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Record W2114279899 · doi:10.1109/cicc.1999.777361

The μPP ASIC: design, methodologies and tools for a pay phone system-on-a-chip based on an ARM core and design reuse

2003· article· en· W2114279899 on OpenAlexfundno aff
J. Riesco, Juan Carlos Burgos Díaz, Pedro Plaza

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsnot available
FundersNew Brunswick Innovation Foundation
KeywordsApplication-specific integrated circuitEmbedded systemReuseMicroprocessorMicrocontrollerSystem on a chipARM architectureComputer sciencePhoneChipPower consumptionArchitectureComputer hardwareComputer architectureEngineeringPower (physics)Telecommunications

Abstract

fetched live from OpenAlex

This paper describes the /spl mu/PP (Microcontroller for Pay Phones) ASIC, a system-on-a-chip solution based on the present Spanish pay phone system. The design integrates an ARM embedded microprocessor, several third party blocks and new custom modules developed in house, using ARM's Advanced Microprocessors Bus Architecture (AMBA). The system has been designed for low power consumption and management. Design reuse, aided by the use of new management tools, and co-design, allowed an important reduction in global design time.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.948
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.212
GPT teacher head0.326
Teacher spread0.115 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2003
Admission routes1
Has abstractyes

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