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Record W1915497888 · doi:10.1109/digcom.1992.211649

Future standardization issues of intelligent network

2003· article· en· W1915497888 on OpenAlexaff
Keerthiraj Nagaraj, S. Harris

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsStandardizationComputer scienceService (business)Service providerSet (abstract data type)Software engineeringArchitectureIntelligent NetworkEngineering managementWorld Wide WebTelecommunicationsEngineeringOperating systemBusiness

Abstract

fetched live from OpenAlex

The main impetus for IN is their ability to assure service transparency in a multivendor environment and to provide a flexible platform for network providers to create and introduce new services quickly and easily. The IN standards activity in the CCITT is based on a service-driven approach and the main objective is to ensure that the standards developed are easily evolvable to address future services and network capabilities. The authors describe work on Capability Set-1 (CS-1) which is a subset of IN capabilities and addresses the near-term requirements of both manufacturers and network operators and defines the network capabilities to support current services. According to CCITT plans, CS-1 and related network architecture standards will be completed by the end of 1992. The author addresses future IN standardization issues that need to be resolved to define CS-2 and beyond network capabilities.>

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)0.031
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0020.005
Scholarly communication0.0120.018
Open science0.0030.003
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0060.002

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 head0.007
GPT teacher head0.237
Teacher spread0.231 · 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 designTheoretical or conceptual
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
Published2003
Admission routes1
Has abstractyes

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