Bibliographic record
Abstract
The petroglyphs of Petroglyph Park, Peterborough, created by the Algonquin Peoples between 900 and 1400 A.D., were documented in 1983 by the Heritage Recording Directorate of theGovernment of Canada. With the aim of rerecording the glyphs again at a later date to monitor the conditions and weathering, several sets of photogrammetric stereo pairs were taken of the site using Zeiss UMK and a Wild P-31 film cameras. After this project was completed, the site became designated as sacred and photography was no longer permitted, thus rendering the completion of a second recording of the site all but impossible. Therefore, the photographs taken of these magnificent petroglyphs in the 1980s are the most recent documentation available. Using the ADAMTech Mine Mapping Suite, developed in Perth Australia for the mining industry, I was able to bring these archival photos to life by creating dense 3D models that rival those produced by LiDAR. I used the photos, digitized in Ottawa on a Wehri RM-6 photogrammetric scanner, to create 3D models of the glyphs. A similar Federal project from Writing on Stone National Park in Alberta also used film photogrammetry to record the glyphs at that site in 1982. From these images as well I was able to compile 3D models. It is hoped that by scanning the original glass-plate negatives from the 1980s, and not the film copies, as we have done thus far for both projects, measurement data of even greater accuracy (down to 60um) and density can be achieved.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".