Bibliographic record
Abstract
The reconstruction number rn(G) of graph G is the minimum number of vertex-deleted subgraphs of G required in order to identify G up to isomporphism. Myrvold and Molina have shown that if G is disconnected and not all components are isomorphic then rn(G) = 3, whereas, if all components are isomorphic and have c vertices each, then rn(G) can be as large as c + 2. In this paper we propose and initiate the study of the gap between rn(G) = 3 and rn(G) = c + 2. Myrvold showed that if G consists of p copies of Kc, then rn(G) = c + 2. We show that, in fact, this is the only class of disconnected graphs with this value of rn(G). We also show that if rn(G) c + 1 (where c is still the number of vertices in any component), then, again, G can only be copies of K ≥ c. It then follows that there exist no disconnected graphs G with c vertices in each component and rn(G) = c + 1. This poses the problem of obtaining for a given c, the largest value of t = t(c) such that there exists a disconnected graph with all components of order c, isomorphic and not equal to Kc and is such that rn(G) = t.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".