MétaCan
Menu
Back to cohort

Dish Surface Characterisation for CHORD and HIRAX Using Metrology and Electromagnetic Simulations

2025· article· en· W4408235715 on OpenAlexaffabout

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSurface Roughness and Optical Measurements
Canadian institutionsMcGill University
Fundersnot available
KeywordsMetrologyChord (peer-to-peer)Surface metrologyElectromagneticsOpticsComputer scienceMaterials scienceSurface roughnessPhysicsEngineeringElectronic engineeringComposite material

Abstract

fetched live from OpenAlex

The Hydrogen Intensity and Real-time Analysis eXperiment (HIRAX) and the Canadian Hydrogen Observatory and Radio-transient Detector (CHORD) are next-generation radio interferometers designed to measure baryonic acoustic oscillations through 21-cm intensity mapping and also act as powerful platforms for studying fast radio bursts, pulsars, and cross-correlation studies. HIRAX and CHORD are being developed for deployment in the Karoo desert, South Africa, and the Dominion Radio Astrophysical Observatory (DRAO) in Kaleden, Canada, respectively, and operate in a drift-scan mode with manual adjustments in zenith angle within ±30° to build up sky coverage. HIRAX operates within a frequency range of 400–800 MHz, corresponding to a redshift range of 0.8 < <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$z$</tex> < 2.5, while CHORD covers a broader bandwidth from 300 to 1500 MHz, focusing on redshifts < 3.7. HIRAX and CHORD will consist of 256 and 512 elements, respectively, and both utilize six-meter diameter parabolic composite dishes with a focal ratio of f/0.21.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
Threshold uncertainty score0.281

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 head0.017
GPT teacher head0.254
Teacher spread0.238 · 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 designSimulation or modeling
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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same topicSurface Roughness and Optical MeasurementsFrench-language works237,207