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Record W2158194600 · doi:10.1109/ccece.2008.4564790

HTTP modification to reduce client latency

2008· article· en· W2158194600 on OpenAlexaffvenue
Abdolreza Abhari, Adam Serbinski

Bibliographic record

VenueConference proceedings - Canadian Conference on Electrical and Computer Engineering · 2008
Typearticle
Languageen
FieldComputer Science
TopicWeb Data Mining and Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer scienceFat clientOperating systemWeb serverClient–server modelClient-sideWeb APIFile serverServer-sideClientApplication serverAppleShareLatency (audio)Thin clientHypertext Transfer ProtocolProtocol (science)Dynamic web pageWeb pageWorld Wide WebWeb serviceServerThe Internet

Abstract

fetched live from OpenAlex

In this paper, we have developed an additional enhancement to the HTTP protocol. This modification eliminates the need for the client to wait for the delivery of the HTML file before being able to request the embedded objects. In our solution, the server delivers the embedded objects of a Web page to the client without being explicitly requested. In essence, the requests for the embedded objects are generated by the server instead of by the client. We introduced, in the form of a module for Apache HTTP server, a mechanism for preloading Web page from server to client. The client Web browser is able to receive this modified response through the use of a custom built proxy.

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)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.008
Open science0.0060.005
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0110.008

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 head0.033
GPT teacher head0.220
Teacher spread0.188 · 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 designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations6
Published2008
Admission routes2
Has abstractyes

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