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>A bipartite labeling of a tree of order <span class="math inline">\(n\)</span> is a bijective function that identifies the vertices of <span class="math inline">\(T\)</span> with the elements of <span class="math inline">\(\{0, 1, \dots, n-1\}\)</span> in such a way that there exists an integer <span class="math inline">\(\lambda\)</span> such that the set of labels on the stable sets of <span class="math inline">\(T\)</span> are <span class="math inline">\(\{0,1, \dots, \lambda\}\)</span> and {<span class="math inline">\(\lambda + 1, \lambda +2. \dots, n-1\}.\)</span> The most restrictive and versatile bipartite labeling is the variety called <span class="math inline">\(\alpha\text{-labeling}\)</span>. In this work we present a new construction of <span class="math inline">\(\alpha\text{-labeled}\)</span> trees where any two adjacent vertices of a path-like tree, or a similar caterpillar, can be amalgamated with selected vertices of two equivalent trees.</p>
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 | 0.001 | 0.001 |
| 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