Bibliographic record
Abstract
QoS routing has been shown to be NP-hard. A recent study of its hardness suggests that the "worst-case" may not occur in practice, and thus there may exist a fast exact algorithm. We deploy the idea of iterative deepening search and look ahead to design an exact algorithm for finding the shortest path subject to multiple constraints (the MCSP problem). The accuracy of look-ahead information determines the efficiency of a search algorithm. The higher the accuracy of the look-ahead information, the more efficient the search process. An empirical study on a wide range of topologies shows the high accuracy of look-ahead information in the studied cases. Experimental results also show that our algorithm, IDA*/spl I.bar/MCSP, is fast and, in general, significantly outperforms A*Prune, an algorithm designed for the MCSP problem. The characteristics of iterative deepening search and the high accuracy of look-ahead information make IDA*/spl I.bar/MCSP a fast exact algorithm for the MCSP problem.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".