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Record W2359349409

The Application of Abstract Syntax Notation One in TD-SCDMA

2008· article· en· W2359349409 on OpenAlexaff
Mii Key

Bibliographic record

VenueShanxi Electronic Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicPower Systems and Technologies
Canadian institutionsL'Alliance Boviteq
Fundersnot available
KeywordsComputer scienceTransmission (telecommunications)Coding (social sciences)NotationSyntaxEncoding (memory)Layer (electronics)GrammarTD-SCDMATheoretical computer scienceNatural language processingArtificial intelligenceTelecommunicationsLinguisticsArithmeticCode division multiple accessMathematics
DOInot available

Abstract

fetched live from OpenAlex

In the layer 3 information system of 3GPP,the layer 3 information is described with the using of ASN.1,and the various algorithms of ITU-T X.691 recommendations in the definition are used to the description of ASN.1 transformed into a transmission encoding.This would have an advantage to separate the definition of the information content and transmission grammar phase that has the definition of news independent in the transmission coding.This paper introduces the basic knowledge of ASN.1,and combines the analytical approach of RRC news to expound the applications of ASN.1 in the TD-SCDMA.

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)0.003
metaresearch head score (Gemma)0.005
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: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0030.005
Open science0.0010.001
Research integrity0.0010.003
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 head0.005
GPT teacher head0.194
Teacher spread0.189 · 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
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

Citations0
Published2008
Admission routes1
Has abstractyes

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