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Record W2042739420 · doi:10.1088/0004-637x/775/1/53

TESTING IN SITU ASSEMBLY WITH THE<i>KEPLER</i>PLANET CANDIDATE SAMPLE

2013· article· en· W2042739420 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsCanadian Institute for Theoretical Astrophysics
Fundersnot available
KeywordsPlanetMonte Carlo methodRADIUSMass distributionSolar SystemRange (aeronautics)Terrestrial planetPlanetary systemDissipation

Abstract

fetched live from OpenAlex

We present a Monte Carlo model for the structure of low mass (total mass < 25 earth mass) planetary systems that form by the in situ gravitational assembly of planetary embryos into final planets. Our model includes distributions of mass, eccentricity, inclination and period spacing that are based on the simulation of a disk of 20 earth masses, forming planets around a solar mass star, and assuming a power law surface density distribution $\propto a^{-1.5}$. The output of the Monte Carlo model is then subjected to the selection effects that mimic the observations of a transiting planet search such as that performed by the Kepler satellite. The resulting comparison of the output to the properties of the observed sample yields an encouraging agreement in terms of the relative frequencies of multiple planet systems and the distribution of the mutual inclinations, when moderate tidal circularisation is taken into account. The broad features of the period distribution and radius distribution can also be matched within this framework, although the model underpredicts the distribution of small period ratios. This likely indicates that some dissipation is still required in the formation process. The most striking deviation between model and observations is in the ratio of single to multiple systems, in that there are roughly 50% more single planet candidates observed than are produced in any model population. This suggests that some systems must suffer additional attrition to reduce the number of planets or increase the range of inclinations.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.384

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 integrity0.0000.001
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 head0.012
GPT teacher head0.212
Teacher spread0.200 · 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

Citations263
Published2013
Admission routes1
Has abstractyes

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