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Record W2095334143 · doi:10.1145/1233341.1233373

Apocrita

2007· article· en· W2095334143 on OpenAlexaff
Joshua J. Reynolds, Robbie L. McLeod, Qusay H. Mahmoud

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicPeer-to-Peer Network Technologies
Canadian institutionsUniversity of Guelph-Humber
Fundersnot available
KeywordsComputer scienceWorld Wide WebProcess (computing)File sharingDocument management systemElectronic documentInformation retrievalThe Internet

Abstract

fetched live from OpenAlex

Many organizations are required to author documents for various purposes, and such documents may need to be accessible by all member of the organization. This access may be needed for editing or simply viewing a document. In some cases these documents are shared between authors, via email, to be edited. This can easily cause incorrect version to be sent or conflicts created between multiple users trying to make amendments to a document. There may even be multiple different documents in the process of being edited. The user may be required to search for a particular document, which some search tools such as Google Desktop may be a solution for local documents but will not find a document on another user's machine. Another problem arises when a document is made available on a user's machine and that user is offline, in which case the document is no longer accessible. In this paper we present Apocrita, a revolutionary distributed P2P file sharing system for Intranets.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.674
Threshold uncertainty score0.674

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.011
GPT teacher head0.257
Teacher spread0.246 · 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 teacher head, not a consensus.

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

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

Citations2
Published2007
Admission routes1
Has abstractyes

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