MétaCan
Menu
Back to cohort
Record W2154764098 · doi:10.1109/milcom.2000.904904

An example of efficient spectrum management: army tactical radio operations in broadcasting bands

2002· article· en· W2154764098 on OpenAlexaffabout
A. Chubukjian, H. Nappert, Kaushik Mehta, A. Legris

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSimulation and Modeling Applications
Canadian institutionsInnovation, Science and Economic Development Canada
FundersCentre National de la Recherche Scientifique
KeywordsBroadcasting (networking)Electromagnetic compatibilityRadio broadcastingTactical communicationsInterference (communication)Radio spectrumRadio equipmentElectromagnetic interferenceTelecommunicationsComputer scienceMobile radioRadio frequencyFrequency assignmentEngineeringElectronic engineeringElectrical engineeringComputer network

Abstract

fetched live from OpenAlex

An overview of the methodology used to accommodate army tactical radio operations in broadcasting bands is presented. A detailed electromagnetic compatibility (EMC) analysis was carried out to maximize the spread spectrum operation of army tactical radios in Canadian bases, while minimizing the interference potential to the reception of TV and EM radio broadcast signals outside the bases. In Canada, the radio's tuning range of 30-108 MHz spans broadcast, land mobile and other bands. The details of the EMC study involved laboratory determination of broadcast receiver response to frequency hopping transmissions, the design of the appropriate EMC analysis algorithms, and the applications of specially prepared computer programs to obtain interference-free operation parameters for the military radios.

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)0.000
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.039
GPT teacher head0.252
Teacher spread0.213 · 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
GenreOther

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
Published2002
Admission routes2
Has abstractyes

Explore more

Same topicSimulation and Modeling ApplicationsFrench-language works237,207