Bibliographic record
Abstract
During the summer 2019 field season, ten human skeletons were excavated from the ongoing project (PAH-178) at the Hospital Hill Royal Navy Cemetery that was operational between the years of 1793-1822 on the island of Antigua, near English Harbour. As a student of Dr. Treena Swanston, a professor of MacEwan University, and one of the researchers invested in the project, I was hired as a research assistant and excavating archaeologist to assist with analyzing the skeletal remains excavated from a burial site associated with the Royal Navy Hospital for evidence of pathological changes. In studying disease on skeletal remains, paleopathologists look for evidence of skeletal changes or lesions associated with pathological conditions. In order for skeletal changes to occur, an individual must live with a disease or illness for an extended period of time, meaning those who succumb quickly will typically not show any skeletal evidence of bony changes or pathologies. This is known as the osteological paradox. However, we did not find any evidence of pathological changes at site PAH-178 during the 2019 field season. Presented in absentia on April 27, 2020 at Student Research Day at MacEwan University in Edmonton, Alberta. (Conference cancelled) Faculty Mentor: Treena Swanston Department: Anthropology
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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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.033 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 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".