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Record W2390862005

Abstract Syntax Notation One and Its Application in TD-SCDMA

2008· article· en· W2390862005 on OpenAlexaff
Jun Huang, Mii Key

Bibliographic record

VenueCommunications technology · 2008
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsL'Alliance Boviteq
Fundersnot available
KeywordsComputer scienceTD-SCDMAEncoding (memory)Transmission (telecommunications)NotationCoding (social sciences)Interface (matter)Computer networkTelecommunicationsCode division multiple accessArtificial intelligenceOperating systemArithmetic
DOInot available

Abstract

fetched live from OpenAlex

In the TD-SCDMA system,the RRC information is used in the ASN.1 encoding format to increase the transmission efficiency of PER RRC message in the air interface,and in the TD-SCDMA network side of the Iur,Iu and Iub interface are ASN.1 encoding format is used in the Iur,Iub and Iu interfaces of YD-SCDMA network side for transmission.This paper tells of the basic knowledge and ASN.1 BER and PER coding rules,including how to combine TD-SCDMA analytical methods and concretely explain the application of ASN.1.

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)0.004
metaresearch head score (Gemma)0.011
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 score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0020.003
Scholarly communication0.0060.007
Open science0.0020.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0220.014

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 head0.061
GPT teacher head0.316
Teacher spread0.255 · 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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