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Record W2866012319 · doi:10.1117/12.2311812

Design and characterization of the Cosmology Large Angular Scale Surveyor (CLASS) 93 GHz focal plane

2018· article· en· W2866012319 on OpenAlexaff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsUniversity of British Columbia
FundersDivision of Astronomical SciencesGoddard Space Flight CenterComisión Nacional de Investigación Científica y TecnológicaNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsCosmic microwave backgroundDetectorCardinal pointBolometerPolarimeterSkyAngular resolution (graph drawing)Planar

Abstract

fetched live from OpenAlex

The Cosmology Large Angular Scale Surveyor (CLASS) aims to detect and characterize the primordial Bmode signal and make a sample-variance-limited measurement of the optical depth to reionization. CLASS is a ground-based, multi-frequency microwave polarimeter that surveys 70% of the microwave sky every day from the Atacama Desert. The focal plane detector arrays of all CLASS telescopes contain smooth-walled feedhorns that couple to transition-edge sensor (TES) bolometers through symmetric planar orthomode transducer (OMT) antennas. These low noise polarization-sensitive detector arrays are fabricated on mono-crystalline silicon wafers to maintain TES uniformity and optimize optical efficiency throughout the wafer. In this paper, we discuss the design and characterization of the first CLASS 93 GHz detector array. We measure the dark parameters, bandpass, and noise spectra of the detectors and report that the detectors are photon-noise limited. With current array yield of 82%, we estimate the total array noise-equivalent power (NEP) to be 2.1 aW√s.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score0.307

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 head0.011
GPT teacher head0.211
Teacher spread0.200 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations17
Published2018
Admission routes1
Has abstractyes

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