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Record W2906599145 · doi:10.3847/2041-8213/ab01db

Crater Density Predictions for New Horizons Flyby Target 2014 MU69

2019· article· en· W2906599145 on OpenAlexaff
Sarah Greenstreet, Brett Gladman, W. B. McKinnon, J. J. Kavelaars, K. N. Singer

Bibliographic record

VenueThe Astrophysical Journal Letters · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsNational Research Council CanadaUniversity of British Columbia
Fundersnot available
KeywordsImpact craterNew horizonsGeologyAstrobiologyGeophysicsPhysicsAstronomy

Abstract

fetched live from OpenAlex

Abstract In preparation for the 2019 January 1 encounter between the New Horizons spacecraft and the Kuiper Belt object 2014 MU69, we provide estimates of the expected impact crater surface density on the Kuiper Belt object. Using the observed crater fields on Charon and Pluto down to the resolution limit of the 2015 New Horizons flyby of those bodies and estimates of the orbital distribution of the crater-forming projectiles, we calculate the number of craters per unit area formed as a function of the time a surface on 2014 MU69 has been exposed to bombardment. We find that if the shallow crater size distribution from roughly 1–15 km exhibited on Pluto and Charon is indeed due to the sizes of Kuiper Belt projectiles, 2014 MU69 should exhibit a surface that is only lightly cratered below 1 km scale, despite being bombarded for ∼4 billion years. Its surface should therefore be more clearly indicative of its accretionary environment. In addition, this object may be the first observed for which the majority of the bombardment is from exogenic projectiles moving at less than or near the speed of sound in the target materials, implying morphologies more akin to secondary craters elsewhere in the solar system. Lastly, if the shallow Kuiper Belt size distribution implied from the Pluto and Charon imaging is confirmed at 2014 MU69, then we conclude that this size distribution is a preserved relic of its state ≃4.5 Gyr ago and provides a direct constraint on the planetesimal formation process itself.

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 score0.676
Threshold uncertainty score0.732

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)0.0010.001

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 head0.006
GPT teacher head0.196
Teacher spread0.190 · 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

Citations33
Published2019
Admission routes1
Has abstractyes

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