MétaCan
Menu
Back to cohort
Record W4213204652 · doi:10.3389/fspas.2022.809771

Rotation Periods of Asteroids Determined With Bootstrap Convex Inversion From ATLAS Photometry

2022· article· en· W4213204652 on OpenAlexfundno aff
Josef Ďurech, Michael Vávra, R. Vančo, Nicolas Erasmus

Bibliographic record

VenueFrontiers in Astronomy and Space Sciences · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsnot available
FundersQueen's UniversityGrantová Agentura České RepublikyNational Aeronautics and Space AdministrationQueen's University BelfastNuclear Safety and Security CommissionSpace Telescope Science Institute
KeywordsAsteroidRotation periodPhysicsSidereal timePhotometry (optics)Light curveRotation (mathematics)AstronomyEphemerisGeodesyAstrophysicsGeometryGeologyStarsMathematics

Abstract

fetched live from OpenAlex

The rotation period is one of the fundamental physical characteristics of asteroids. It can be determined from photometric measurements by standard methods of time-series period analysis or by creating a physical model of an asteroid with the rotation period being one of the fitted parameters. We used the latter approach to determine the sidereal rotation period for more than 5000 asteroids, out of which about 1600 are those for which their period was not known. We processed photometric measurements of about 100,000 asteroids from the ATLAS survey with the light curve inversion technique in the Asteroids@home project to search for the best-fit rotation period. This was repeated 25 times with randomly resampled—bootstrapped—data. For thousands of asteroids, their best-fit period was the same for most of the bootstrapped data sets; thus, their rotation period was determined with a high degree of reliability.

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 score0.156
Threshold uncertainty score0.438

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 head0.008
GPT teacher head0.208
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

Citations9
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Astronomy and Space SciencesSame topicAstro and Planetary ScienceFrench-language works237,207