Bibliographic record
Abstract
Art (Arthur) and Mary Aufderheide are very well known in the world of mummy studies, as well as that of physical and forensic anthropology.For me, the sight of his cheerful visage, signature bolo ties, enthusiastic greetings, and a hug from Mary always heralded the start of a great conference and lively discussions about subjects ranging from the rate of fly infestations in corpses, to ethics of autopsies, to music.Art was very much a Minnesota man.He was born on 9 th September, 1922 in New Ulm, he attended St. Olaf 's college, then medical school at the University of Minnesota, and ultimately taught in Minnesota, after a brief sojourn in Rochester (NY) and a stint in the army medical corps (1947)(1948)(1949).He married a Minnesota woman, Mary (née Buryk) who was a nurse and a linguist and as daring and unconventional as Art.It is probably the Minnesota weather that helped inspire one of Art's more extraordinary adventures -a trip to the North Pole (Plaisted Expedition) on snowmobiles.Being a glutton for punishment, he went there not once, but twice (1967 and 1968), facing down polar bears as well as the elements.He also spent three winters with the Inuit, channelling his inner anthropologist, an experience that served him well in his life as a palaeopathologist.Once mummies entered his life in the mid-1970s, due to Michael Zimmerman, Art did not restrict his adventures to cold places -he went wherever there were bodies to be found, regardless of climate or conditions, with Mary frequently by his side.
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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".