Bibliographic record
Abstract
Many elliptic curve based cryptographic protocols,such as ECDSA signature verification require computation of multiple scalar multiplications such as kP+IQ.Common methods to compute it are the Shamir method and the interleaving method whereas their speed mainly depends on the (joint) Hamming weight of the scalars.The common drawback of these algorithms is that they are based on the radix-2 representations.So no matter what recording is used,only the number of point addition (or subtraction) can be diminished,but the number of point doubling can not be diminished.In this paper,a new recoding method based on the radix-4 representation is proposed.A new radix-4 representation based scalar multiplication algorithm is given. This method adopts point quadruple instead of point doubling,and examines the integer from left to right (from the most significant digit to the least significant digit).This results in the merging of recoding and evaluation stages.So the proposed algorithm can improve the performance and reduce the memory consumption of scalar multiplication operation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".