Utilizing a Discrete Global Grid System for Handling Point Clouds with Varying Locations, Times, and Levels of Detail
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Discrete global grid systems (DGGSs) have emerged in recent years as a new specification for working with global heterogeneous data sets in a Digital Earth framework. Point clouds originating from different sources usually have varying initial characteristics. This research aims to analyze to what extent a DGGS can be used to handle point clouds having varying coordinate systems, acquired at different levels of detail (densities), and at different times in the creation of a global map of point clouds. DGGSs, which are currently limited to a 2D (surface) space, are extended into 3D and 4D spaces to fully harness the multidimensional nature of point clouds. A continuous spatial indexing strategy, based on a space-filling curve, is then developed on an ellipsoidal model of the Earth and used to efficiently cluster and retrieve DGGS-based point clouds stored in a database. Finally, the queried points are visualized in a Web browser. The hierarchical, multi-resolution nature of a DGGS is exploited to achieve a variable-scale smooth-zoom visualization. The challenges and opportunities of point cloud integration in a DGGS are presented.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it