Extending the SAND Spatial Database System for the Visualization of Three‐Dimensional Scientific Data
Bibliographic record
Abstract
The three‐dimensional extension of the SAND (Spatial and Nonspatial Data) spatial database system is described as is its use for data found in scientific visualization applications. The focus is on surface data. Some of the principal operations supported by SAND involve locating spatial objects in the order of their distance from other spatial objects in an incremental manner so that the number of objects that are needed is not known a priori. These techniques are shown to be useful in enabling users to visualize the results of certain proximity queries without having to execute algorithms to completion as is the case when performing a nearest‐neighbor query where a Voronoi diagram (i.e., Thiessen polygon) would be computed as a preprocessing step before any attempt to respond to the query could be made. This is achieved by making use of operations such as the spatial join and the distance semijoin. Examples of the utility of such operations is demonstrated in the context of posing meteorological queries to a spatial database with a visualization component.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".