Shrack: Description and Performance Evaluation of a Peer-to-Peer System for Document Sharing and Tracking using Pull-Only Information Dissemination
Bibliographic record
Abstract
Shrack is a peer-to-peer framework for document sharing and tracking. Shrack peers provide support to researchers in forming direct collaboration in autonomous sharing and keeping track of newly published documents based on their interests. We propose a pull-only information dissemination protocol for peers to distribute information about new documents among peers with similar interests. Each peer can use the disseminated information to build a local view of semantic overlay of peer interests in the network. Each peer can later use the semantic overlay to find new contact information about other peers with a particular interests, as well as search for documents archived by other peers. After presenting an overview architecture of the system and the dissemination protocol, we present the evaluation results of the system performance, based on a simulated environment. The results indicate that the Shrack protocol is scalable and reliable as the network size increases.
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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 | 0.005 | 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 | 0.003 |
| Open science | 0.000 | 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".