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
The problem of minimizing the number of garbage outputs is an important issue in reversible logic design. We start with the analysis of the number of garbage outputs that must be added to a multiple output function to make it reversible. We give a precise formula for the theoretical minimum of the required number of garbage outputs. For some benchmark functions, we calculate the garbage required by some proposed reversible design methods and compare it to the theoretical minimum. Based on the information about minimal garbage, we suggest a new reversible design method that uses the minimum number of garbage outputs. We show that any Boolean function can be realized as a reversible network in terms of this new approach by giving the theoretical method of finding such a network. Using a heuristics synthesis approach, we create a program and run it to compare results of our synthesis to the previously reported synthesis results for the benchmark functions with up to ten variables. Finally, we show that the synthesis for the proposed model can be accomplished with lower cost than the synthesis of EXOR programmable logic arrays.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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