MétaCan
Menu
Back to cohort
Record W4229703224 · doi:10.1109/imtc.1993.382690

A high precision RF vector analyzer based on synchronous sampling

2002· article· en· W4229703224 on OpenAlexaff
R. Courteau, T.K. Bose

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSensor Technology and Measurement Systems
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsSampling (signal processing)LinearityComputer scienceDetectorDigital signal processingElectronic engineeringSIGNAL (programming language)Spectrum analyzerStability (learning theory)EngineeringComputer hardwareTelecommunications

Abstract

fetched live from OpenAlex

The authors have developed a RF/microwave amplitude and phase measurement system of exceptional linearity and stability. In the system, the signals to be measured are transformed to discrete time digital signals by synchronous sampling. These digital signals are processed by a digital signal processor for vector detection and for computing digital feedback sent to the sampling gates. The sampling section uses digital feedback to make it insensitive to gain variations of the sampling gates. Digital processing of the IF signals avoids the various IF imperfections of conventional vector analyzers such as gain range errors and detector circularity errors, which explains the exceptional linearity of the system. The operating principles are given, and the design of the system, which works over the frequency range from 10 kHz to 500 MHz, is described.>

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.044
GPT teacher head0.245
Teacher spread0.201 · 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 designBench or experimental
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
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicSensor Technology and Measurement SystemsFrench-language works237,207