Methodical Extensions for Decomposition of Matrix-Based Design Problems
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 two-phase method is a matrix-based approach for system decomposition, in which a system is represented by a rectangular matrix to capture dependency relationships of two sets of system elements. While the two-phase method has its own advantages in problem decomposition, this paper focuses on two methodical extensions to improve the method’s capability. The first extension is termed nonbinary dependency analysis, which can handle nonbinary dependency information, in addition to just binary information, of the model. This extension is based on the formal analysis of a resemblance coefficient to quantify the couplings among the model’s elements. The second extension is termed heuristic partitioning analysis, which allows the method to search for a reasonably good decomposition solution with less computing effort. This extension can be viewed as an alternative to the original partitioning approach that uses an enumerative approach to search for an optimal solution. At the end, the relief valve redesign example is applied to illustrate and justify the newly developed method components.
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 | 0.001 | 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 | 0.000 | 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