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Record W4388821621 · doi:10.1051/0004-6361/202348137

A new meteor shower from comet 46P/Wirtanen expected in December 2023

2023· article· en· W4388821621 on OpenAlexaff
Jérémie Vaubaillon, Quanzhi Ye, Auriane Egal, Mikiya Sato, Danielle E. Moser

Bibliographic record

VenueAstronomy and Astrophysics · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsEspace pour la vieWestern University
FundersObservatoire de Paris, Université de Recherche Paris Sciences et LettresNuclear Safety and Security CommissionNational Aeronautics and Space Administration
KeywordsMeteoroidMeteor showerCometPhysicsShowerContext (archaeology)AstrophysicsComet dustMeteor (satellite)AstronomyAstrobiologyInterplanetary dust cloudSolar SystemGeography

Abstract

fetched live from OpenAlex

Context. Comet 46P/Wirtanen is a near-Earth object (NEO) for which no associated meteor shower has ever been reported. Aims. This study is aimed at improving our understanding of why there has been no observed shower activity for this NEO to date, as well as to consider whether any past activity could be uncovered from the post-prediction results. Methods. The usual dynamic tools for meteoroid streams were used to describe the behavior of the particles ejected by the comet. The resulting modeled meteoroid stream was thoroughly inspected for collisions between the stream and the Earth. Results. The results show a possible encounter forecast for December 12, 2023, between 8:00 and 12:30 UT. The slow entry velocity is typically known to cause dim meteors. The activity level of the shower is highly uncertain due to the absence of reported past showers. Conclusions. Overall, the most optimal observations on the forecasted day would be achieved from Eastern Australia, New Zealand, and Oceania. These observations will help constrain the size distribution of meteoroids from comet 46P/Wirtanen in the millimeter range.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.211
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2023
Admission routes1
Has abstractyes

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