Modeling of Bitcoin's Blockchain Delivery Network
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we provide a comprehensive analytical model for Bitcoin's blockchain distribution network. Components of the model are derived from recent measurements and business analysis reports. We model the data distribution algorithm using branching processes in the network with random distribution of node connectivity. Then, we apply Jackson network model to the entire network in which individual nodes operate as priority M/G/1 queuing systems. Data arrival to the nodes is modeled as a non-homogeneous Poisson process where the distribution of arrival rate to the nodes is derived from the analytical model of data delivery protocol. Within performance results, we present probability distributions of block and transaction distribution time, node response time, forking probabilities, network partition sizes, and duration of ledger's inconsistency period.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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