A Distributed Wiki System Based on Peer-to-Peer File Sharing Principles
Bibliographic record
Abstract
In peer-to-peer (P2P) file-sharing networks, each peer maintains its own repository, publishing files, downloading files from others, and making its own files available for download. We present P2Pedia, a distributed wiki system applying these principles to collaborative editing of documents: contributors may maintain their own version of each document, while accessing and reusing the contributions of others. This collaboration model, by allowing for multiple versions of a document, generates a different type of versioning hierarchy, and changes the semantics of wikilinks. We show how the versioning hierarchy of documents and the wikilinks create a graph of documents, that can be searched using an existing file-sharing infrastructure, and we propose some trust indicators to help users choose between available search results. Finally, we present the design and implementation of P2Pedia, and propose some scenarios where our proposed collaboration model is most appropriate.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".