MétaCan
Menu
Back to cohort
Record W3104646966

Rings and gaps in protoplanetary disks: planets or snowlines?

2018· article· en· W3104646966 on OpenAlexaff

Bibliographic record

VenueMPG.PuRe (Max Planck Society) · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsPlanetIsotopologueAstrophysicsPhysicsProtoplanetary diskSaturnJupiter (rocket family)AstrobiologyAstronomySpectral line
DOInot available

Abstract

fetched live from OpenAlex

High resolution ALMA observations of protoplanetary disks have revealed that many, if not all primordial disks consist of ring-like dust structures. The origin of these dust rings remains unclear, but a common explanation is the presence of planetary companions that have cleared gaps along their orbit and trapped the dust at the gap edge. A signature of this scenario is a decrease of gas density inside these gaps. In recent work, Isella et al. 2016 derived drops in gas density consistent with Saturn-mass planets inside the gaps in the HD163296 disk through spatially resolved CO isotopologue observations. However, as CO abundance and temperature depends on a large range of factors, the interpretation of CO emission is non-trivial. We use the physical-chemical code DALI to show that the gas temperature increases inside dust density gaps, implying that any gaps in the gas, if present, would have to be much deeper, consistent with planet masses higher than a Jupiter mass. Furthermore, we show that a model with increased grain growth at certain radii, as expected at a snowline, can reproduce the dust rings in HD163296 equally well without the need for companions. This scenario can explain both younger and older disks with observed gaps, as gaps have been seen in systems as young <1 Myr. While the origin of the rings in HD163296 remains unclear, these modeling results demonstrate that care has to be taken when interpreting CO emission in protoplanetary disk observations.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.720

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 head0.010
GPT teacher head0.239
Teacher spread0.229 · 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 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

Citations44
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueMPG.PuRe (Max Planck Society)Same topicAstrophysics and Star Formation StudiesFrench-language works237,207