Bibliographic record
Abstract
You are a medical student in 1820, training in anatomy has now become a prerequisite to graduation but there are limited cadavers available for dissection. Could you be a body snatcher? What about if you only took unclaimed bodies? What if you didn’t actually excavate, just helped drive the wagon? What would be your conditions before you would turn to a life of crime? Keep in mind that just by “borrowing” the occasional body you would provide yourself with ample opportunities to learn anatomy and also easily afford your tuition.
 If you do decide to go ahead and become a body snatcher you’re going to have to learn the classic modus operandi employed by the best in the business. 
 First of all you want to do some daytime reconnaissance by attending the burial to see if any booby traps are being set for potential body snatchers. Next, you return at night with a wagon and drop two men off at the burial site. They then start digging a 3’X3’ hole until they hit the coffin. The body is carefully extracted and any identifying clothing or jewelry is removed and put back in the coffin before being reburied.
 Now you might be worried about retribution but you really don’t have much to fear. Townsfolk have been known to protest in front of medical schools but you’d have to deal with this even if you weren’t a body snatcher. If you end up going to court the worst that would happen is a fine that you could easily pay off by stealing another body or two. 
 Highet MJ. 2005. Body snatching and grave robbing: bodies for science. History and Anthropology 2005; 16(4):415-440.
 MacGillivray R. Body snatching in Ontario. CBMH/BCHM 1988; 5:51-60. 
 Ross I, Ross CU. Body snatching in 19th Century Britain: from exhumation to murder. British Journal of Law and Society 1979; 6(1):108-118.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| 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".