A new algorithm for transitive closures and computation of recursion in relational databases
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Bibliographic record
Abstract
We propose a new algorithm for computing recursive closures. The main idea behind this algorithm is tree labeling and graph decomposition, based on which the transitive closure of a directed graph can be computed in O(e/spl middot/d/sub max//spl middot/d/sub out/) time and in O(n/spl middot/d/sub max//spl middot/d/sub out/) space, where n is the number of the nodes of the graph, e is the numbers of the edges, d/sub max/ is the maximal indegree of the nodes, and d/sub out/ is the average outdegree of the nodes. Especially, this method can be used to efficiently compute recursive relationships of a directed graph in a relational environment.
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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 | 0.000 |
| 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