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Record W7099788720

The Astrophysics of Planetary Systems: Formation, Structure, and Dynamical Evolution Proceedings IAU Symposium No. 276, 2010

2016· article· en· W7099788720 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHistorical Astronomy and Related Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPlanetGiant planetGas giantRadiative transferLine (geometry)Eccentricity (behavior)Planetary systemGravitationCircumstellar disk
DOInot available

Abstract

fetched live from OpenAlex

Abstract. Theories of planet formation predict the birth of giant planets in the inner, dense, and gas-rich regions of the circumstellar disks around young stars. These are the regions from which strong CO emission is expected. Observations have so far been unable to confirm the presence of planets caught in formation. We have developed a novel method to detect a giant planet still embedded in a circumstellar disk by the distortions of the CO molecular line profiles emerging from the protoplanetary disk’s surface. The method is based on the fact that a giant planet significantly perturbs the gas velocity flow in addition to distorting the disk surface density. We have calculated the emerging molecular line profiles by combining hydrodynamical models with semianalytic radiative transfer calculations. Our results have shown that a giant Jupiter-like planet can be detected using contemporary or future high-resolution near-IR spectrographs such as VLT/CRIRES or ELT/METIS. We have also studied the effects of binarity on disk perturbations. The most interesting results have been found for eccentric circumprimary disks in mid-separation binaries, for which the disk eccentricity- detectable from the asymmetric line profiles- arises from the gravitational effects of the companion star. Our detailed simulations shed new light on how to constrain the disk kinematical state as well as its eccentricity profile.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.696
Threshold uncertainty score0.218

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 head0.002
GPT teacher head0.159
Teacher spread0.157 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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