Bibliographic record
Abstract
I do health research on convenience stores corner stores about with stores.1Corner stores are a holistic intersectoral business model for healthier retailing, with support from grassroots and public health. People come together around food, and to build community.2Convenience stores are “fronts for drugs, money laundering, and other stuff.”3Corner stores make sandwiches. The best sandwiches are at the place where the school cook works on her summers off.4 She makes turkey sandwiches with dressing and cranberry, to order, on homemade bread. They’re much better than at that other place with the turkey sandwich. I haven’t eaten there for years.5Convenience stores are unhealthy.6Convenience stores (44512) are grocery stores (4451), but a convenience store is not a supermarket (44511), except where it sells a lot of fruit, in which case it might be a specialty food store (4452), specifically a fruit and vegetable market (44523). You know the ones. It’s awfully nice when they have all those flowers out front (4531). Oh, and except where the convenience store is really a gasoline station (4471) with convenience (44711), even if the owner is only getting a commission on sale of fuel and the gas pump is really not the main thing. Can you believe, $2.00/liter? $7.00/gallon. This is all true in Canada and the United States but not in Mexico.7Corner stores sell smokes, and a Pepsi.8Convenience stores are big (business). Corner stores are small. Independent.9Corner stores sell products my customers want—if we can get it.10 Convenience stores sell convenience. They sell what they can sell. Consumer demand.Corner stores are so expensive. It’s okay. They must make a living.11 Convenience stores are so expensive, except where they are not.12Corner stores employ staff. Convenience stores employ staff.
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.
How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".