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Record W2588603777 · doi:10.29173/cais420

Dual Acceptance of Web Diffusion: A Case of Clients and Servers

2013· article· en· W2588603777 on OpenAlexvenueno aff
Hsiang Chen

Bibliographic record

VenueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI · 2013
Typearticle
Languageen
FieldComputer Science
TopicOpen Source Software Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsServerDual (grammatical number)DiffusionReciprocalComputer scienceWorld Wide WebWeb serverPhenomenonClient–server modelWeb serviceInnovation diffusionArchitectureThe InternetKnowledge managementPhysics

Abstract

fetched live from OpenAlex

This study introduces the concept of dual acceptance to the diffusion of innovation theory and calls for new modifications to the diffusion of interactive media in the particular case of the Web technology, a client/server architecture. The diffusion of Web clients and Web servers creates a dual acceptance phenomenon and crossed-reciprocal interdependence relationships, which stimulate. . .

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)0.011
metaresearch head score (Gemma)0.025
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0070.012
Scholarly communication0.0120.012
Open science0.0020.008
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0050.001

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 head0.017
GPT teacher head0.242
Teacher spread0.225 · 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
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

Citations1
Published2013
Admission routes1
Has abstractyes

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Same venueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSISame topicOpen Source Software InnovationsFrench-language works237,207