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Towards a Characterization of the Developmental Environment of Web Applications and its Business Implications

2011· book-chapter· en· W2494841366 on OpenAlexaff
Pankaj Kamthan

Bibliographic record

VenueIGI Global eBooks · 2011
Typebook-chapter
Languageen
FieldComputer Science
TopicWeb Applications and Data Management
Canadian institutionsConcordia University
Fundersnot available
KeywordsCharacterization (materials science)Computer scienceWorld Wide WebSocial Semantic WebKnowledge managementSemantic WebData scienceWeb engineeringWeb intelligenceWeb developmentWeb serviceNanotechnology

Abstract

fetched live from OpenAlex

The Web has been changing since its inception. In particular, the evolution of the developmental environment of Web Applications has been multi-directional. This chapter provides a conceptual characterization of such technical directions, relationships between these directions, and their implications towards business organizations. The consequences of a commitment to these directions are considered with the support of examples and/or empirical studies as appropriate. The challenges faced by Semantic Web Applications and Social Web Applications are briefly outlined.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.005
Scholarly communication0.0100.013
Open science0.0010.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.002

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 head0.020
GPT teacher head0.208
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 designQualitative
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

Citations0
Published2011
Admission routes1
Has abstractyes

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