Fort York National Historic Site
Bibliographic record
Abstract
Partnering with Iron Mountain in 2017, CyArk documented Fort York as part of an innovative preservation initiative commemorating 'Canada 150.' Using terrestrial LiDAR scanning, photogrammetry, and aerial drone photography, CyArk created a digital record of the eight buildings and surrounding earthworks that make up the site. Site mangers were able to use the data CyArk collected to determine the exact location of a historic ammunition magazine that had been previously unconfirmed. Canadian conservators will continue to use this data to monitor site conditions and help guide archaeological field work in the future. Canada's largest collection of original War of 1812 buildings and 1813 battle site, Fort York marks the birthplace of modern day Toronto, Canada. The fort was a site of major battle between the United States and Britain just a decade after the revolutionary war. Troops at the fort consisting of British, Canadians, Mississaugas, and Ojibways defended the fort against 2,700 American soldiers. With over three times as many soldiers the Americans forced the British to retreat. American troops occupied the the city of York for six days, burning down buildings and looting homes. The city of York would remain in the hands of the British at the end of the war, but Fort York's landscape, marked with original buildings from the war of 1812, remains a significant place for understanding colonial influence on the roots of Ontario as a province and Canada as a nation. External Project Link: https://artsandculture.google.com/exhibit/rwLiJDfgARvbLQ Additional Info Link: https://cyark.org/projects/fort-york-national-historic-site
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.494 | 0.131 |
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".