Decimal floating-point antilogarithmic converter based on selection by rounding: algorithm and architecture
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Bibliographic record
Abstract
This study presents the algorithm and architecture of the decimal floating-point (DFP) antilogarithmic converter, based on the digit-recurrence algorithm with selection by rounding. The proposed approach can compute faithful DFP antilogarithmic results for any one of the three DFP formats specified in the IEEE 754-2008 standard. The proposed architecture is synthesised with an STM 90-nm standard cell library and the results show that the critical path delay and the number of clock cycles of the proposed Decimal64 antilogarithmic converter are 1.26 ns (28.0 FO4) and 19, respectively, and the total hardware complexity is 29325 NAND2 gates. The delay estimation results of the proposed architecture show that it has a significant decrease in terms of latency in contrast with recently published high performance decimal CORDIC implementations.
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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 | 0.001 | 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