Inertias of zero–nonzero patterns
Bibliographic record
Abstract
An n by n zero–nonzero pattern is a matrix with entries ∈{*, 0} where * denotes a nonzero real number. If allows all possible inertias, then is inertially arbitrary. It is shown that there exists a reducible n by n inertially arbitrary zero–nonzero pattern with 2n−1 nonzero entries for each n ≥ 6; and that for n = mt with t ≥ 6 and m ≥ 1, there exists a reducible n by n inertially arbitrary zero–nonzero pattern with 2n−m nonzero entries. These reducible inertially arbitrary zero–nonzero patterns are direct sums of irreducible zero–nonzero patterns, one of which is not inertially arbitrary. Furthermore, for these inertially arbitrary zero–nonzero patterns, it is shown that a superpattern need not be inertially arbitrary, these zero–nonzero patterns do not allow all possible spectra, and there are no inertially arbitrary sign patterns having these zero–nonzero patterns.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".