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Record W1935178354 · doi:10.1175/bams-d-15-00048.1

The Threat to Weather Radars by Wireless Technology

2015· article· en· W1935178354 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.

Bibliographic record

VenueBulletin of the American Meteorological Society · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPrecipitation Measurement and Analysis
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsWirelessRadarTelecommunicationsProcess (computing)Wireless networkComputer scienceRadio spectrumWeather radarWork (physics)Engineering

Abstract

fetched live from OpenAlex

Abstract Wireless technology, such as local area telecommunication networks and surveillance cameras, causes severe interference for weather radars because they use the same operational radio frequencies. One or two disturbances can be removed from the radar image, but the number and power of the interfering wireless devices are growing all over the world, threatening that one day the radars could become useless for weather observations. Some agencies have already changed or are considering changing frequency bands, but now even other bands are under threat. Use of equipment at radio frequencies is regulated by laws and international agreements. Technologies have been developed for peaceful coexistence. If wireless devices use these technologies to protect weather radars, their data transmission capabilities become limited, so it is tempting to violate the regulations. Hence, it is an important task for the worldwide weather community to involve themselves in the radio frequency management process and work in close contact with their national radio authorities to ensure that meteorological interests be duly taken into account in any decision-making process toward the future usage of wireless devices.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.017
GPT teacher head0.223
Teacher spread0.206 · 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