Mostar index of certain classes of bicyclic graphs
Bibliographic record
Abstract
The Mostar index (MoI) of a nite and connected graph G is a measure of asymmetry, focusing on the edge-based structure of the graph.For an edge xy in G, let xy and yx denote the cardinalities of the sets of vertices closer to x and y respectively, then the Mostar index is dened as:where the summation is taken over all edges xy G.This edge-wise dierence reects how asymmetrically the graph is structured around each edge and summing these dierences across all edges yields the Mostar index for the graph.In this article, we compute the MoI for certain classes of bicyclic graphs that are of particular interest due to their moderately complex structure, lying between acyclic and polycyclic graphs.We classify bicyclic graphs into three distinct types, namely B 1 (m, n), B 2 (l, m, n) and B 1 (l, m), based on their cycle arrangements and then provide explicit formulas for calculating the exact value of the Mostar index.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".