. also operated 679 Wal‐Mart stores in Mexico, 282 in the U.K., 262 in Canada, 91 in Germany, 54 in Puerto Rico, 149 in Brazil, 16 in South Korea, and eleven in Argentina. Co. also operated 43 stores in China under joint venture agreements. Co.'s supercenters combine food, general merchandise, and services including pharmacy, dry cleaning, portrait studios, photo finishing, hair salons, and optical shops. In addition, Co. owns approximately 37.0% interest in Seiyu, Ltd., which operates over 403 stores throughout Japan.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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