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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

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.

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)0.000
metaresearch head score (Gemma)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.039
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

Quick stats

Citations1
Published2002
Admission routes2
Has abstractyes

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