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
<p>Let <span class="math inline">\(G\)</span> be a graph with vertex set <span class="math inline">\(V(G) = \{v_1, v_2, \dots, v_n\}\)</span>. We associate to <span class="math inline">\(G\)</span>, a matrix <span class="math inline">\(P(G)\)</span> whose <span class="math inline">\((i, j)\)</span>-th entry is the maximum number of vertex-disjoint paths between the corresponding vertices if <span class="math inline">\(i\neq j\)</span>, and is zero otherwise. We call this matrix the <em>path matrix</em> of <span class="math inline">\(G\)</span>, and its eigenvalues are referred to as the <em>path eigenvalues</em> of <span class="math inline">\(G\)</span>. In this paper, we investigate the path eigenvalues of graphs resulting from certain graph operations and specific graph families.</p>
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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 | 0.001 |
| 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