Bibliographic record
Abstract
BitTorrent is todays most influential peer-to-peer content distribution system. Currently BitTorrent has two very different operating models: (i) public trackers, and (ii) private trackers (a.k.a. PTs, Darknets). A PT can only be accessed by its registered users, and can provide ultrahigh downloading speed because of its effective share-ratio enforcement (SRE) incentive mechanism which stimulates the users to upload contents as much as possible. Although PTs are becoming more and more popular, they receive little attention from the research literature, possibly because they are operated underground. To understand the popularity of Darknets, the authors have traced 17 PT sites, 2 public tracker sites and 1 BitTorrent search engine for over a year. The authors investigate these PT sites from several aspects and try to understand why they are so successful in terms of attracting loyal users and providing high downloading speed. The authors then analyse the SRE mechanism and ratio free system which are commonly used by PTs. Our results unveil the reason of popularity and effectiveness of PTs. These understandings are essential to the sustainable development of future BitTorrent content distribution systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".