Bibliographic record
Abstract
This thesis evaluates the importance and impact of photorealistic visualization in contemporary geomatics and identifies and operationalizes state of the art technology for integrating photorealistic visualization within geomatics. Currently, the creation of photorealistic visualization is a challenge due to present deficiencies in geomatics technology. The visualization capabilities of state of the art geomatics platforms are at least a decade behind contemporary 3D visualization packages and workflows. Therefore, this thesis identifies a need for an integrated approach where the advantages of both technologies can be combined to improve communication in geomatics. To illustrate the integration, a case study underlines the benefits of photorealistic visualization as a geomatics communication tool and clarifies the benefits of this approach over the capabilities of current geomatics visualization approaches and technologies. The case study applies a novel integrated approach combining geomatics, earth observation data and 3D visualization technologies to create photorealistic visualizations in select Canadian National Parks. The potential of these visualizations as communication tools
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.325 | 0.179 |
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".