Complexity Study of the Continuous Valued Number System Adders
Why this work is in the frame
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Bibliographic record
Abstract
The Continuous Valued Number System (CVNS) is a novel analog digit number system which employs digit level analog modular arithmetic. The information redundancy among the digits, allows efficient binary operations using analog circuitry with arbitrary accuracy, which in turn reduces the area and the number of required interconnections. CVNS theory can open up a new approach for performing digital arithmetic with classical analog elements, such as current comparators and current mirrors, and with arbitrary precision. Addition in the CVNS is digit wise and digits do not intercommunicate. In this paper the two operand CVNS adder complexity is compared with similar CVNS adders, as well as conventional threshold adders. Comparisons show that the CVNS adder is more area efficient than conventional threshold logic adders.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 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