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Record W4285130018 · doi:10.1093/mnras/stac1285

Variable structure in the PDS70 disc and uncertainties in radio-interferometric image restoration

2022· article· en· W4285130018 on OpenAlexfundno aff
Simón Casassus, Miguel Cárcamo

Bibliographic record

VenuearXiv (Cornell University) · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsnot available
FundersNational Research Council CanadaNational Institutes of Natural SciencesAgencia Nacional de Investigación y DesarrolloEuropean Southern ObservatoryMinistry of Science and TechnologyKorea Astronomy and Space Science InstituteNational Science Foundation
KeywordsPhysicsOffset (computer science)WavelengthOpticsAstrophysicsComputer science

Abstract

fetched live from OpenAlex

The compact mm-wavelength signal in the central cavity of the PDS70 disc, revealed by deep ALMA observations, is aligned with unresolved Halpha emission, and is thought to stem from a circum-planetary disc (CPD) around PDS70c. We revisit the available ALMA data on PDS70c with alternative imaging strategies, and with special attention to uncertainties and to the impact of the so-called "JvM correction", which is thought to improve the dynamic range of restored images. We also propose a procedure for the alignment and joint imaging of multi-epoch visibility data. We find that the JvM correction exaggerates the peak signal-to-noise of the data, by up to a factor of 10. In the case of PDS70, we recover the detection of PDS70c from the July 2019 data, but only at 8sigma. However, its non-detection in Dec. 2017 suggests that PDS70c is variable by at least 42%+-13% over a 1.75yr time-span, so similar to models of the Halpha variability. We also pick up fine structure in the inner disc, such that its peak is offset by ~ 0.04" from the disc centre. The inner disc is variable too, which we tentatively ascribe to Keplerian rotation as well as intrinsic morphological changes.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.282

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.165
Teacher spread0.141 · 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 designTheoretical or conceptual
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

Citations36
Published2022
Admission routes1
Has abstractyes

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