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Record W4297686164 · doi:10.1117/12.2627870

Design and analysis of the NRC Q-band receiver for ngVLA band-5

2022· article· en· W4297686164 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

VenueMillimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy XI · 2022
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Optimization
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

The radio instrumentation team (RIT) at NRC’s (National Research Council Canada) Herzberg astronomy and astrophysics research center (HAA) is currently developing a dual-linear polarization, single-feed Q-band cryogenic radio astronomy receiver to develop and demonstrate important technologies needed for front-end development for the next generation very large array (ngVLA) project lead by the National Radio Astronomy Observatory (NRAO). The specific target is the ngVLA band-5 receiver, which covers the frequency range 30.5–50.5 GHz. It also serves as a technology demonstrator for component development for ngVLA bands-3, 4, and 6. The Q-band receiver system is designed to achieve a receiver noise temperature of less than 20 K over 70% of the bandwidth and better than 24 K over the complete operating bandwidth, and is compliant with the current ngVLA Band-5 receiver requirement. The receiver system consists of a cryostat with a cooled feed horn, a turnstile OMT (orthomode transducer) plus two noise couplers for calibration, two cryogenic mHEMT low noise amplifiers with noise temperature lower than 14 K, IR filters, and a vacuum window for low-loss transmission of electromagnetic fields into the cryostat.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score0.914

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 head0.012
GPT teacher head0.201
Teacher spread0.189 · 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