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
Kentucky’s nineteenth-century distillers used Indian corn as their primary grain, but they also distilled wheat, rye, and barley. Thus, they needed reliable sources of quality grain. Corn became a staple grain, consumed in quantity by farm families and town residents alike. Corn was widely grown in the nineteenth century, but before 1860, only farmers in the Bluegrass region were producing sufficient grain to feed their own livestock, sell to millers for human consumption, and meet distillers’ demands. After the Civil War, corn production increased, and the grain became more widely available for industrial-scale distilling. Wheat and rye were not extensively grown in Kentucky; they were more valuable than corn for foodstuffs and were not favored by distillers. Although Kentucky farmers produced barley, supplies were often deficient in quantity and quality for malting and use by distillers, necessitating its importation by rail from producers on the Great Plains and in the Canadian Prairie Provinces. Distillers fed hogs and cattle on spent grains, or slop, throughout the distilling season, and by season’s end in late spring, the animals had achieved market weight. This was a form of agriculture-distilling complementarity.
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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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