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Record W4223416449 · doi:10.1093/mnras/stac1031

The northern cross fast radio burst project – II. Monitoring of repeating FRB 20180916B, 20181030A, 20200120E, and 20201124A

2022· article· en· W4223416449 on OpenAlexfundno aff
M. Trudu, M. Pilia, G. Bernardi, A. Addis, G. Bianchi, Alessio Magro, G. Naldi, D. Pelliciari, G. Pupillo, Gianluca Setti, C. Bortolotti, C. Casentini, D. Dallacasa, Vishal Gajjar, Nicola Locatelli, Roberto Lulli, G. Maccaferri, A. Mattana, Daniele Michilli, Federico Perini, Andrea Possenti, Mauro Roma, Marco Schiaffino, M. Tavani, F. Verrecchia

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsnot available
FundersInstitut sur la Nutrition et les Aliments FonctionnelsUniversità di BolognaH2020 European Research CouncilIstituto Nazionale di Astrofisica
KeywordsPhysicsAstrophysicsFast radio burstRadio telescopeDetection thresholdTelescopeFluenceAstronomyReal-time computingOptics

Abstract

fetched live from OpenAlex

ABSTRACT In this work, we report the results of a 19-month fast radio burst observational campaign carried out with the north–south arm of the Medicina Northern Cross radio telescope at 408 MHz in which we monitored four repeating sources: FRB20180916B, FRB20181030A, FRB20200120E, and FRB20201124A. We present the current state of the instrument and the detection and characterization of three bursts from FRB20180916B. Given our observing time, our detections are consistent with the event number we expect from the known burst rate (2.7 ± 1.9 above our 10σ, 38 Jy ms detection threshold) in the 5.2 d active window of the source, further confirming the source periodicity. We detect no bursts from the other sources. We turn this result into a 95 per cent confidence level lower limit on the slope of the differential fluence distribution α to be α > 2.1 and α > 2.2 for FRB20181030A and FRB20200120E, respectively. Given the known rate for FRB20201124A, we expect 1.0 ± 1.1 bursts from our campaign, consistent with our non-detection.

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)0.001
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 score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.280
Teacher spread0.269 · 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

Citations9
Published2022
Admission routes1
Has abstractyes

Explore more

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