Optimized Algorithm for Collision Probability Calculations in Cubic Geometry
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Bibliographic record
Abstract
An optimized algorithm for implementing a recently developed method of computing collision probabilities (CPs) in three dimensions is reported in this work for the case of a homogeneous cube. Use is made of the geometrical regularity of the domain to rewrite, in a very compact way, the approximate formulas for calculating CPs in general three-dimensional geometry that were derived in a previous work by the author. The ensuing gain in computation time is found to be substantial: While the computation time associated with the general formulas increases as K2, where K is the number of elements used in the calculation, that of the specific formulas increases only linearly with K. Accurate numerical results are given for several test cases, and an extension of the algorithm for computing the self-collision probability for a hexahedron is reported at the end of the work.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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