Proceedings of the 2005 ACM workshop on Information retrieval in peer-to-peer networks
Bibliographic record
Abstract
It is our great pleasure to welcome you to the 2th Workshop on Information Retrieval in Peer-to-Peer Networks -- P2PIR 2005. This year's workshop aims at bringing together young researchers from Information Retrieval and Database Systems working on peer-to-peer information systems. Both communities have their own strategies at solving the problem of efficient and effective query routing in peer-to-peer networks, and a closer collaboration could have a large impact on future P2PIR research. As such, this proposed workshop continues the efforts from an SIGIR workshop last year on the same topic, and the primary goal is to foster the collaboration process started there.The call for papers attracted 15 submissions from Asia, Canada, the United States, Australia and Europe. The program committee accepted 6 papers that cover a variety of topics, including query routing, clustering and browsing, queries over RDF data and weighting schemes for peer-to-peer networks. In addition, the program includes two discussion sessions in order to benefit from different views in the two research communities. One discussion session will deal with problems and potential solutions in evaluating large-scale peer-to-peer networks, the other one about algorithmic and methodological problems.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.002 |
| 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".