Bibliographic record
Abstract
announcement of the first US case of mad cow disease raised the public's sense of alarm about beef safety, deflated beef stock options prices, and opened a new discourse among US policy makers and scientists about the aims of research into this perplexing disease.Mad cow disease, or bovine spongiform encephalopathy (BSE), is one of several transmissible spongiform encephalopathies (TSEs).These diseases are caused by an altered structural form of the normal cellular prion protein.Transmission of this aberrant protein form can occur through various means, including the ingestion of contaminated food.This last possibility, and the knowledge that BSE had entered human food sources in the UK and elsewhere in Europe and had led in the 1990s to a variant form of Creutzfeldt-Jakob disease (vCJD) in humans, has raised public awareness and fears of the potential widespread risk of this disease in humans.Robert Klitzman of Columbia University advises that the relative risk to the US population remains unknown but that understanding that risk is essential for making research policy.Klitzman told the JCI, "It would not surprise me if there were other cattle in the US from Canada that [are] infected."From previous studies he notes that, "epidemiologically, we know there is a bell-shaped curve for the incubation [of this disease]."Thus, this single case of BSE in the US may be only the beginning.Klitzman hopes, however, that the US will be lucky and this will be the only case.The real question for health officials is whether BSE in the US cattle population will translate into human disease.Klitzman's work on kuru in New NEWS Assessing risk is the business of prion disease researchElizabeth Williams: determining the actual risk.Robert Klitzman asks how society deals with risk.
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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 | 0.096 | 0.213 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.005 | 0.027 |
| Scholarly communication | 0.024 | 0.041 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.017 | 0.021 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".