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Record W4254029868 · doi:10.1145/1011767

Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing

2004· paratext· en· W4254029868 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeparatext
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This volume contains the 39 papers and 36 brief announcements presented at the 23rd ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing (PODC), which was held from July 25 to 28, 2004, in St. John's, Newfoundland, Canada. This year, PODC included a special track on Algorithms and Data Structures for the Internet, chaired by Michael Mitzenmacher. The special track papers competed with the other papers for acceptance. (The numbers 39 and 36 above include special track papers.) The goal of this track was to enhance the integration within PODC of new and relevant subjects in distributed computing. We would like PODC to continue attracting papers in these areas. Similarly, the submission of papers in areas that were emphasized in recent years was also encouraged (e.g., papers in security of distributed systems, and in the implementation, analysis, evaluation, and deployment of real systems). Another event for this year was the co-location with the PODC Workshop on Concurrency and Synchronization in Java Programs. The goal was to promote interaction between PODC and the community of researchers investigating synchronization in actual platforms such as Java.The contributed papers were selected from 224 submissions to the regular presentations track and 90 submissions to the brief announcements track. The selection was done using electronic discussions as well as multiple phone conference calls. The regular presentations were read and evaluated by the program committee, aided by other members of the community as needed. However, as in previous years, the papers were not formally refereed; it is expected that many of these papers will appear in more polished form in fully refereed scientific journals. A selection of papers will appear in a special issue of Distributed Computing dedicated to PODC 2004. The brief announcements were screened by the program committee based on short abstracts; it is expected that many of them will be published elsewhere (including in other conferences).The number of submissions to PODC has grown very fast over the last very few years. We coped with the high number this year by several methods, including increasing the number of accepted papers, and extending the evaluation period as well as the program committee meeting period. We also tried to provide the authors with more detailed reviews, given the tougher competition, even though this increased the size of an already large task. The competition among the papers was very fierce, and many very good papers were not accepted. Similarly, many very good brief announcements were not accepted. I think that the fact that PODC manages to attract a growing interest shows that PODC manages to remain relevant to the growing "boom" in distributed computing. Still, if the area continues to grow, PODC may need to try additional ways to deal with its size. Finally, this year PODC includes posters. (The posters are not included in the proceedings, but the collection of the posters is published as a Technical Report.On behalf of the Program Committee, I would like to thank all the authors who submitted extended abstracts for consideration. As mentioned above, we think that many papers that were not accepted are very good, and it is really a pity we could not fit more of them into the program. We hope to see their authors in this PODC, and in future PODCs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.091
Threshold uncertainty score0.305

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0070.004
Open science0.0020.003
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0910.060

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.

Opus teacher head0.019
GPT teacher head0.250
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations27
Published2004
Admission routes1
Has abstractyes

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