Extracting information from very large datasets: modelling the erechtheion
Bibliographic record
Abstract
The National Research Council in Canada (NRCC) has created a framework for gleaning information from very large TLS and imagery datasets, an evolution demonstrated in the Erechtheion project. Cultural heritage has been a central factor in the NRCC research and development program in 3D technologies. Erechtheion is on the Acropolis, next to the Parthenon in Athens, Greece, whos refurbishment began in 1987. The 'Porch of the Maidens' is on the north side and consists of six draped female figures. NRCC has created algorithms for 3D-image processing, management and real-time visualization as part of Atelier3D.ca, a general framework evolved for acquisition, processing, modeling, analysis and visualization of very large 2D/3D datasets created from 3D point-clouds and imagery. Atelier 3D.ca allows view-dependent, real-time visualization of multi-resolution models. Algorithms have been created for displaying these datasets interactively at full resolution on inexpensive laptops or desktop computers.
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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 | 0.008 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".