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Record W3033442573 · doi:10.3390/galaxies8030053

Magnetism Science with the Square Kilometre Array

2020· preprint· en· W3033442573 on OpenAlexafffund
G. Heald, Sui Ann Mao, V. Vacca, Takuya Akahori, Ancor Damas-Segovia, B. M. Gaensler, M. Hoeft, I. Agudo, Aritra Basu, R. Beck, M. Birkinshaw, A. Bonafede, Tyler L. Bourke, A. Bracco, E. Carretti, L. Feretti, J. M. Girart, F. Govoni, James Green, J. L. Han, M. Haverkorn, C. Horellou, M. Johnston‐Hollitt, R. Kothes, T. L. Landecker, B. Nikiel-Wroczyński, S. P. O’Sullivan, M. Padovani, F. Poidevin, Luke Pratley, Marco Regis, C. J. Riseley, Timothy Robishaw, L. Rudnick, C. Sobey, J. M. Stil, Xiaohui Sun, Sharanya Sur, A. R. Taylor, A. J. M. Thomson, Cameron L. Van Eck, F. Vazza, Jennifer West

Bibliographic record

VenueGalaxies · 2020
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsUniversity of CalgaryNational Research Council CanadaCanadian Institute for Theoretical AstrophysicsHerzberg Institute of AstrophysicsUniversity of Toronto
FundersInstituto de Astrofísica de AndalucíaMinisterio de Ciencia e InnovaciónMinistero dell’Istruzione, dell’Università e della RicercaMinisterio de Ciencia, Innovación y UniversidadesCanada Research ChairsNatural Sciences and Engineering Research Council of CanadaEuropean CommissionUniversity of TorontoBundesministerium für Bildung und ForschungDipartimenti di Eccellenza
KeywordsPathfinderMagnetismPhysicsContext (archaeology)Radio telescopeDark matterAstronomyAstrophysicsGeographyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

The Square Kilometre Array (SKA) will answer fundamental questions about the origin, evolution, properties, and influence of magnetic fields throughout the Universe. Magnetic fields can illuminate and influence phenomena as diverse as star formation, galactic dynamics, fast radio bursts, active galactic nuclei, large-scale structure, and dark matter annihilation. Preparations for the SKA are swiftly continuing worldwide, and the community is making tremendous observational progress in the field of cosmic magnetism using data from a powerful international suite of SKA pathfinder and precursor telescopes. In this contribution, we revisit community plans for magnetism research using the SKA, in light of these recent rapid developments. We focus in particular on the impact that new radio telescope instrumentation is generating, thus advancing our understanding of key SKA magnetism science areas, as well as the new techniques that are required for processing and interpreting the data. We discuss these recent developments in the context of the ultimate scientific goals for the SKA era.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.014
GPT teacher head0.226
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes2
Has abstractyes

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