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Record W3099711606

Nine New Repeating Fast Radio Burst Sources from CHIME/FRB

2020· article· en· W3099711606 on OpenAlexaffabout
Kaitlyn Shin

Bibliographic record

VenueDSpace@MIT (Massachusetts Institute of Technology) · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsFast radio burstPhysicsAstrophysicsSkyGalaxyTelescopeAstronomy
DOInot available

Abstract

fetched live from OpenAlex

© 2020. The American Astronomical Society. All rights reserved.. We report on the discovery and analysis of bursts from nine new repeating fast radio burst (FRB) sources found using the Canadian Hydrogen Intensity Mapping Experiment (CHIME) telescope. These sources span a dispersion measure (DM) range of 195-1380 pc cm-3. We detect two bursts from three of the new sources, three bursts from four of the new sources, four bursts from one new source, and five bursts from one new source. We determine sky coordinates of all sources with uncertainties of ∼10′. We detect Faraday rotation measures (RMs) for two sources, with values-20(1) and-499.8(7) rad m-2, that are substantially lower than the RM derived from bursts emitted by FRB 121102. We find that the DM distribution of our events, combined with the nine other repeaters discovered by CHIME/FRB, is indistinguishable from that of thus far non-repeating CHIME/FRB events. However, as previously reported, the burst widths appear statistically significantly larger than the thus far non-repeating CHIME/FRB events, further supporting the notion of inherently different emission mechanisms and/or local environments. These results are consistent with previous work, though are now derived from 18 repeating sources discovered by CHIME/FRB during its first year of operation. We identify candidate galaxies that may contain FRB 190303.J1353+48 (DM = 222.4 pc cm-3).

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.061
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.278
Teacher spread0.262 · 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 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

Citations202
Published2020
Admission routes2
Has abstractyes

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