Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We have previously reported on a novel number representation using 2 bases which we refer to as the double-base number system (DBNS). Our preferred implementation uses the relatively prime bases {2,3}. If we allow the exponents of the bases to be arbitrarily large signed integers, then we can represent any real number to any arbitrary precision by a single digit DBNS representation. By representing the digit position by the exponent values, we generate a logarithmic-like representation which we can manipulate using an index calculus. A multiplier accumulator architecture for a FIR filter application has been reported which uses a half-index domain to remove the problem of addition within the index calculus. In this paper we show that using a 2-digit DBNS representation for both the input data and the filter coefficients can result in substantial hardware savings compared to both the single-digit a DBNS approach and an equivalent binary implementation of a general multiplier accumulator. In the paper we discuss the filter architecture, techniques for converting between binary and the 2-digit DBNS representations, and also the design technique used to generate the 2-digit DBNS FIR filter coefficients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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