Mad Cow Disease: FDA's Management of the Feed Ban Has Improved, but Oversight Weaknesses Continue to Limit Program Effectiveness
Bibliographic record
Abstract
A letter report issued by the Government Accountability Office with an abstract that begins "More than 5 million cattle across Europe have been killed to stop the spread of bovine spongiform encephalopathy (BSE), commonly called mad cow disease. Found in 26 countries, including Canada and the United States, BSE is believed to spread through animal feed that contains protein from BSE-infected animals. Consuming meat from infected cattle has also been linked to the deaths of about 150 people worldwide. In 1997, the Food and Drug Administration (FDA) issued a feed-ban rule prohibiting certain animal protein (prohibited material) in feed for cattle and other ruminant animals. FDA and 38 states inspect firms in the feed industry to enforce this critical firewall against BSE. In 2002, GAO reported a number of weaknesses in FDA's enforcement of the feed ban and recommended corrective actions. This report looks at FDA's efforts since 2002 to ensure industry compliance with the feed ban and protect U.S. cattle."
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".