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Record W2126868220 · doi:10.1145/2405153.2405154

Introducing Publiy

2012· article· en· W2126868220 on OpenAlexaff
Reza Sherafat Kazemzadeh, Hans‐Arno Jacobsen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicPeer-to-Peer Network Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMiddleware (distributed applications)Computer scienceJavaVariety (cybernetics)Fault toleranceThroughputPublicationReliability (semiconductor)Scale (ratio)SoftwareDistributed computingOperating systemSoftware engineeringWorld Wide WebWireless

Abstract

fetched live from OpenAlex

We have recently witnessed widespread adoption of the publish/subscribe (pub/sub) communication paradigm in the development of large-scale distributed systems. Existing and anticipated use cases demand the pub/sub middleware to support a variety of capabilities ranging from reliability and fault-tolerance to high throughput mass-scale publication delivery, or bulk data dissemination (e.g., software patch distribution). This paper introduces Publiy, our multi-purpose distributed content-based pub/sub system that features the aforementioned capabilities in its different modes of operation. Publiy is developed in Java as an open-source project.

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)0.007
metaresearch head score (Gemma)0.020
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: none
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.074
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.004
Scholarly communication0.0110.023
Open science0.0030.010
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0740.047

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 head0.016
GPT teacher head0.242
Teacher spread0.226 · 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
GenreSoftware

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

Citations0
Published2012
Admission routes1
Has abstractyes

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Same topicPeer-to-Peer Network TechnologiesFrench-language works237,207